Dynamic simulation and control of a distillation column

DYNAMIC SIMULATION AND CONTROL OF A DISTILLATION COLUMN INDERJEET CHAWLA NATIONAL UNIVERSITY OF SINGAPORE 2007 Acknowledgements i Acknowledgements I would like to express my deep sense of gratitude to my supervisor, Professor G.P. Rangaiah. He guided me with warm encouragement and provided valuable resources, instructive advice and sharp insights into my research work. I also like to thank the National University of Singapore in giving me flexibility in carrying out the research work reported in this thesis. Finally, my deepest thanks are to my parents, my wife Nidhi Chawla and my kids for their selfless love and endless support. ii Contents Acknowledgements i Contents ii Summary v Nomenclature vii List of Figures ix List of Tables xiv Chapter 1 Chapter 2 Chapter 3 Introduction 1 1.1 Distillation and its control 1 1.2 Motivation 4 1.3 Scope of this work 5 1.4 Organisation of this Thesis 6 Literature Survey 7 2.1 Modeling of columns 8 2.2 control structure design 11 2.3 Controller tuning 14 2.4 Summary 15 Design, Simulation and Control of a Depropaniser 17 3.1 Basis and Method 17 3.2 Number of trays and Feed Tray Location 20 3.3 Temperatures for Composition Controls 23 3.4 Control Configurations 25 iii 3.5 RGA Analysis 30 3.6 Tuning of Level Controllers 32 3.7 Tuning of Composition Controllers 35 3.8 Open loop responses 39 3.9 Summary 40 Chapter 4 Chapter 5 Chapter 6 References Single Ended Composition Control 42 4.1 Base case model and control 42 4.2 Effect of Level Controller Tuning 51 4.3 Effect of Ratioing with feed flow 56 4.4 Effect of Turndown 60 4.5 Effect of feed tray location 66 4.6 Summary 69 Dual Ended Composition Control 71 5.1 Base case model and control 71 5.2 Effect of Level Controller Tuning 77 5.3 Effect of Ratioing with feed flow 84 5.4 Effect of Turndown 90 5.5 Effect of feed tray location 96 5.6 Summary 98 Conclusions and Recommendations 100 6.1 Conclusions 100 6.2 Recommendations for Future Work 104 106 iv Appendix A: Macro for Step Changes in Single Ended Composition Controller 109 Appendix B: Macros for Sinusoidal Disturbance in Single Ended Composition Controller 115 Appendix C: Macros for Step Changes in Dual Ended Composition Controller 123 Appendix D: Macros for Sinusoidal Disturbance in Dual Ended Composition Controller 139 v Summary Distillation continues to be a critical and essential separation step in many process industries. Although extensive literature is available on its design and control, it is observed that some design and operational aspects are consistently overlooked. Firstly, there is no comprehensive study concerning the performance of control loops within the entire operating envelope of columns (e.g., at different throughputs). Secondly, there is very limited research comparing the control configurations based on with and without flow ratioing the manipulated variables with feed flow, for a column. Thirdy, there is minimal research on the effect of tuning level controllers on the composition control performance of a column. Fourthly, the effect of alternate feed tray location is seldom covered in any research. Finally, there is hardly any comprehensive study conducted using rigorous simulation software like Hysys to compare various control schemes. These important gaps in the current literature led to this study. This study specifically deals with the composition control of distillation columns taking depropaniser as an example. A rigorous steady state and dynamic model for depropaniser is developed using Hysys. Various decentralized, composition control configurations with and without ratioing to feed flow, are evaluated; the effect of feed flow turndown, alternate feed tray locations and alternate tuning of level controllers, on each configuration is also evaluated. The controllers in each configuration are tuned on a consistent basis. The performance of each configuration in each case is evaluated using step disturbances in feed flow rate, feed composition and sinusoidal disturbance in feed composition. This study considers both single ended and dual ended composition control of the depropaniser. Single ended control, wherein the composition at one end of the vi column is controlled automatically while the other end is manually set, is widely used for industrial columns. Dual ended control is designed to control the composition at both ends of the column. If the control structure is selected and tuned adequately, dual ended control gives advantage over single ended control in terms of reduced product variability and energy cost at the expense of increased complexity, investment and coupling. Simulation results show that (L/D, V/B) configurations performed best for single ended controls. They are least sensitive to level tuning and feed flow rate but they require additional measurements, are more complex and expensive. If simple configuration is preferred, (D, V) is a good alternative with tight level tuning for D and sluggish level tuning for V. The only disadvantage with D-control is the sensitivity to sinusoidal disturbances in feed composition at significantly lower feed flow rates. For dual ended controls, it has been observed that tight level tuning, in general, is not preferred. The configurations (L/F,V/F-SL), (L,V/B-SL) and (L/D,V/B-SL) are the best options. The turndown flow adversely affects the performance of most of the dual ended control configurations; however, these configurations are also least sensitive to feed flow rate. Locating the feed tray suitably can improve the dynamic performance. vii Nomenclature (A,B) or A, B ATV : Composition control configuration, where ‘A’ controls the overhead composition, and/or ‘B’ controls the bottom composition Auto tune variation method for controller tuning btmliq : Bottom Liquid product FIC : Flow Indicator and Controller HFT : Higher Feed Tray - feed tray located above the optimum feed tray HK : Heavy Key Component HYSYS : Proprietary Process Simulation software by Aspentech IC : Indicator Controller with Set Point from Spreadsheet IAE : Integral Absolute Error Kc : Proportional Gain of Controller LIC : Level Indicator and Controller LFT : Lower Feed Tray - feed tray located below the optimum feed tray LK : Light Key Component OP : Overhead Temperature Controller Output OPb : Bottoms Temperature Controller Output ovhdliq : Overhead Liquid product P-100 : Reflux Pump PID : Proportional, Integral and Derivative Controller Q : Duty stream RGA : Relative Gain Array SL : Sluggish level tuning for both overhead and bottom levels; if suffix SL is missing, this means tight level tuning for both overhead and bottom levels TD : Turndown i.e., minimum throghput required through the column for operation TS : Tight level tuning for overhead level and sluggish level tuning for bottoms level viii T-100@Main : Tray used for temperature control Ti : Integral time of controller TL : Tyreus-Luyben settings for controller tuning TIC : Temperature Indicator and Controller TRF : Transfer Function, used for specifying sinusoidal disturbance in feed propane composition TRF-1 : Transfer Function, used for specifying sinusoidal disturbance in feed i-butane composition VB : Visual Basic VLV : Control Valve XIC : Composition Indicator and Controller, used only as an indicator Greek Symbol λ : Relative Gain ix List of Figures Figure 3.1 Effect of Feed Tray location on Reflux Ratio and Boil-up Ratio 21 Figure 3.2 Effect of Feed Tray location on Key Component Ratio 22 Figure 3.3 Liquid Composition Versus Tray Number Counted from the 23 Column Bottom Figure 3.4 Column Temperature Profile for Base Case and 1% Change in 24 D/F Figure 3.5 PFD for L, V Configuration in Hysys 28 Figure 3.6 PFD for L/F, V/F Configuration in Hysys 29 Figure 3.7 PFD for L/D, V/B Configuration in Hysys 30 Figure 3.8 PFD for L/D, V Configuration in Hysys 33 Figure 3.9 IAE V/s Detuning Factor for Single Ended Flow Ratioed 36 Configurations Figure 3.10 Open Loop Responses Figure 4.1 Performances of Various Configurations Composition Control for Base Case Figure 4.2 Closed Loop Response and Temperature Controller Output for 46 Step Disturbance in Feed Composition for Base Case Figure 4.3 Closed Loop Response and Temperature Controller Output for 47 Step Disturbance in Feed Flow for Base Case Figure 4.4 Performances of Various Configurations for Single Ended 48 Bottoms Composition Control for Base Case Figure 4.5 Closed Loop Responses and Temperature Controller Output for 49 Step Disturbance in Feed Composition for Base Case Figure 4.6 Closed Loop Responses and Temperature Controller Output for 50 Step Disturbance in Feed Flow for Base Case 39 for Overhead 45 x Figure 4.7 Effects of Configuration and Frequency on Amplitude Ratio for 51 Sinusoidal Disturbance in Feed Composition Figure 4.8 Performance of Various Configurations for Single Ended 52 Overhead Composition Control with Sluggish Level Tuning compared to Base Case (Tight Tuning) Figure 4.9 Comparison of Closed Loop Response between Base Case and 53 Sluggish Level Tuning for a Step Disturbance in Feed Composition Figure 4.10 Comparison of Closed Loop Response between Base Case and 54 Sluggish Level Tuning for Step Disturbance in Feed Flow Figure 4.11 Performance of Various Configurations for Single Ended Bottoms 54 Composition Control with Sluggish Level Tuning compared to Base Case (Tight Tuning) Figure 4.12 Comparison of Closed Loop Response between Base Case and 55 Sluggish Level Tuning for Step Disturbance in Feed Composition Figure 4.13 Comparison of Closed Loop Response between Base Case and 55 Sluggish Level Tuning for Step Disturbance in Feed Flow Figure 4.14 Performance of Various Configurations for Single Ended 57 Overhead Composition Control with Flow Ratioing compared to Base Case Figure 4.15 Comparison of Closed Loop Response between Base Case and 57 Flow Ratioing for Step Disturbance in Feed Composition Figure 4.16 Comparison of Closed Loop Response between Base Case and 58 Flow Ratioing for Step Disturbance in Feed Flow Figure 4.17 Performance of Various Configurations for Single Ended Bottoms 59 Composition Control for Flow Ratioing compared to Base Case Figure 4.18 Comparison of Closed Loop Response between Base Case and 59 Flow Ratioing for Step Disturbance in Feed Composition Figure 4.19 Comparison of Closed Loop Response between Base Case and 60 Flow Ratioing for Step Disturbance in Feed Flow Figure 4.20 Comparison of Open Loop Response at Turndown compared to 61 Design Case xi Figure 4.21 Performance of Various Configurations for Single Ended 62 Overhead Composition Control for Turndown Flow compared with Base Case Figure 4.22 Comparison of Closed Loop Response between Base Case and 63 Turndown for Step Disturbance in Feed Composition Figure 4.23 Comparison of Closed Loop Response between Base Case and 63 Turndown for Step Disturbance in Feed Flow Figure 4.24 Performance of Various Configurations for Single Ended Bottoms 64 Composition Control for Turndown Flow compared with Base Case Figure 4.25 Comparison of Closed Loop Response between Base Case and 65 Turndown for Step Disturbance in Feed Composition Figure 4.26 Comparison of Closed Loop Response between Base Case and 65 Turndown for Step Disturbance in Feed Flow Figure 4.27 Performance of Various Configurations for Single Ended 68 Overhead Composition Control with lower (LFT) or higher (HFT) Feed Tray Location compared with base configuration Figure 4.28 Performance of Various Configurations for Single Ended Bottoms 69 Composition Control with lower (LFT) or higher (HFT) Feed Tray Location compared with base configuration Figure 5.1 Performances of Various Configurations for Dual Ended 72 Composition Control for Base Case Figure 5.2a Closed Loop Responses for Step Disturbance in Composition for Base Case Figure 5.2b Temperature Controller Output for Step Disturbance in Feed 74 Composition for Base Case Figure 5.3a Closed Loop Responses for Step Disturbance in Feed Flow for 75 Base Case Figure 5.3b Temperature Controller Output for Step Disturbance in Feed 76 Flow for Base Case Figure 5.4 Performance of Various Configurations for Dual Ended Overhead 78 Composition Control with Sluggish Level Tuning compared to Feed 73 xii Base Case (Tight Tuning) Figure 5.5 Comparison of Closed Loop Response between Base Case and 79 Sluggish Level Tuning for Step Disturbance in Feed Composition Figure 5.6 Comparison of Closed Loop Response between Base Case and 80 Sluggish Level Tuning for Step Disturbance in Feed Flow Figure 5.7 Comparison of Closed Loop Response between Base Case and 81 Sluggish Level Tuning for Step Disturbance in Feed Composition Figure 5.8 Comparison of Closed Loop Response between Base Case and 82 Sluggish Level Tuning for Step Disturbance in Feed Flow Figure 5.9 Performance of Various Configurations for Dual Ended 85 Composition Control with Flow Ratioing compared to Base Case Figure 5.10 Comparison of Closed Loop Response between Base Case and 86 Flow Ratioing for Step Disturbance in Feed Composition Figure 5.11 Comparison of Closed Loop Response between Base Case and 87 Flow Ratioing for Step Disturbance in Feed Flow Figure 5.12 Comparison of Closed Loop Response between Base Case and 88 Flow Ratioing for Step Disturbance in Feed Composition Figure 5.13 Comparison of Closed Loop Response between Base Case and 89 Flow Ratioing for Step Disturbance in Feed Flow Figure 5.14 Performance of Various Configurations for Dual Ended 91 Composition Control for Turndown Flow compared with Base Configuration Figure 5.15 Comparison of Closed Loop Response between Base 92 Configuration and Turndown for Step Disturbance in Feed Composition Figure 5.16 Comparison of Closed Loop Response between Base 93 Configuration and Turndown for Step Disturbance in Feed Flow Figure 5.17 Comparison of Closed Loop Response between Base 94 Configuration and Turndown for Step Disturbance in Feed Composition Figure 5.18 Comparison of Closed Loop Response between Base 95 Configuration and Turndown for Step Disturbance in Feed Flow xiii Figure 5.19 Performance of Various Configurations for Dual Ended 97 Composition Control with lower (LFT) or higher (HFT) Feed Tray Location compared with Base Configuration xiv List of Tables Table 3.1 Steady State Design Data and Assumptions 17 Table 3.2 Design Parameters for Dynamic Simulation 19 Table 3.3 Data for and Results from Short-cut Distillation 21 Table 3.4: Possible Pairings of Controlled and Manipulated Variables 27 Table 3.5: Significance of Relative Gain 31 Table 3.6 Steady State Relative Gain 32 Table 3.7: Controller Parameters for Tight Level Tuning in Various 34 Configurations Table 3.8: Controller Parameters for Sluggish Level Tuning in Various 34 Configurations Table: 3.9: Set Point Changes used for Tuning Composition Controllers 36 Table 3.10: Controller Parameters for Single Ended Composition Control 37 Table 3.11: Controller Parameters for Dual Ended Composition Control 38 Table 3.12: Time Constant of Composition Response to a Step Change in L and V 39 Table 4.1: Details of Disturbances used for Performance Evaluation 44 Table 4.2: Comparison of Time Constants for Composition Response to a Step Change in L and V 61 Table 4.3: Comparison of Temperature Control Set Points Required for 66 Controlling Overhead and Bottoms Composition at Design Flow 1. Introduction 1 Chapter 1 Introduction 1.1 Distillation and Its Control Process control and optimization have gained wide interest in Chemical Process Industry. Appreciable savings in energy cost can be obtained, and product variability can be minimized by proper design of controls. In particular, distillation columns are highly coupled and non-linear, and have major impact on the utilities consumption and product quality. Thus selection of proper controls for distillation columns is both challenging and critical. The dynamic behavior of a column is a combination of steady state design, control structure selected and the column integration with the rest of the plant. This makes each column unique in terms of its overall performance. So, in order to provide an optimal scheme, it is very important to review the control structure, operating envelope, expected disturbances for each column and the controllers tuning. Control structure design involves selecting the controlled and manipulated variables, and appropriately pairing them to form control loops. Usually, it is based on operating experience and engineering judgment which may not give optimal performance. A systematic approach is required to decide the most appropriate control structure. The composition control for distillation columns can broadly be divided into single ended and dual ended controls. Single ended control is widely used for industrial columns in industry, which allow the composition of one end of the column to be controlled automatically while the other end is manually set. The advantages with this scheme 1. Introduction 2 include simplicity, good disturbance rejection and minimum coupling. Moreover, the process design of a distillation column typically includes heat integration with other streams from the plant. With single ended control the disturbance to such streams can be minimized. The major disadvantage with single ended control is the higher energy cost as the uncontrolled end may over-purify the product. Dual ended control is designed to control the composition at both ends of the column. If the control structure is selected and tuned adequately, dual ended control gives advantage over single ended control in terms of reduced product variability and hence reduced energy cost at the cost of increased complexity, investment and coupling. One critical aspect of control performance is the controller tuning to achieve performance objective of the control loop. The distillation column experiences extensive coupling between overhead and bottom products as both the manipulated variables affect both the controlled variables. Hence, the conventional tuning methods cannot be directly applied. Also controller tuning depends on the disturbance rejection required. A distillation column never operates at steady-state. The most common disturbances in a column include variations in feed flow rates, feed composition, utility conditions, product purity specifications, thunderstorms, and environmental changes. The most severe disturbances include failure of power, cooling water, steam, instrument air, pumps, control valve and operator. The column controls are designed for common disturbances while the column safety accounts for the severe disturbances. In view of the critical role of distillation and its role in chemical process industries, numerous studies have been reported on distillation control. There are many books and vast literature available on distillation design and control. Shinskey (1984) gives some 1. Introduction 3 insight into the distillation control behaviour. Deshpande (1985) systematically takes the reader through understanding distillation concepts, steady-state design and various control strategies. Kister (1990) presented operational aspects of distillation units and provided practical recommendations for troubleshooting distillation problems. Luyben (1990) describes the concept of mathematical modeling and simulation of process systems and describes the concepts of advanced control systems. Ludwig (1997) presents design methods for process design for a range of unit operations including distillation columns. In the recent years, Skogestad (1997) described various control configurations for distillation columns based on Closed Loop Disturbance Gain (CLDG). Riggs (1998) gave a comprehensive description of various distillation column controls based on relative volatility and generalized the control performance for each category. Engelien et al. (2003) discussed the concept and identification of self optimizing control for selecting the controlled variables which can provide optimization effect within acceptable degree of variation. Mahoney and Fruehauf1 highlighted the importance of rigorous dynamic simulation like Hysys to assess the suitability and performance of various schemes shortlisted by steady-state analysis. Alsop and Ferrer (2004, 2006) validated the rigorous Hysys model with site data for an industrial propylene/propane column. There is limited literature available on tuning level controllers and their effect on composition control performance. Buckley et al. (1985) described that for level control via reflux flow manipulation, it is necessary to sacrifice flow smoothening in the interest of good composition control. Alternately, PI level control with flow cascading is suggested for maximum product flow smoothening. Lundstrom and Skogestad (1995) described that, for some configurations, the composition control is independent of tuning 1 www.aspentech.com/publication_files , cited on 01 Jan 2007 1. Introduction 4 of level loops. Duvall (1999) tuned level controllers for critically damped response to keep level and composition control independent of each other. Skogestad (2001) reviewed the effect of level control on the distillation column performance. He concluded that composition control using LV configuration is almost independent of level controller tuning, however, for other configurations improper level controller tuning can make distillation column control difficult. Huang and Riggs (2002) tuned Level controllers for slow response to avoid oscillations to the column and amplify disturbances. 1.2 Motivation There is extensive literature available on distillation design and control. However, it is observed that some design and operational aspects are consistently overlooked. Firstly, there is no comprehensive study concerning the performance of control loops within its entire operating envelope (e.g., at different throughputs). A distillation column rarely operates at its design conditions. The market considerations and operational constraints may demand its operation away from the original design conditions. The feed compositions, throughput and operating conditions may vary due to upstream unit operations, while the operating pressures and product specifications may be affected by the operation of downstream units. Secondly, there is very limited research comparing the configurations based on with and without flow ratioing the manipulated variables with feed flow. It is important to know the extent of performance improvement using flow ratios as measuring feed flow is not always possible especially if the feed is multi-phase fluid or if flashing saturated liquid feed across the measuring device can affect the flow measurement. Riggs (1998) suggested ratioing column manipulated variables to feed rate 1. Introduction 5 flow rate for all configurations. Buckley et al. (1985) described the ratioing approach as ‘feed-forward approach’ and utilized it for composition control. Thirdy, there is minimal research which outlines the effect of tuning level controllers on the composition control performance. A comprehensive study can provide some guidelines on how the level controllers should be tuned for various configurations. Fourthly, the effect of alternative feed tray location is seldom covered in any research. Knowing this can help in improving dynamic response within tight limits of utility consumption. Finally, there is hardly any systematic study conducted using rigorous simulation software like Hysys to compare the various control schemes. These important gaps in the current literature led to this study. 1.3 Scope of this Work This study specifically deals with the composition control of distillation columns. The objectives of this study are outlined below. • To develop and validate a rigorous steady state model for depropaniser using Hysys, and then optimize the column design. • To prepare a ‘base case’ dynamic model of depropaniser using the smooth interface of Hysys steady-state model with dynamic simulation. The ‘base case’ model is defined as the model with no ratioing of manipulated variables with feed flow, fast response of level controls, and optimized composition control loops. • To evaluate the performance of several control configurations for the ‘base case’ model for small disturbances in feed flow rates, feed composition, and sinusoidal feed composition. 1. Introduction • 6 The ‘base case’ model is updated to study the effect of following parameters on control configurations and their performance for the same disturbances as used for the ‘base case’ model. o Ratioing the manipulated variables with feed flow. o Feed flow is reduced to 60% of base case to study the effect of turndown. o Level controllers tuned as slow loops o Feed tray location is changed to 2 trays above and 2 trays below the base case location. Results of the above cases are carefully and comprehensively presented and analyzed to provide useful conclusions. 1.4 Organization of this Thesis There are seven chapters in this thesis. Following this chapter, Chapter 2 includes a detailed review of relevant literature in the area of distillation control. Chapter 3 contains the basis and development of a rigorous steady-state and dynamic models for depropaniser using Hysys. After presenting a dynamic simulation model for single ended composition control, Chapter 4 details the study on the effect of ratioing controlled variables with feed rate, feed rate, level tuning and varying feed tray location on the performance of several control structures. Chapter 5 covers a similar study for dual ended composition control. Appropriate conclusions from this work and recommendations for further work are presented in Chapter 6. 2. Literature Survey 7 Chapter 2 Literature Survey Distillation processes are characterized by high consumption of energy and operating difficulties. Choosing the right control technique is important from operational and economic perspective. There are many books and vast literature available on distillation design and control. For example, Shinskey (1984) included a wide range of topics on distillation control including composition control and configuration selection. It gives some insight into the Distillation control behaviour. The issue of composition control and various configurations is also covered. Deshpande (1985) systematically takes the reader through understanding distillation concepts, steady-state design and various control strategies. Kister (1990) presented operational aspects of distillation units and provided practical recommendations for troubleshooting distillation problems. He also devoted some sections to basic control philosophy and design, and covered temperature sensor location and composition control. Luyben (1990) described mathematical modeling and simulation of process systems as well as advanced control systems. Ludwig (1997) presented methods for process design for a range of unit operations including distillation columns. These are widely accepted in the industry. Among the recent literature, most extensive research on distillation is covered by Skogestad (1997) and Riggs (1998). The contents of this chapter are organized as follows. Section 2.1 includes a detailed review of importance of modeling, design objectives and tools utilised in the distillation design and control. Section 2.2 discusses the control objectives, manipulated 2. Literature Survey 8 and control variables, control loop interaction, controllability, inferential composition control and the importance of dynamic simulation in selection of control structures. Section 3.3 discusses the tuning methods for control loops with and without interaction, tuning cascade loops and the interaction between composition and level loops. 2.1 Modelling of Columns Process simulation and modeling is now a well established tool in the process industry. These can be used to study individual unit operations or multiple interconnected units. Skogestad (1991) described that the modeling of a process can be utilized for equipment design, optimization, troubleshooting, process monitoring, operator training, preparing startup/shutdown procedures and process control. Alsop and Ferrer (2004) listed additional applications, viz., revamp studies and testing of DCS configurations. Steadystate techniques have been used for decades, and these are usually sufficient for equipment design and optimization. Dynamic simulation is required for operator training and process control involving special and complex units like distillation columns. Other applications may require either steady-state and/or dynamic simulation depending on the process type and insight required. Modelling the column is an important step for meaningful outcomes of the overall study. Determining the number of stages required for the desired degree of separation and the location of the feed tray is merely the first steps in producing an overall distillation column design. Other things that need to be considered are tray spacing, column diameter, internal configurations, heating and cooling duties, etc. All of these can lead to conflicting design parameters. Thus, distillation column design is often an iterative procedure. If the 2. Literature Survey 9 conflicts are not resolved at the design stage, then the column will not perform well in practice. If the plant data and design are available, it would be worthwhile to model the plant and match the simulation results with the operating data. Alsop and Ferrer (2006) described how some critical design parameters were tuned to match the site data for propylene/propane splitter with hysys dynamic simulation model. For scenarios where the job is under definition stage, a thorough analysis is required to conclude the steady state design. The column integration with the rest of the plant like feed/bottom exchanger, feed supply from other units, product destination to other units etc. are also part of the design evaluation. Column optimization involves options such as selecting feed tray location, reflux ratio, pressures, side condensing/reboiling and feed preheating/cooling requirements. Column design is generally based on rules of thumb and general guidelines, e.g., the number of theoretical stages is typically selected as twice the minimum number of stages required for infinite reflux (Skogestad, 1997). It is observed that there are exceptions to these heuristics. Lek et al. (2004) revisited these heuristics based on the changes in equipment and energy costs. Ludwig (1997) gave a comprehensive description of column design. Mukherjee (2005) has described the design rules for tray column design. One of the design objectives of distillation column design is to achieve the desired separation using minimum energy. Engelien and Skogestad (2005) focused on Vmin diagram to compare the energy requirement of different multi-effect distillation arrangements. Engelien et al. (2003) discussed the concept and identification of self optimizing control, which can provide optimization effect within acceptable degree of variation and thus it can potentially eliminate the optimization layer in control structure. 2. Literature Survey 10 Dhole and Linnhoff (1993) addressed the problem identifying appropriate column design modifications with respect to energy consumption using Column Grand Composite Curve (CGCC) and Column Composite Curve (CCC). The starting point for a dynamic simulation is a sound steady-state simulation, as this forms a basis for any control study (Alsop and Ferrer, 2004). Skogestad (1988, 1997) gave insight into column behavior using fundamentals and short-cut methods in steady state and dynamics of distillation column. He explained some concepts related to modeling of distillation column for dynamic performance. Shinskey (2002) highlighted the consistent gap between industry and academia on column modeling and control such as usage of unrealistic linear models, assumption of minimum phase dynamics, assumption of constant time delay, missing interacting lags in columns and arbitrary objective functions by academics. The latest generation of process simulators is quite easy to use, flexible, thermodynamically sound, and can provide more realistic models. Recently, there has been a shift in the academia using more industrially acceptable simulators. Hysys® and Aspen Plus from Aspentech, and Pro-II from Scimsci are such simulators which can be used for steady-state modeling. Hysys can give a smooth transition from steady state to dynamic simulation. Visual Basic (VB) can be used as an interface of HYSYS with Excel (John Green, 2003 and VBA Tutorials from HYSYS). Amrithalingham et al. (1999) used Hysys as a dynamic simulation software and interfaced it with Matlab for building an inferential control model for a depropaniser. Ross et al. (2000) analyzed operating problems of a highly non-linear industrial column using mixedinteger dynamic optimization (MIDO) as the dynamic optimization tool to design the 2. Literature Survey 11 system via simultaneous design and control approach. FORTRAN, CONSYDEX, MATLAB and Chemcad are also widely used for modelling. 2.2 Control Structure design Before selecting the control structure, it is important to understand the design objectives. Buckley et al. (1985) have given a comprehensive description of distillation column control objectives, which are material balance control, product quality control and satisfaction of constraints. The material balance requires that the average sum of product rates should be equal to average sum of feed rates. Shinskey (1984) recommended that the stream which is the largest as well as the most variable should be used to close the material balance. For product quality control, all the products should meet the respective quality specifications. Pressure must be controlled tightly for the temperature controller to function properly. The overall design should function satisfactorily in the face of possible disturbances in feed, utility and ambient conditions. It should be intended to minimize the impact of these disturbances in the first instance. The column should operate within its design constraints, viz, flooding, pressure drop, reboiler/condenser design, throughput, design pressure/temperature. Overrides control can be used to keep the operation away from constraints. A distillation unit may have a large number of measurements. However, there are some critical parameters which need to be controlled. Lundstrom and Skogestad (1995) explained that a one-feed two-product distillation column has five manipulated variables (flow of reflux, distillates and bottoms, and duty of reboiler and condenser) and at least five controlled variables (liquid holdup in reboiler and condenser, pressure, product 2. Literature Survey 12 compositions, ratioed variables, cascade loops etc). The ratioed variables could be flow of primary control variables ratioed with the feed flow (e.g., L/F, D/F, V/F, B/F) or control variables ratioed with each other (e.g. L/D, V/B). These manipulated and controlled variables could result in numerous control configurations (Shinskey, 1984). This makes the design of control systems difficult. Fortunately, most of these configurations can be ruled out by inspection (Deshpande, 1985). The expression of control loop interaction was first proposed by E.H. Bristol in 1966, which was later named as “relative gain’ and described in detail by Shinskey (1984). McAvoy (1981) extended the Bristol’s steadystate relative gain concept to include the effect of process dynamics (Deshpande, 1985). Skogestad (1997) explained some fundamentals of steady state and dynamic behavior of distillation columns. He provided some short-cut formulas for estimating RGA for different configurations, and various types of control configuration and their selection based on Closed Loop Disturbance Gain (CLDG). Mahoney and Fruehauf1 highlighted the importance of dynamic simulation to assess the suitability and performance of schemes short-listed by steady-state analysis and provided a control design approach. Engelien et al. (2003) discussed the concept and identification of self optimizing control for selecting the controlled variable which can provide optimization effect within acceptable degree of variation. Segoviam-Hernandez et al. (2004) showed that for separation of ternary mixtures, the best scheme depends on the prime control product (lightest, heaviest or intermediate) as predicted by the dynamic analysis. Skogestad and Govatsmark (2002) reviewed the dynamic behaviour of columns with more or fewer stages than required. It is better to have more stages as the system becomes less interactive and thus less sensitive to uncertainty. Also, a pinch zone develops around the 1 www.aspentech.com/publication_files, cited on 01 Jan 2007 2. Literature Survey 13 feed stage, which decouples the two column ends. Ludwig (1997) also suggested adding more trays for controllability. Duvall (1999) described the systematic procedure for analyzing the control schemes for high relative volatility columns taking depropaniser as an example. Hurowitz (1998) discussed various control configurations for the C3 splitter with varying degree of separation. Anderson (1998) discussed the control of xylene-toluene and styrene-EBZ columns. Finally, Hurowitz et al. (2003) compared the distillation column configurations (L/F, V/F; D/F,V/F; L/F,B/F; L/D, V/B; L/D, V/F; L/D, B/F; L/F, V/B; D/F, V/B; and D/F,B/F) and their selection based on reflux ratio. It was concluded that high reflux ratio columns should utilize material balance control, while energy balance control performs better for low reflux ratio columns. To implement the composition control, the controlled variable needs to selected. Since on-line composition analysers have large sampling time, temperature controls are usually utilized to infer the product composition. Luyben (2006) discussed the various criteria used for selecting the tray location for temperature control and provided a comparison for these methods. The criteria discussed are slope of temperature profile, sensitivity, singular value decomposition (SVD) analysis, feed composition disturbance and minimum variability. Luyben (2006) highlighted the advantage of using dynamic analysis as it considers the hydraulic effect of flow changes. Kano et al. (2003) described predictive inferential control, where future compositions are predicted based on online measurement of process variables. He showed that predictive inferential control with temperature cascade performs significantly better than conventional temperature control. 2. Literature Survey 2.3 14 Controller Tuning Distillation operation requires tuning for composition, level, pressure and cascade loops. Level and pressure loops are usually tuned independently as SISO loops while composition control loops require tuning to consider the interaction between the loops. Various methods are available for tuning of SISO controllers. Skogestad (2001) compared the performance of tuning methods available for various processes. The tuning rules for fast response, slow response, disturbance rejection and robustness are discussed. Foley et al. (2005) discussed the various tuning methods based on simplified first order plus dead time models. . There is limited literature available on tuning controllers which interact with each other. Luyben (1990) suggested that for dual ended composition control of distillation columns, where the two control loops interact, one loop can be tuned very tight and the other loop loose. The performance of slow loop will be compromised. Huang and Riggs (2002) described the PID controller tuning methods for composition control loops using auto tune variation (ATV) method to arrive at initial PID parameters. Then the tuning parameters were fine-tuned using a detuning factor which results in minimum IAE and applying Tyreus-Luyben (TL) settings to find corresponding PI tuning parameters. Segoviam-Hernandez et al. (2004) also utilized the IAE criteria to tune the controller parameters for thermally coupled distillation columns. Shinskey (1984) proposed the feed forward control loop for overhead level control loop to improve composition dynamics of a column. He described that IAE for a controller is linearly related to the product of proportional and integral settings. Buckley et al. (1985) described that small hold-ups in the system favor good composition control. 2. Literature Survey 15 Lundstrom and Skogestad (1995) noted that, for some configurations, composition control is independent of tuning of level loop. Skogestad (1997) reviewed the effect of level control on the distillation column performance. He concluded that LV configuration is almost independent of level controller tuning, however, for other configurations improper level controller tuning can make column control difficult. Buckley et al. (1985) described that for level control via reflux flow manipulation (composition control through overhead product flow), fast level control is desirable for good composition control. For maximum product flow smoothening, PI level control with flow cascading has been suggested. Huang and Riggs (2002) tuned Level controllers for sluggish performance. Kister (1990) suggested using tighter level control when accumulator level controls reflux or condensation rate, while loose control is suggested when level controls the product flow. He also suggested using cascade control for smoothest flow variation. Teo et al. (2005) reviewed the various tuning methods of cascade loops and showed that the conventional way of tuning the inner loop followed by the outer loop may lead to suboptimal performance for the primary controlled variable. 2.4 Summary There is vast literature available on various aspects of distillation design and control, viz steady-state and dynamic modeling, design and control objectives, control structure design, controllability and control loop interactions, tuning of controllers, and various tools available for design. However, it is observed that some key design and operational aspects need further research. The performance of control system design at turndown flow is hardly covered in any literature. There is very limited research 2. Literature Survey 16 comparing the configurations based on with and without flow ratioing the manipulated variables with feed flow. Moreover, there is minimal research which outlines the interaction between level controllers and the composition control. Also, the effect of alternative feed tray location is seldom covered in any research. Finally, there is a need to perform a systematic study conducted using rigorous simulation software like Hysys to compare the various control schemes. These aspects are investigated in this study for a depropaniser. 3. Design, Simulation and Control of a Depropaniser 17 Chapter 3 Design, Simulation and Control of a Depropaniser 3.1 Basis and Method A depropaniser column design similar to that defined in the doctoral thesis of Duvall (1999) has been used for this study. Rigorous simulation software: Hysys from Aspentech has been used for simulating this depropaniser. The design is based on the design data and assumptions summarized in Table 3.1. Table 3.1 Steady State Design Data and Assumptions Quantity Feed Bottom Product Overhead Product Vapour Fraction 0 0 0 o Temperature [ C] 93 Saturated Liquid Saturated Liquid Pressure [kPa] Note 1 Note 1 Note 1 Flow Rate [kgmole/h] 1001 Mole Fractions Ethane Propane (Light Key) i-Butane (Heavy Key) n-Butane n-Pentane n-Hexane Overall Stage Efficiency Fluid Package Column Turndown 0.0189 0.3081 0.1055 0.2049 0.1559 0.2067 0.005 0.005 0.69 (Note 2) SRK 0.6 Note 1: Hysys tray utility was used to estimate the column pressure drop and the corresponding feed pressure with condenser pressure at 1712 kPa (absolute). Note 2: Efficiency is considered to be the same for both design and turndown feed flow. 3. Design, Simulation and Control of a Depropaniser 18 The steady-state HYSYS model was then converted to the dynamic model. The key steps requiring this transition are: • sizing of equipments and specifying hold-ups • giving pressure-flow specifications and • adding control valves, controllers and strip charts In dynamics, the pressure drop across equipment is not constant and will be automatically adjusted based on flow changes. All boundary streams (feed and products) need to be supplied with either pressure or flow specification. The internal stream pressure and flows are calculated from the pressure gradient in the process. This is termed as pressure-flow specifications. For depropaniser simulation, the following information is provided for pressure-flow specification for the design case (see Table 3.2): • Control valves are placed on feed and products to aid in pressure-flow specifications. • Feed pressure is fixed at 70 kPa above column inlet pressure. • Pressure drop for control valves and column trays is specified. • Reflux pump pressure rise is specified as 70 kPa . • Conductance through equipments, which includes hold-up for condenser, reboiler and heating medium, is specified. • Condenser outlet temperature is fixed based on saturated liquid as the overhead product. This automatically sets the column pressure The above parameters for design case are converted into pressure-flow relation for the dynamic case and the pressure drop at any other flow rate flow is pro-rated considering pressure drop is proportional to flow squared. Controllers are added to 3. Design, Simulation and Control of a Depropaniser 19 manipulate the stream variables. Strip charts are included to show how the variables change with time. Table 3.2 Design Parameters for Dynamic Simulation Reboiler Reboiler holdup, min Liquid level (at design feed rate) Reboiler Utility Fluid Name Average MW Heat Capacity, kJ/kgmole-oC Inlet Temperature, oC Available UA, kJ/oC-h Holdup, kg-mole 5 50% Therminol-66 252 616 290 162000 1 Condenser (Note 1) Reflux Drum Holdup, min Liquid Level (at design feed rate) 5 50% Tray (Note 2) Type Tray Spacing [mm] Max Flooding [%] Weir Height [mm] Downcomer Clearance [mm] Diameter [m] Sieve 510 85 51 50 3.35 Control Valves Trim Cv Minimum Pressure Drop at Design Flow, kPa Hysys Integration Step, sec Pressure Flow Solver Control and Logical Operations Energy Calculations Composition and Flash Calculations Composition Controllers Sampling plus Dead Time, min Linear Note 3 70 (Note 4) Note 5 0.5 1 1 5 5 Note 1: If cooling water is used as the cooling medium, the flow rate is manually kept higher than required and thus dynamics is not critical. Hence, utility fluid is not modeled for condenser. (Footnote continued on next page) 3. Design, Simulation and Control of a Depropaniser 20 Note 2: Column diameter is calculated using Hysys rating. Other parameters are based on Hysys recommendations and Ludwig (1997) Note 3: Control valve Cv is selected to give 50% opening at design flow. Note 4: Reflux pump is used to provide the necessary head for reflux and overhead product streams. Note 5: With decrease in step time to 1/5th of those selected, the time constant changes by less than 10%, while the simulation time increases by 5 times. Hence, the selected integration step time is based on compromising between the speed and accuracy of simulation. Moreover, this should be adequate for comparison purpose. 3.2 Number of Trays and Feed Tray Location The short-cut distillation method in Hysys is used to estimate minimum reflux ratio and number of trays. The feed flow rate, feed composition and composition of key components in products are defined as per Table 3.1. The external reflux ratio is considered around 1.2 times the minimum reflux ratio as suggested by Lek et al. (2004). The trays are numbered from bottom to top, counting reboiler as 1, Condenser is considered zero stages being ‘total condenser’. Reboiler is considered as one stage. The results of short-cut distillation are summarized in Table 3.3. Based on these results and assumed overall stage efficiency of 0.69, 50 real trays (excluding reboiler) are selected. This number of trays matches with the base case design used by Duvall (1999), which validates the present design. Short-cut distillation suggests tray 25 for feed tray from bottom, which is further reviewed below. However, most widely accepted practice is to set the feed tray location is to minimize boil-up or reflux ratio, which would minimise the reboiler and condenser duties (Lek et al , 2004). Another approach described by Deshpande (1985) is to select a tray for which the key component ratio based on feed composition lies between that of 3. Design, Simulation and Control of a Depropaniser 21 feed tray and a tray above feed tray. The results using these two approaches are shown in Figs. 3.1 and 3.2. For this analysis, trays are numbered from bottom of column with reboiler as 0. Table 3.3 Data for and Results from Short-cut Distillation Parameter Value External Reflux Ratio 2.8 Minimum Reflux Ratio 2.26 Condenser [oC] 44.0 Reboiler [oC] 134.7 Condenser Pressure, kPa Reboiler Pressure, kPa 1712.0 1747.0 Minimum Number of Ideal Trays Number of Ideal Trays for Specified External Reflux Ratio Considering overall efficiency Real Feed Tray Location Number of Real Trays 4.5 16.2 35.7 0.69 26 51 Reflux Ratio Boilup Ratio 3.5 2.5 1.5 19 22 25 28 31 34 Feed Tray Location Fig 3.1 Effect of Feed Tray location on Reflux Ratio and Boil-up Ratio 37 3. Design, Simulation and Control of a Depropaniser Key Component Ratio 5 22 key component ratio-feed tray key comp ratio-tray above feed tray feed composition 4 3 2 1 0 19 22 25 28 31 34 37 Feed Tray Location Fig 3.2 Effect of Feed Tray location on Key Component Ratio Figs. 3.1 and 3.2 indicates that Tray 28 (from bottom) should be selected as the optimum feed tray to minimise energy cost, while the key component ratios suggest tray 34 as feed tray. Since tray 34 would require appreciably higher energy than tray 28, the later one is selected for further study. Since the stage efficiency (Table 3.1) at turndown flow is considered to be the same as at design flow, the reflux ratio and boil-up ratio at these extreme flow conditions will remain the same. Note that the curves in Fig. 3.1 are nearly flat for feed tray location 26 to 30, with less than 1% increase in reflux and boilup ratios above the minimum. Hence, varying the feed tray location within this range will not significantly increase the energy cost. This aspect of design will later be utilized to study the effect of varying the feed tray location (within 26 to 30) on the system dynamics. 3. Design, Simulation and Control of a Depropaniser 3.3 23 Temperatures for Composition Controls Composition analyzers have significant sampling time which adversely affects the composition control of a column. Temperature control is an easy, cheaper, reliable, faster and far more popular means of controlling product compositions (Kister, 1990). A change in the suitably selected temperature represents a corresponding variation in the concentration of key components in the product. The main issues with temperature control instead of composition control are sensitivity and correlation of temperature with composition. The column composition profile for the optimized column design described above is shown in Fig 3.3. This profile indicates that temperature is sensitive to composition of key components (propane and i-butane) between trays 10 to 47. For other trays, temperature is more sensitive to non-key components. 1 Ethane Propane i-Butane n-Butane n-Pentane n-Hexane Mole Fraction 0.8 0.6 0.4 0.2 0 0 10 20 30 40 50 Tray Fig. 3.3 Liquid Composition Versus Tray Number Counted from the Column Bottom For the best location of temperature control, Kister (1990) recommended sensitivity studies using D/F variation within ±0.1% to ±5% change (with reboiler duty kept constant), with lower values for high purity columns and higher value for low purity 3. Design, Simulation and Control of a Depropaniser 24 columns. Mahoney and Fruehauf1 suggests ±1% to ±10% changes in manipulated variable. For the present design, ±1% change in D/F has been used and the results are shown in Fig 3.4. The profiles shown in Figs 3.3 and 3.4 are similar to those provided by Kister (1990) for a depropaniser. Tray 16 is selected for bottom composition control as it shows large temperature variation per unit composition change. Overheads composition control can be done using any tray between 30 and. However, the composition profiles (Fig. 3.3) indicate that trays around 32 should be avoided for temperature control as they show retrograde distillation. Hence, tray 40 is selected for overhead composition control; this gives some margin for feed composition changes affecting the retrograde distillation region. 160 Base Case +1% D/F -1% D/F Temperature 120 80 40 0 0 10 20 Tray No. 30 40 50 Fig. 3.4 Column Temperature Profile for Base Case and ±1% Change in D/F 1 www.aspentech.com/publication_files, cited on 01 Jan 2007 3. Design, Simulation and Control of a Depropaniser 25 Duvall (1999) employed the following equation to infer composition of propane in bottoms and i-Butane in the overheads from temperature of the selected tray. ln(x ) = A + B T (3.1) Constants A and B have been deduced from steady state analysis. For overhead composition, A and B are 65 and -23120 respectively; and, for bottoms composition, A and B are -65 and 22060 respectively. During dynamics, A is kept unchanged while B is adjusted after each composition measurement using equation 1. 3.4 Control Configurations Lunderstrom and Skogestad (1995) described that a distillation column with one feed two product column can be viewed as a 5×5 dynamic system with 5 manipulated variables (inputs) and 5 controlled variables (outputs). The manipulated variables are reflux flow (L), reboiler duty (QR), condenser duty (QC), distillate flow (D) and bottoms flow (B), and the controlled variables are distillate composition (xD), bottoms composition (xB), condenser pressure (PD), condenser holdup (MD) or level, and reboiler holdup (MB) or base level. For a column on pressure control (say using condenser duty), this can be reduced to a 4×4 system, with 4! or 24 possible ways of pairing these variables (Deshpande, 1985). However, most of these schemes can be discarded based on some undesirable factors like control of reboiler level by L or D, control of condenser level by QR or B, etc. Finally, we are left with the first 4 schemes listed in Table 3.4. Additional schemes have been added in this table based on ratioing the variables with respect to F, D or B. Note that for single ended control, one of the manipulated variables for composition control will be free and is not adjusted. A typical process flow diagram (PFD) built in 3. Design, Simulation and Control of a Depropaniser 26 Hysys for L, V; L/F, V/F and L/D, V/B configurations are shown in Figs. 3.5 to 3.7. The terminology used in these figures is as follows: btmliq : Bottom Liquid product FIC : Flow Indicator and Controller IC : Indicator Controller with set point from Spreadsheet LIC : Level Indicator and Controller ovhdliq : Overhead Liquid product P-100 : Reflux Pump Q : Duty stream T-100@Main : Tray used for temperature control TIC : Level Indicator and Controller TRF : Transfer Function, used for specifying sinusoidal disturbance in feed propane composition TRF-1 : Transfer Function, used for specifying sinusoidal disturbance in feed i-butane composition VLV : Control Valve XIC : Composition Indicator and Controller, used only as an indicator 3. Design, Simulation and Control of a Depropaniser 27 Table 3.4: Possible Pairings of Controlled and Manipulated Variables Configuration Bottoms Composition V B V B Condenser Level D D L L Base Level B V B V Reflux/ Boil-up Ratio Schemes L/D, V L/D L/D, B L/D L, V/B L D, V/B D L/D, V/B L/D V B V/B V/B V/B L+D L+D L L D B V V+B V+B B Ratioed with Feed Flow L/F, V/F L/F, B/F D/F, V/F D/F, B/F V/F B/F V/F B/F D D L L B V B V V/F B/F V/B V/B L+D L+D L L B V V+B V+B L, V L, B D, V D, B Overhead Composition L L D D L/F L/F D/F D/F Ratioed with Feed Flow/Reflux/Boil-up L/D, V/F L/D L/D, B/F L/D L/F, V/B D/F D/F, V/B D/F 3. Design, Simulation and Control of a Depropaniser Fig 3.5: PFD for L, V Configuration in Hysys 28 3. Design, Simulation and Control of a Depropaniser Fig 3.6: PFD for L/F, V/F Configuration in Hysys 29 3. Design, Simulation and Control of a Depropaniser 30 Fig 3.7: PFD for L/D, V/B Configuration in Hysys 3.5 RGA Analysis Shinskey (1984) described that each controlled variable in an interacting process is subject to influence by each manipulated variable. The relative gain for a selected pair of variables ci and mj is defined by λi , j = (∂ci / ∂m j ) m=cons tan t (∂ci / ∂m j ) c =cons tan t (3.2) 3. Design, Simulation and Control of a Depropaniser 31 and the relative gain array (RGA) is a square matrix with elements λi, j . For a 2 x 2 system, equation 3.2 can be reduced to one element (say, λ), with other elements derived from this. For this study, the steady state relative gain analysis has been conducted based upon the approach described by Deshpande (1985) using computer simulation. He used ±1% change in measured variables for calculating RGA, however for this study, ±0.5% change is considered to keep the process linear. For each configuration, the relative gain ( λ ) is calculated using the following equation: λm ,m = 1 2 (∂x D / ∂m1 ) m2 =cons tan t (∂x D / ∂m1 ) xB =cons tan t = (∂x B / ∂m2 ) m1 =cons tan t (3.3) (∂x B / ∂m2 ) xD =cons tan t where m1 is the manipulated variable used for control of xD (e.g., L for L, V configuration), m2 is the manipulated variable used for control of xB (e.g., V for L, V configuration), xD is the heavy key component (i-Butane) mole fraction in overhead product, and xB is the light key component (propane) composition in bottoms product. Significance of λ on the control loop is summarized in Table 3.5. Table 3.5 Significance of Relative Gain Value of λ Significance 1 Interaction reduces control effectiveness ∞ Loops are completely dependent 3. Design, Simulation and Control of a Depropaniser 32 Table 3.6 Steady State Relative Gain Configuration λ L, V 3.6 D, V 0.4 L, B 0.7 L/D, V/B 1.8 L/D, V 2.1 L/D, B 0.8 L, V/B 2.4 D, V/B 0.4 D, B ∞ The relative gain analysis of various configurations for dual composition control (Table 3.6) indicates that the best configurations are (L, B); (L/D, B) and (L/D, V/B), while the worst scheme is (D, B). This will be later reviewed using dynamic simulation. Note that the difference in value of λ obtained using -0.5% and +0.5% change in the manipulated variable is not significant to affect the pairing of controlled and manipulated variable. 3.6 Tuning of Level Controllers The level controllers are tuned using two approaches – tight level control (PI) and sluggish level control (P). The intention is to review the best tuning approach for various control configurations. Tight tuning can minimize the liquid holdup requirements in reboiler and reflux drum, while sluggish level tuning has the benefit of smoothening the product flows. Auto-tune variation (ATV) method available in HYSYS is used for tight tuning of a PI controller. This would aim to maintain the reboiler and condenser levels at 50%. The controller parameters using this approach are given in Table 3.7. For controlling the reflux drum levels by L+D (Table 3.4), cascade control is used, as shown in Fig 3.8. 3. Design, Simulation and Control of a Depropaniser 33 The value for L+D is calculated using hysys spreadsheet, which is not visible in the figure. Similar cascade loops are used for reboiler level control by V+B. Fig 3.8: PFD for L/D, V Configuration in Hysys Sluggish level tuning is provided using proportional only controller. The proportional gain (Kc) is selected to maintain 50% level for design flow and 40% level for turndown operation. The level can rise above 50% for higher than design flow. The objective is to maintain level variation within 40% to 60% in order to keep sufficient margin from level alarm levels which are usually set at 20% and 80%. The controller parameters using this approach are given in Table 3.8. 3. Design, Simulation and Control of a Depropaniser 34 Table 3.7 Controller Parameters for Tight Level Tuning in Various Configurations L D L/D Overhead (Notes 1 and 2) Outer Loop Inner Loop Kc Ti Kc Ti 6.9 15.5 5.54 11.0 0.63 44.3 0.94 0.86 Bottoms (Notes 1 and 2) Outer Loop Inner Loop Kc Ti Kc Ti 7.89 14.4 7.89 14.4 7.89 14.4 V B V/B 6.9 6.9 6.9 15.5 15.5 15.5 7.89 5.76 0.94 14.4 82.1 51.6 0.475 0.972 L,V D,V L,B L/D, V/B L/D, V L/D, B L, V/B D, V/B 6.9 5.54 8.18 7.8 0.63 0.633 6.9 5.62 15.5 11 17.2 18.7 44.30 45 15.5 10.3 7.89 7.89 0.65 8.07 7.89 5.04 0.94 0.94 14.4 14.4 822 14.3 14.4 97.4 51.6 51.6 0.475 0.475 0.972 0.972 Configuration 0.94 0.94 0.86 0.86 Note 1: Inner loop and outlet loop parameters are specified for cascade loops. Configurations with no inner loop parameters indicate absence of a cascade loop. Note 2: Units for Kc is %/% and Ti is sec. The above Figure shows that cascade loops are required to implement ratio schemes. The ratios are calculated using Hysys spreadsheet, which becomes the secondary loop, whereas the composition control is the primary loop. Table 3.8 Controller Parameters for Sluggish Level Tuning in Various Configurations Overhead Configuration L D L/D Kc, %/% 2.65 2.86 1.96 Bottoms configuration V B V/B Kc, %/% 1.82 4.15 2.06 3. Design, Simulation and Control of a Depropaniser 3.7 35 Tuning of Composition Controllers The tuning approach used in this study is based the PID controller tuning method described by Huang and Riggs (2002) for composition control loops. It utilises the ATV method and then Tyreus-Luyben (TL) settings to arrive at initial PID parameters. Then the parameters were fine-tuned using a detuning factor which results in minimum IAE for a step change in the set point. Riggs (1998) observed that tuning controllers based upon set point changes provides a good compromise between performance and robustness. Hence, this approach is used for controller tuning. The optimum detuning factor is calculated by using a macro written in visual basic (VB), and using it as an interface with HYSYS. Refer to Appendix A, B, C and D for the details of macros. Typical effect of detuning factors on IAE for single ended flow ratioed configurations is given in Fig 3.9. It can be seen from Tables 3.10 and 3.11 that for most of the configurations, the detuning factors are less than 1, while some schemes require detuning factors above 1 to minimize the IAE. Duvall (1999) also observed that certain configurations required detuning factors above 1 to minimize IAE. The disturbances used for controllers tuning are shown in Table 3.9. Table 3.10 and 3.11 lists the controller parameters used for single and dual ended configurations. The terminology used is: TD : Turndown Flow SL : Sluggish level tuning for both overhead and bottom levels (If suffix SL is missing, this means tight level tuning for both overhead and bottom levels) TS : Tight level tuning for overhead level and sluggish level tuning for bottoms level 3. Design, Simulation and Control of a Depropaniser 36 Table: 3.9 Set Point Changes used for Tuning Composition Controllers Single Ended Composition Control time, min mole fraction Comments Initial HK and LK Set Points 0 0.005 HK or LK Set point change 1 40 0.00375 -25% Set point change 2 240 0.00625 +25% Stop Simulation 520 Dual Ended Composition Control Initial HL and LK Set Points HK Set Point change 1 HK Set Point change 2 LK Set Point change 1 LK Set Point change 2 Stop Simulation time, min 0 20 240 520 760 1040 mole fraction 0.005 0.00375 0.00625 0.00375 0.00625 Comments -25% +25% -25% +25% 25 20 B/F IAE 15 D/F L/F 10 V/F 5 0 0 0.5 1 1.5 2 Detuning Factor Figure 3.9 IAE V/s Detuning Factor for Single Ended Flow Ratioed Configurations 3. Design, Simulation and Control of a Depropaniser Table 3.10 Controller Parameters for Single Ended Composition Control Configuration Detuning Factor L L/F L-SL L-SL LFT L-SL HFT D D/F D-SL D-TS LFT D-TS HFT L/D L/D-SL L/D-SL LFT L/D-SL HFT V V/F V-SL V-SL LFT V-SL HFT B B/F B-SL B-SL LFT B-SL HFT V/B V/B-SL V/B-LFT V/B-HFT 0.4 0.2 0.4 0.4 0.4 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 1.3 0.2 0.2 0.2 0.8 1.3 0.3 0.4 0.3 0.4 0.5 0.4 0.4 Tuning Parameters (Note 1, 2) Outer Loop Inner Loop Kc Ti Kc Ti 1.6 262 3.6 120 0.3 0.5 1.5 309 1.5 309 1.5 309 18.4 97 11.7 95 0.3 0.5 12.8 145 20.3 87 17.6 90 22.5 107 0.2 1.1 24.8 101 0.1 0.8 24.8 101 21.5 103 142.0 20 2.9 264 1.9 7 134.0 23 134.0 23 134.0 23 0.8 658 0.4 1084 0.2 0.8 2.1 305 1.6 406 2.1 305 5.2 172 0.7 11 4.6 199 0.7 12 5.2 172 5.2 172 Note 1: Units for Kc is %/% and Ti is sec. Note 2: Final Tuning Kc = ATV tuning Kc / Detuning Factor. Final Tuning Ti = ATV tuning Ti * Detuning Factor. During Turndown (TD), the tuning parameters are kept same as at design flow. 37 3. Design, Simulation and Control of a Depropaniser 38 Table 3.11 Controller Parameters for Dual Ended Composition Control Bottom Loop (Note 1, 2) Detn Overhead Loop (Note 1, 2) ing Outer Loop Inner Loop Outer Loop Inner Loop Configuration Fact or Kc Ti Kc Ti Kc Ti Kc Ti L,V L/F, V/F L,V-SL L,V-SL, LFT L,V-SL, HFT D,V D/F, V/F D,V-SL D,V-TS D,V-TS LFT D,V-TS HFT L,B L/F, B/F L,B-SL L,B-SL LFT L,B-SL HFT L/D, V/B L/D, V/B-SL L/D,V/B-SL- LFT L/D,V/B-SL- HFT L/D, V L/D, V/F L/D, V-SL L/D,V-SL LFT L/D, V-SL HFT L/D, B L/D, B/F L/D, B-SL L/D, B-LFT L/D,B-SL HFT L, V/B L/F, V/B L, V/B-SL L, V/B-LFT L, V/B-HFT D, V/B D/F, V/B D, V/B-SL D, V/B-LFT D, V/B-HFT 0.3 0.7 0.2 0.2 0.2 0.5 0.4 0.9 0.5 0.5 0.5 1.5 1.4 1.3 1.3 1.3 0.4 0.4 0.4 0.4 1 1 1 0.8 1 0.7 0.8 0.7 1 1.4 0.3 0.8 0.7 0.4 0.3 0.6 0.4 0.4 0.6 0.5 2.1 1.0 3.0 3.2 2.8 7.4 3.0 2.9 7.8 8.1 7.0 0.5 0.5 0.7 0.8 0.7 4.9 7.5 8.0 7.5 4.5 5.0 5.0 6.3 4.3 11.1 9.3 9.4 7.8 4.7 2.1 0.9 1.6 1.6 2.1 6.6 3.0 6.4 6.6 7.9 196.2 418.6 154.6 152.4 151.2 243.5 202.4 652.5 230.0 218.0 225.5 450.0 837.2 564.2 564.2 564.2 207.2 90.8 91.2 90.8 535.0 498.0 504.0 403.2 516.0 243.6 285.6 277.9 348.0 555.8 198.0 480.0 179.2 264.0 198.0 279.0 202.4 292.4 279.0 232.5 0.264 0.479 0.464 0.565 0.264 0.479 0.1 0.06 0.07 0.06 0.166 0.17 0.17 0.17 0.19 0.166 0.17 0.166 0.923 0.781 1.06 0.781 1.06 1.05 1.05 1.05 1.19 1.06 1.05 1.06 0.166 1.06 0.264 0.479 0.464 0.565 93.0 5.3 134.0 146.5 134.0 28.6 5.0 22.4 29.4 32.4 44.8 0.4 0.4 0.5 0.5 0.5 1.7 5.6 5.8 5.6 27.1 5.3 29.2 36.5 29.2 0.9 0.7 0.9 0.6 0.5 6.9 11.9 3.3 5.3 7.0 13.1 17.0 11.7 13.1 15.7 28.4 142.0 23.0 21.8 23.0 70.5 72.4 122.4 76.5 72.0 59.5 1233.0 1167.6 1319.5 1279.2 1319.5 208.4 54.4 62.0 54.4 99.0 128.4 102.0 81.6 102.0 634.2 700.8 718.9 906.0 1437.8 129.0 150.4 277.9 172.0 129.0 110.4 79.6 90.0 110.4 92.0 1.93 7.18 1.93 7.18 0.186 0.775 0.64 0.83 0.83 0.83 19.0 7.14 7.14 7.14 1.85 7.06 0.186 0.775 0.683 0.658 11.4 13.7 0.683 0.658 0.719 11.4 13.7 11.6 Note 1: Units for Kc is %/% and Ti is sec. Note 2: Final Tuning Kc = ATV tuning Kc / Detuning Factor. Final Tuning Ti = ATV tuning Ti * Detuning Factor. During Turndown, the tuning parameters are kept same as at design flow 3. Design, Simulation and Control of a Depropaniser 3.8 39 Open Loop Responses The open loop responses for step change in L (0.7%) and V (0.1%) are given in Figure 3.10. For this, the level loops were closed with tight tuning, while composition tuning loops were open. The open loop response follows deadtime plus first order dynamics (Shinskey, 2002). The corresponding time constants are calculated as time for reaching 63.2% of the final response and summarized in Table 3.12. This emphasizes the importance of dual composition control. Btm Comp- Step Change in L Ovhd Comp-Step Change in L Btm Comp- Step Change in V Ovhd Comp-Step Change in V 0.007 mole fraction 0.006 0.005 0.004 0.003 0 300 600 900 1200 Time (min) Fig 3.10 Open Loop Responses Table 3.12: Time Constant of Composition Response to a Step Change in L and V Overhead Composition Bottoms Composition Step Change in L 160 min 260 min Step Change in V 240 min 200 min 3. Design, Simulation and Control of a Depropaniser 40 Duvall et al (2001) obtained a time constant of approximately 150 min for the same design used for this study. Skogestad and Morari (1988) studied the dynamic response for a range of distillation columns described as A to G. Column A design with 40 trays and 1% impurity at both ends is closest to the column used for this study, with dominant time constant of 194 min. Alsop and Ferrer (2006) obtained the settling time for an industrial 182 trayed propylene/propane splitter as around 2.8 days, which corresponds to a time constant of around 900 min. Hence, the time constants calculated are reasonable for a depropaniser. 3.9 Summary Hysys has been used for steady-state and dynamic simulation of a depropaniser. Short-cut distillation is used to estimate minimum number of trays, which is further used to calculate the actual number of trays using efficiency and actual reflux ratio, thus resulting in 50 real trays. Then, feed tray 28 (from bottom) is selected, based on minimum energy cost. After this, trays 16 and 40 are selected for temperature controls based on sensitivity analysis. Once steady state design is defined, the possible control configurations to be used for analysis are selected. Steady-state relative gain analysis was carried out, which indicates that L, B; L/D, B; and L/D, V/B are the best configurations, while D, B should be avoided. Finally, control loops are tuned for optimum performance. Level controllers are tuned independent of composition loops using both tight and sluggish tuning choices. Once the level loops are tuned, the composition loops are tuned to minimize the IAE. The open loop responses of composition to step changes in the 3. Design, Simulation and Control of a Depropaniser 41 manipulated variable are obtained to understand the process dynamics and validate the dynamic model. 4. Single Ended Composition Control 42 Chapter 4 Single Ended Composition Control Single ended composition control is much easier to implement, tune, control and maintain than dual-composition control (Riggs, 1998). Hence, it is widely used for distillation columns in industry, which makes it important to study single ended composition control in detail. A ‘base case’ dynamic model of depropaniser is built for each single ended control configuration using Hysys simulator and based on fast response of level controls. The performance of the control configurations is tested for feed flow and composition disturbances. The ‘base case’ model is then updated to study the effect of ratioing the manipulated variables with feed flow, turndown, level controller tuning, and feed tray location, on the performance of the control configurations. Results of all these tests on single ended composition control are presented and discussed in this chapter. 4.1 Base case model and control For tuning the PI composition control loops, the method described by Duvall (1999), and Huang and Riggs (2002) has been used. It uses auto tune variation (ATV) method for initial tuning based on step changes in product purity specifications and Tyreus-Luyben (TL) settings to find the PI parameter values. Then these are fine-tuned using a detuning factor which results in minimum IAE. The detuning factors and tuning parameter values are given in Chapter 3. Once the PI parameters of composition control loop are tuned, the performance of different control configurations for the ‘base case’ model is calculated for step 4. Single Ended Composition Control 43 disturbances in feed flow rate and composition, and sinusoidal disturbance in feed composition; details of these disturbances are summarized in Table 4.1. The IAE is calculated for each of these disturbances using a macro written in Visual Basic (VB), and using it as an interface with HYSYS dynamics. Refer to Appendices A to D for the macros and Section 3.4 for details of control configurations studied. Skogestad (1997) suggested that if there is a large disturbance in feed flow to a distillation column, then it is difficult to use a small flow for level control. Hence, this suggests that reflux flow, L (reflux ratio = 2.8) should be used for reflux drum level control and boilup, V (boilup ratio = 1.7) for reboiler level control. This suggests (D, B) configuration; for single-ended composition control; the notation: (D, B) in single ended composition control means using D for overhead or B for bottoms composition control. The performance of various configurations for the depropaniser column for base case is shown in Figure 4.1 to 4.6. Note that the detuning factors used for minimizing IAE are in increments of 0.1, and hence only significant difference in IAE will be considered for comparison and discussion. Feed flow and feed composition are the most common disturbances a column can be subjected to for a long time. Hence, these are mainly used for configuration evaluation. It is evident from Figures 4.1 to 4.3 that, for overhead composition control, configuration D performs best and is marginally better than L/D. This conclusion is in agreement with the results obtained by Skogestad (1997). Configuration D has the advantage that it is less sensitive to feed composition disturbance due to its direct effect on material balance. The level control is by reflux rate which is higher than distillate rate, which again follows the suggestion of Skogestad (1997). 4. Single Ended Composition Control 44 Table 4.1 Details of Disturbances used for Performance Evaluation 1. Set point disturbance in feed composition Component Ethane Propane i-Butane n-Butane n-Pentane n-Hexane Simulation time, min Initial composition (mole fraction) 0.0189 0.3081 0.1055 0.2049 0.1559 0.2067 520 Final composition (mole fraction) 0.0192 0.2928 0.1108 0.2081 0.1590 0.2101 Remarks (Note 1) Normalised -5% in LK +5% in HK Normalised Normalised Normalised Final feed flow 1016 609 520 +1.5% +1.5% 2. Set point disturbance in feed flow design case turndown case Simulation time, min Initial feed flow 1001 600 520 3. Sinusoidal disturbance in feed composition Initial composition Components (mole fraction) Propane 0.3081 i-Butane 0.1055 Frequency range, radians per sec 10-4 to 10-2 Simulation time, min 540 Amplitude ± 1.5% ± 1.5% Note 1: The magnitude of disturbance should be based on expected disturbances in practice. The values used for this study are those used by Duvall (1999), except for feed flow which was not considered in his study. Skogestad (1997) used 1 to 20% change in feed flow rate or composition, and frequency range of 10-4 to 10-1 radians/sec for sinusoidal disturbances. 4. Single Ended Composition Control 45 0.2 IAE for Step Disturbances 0.9 0.8 0.7 0.6 Step Disturbance in Feed Composition 0.18 Step Disturbance in Feed Flow 0.14 0.16 0.5 Sinusoidal Disturbance 0.12 in Feed Composition 0.1 0.4 0.08 0.3 0.06 0.2 0.04 0.1 0.02 0 Max AR for Sinusoidal Disturbance 1 0 L D L/D Single Ended Configurations Figure 4.1: Performance of Various Configurations for Overhead Composition Control for Base Case Temperature controller outputs plotted in Figures 4.2 show that the distillate rate changes (and hence L/D in opposite direction) to account for change in feed rate, while there is no significant change required in L to maintain the product specifications. Similar responses are observed in Figure 4.3, except that the effect of change in feed flow rate is less significant than change in composition. 4. Single Ended Composition Control 46 Heavy Key Composition in Overhead Product 0.0052 L/D 0.00515 0.0051 L D 0.00505 0.005 0.00495 0.0049 0.00485 0.0048 0.00475 0.0047 0 100 200 Temperature Controller Output (%) Time (min) 62 59 L/D L D 56 53 50 47 44 0 100 200 Time (min) Figure 4.2: Closed Loop Response and Temperature Controller Output for Step Disturbance in Feed Composition for Base Case 4. Single Ended Composition Control 47 Heavy Key Composition in Overhead Product 0.00504 0.00503 0.00502 0.00501 0.005 0.00499 0.00498 0.00497 L/D 0.00496 L 0.00495 D 0.00494 0 100 200 300 Temperature Controller Output (%) Time (min) 59 58 57 56 55 54 53 52 51 50 49 48 L/D L D 0 100 200 Time (min) Figure 4.3: Closed Loop Response and Temperature Controller Output for Step Disturbance in Feed Flow for Base Case 300 4. Single Ended Composition Control 48 Step Disturbance in Feed Composition Step Disturbance in Feed Flow Sinusoidal Disturbance in Feed Composition 4.5 4 3.5 3 2.5 0.2 0.18 0.16 0.14 0.12 0.1 2 0.08 1.5 0.06 1 0.04 0.5 0.02 0 Max AR for Sinusoidal Disturbance IAE for Step Disturbances 5 0 V B V/B Single Ended Configurations Figure 4.4: Performance of Various Configurations for Single Ended Bottoms Composition Control for Base Case For bottoms composition control, it is clear from Figures 4.4 to 4.6 that B configuration is very sensitive to feed disturbances compared to the other two configurations. This contradicts the suggestion of Skogestad (1997) that higher flow should be used for level control. For B-control in the depropaniser, the reboiler level will then be controlled using V, which requires vaporizing the excess level by supplying more energy/steam and hence creates additional lag in control. This differs from overhead composition control in that the flow through boilup loop is driven by thermosiphon effect and it is not possible to add any restriction to directly control the boil-up rate. However for designs where a pump is used to provide the necessary pressure (e.g., if a furnace is used as reboiler requiring a large pressure drop), it should be possible to directly control the boil-up rate. Light Key Composition in Bottoms Product 4. Single Ended Composition Control 49 0.006 0.0058 0.0056 0.0054 0.0052 0.005 0.0048 0.0046 0.0044 0.0042 0.004 V/B V B 0 100 200 300 400 500 Temperature Controller Output (%) Time (min) 85 80 75 70 65 60 55 50 45 40 35 V/B V B fbnrvc 0 100 200 300 400 500 Time (min) Figure 4.5: Closed Loop Response and Temperature Controller Output for Step Disturbance in Feed Composition for Base Case Light Key Composition in Bottoms Product 4. Single Ended Composition Control 50 0.00515 0.0051 0.00505 0.005 0.00495 0.0049 0.00485 V/B 0.0048 V 0.00475 B 0.0047 0 100 200 300 400 500 Temperature Controller Output (%) Time (min) 74 V/B V B 69 64 59 54 49 44 39 0 100 200 300 400 500 Time (min) Figure 4.6: Closed Loop Response and Temperature Controller Output for Step Disturbance in Feed Flow for Base Case V configuration is significantly less sensitive to feed disturbances compared to B, and it can be further improved by using V/B configuration. B configuration is unstable and hence not recommended for control (Figure 4.5). Hence, for single ended base case, (D, V) performs better than (L, B) and it can be further improved by using (D, V/B) configuration. 4. Single Ended Composition Control 51 Temperature controller outputs plotted in Figures 4.5 and 4.6 show small changes in B results in large variation in composition, while large changes in V results small composition variation. V/B-control shows most stable controller action and composition. Figure 4.7 shows the typical variation of Amplitude Ratio with feed composition frequency disturbance. It shows that most of the configurations are insensitive to frequencies outside the range of 0.02 rad/min to 0.3 rad/min. These results are quite similar to those obtained by Duvall (1999). 0.2 L D Amplitude Ratio L/D 0.15 V B 0.1 V/B 0.05 0 0.01 0.1 1 Frequency (rad/min) Figure 4.7: Effect of Configuration and Frequency on Amplitude Ratio for Sinusoidal Disturbance in Feed Composition 4.2 Effect of Level Controller Tuning The ‘base case’ model is modified to study the effect of sluggish level (SL) tuning on the composition control performance for the same disturbances as used for the ‘base case’ model (Table 4.1). Sluggish level control is quite commonly used in industry. This has the advantages of smooth hydraulics and minimizing disturbance propagation to downstream units. On the other hand, tight level tuning would require lower liquid hold- 4. Single Ended Composition Control 52 up in reflux drum and reboiler, which is both economical and safer. Hence, the decision between the two should be taken considering all these factors and composition control performance. Here, we will study the effect of level tuning on the column performance. 0.2 Step Disturbance in Feed Composition Step Disturbance in Feed Flow Sinusoidal Disturbance in Feed Composition IAE for Step Disturbances 0.9 0.18 0.8 0.16 0.7 0.14 0.6 0.12 0.5 0.1 0.4 0.08 0.3 0.06 0.2 0.04 0.1 0.02 L/D-SL L/D D-SL L-SL D 0 L 0 Max AR for Sinusoidal Disturbance 1 Single Ended Configurations Figure 4.8: Performance of Various Configurations for Single Ended Overhead Composition Control with Sluggish Level Tuning compared to Base Case (Tight Tuning) Figure 4.8 shows that the response of D configuration to sinusoidal disturbances is deteriorated by sluggish level tuning, while the response for L and L/D configuration are nearly independent of level tuning. Heavy Key Composition in Overhead Product 4. Single Ended Composition Control 53 0.00502 0.00530 0.00501 0.00520 0.005 0.00499 0.00510 0.00498 0.00500 0.00497 0.00490 0.00496 0.00495 0.00480 0.00494 0.00493 0 100 200 L/D 0.00470 L/D-SL 0.00460 300 400 L L-SL 0 100 200 0.00506 0.00504 0.00502 0.005 0.00498 0.00496 0.00494 D 0.00492 D-SL 0.0049 0 100 200 Time (min) Figure 4.9: Comparison of Closed Loop Response between Base Case and Sluggish Level Tuning for a Step Disturbance in Feed Composition Figures 4.8 to 4.10 show that L configuration is unaffected by level tuning, L/D is slightly improved, while D is slightly deteriorated for step disturbances. For configuration D, the overhead composition is controlled by distillate rate, while the reflux drum level sets the reflux rate. For good composition control, the reflux control should be quick. For sluggish level tuning, the response of reflux rate is slow, thus affecting the composition control. This shows that sluggish level tuning is not always the best choice, and is in agreement with Shinskey (1984). 4. Single Ended Composition Control 54 0.00504 0.00503 0.00502 0.00501 0.00500 0.00499 0.00498 0.00497 0.00496 0.00495 0.00494 Heavy Key Composition in Overhead Product 0.00503 0.00502 0.00501 0.005 0.00499 0.00498 L/D 0.00497 L/D-SL 0.00496 0 100 200 300 400 500 L L-SL 0 100 200 300 400 500 0.00504 0.00503 0.00502 0.00501 0.005 0.00499 0.00498 D 0.00497 D-SL 0.00496 0 100 200 300 400 500 Time (min) Figure 4.10: Comparison of Closed Loop Response between Base Case and Sluggish Level Tuning for Step Disturbance in Feed Flow 0.2 Step Disturbance in Feed Composition Step Disturbance in Feed Flow Sinusoidal Disturbance in Feed Composition 4.5 IAE for Step Disturbances 4 3.5 3 0.18 0.16 0.14 0.12 0.1 2.5 2 0.08 1.5 0.06 1 0.04 0.5 0.02 V/B-SL V/B B-SL B V-SL 0 V 0 Single Ended Configurations Figure 4.11: Performance of Various Configurations for Single Ended Bottoms Composition Control with Sluggish Level Tuning compared to Base Case (Tight Tuning) Max AR for Sinusoidal Disturbance 5 Light Key Composition in Bottoms Product 4. Single Ended Composition Control 55 0.0054 0.0054 V/B 0.0053 V 0.0053 V/B-SL V-SL 0.0052 0.0052 0.0051 0.0051 0.005 0.005 0.0049 0.0049 0.0048 0.0048 0.0047 0 100 200 300 400 0.007 0 100 200 300 400 B 0.0065 B-SL 0.006 0.0055 0.005 0.0045 0.004 0.0035 0.003 0 100 200 300 400 Time (min) Light Key Composition in Bottoms Product Figure 4.12: Comparison of Closed Loop Response between Base Case and Sluggish Level Tuning for Step Disturbance in Feed Composition 0.00515 V/B V/B-SL 0.0051 0.00505 0.005 0.00495 0.0049 0 50 100 150 0.0052 0.00515 0.0051 0.00505 0.005 0.00495 0.0049 0.00485 0.0048 0.00475 0.0047 200 0.00505 0.00504 0.00503 0.00502 0.00501 0.005 0.00499 0.00498 0.00497 0.00496 0.00495 V V-SL 0 100 200 300 400 B B-SL 0 100 200 300 400 Time (min) Figure 4.13: Comparison of Closed Loop Response between Base Case and Sluggish Level Tuning for Step Disturbance in Feed Flow 4. Single Ended Composition Control 56 For bottoms composition control, Figures 4.12 and 4.13 show that the performance of V/B-control is unaffected by level tuning. However, B and V configurations show marked improvement in performance by using sluggish level control. Shinskey (1984) described that base level controlled by bottoms product flow is stable and responsive except for kettle reboilers or if the bottom flow is extremely small. In this study, we are using kettle reboiler and performance of V-control is better than B-control, when sluggish level tuning is used, which is in agreement with Shinsky (1984). It can be concluded that for single ended composition control with sluggish level tuning, configuration (D, V) performs better than (L, B), with (L/D, V) being the best choice. 4.3 Effect of Ratioing with feed flow Skogestad (1997) and Riggs (1998) described that ratioing the manipulated variable with feed flow provides self regulation with respect to feed flow and is equivalent to feed forward control. Similarly, he noted that L/D and V/B configurations have self regulation with respect to feed flow. To confirm these, the ‘base case’ model is updated to study the effect of ratioing the manipulated variables with feed flow on their performance for the same disturbances as used for the ‘base case’ model (Table 4.1). Figures 4.14 to 4.16 show that, for L configuration, the response to feed composition disturbance improves substantially by using flow ratioing, while response to feed flow disturbance is nearly unchanged. The performance of D-control for feed flow disturbance is slightly deteriorated by flow ratioing. This can be explained by the large effect mass balance has on the product composition than the reflux rate as illustrated by Skogestad (1988) through the concept of internal and external flows. It can be concluded 4. Single Ended Composition Control 57 that L/F is least sensitive to feed disturbances. This matches with the results obtained by Skogestad (1997), Riggs (1998) and Duvall (1999). Note that L/F control is similar to D and L/D control (Figure 4.14). 1 0.2 Step Disturbance in Feed Composition 0.9 0.18 Step Disturbance in Feed Flow 0.8 0.16 0.7 0.14 0.6 0.12 0.5 0.1 0.4 0.08 0.3 0.06 0.2 0.04 0.1 0.02 L/D D/F L/F D 0 L 0 Max AR for Sinusoidal Disturbance IAE for Step Disturbances Sinusoidal Disturbance in Feed Composition Single Ended Configurations Heavy Key Composition in Overhead Product Figure 4.14: Performance of Various Configurations for Single Ended Overhead Composition Control with Flow Ratioing compared to Base Case 0.00506 0.00520 0.00515 0.00510 0.00505 0.00500 0.00495 0.00490 0.00485 0.00480 0.00475 0.00470 0.00504 0.00502 0.005 0.00498 0.00496 0.00494 L 100 200 D/F 0.0049 L/F 0 D 0.00492 300 0 100 200 300 400 Time (min) Figure 4.15: Comparison of Closed Loop Response between Base Case and Flow Ratioing for Step Disturbance in Feed Composition Heavy Key Composition in Overhead Product 4. Single Ended Composition Control 58 0.00504 0.00503 0.00502 0.00502 0.00501 0.00500 0.005 0.00498 0.00499 0.00496 0.00498 L L/F 0.00494 0 100 200 300 400 D 0.00497 D/F 0.00496 0 100 200 300 400 Time (min) Figure 4.16: Comparison of Closed Loop Response between Base Case and Flow Ratioing for Step Disturbance in Feed Flow For bottoms composition control, flow ratioing V gives significant improvement in IAE for step disturbance in feed composition but similar IAE for the other disturbances (Figures 17 to 19). Both B and B/F configurations are very sensitive to all disturbances. Overall, V/B performs best. Riggs (1998) described that ratioing with feed always improves the performance. However, contrary to that, for (D, B) configurations, the performance due to feed flow disturbance is deteriorated by flow ratioing (D/F, B/F). This can be explained by the large effect that mass balance has on the product composition than the reflux rate, as illustrated by Skogestad (1988). 4. Single Ended Composition Control 59 0.2 4.5 Step Disturbance in Feed Composition 0.18 4 Step Disturbance in Feed Flow 0.16 3.5 Sinusoidal Disturbance in Feed Composition 0.14 3 0.12 0.1 2.5 2 0.08 1.5 0.06 1 0.04 0.5 0.02 V/B B V B/F 0 V/F 0 Max AR for Sinusoidal Disturbance IAE for Step Disturbances 5 Single Ended Configurations Light Key Composition in Bottoms Product Figure 4.17: Performance of Various Configurations for Single Ended Bottoms Composition Control for Flow Ratioing compared to Base Case 0.0054 0.006 0.0053 0.0055 0.0052 0.005 0.0051 0.0045 0.005 0.004 0.0049 V 0.0048 0.0047 0 100 200 300 B 0.0035 V/F B/F 0.003 400 0 100 200 300 Time (min) Figure 4.18: Comparison of Closed Loop Response between Base Case and Flow Ratioing for Step Disturbance in Feed Composition 400 Light Key Composition in Bottoms Product 4. Single Ended Composition Control 60 0.0055 0.00515 0.0054 0.0051 0.0053 0.00505 0.0052 0.0051 0.005 0.005 0.00495 0.0049 V 0.0049 V/F 0.00485 0.0048 B 0.0047 B/F 0.0046 0 100 200 300 0 100 200 300 400 Time (min) Figure 4.19: Comparison of Closed Loop Response between Base Case and Flow Ratioing for Step Disturbance in Feed Flow 4.4 Effect of Turndown The ‘base case’ model is modified to study the effect of turndown (TD) on the performance of the configurations for the same disturbances as used for the ‘base case’ model (Table 4.1). For turndown operation, set points for the tray temperatures have been adjusted to meet the product specifications, which are 56.45oC for overhead (base case: 55.93oC) and 95.7oC for bottoms (base case: 96.5oC) specification. Figure 4.20 and Table 4.2 show that, during turndown, the dynamics could be affected; the time constants have increased substantially. This is due to better distillation performance with higher number of trays (corresponding to turndown flow) than required. Figure 4.20 and Table 4.2 show that, during turndown, the dynamics could be affected; the time constants have increased substantially. 4. Single Ended Composition Control 61 Btm Comp- Step Change in L-TD Ovhd Comp-Step Change in L-TD Btm Comp- Step Change in V-TD Ovhd Comp-Step Change in V-TD 0.007 Btm Comp- Step Change in L Ovhd Comp-Step Change in L Btm Comp- Step Change in V Ovhd Comp-Step Change in V Mole Fraction 0.007 0.006 0.006 0.005 0.005 0.004 0.004 0.003 0.003 0 300 600 900 Time (min) 1200 0 300 600 900 1200 Time (min) Figure 4.20: Comparison of Open Loop Response at Turndown compared to Design Case Table 4.2: Comparison of Time Constants for Composition Response to a Step Change in L and V Step Change in L Step Change in V Design Flow Turndown Design Flow Turndown Overhead Composition 160 min 300 min 240 min 380 min Bottoms Composition 260 min 420 min 200 min 310 min From Figure 4.21, it can be seen that the dynamic performance of all overhead composition control configurations for step disturbances are nearly unaffected or improved at turndown. However, Figure 4.22 and 4.23 shows that the settling time is quite longer at turndown and the IAE could increase if the simulation is run for longer period. Due to complexity of the model and interfacing required with excel macro; it was not possible to run simulation for longer time. The controllers were tuned for design flow and same parameters are used at turndown. For sinusoidal disturbance in feed composition, the performance of L-control is improved at turndown, while D-control is adversely affected. This shows the fast dynamics of L-controls as observed in earlier studies (Riggs, 1998). 4. Single Ended Composition Control 62 L/D control has inherent feed flow compensation due to ratioing the variables; thus, it shows no significant change in performance for turndown operation and any disturbances. 0.2 Step Disturbance in Feed Composition Step Disturbance in Feed Flow Sinusoidal Disturbance in Feed Composition 0.9 IAE for Step Disturbances 0.8 0.18 0.16 0.7 0.14 0.6 0.12 0.5 0.1 0.4 0.08 0.3 0.06 0.2 0.04 0.1 0.02 L/D-SL TD L/D-SL L/D-TD L/D D-SL TD D-SL D-TD D L-SL TD L-SL L-TD 0 L 0 Max AR for Sinusoidal Disturbance 1 Single Ended Configurations Figure 4.21: Performance of Various Configurations for Single Ended Overhead Composition Control for Turndown Flow compared with Base Case Heavy Key Composition in Overhead Product 4. Single Ended Composition Control 63 0.00503 0.00502 0.00520 0.00515 0.00510 0.00501 0.005 0.00505 0.00499 0.00498 0.00500 0.00495 0.00497 0.00496 0.00490 0.00485 0.00495 0.00494 L/D 0.00480 0.00475 L/D-TD 0.00493 L L-TD 0.00470 0 100 200 300 400 0 0.00504 100 200 300 0.00502 0.005 0.00498 0.00496 0.00494 D 0.00492 D-TD 0.0049 0 100 200 300 400 Time (min) Heavy Key Composition in Overhead Product Figure 4.22: Comparison of Closed Loop Response between Base Case and Turndown for Step Disturbance in Feed Composition 0.00503 0.00504 0.00503 0.00502 0.00501 0.00500 0.00499 0.00498 0.00497 0.00496 0.00495 0.00494 L/D 0.00502 L/D-TD 0.00501 0.005 0.00499 0.00498 0.00497 0.00496 0 100 200 300 400 L L-TD 0 100 200 300 400 0.005025 D 0.00502 0.005015 D-TD 0.00501 0.005005 0.005 0.004995 0.00499 0.004985 0.00498 0 100 200 300 400 Time (min) Figure 4.23: Comparison of Closed Loop Response between Base Case and Turndown for Step Disturbance in Feed Flow 4. Single Ended Composition Control 64 0.2 4.5 Step Disturbance in Feed Composition Step Disturbance in Feed Flow Sinusoidal Disturbance in Feed Com position IAE for Step Disturbances 4 3.5 3 0.18 0.16 0.14 0.12 0.1 2.5 2 0.08 1.5 0.06 1 0.04 0.5 0.02 V/B-SL TD V/B-SL V/B-TD V/B B-SL TD B-SL B-TD B V-SL TD V-SL V-TD 0 V 0 Max AR for Sinusoidal Disturbance 5 Single Ended Configurations Figure 4.24: Performance of Various Configurations for Single Ended Bottoms Composition Control for Turndown Flow compared with Base Case From Figures 4.24 to 4.26, it can be seen that the dynamic performance of Bcontrol is improved, while V-SL-control is unaffected at turndown. Similar to L/D control, V/B control has inherent feed flow compensation due to ratioing the variables; thus it shows no significant change in performance for turndown operation and any disturbances. 4. Single Ended Composition Control Light Key Composition in Bottoms Product 0.0054 65 0.0054 V/B 0.0053 V 0.0053 V/B-TD V-TD 0.0052 0.0052 0.0051 0.0051 0.005 0.005 0.0049 0.0049 0.0048 0.0048 0.0047 0 100 200 0 100 200 300 400 0.006 0.0058 0.0056 0.0054 0.0052 0.005 0.0048 0.0046 0.0044 B 0.0042 B-TD 0.004 0 100 200 300 400 Time (min) Light Key Composition in Bottoms Product Figure 4.25: Comparison of Closed Loop Response between Base Case and Turndown for Step Disturbance in Feed Composition 0.00514 0.00512 0.0051 0.00508 0.00506 0.00504 0.00502 0.005 0.00498 0.00496 0.00494 0.00492 0.00515 V/B V/B-TD V 0.0051 V-TD 0.00505 0.005 0.00495 0.0049 0.00485 0 50 100 150 0.0052 0.00515 0.0051 200 0 100 200 300 400 B B-TD 0.00505 0.005 0.00495 0.0049 0.00485 0.0048 0.00475 0.0047 0 100 200 300 400 Time (min) Figure 4.26: Comparison of Closed Loop Response between Base Case and Turndown for Step Disturbance in Feed Flow 4. Single Ended Composition Control 4.5 66 Effect of feed tray location The ‘base case’ model is updated to study the effect of changing the feed tray location on the performance of control configurations for the same disturbances as used for the ‘base case’ model (Table 4.1). Simulation models are generated for lower feed tray (LFT, with feed tray located 2 trays below normal feed tray used for above simulations) and higher feed tray (HFT, with feed tray located 2 trays above normal feed tray used for above simulations). Moving the feed tray affects the steady-state and dynamic performance of the column. These effects are described below. Locating feed tray closer to the product reduces the number of trays available for separation, thus adversely affecting the steady-state performance. This effect is less pronounced if there is lot of margin in selecting number of trays or during turndown operation. In order to remove this effect from the analysis, the simulations are first updated to provide design compositions at both ends, before applying any disturbance. These are summarized in Table 4.3, which shows that the effect of changing feed tray is more pronounced in overhead composition than the bottom one. Moreover, temperature set point in bottoms composition does not show significant variation. Moving the feed tray closer to product end decreases the time (dynamic performance) from feed to controlled tray thus tending to improve the response. Table 4.3: Comparison of Temperature Control Set Points Required for Controlling Overhead and Bottoms Composition at Design Flow Temperature Control Normal Feed Lower Feed Tray Higher Feed Tray Location for controlling: Tray (LFT) (HFT) Overhead Composition 55.93oC 55.60oC 56.44oC Bottoms Composition 96.50oC 96.50oC 96.34oC 4. Single Ended Composition Control 67 Feed disturbances could affect the quality of feed (if the feed is routed through an exchanger, vapor fraction of feed could change), which in turn affects the response. These effects are not covered in this study. For liquid feed, sudden change in feed flow disturbs the temperature profile of the bottom section thus affecting the bottoms specification, while there is no immediate effect on the overhead product purity. Hence, for liquid feed, it may be better to locate the feed tray higher (or temperature control tray higher, closer to the feed tray) to minimize disturbance effect on temperature at reboiler. Although the effect of vapour feed is not included in this study, it can be argued that, for vapour feed, sudden increase in feed flow would tend to disturb the temperature profile of the upper section of column thus affecting the distillate specification, while there is no immediate effect on the bottoms product purity. Hence, for vapour feed, it would be better to locate the feed tray lower (or temperature control tray lower, closer to the feed tray) to minimize disturbance effect on temperature in condenser. The resulting performance with different feed tray locations will be a combination of the effects described above. In order to review the effect of feed tray location, the base configuration to be compared is selected as the better among the base case and sluggish level tuning (section 4.2). Figure 4.27 shows that, for L and D configurations, higher feed tray slightly improves the dynamic performance of overhead composition control for step disturbances. This can be attributed to decrease in the time required from feed to controlled tray. L/D performance is slightly deteriorated at higher feed tray. In general, for bottoms composition control, higher feed tray shows slightly better performance than lower feed tray (Figure 4.28). This could be attributed to liquid feed effect described 4. Single Ended Composition Control 68 above. Overall, there is no significant improvement by changing the feed tray location for single ended composition control. 0.2 0.9 0.18 Step Disturbance in 0.16 Feed Composition Step Disturbance in 0.14 Feed Flow Sinusoidal Disturbance 0.12 in Feed Composition IAE for Step Disturbances 0.8 0.7 0.6 0.5 0.1 0.4 0.08 0.3 0.06 0.2 0.04 0.1 0.02 L/D-SL HFT L/D-SL LFT L/D-SL D-TS HFT D-TS LFT D-SL D L-SL HFT L-SL LFT 0 L-SL 0 Max AR for Sinusoidal Disturbance 1 Single Ended Configurations Figure 4.27: Performance of Various Configurations for Single Ended Overhead Composition Control with lower (LFT) or higher (HFT) Feed Tray Location compared with base configuration (TS shows that the overhead level is tightly tuned, while bottoms level has sluggish tuning) 4. Single Ended Composition Control 69 1 IAE for Step Disturbances 0.8 0.7 0.6 0.18 Step Disturbance in Feed Composition Step Disturbance in Feed Flow Sinusoidal Disturbance in Feed Composition 0.16 0.14 0.12 0.5 0.1 0.4 0.08 0.3 0.06 0.2 0.04 0.1 0.02 V/B-HFT V/B-LFT V/B-SL B-SL HFT B-SL LFT B-SL TD B-SL V-SL HFT V-SL LFT 0 V-SL 0 Max AR for Sinusoidal Disturbance 0.9 0.2 Single Ended Configurations Figure 4.28: Performance of Various Configurations for Single Ended Bottoms Composition Control with lower (LFT) or higher (HFT) Feed Tray Location compared with base configuration 4.6 Summary Each control configuration of a column has its own sensitivity to different disturbances and operational changes. Feed flow and composition are the most common disturbances a column can be subjected for a long time. The performance of single ended composition control configurations for the ‘base case’ deproponiser (i.e., tight level tuning, no flow ratioing and design operation) is studied for disturbances in feed flow rates, feed composition, sinusoidal feed composition. Then, the effect of changes (ratioing to feed flow rate, turndown operation, level tuning and feed tray location) in base case 4. Single Ended Composition Control 70 configurations, on control performance is studied. Main results of these studies are summarized below. Base Case (D, V) performs better than (L, B) and it can be further improved by using (D, V/B) configuration Sluggish B, V: Substantial improvement by sluggish level tuning Level L, L/D, V/B: Nearly independent of level tuning Tuning D: Adversely affected by sluggish level tuning (D, V) performs better than (L, B), with (L/D, V) being the best configuration. Feed Composition Feed Flow Sinusoidal Disturbance Flow All configurations D, B: Deteriorate L: Improves Ratioing improve L, V: Unchanged D, V, B: Unchanged Turndown L, B: Improve L/D, V/B, V-SL: Unchanged D, V: Deteriorate Feed Tray Higher feed tray shows slightly better performance than lower (except for Location L/D) Considering all above factors, it can be concluded that the L/D configuration (with sluggish tuning for reflux drum level), and V/B (with either tight or sluggish tuning for reboiler level) is the best configuration for single ended composition control. It is evident that the best configuration depends on the column design, expected disturbances and the operating envelope. Hence, it is recommended to perform a rigorous dynamic simulation to study these aspects and provide meaningful conclusions. 5. Dual Ended Composition Control 71 Chapter 5 Dual Ended Composition Control The major disadvantage with single ended control is the higher energy cost as the uncontrolled end may over-purify the product. Dual ended control is designed to control the composition at both ends of the column. If the control structure is selected and tuned adequately, dual ended control gives advantage over single ended control in terms of reduced product variability and hence reduced energy cost at the cost of increased complexity, investment and coupling. A ‘base case’ dynamic model of depropaniser is built for each dual-ended control configuration using Hysys simulator and based on fast response of level controls. The ‘base case’ model is modified to study the effect of various parameters on performance of control configurations. These parameters are ratioing the manipulated variables with feed flow, turndown, level controller tuning, and feed tray location. 5.1 Base case model and control For tuning the PI composition control loops, the method described earlier for single ended control in section 4.1 has been used for tuning dual ended composition loops also. It uses auto tune variation (ATV) method for initial tuning based on step changes in product purity specifications and Tyreus-Luyben (TL) settings to find corresponding PI tuning parameters. Then the tuning parameters for overhead and bottoms composition control are fine-tuned simultaneously by using a common detuning factor which results in minimum IAE. The final detuning factors and tuning constants are given in Chapter 3. 5. Dual Ended Composition Control 72 Once the PI tuning parameters of composition control loops are tuned, the performance of different control configurations for the ‘base case’ model is calculated for step disturbances in feed flow rate and composition, and sinusoidal disturbance in feed composition; details of these disturbances are summarized in Table 4.1. The IAE is calculated for each of these disturbances by using a macro written in Visual Basic (VB), and using it as an interface with HYSYS dynamics. Refer to Appendices C and D for the macros and section 3.4 for the details of configurations used for analysis. The performance of column for various configurations of depropaniser for base case is shown in Figure 5.1 to 5.3. Note that the detuning factors used for minimizing IAE are in increments of 0.1, and hence only significant difference in IAE will be considered for comparison and discussion. Feed flow and feed composition are the most common disturbances a column can be subjected to for long time. Hence, these are mainly used for configuration evaluation. 25 Overhead Composition for change in Feed Composition Bottoms Composition for change in Feed Composition Overhead Composition for change in Feed flow Bottoms Composition for change in Feed flow Overhead Composition for change in Feed Composition Bottoms Composition for change in Feed Composition 0.4 0.3 0.2 D, V/B 0 L, V/B 0.1 L/D, B D, V/B L, V/B L/D, B L/D, V L/D, V/B L,B D,V L,V 0 0.5 L/D, V 5 0.6 L/D, V/B 10 0.7 L,B 15 0.8 D,V 20 L,V Max AR for Sinusoidal Disturbance IAE for Step Disturbances 1 0.9 Dual Ended Configurations Figure 5.1: Performance of Various Configurations for Dual Ended Composition Control for Base Case 5. Dual Ended Composition Control 73 0.0053 D,V/B-HK 0.0052 D,V-HK 0.0055 L/D,B-HK 0.0053 0.0051 0.0052 0.005 0.0051 0.005 0.0049 0.0049 0.0048 0.0048 0.0047 0.0047 0 100 200 300 0.0053 0.00525 400 0 L/D,V/B-HK 0.005 0.0045 0.004 0.0049 0.00485 0.0035 0.003 100 200 300 0.0054 0.0053 0.0052 0.0051 0.005 0.0049 0.0048 0.0047 0.0046 0.0045 0.0044 400 D,V/B-LK 300 100 200 300 400 0.0053 500 L,V/B-LK 0.0052 D,V-LK 400 L,V-HK 0 500 200 L,B-HK 0.0065 0.006 0.0055 0.00505 0.005 0.00495 0 100 0.0075 0.007 L/D,V-HK 0.0052 0.00515 0.0051 Composition of Key Components in Products L,V/B-HK 0.0054 L/D,B-LK 0.0051 0.005 0.0049 0.0048 0.0047 0 100 200 0.0054 300 0.0065 L/D,V-LK 0.0053 0 L/D,V/B-LK 0.0052 100 200 300 L,B-LK 0.006 L,V-LK 0.0055 0.0051 0.005 0.005 0.0045 0.0049 0.004 0.0048 0.0047 0.0035 0 100 200 300 400 0 100 200 300 400 Time (min) Figure 5.2a: Closed Loop Response for Step Disturbance in Feed Composition for Base Case 5. Dual Ended Composition Control 49 74 64 D,V/B-OP 48 62 DV-OP 47 60 46 58 L,V/B-OP 45 56 L/D,B-OP 44 54 43 52 42 50 0 100 200 300 Temperature Controller Output (%) 63 400 500 100 200 300 57 L/D,V-OP 62 0 L/D,V/B-OP 55 61 53 60 51 59 49 58 47 57 L,B-OP L,V-OP 45 0 100 200 300 400 80 75 70 65 60 55 50 45 40 500 0 100 200 300 400 500 58 D,V/B-OPb 56 DV-OPb 54 L,V/B-OPb 52 L/D,B-OPb 50 48 0 100 200 300 70 65 L/D,V-OPb 60 L/D,V/B-OPb 55 50 0 100 200 300 0 100 200 300 100 90 80 70 60 50 40 30 20 400 400 L,B-OPb L,V-OPb 0 100 200 300 400 500 Time (min) Figure 5.2b: Temperature Controller Output for Step Disturbance in Feed Composition for Base Case 5. Dual Ended Composition Control 0.00515 75 D,V/B-HK 0.0051 L,V/B-HK 0.00515 DV-HK 0.00505 0.0051 0.005 0.00505 0.00495 0.005 0.0049 0.00495 0.00485 L/D,B-HK 0.0049 0 Composition of Key Components in Products 0.0052 100 200 300 0.00508 0.00506 0.00504 0.00502 0.005 0.00498 0.00496 0.00494 0.00492 400 500 0 0.0065 L/D,V-HK L/D,V/B-HK 100 200 300 L,B-HK 0.006 L,V-HK 0.0055 0.005 0.0045 0.004 0.0035 0 100 200 300 0.00525 0.0052 0.00515 0.0051 0.00505 0.005 0.00495 0.0049 0.00485 0.0048 0.00475 400 500 D,V/B-LK DV-LK 0 100 200 300 0.0054 400 500 L,V/B-LK 0.0052 L/D,B-LK 0.005 0.0048 0.0046 0.0044 0 100 200 300 0.00508 0.00506 0.00504 0.00502 0.005 0.00498 0.00496 0.00494 0.00492 400 500 L/D,V-LK L/D,V/B-LK 0 100 200 300 0 100 200 300 0.0058 0.0056 0.0054 0.0052 0.005 0.0048 0.0046 0.0044 0.0042 0.004 400 400 L,B-LK L,V-LK 0 100 200 300 400 Time (min) Figure 5.3a: Closed Loop Response for Step Disturbance in Feed Flow for Base Case 500 5. Dual Ended Composition Control 52.5 52 51.5 51 50.5 50 49.5 49 48.5 48 76 58 D,V/B-OP DV-OP 57 L/D,B-OP 56 55 54 53 0 100 200 300 57.5 400 500 56.5 56 55.5 55 0 100 200 300 64 62 400 500 100 200 300 L,B-OP L,V-OP 0 100 200 300 400 500 56 D,V/B-OPb 55 54 DV-OPb 60 58 0 57 56 55 54 53 52 51 50 49 L/D,V-OP L/D,V/B-OP 57 Temperature Controller Output (%) L,V/B-OP L,V/B-OPb L/D,B-OPb 53 52 56 54 51 50 52 50 49 0 100 200 300 62 61 60 59 58 57 56 55 54 400 0 500 100 200 300 100 L/D,V-OPb L/D,V/B-OPb 400 L,B-OPb 90 L,V-OPb 80 70 60 50 40 0 100 200 300 400 0 100 200 300 400 Time (min) Figure 5.3b: Temperature Controller Output for Step Disturbance in Feed Flow for Base Case 500 5. Dual Ended Composition Control 77 It is clear from Figures 5.1 to 5.3 that configurations (D,V/B), (D,V) and (L,V/B) are stable for all disturbances, with (D,V) control being the best performance. The configurations (L,B), (L,V), (L/D,B), and (L/D,V/B) are not stable for at least one of the disturbances, hence these are not recommended. Configurations (L,V) and (L,B) are highly sensitive to disturbances. Where L is used for overhead composition control, the reflux drum level is controlled by distillate rate. The tight tuning for level control adversely affects the flexibility for L to control the composition. Where B is used for bottom composition control, the reboiler level will be controlled using V, which requires vaporizing the excess level, and hence creates additional lag in control. It is interesting to note that L-control for overhead composition is a feasible option when V/B-control is used for bottom composition. This can be explained by minimizing the disturbance propagation from bottom section to the top of the column. Temperature controller outputs plotted in Figures 5.2b and 5.3b show similar pattern to composition output in Figures 5.2a and 5.2b. L, V-control shows large fluctuations in controller outputs owing to tight tuning of level controllers. Moreover, the effect of change in feed flow rate is less significant than change in composition. The changes required in B to maintain the specifications are small, which makes it a very sensitive variable for control. 5.2 Effect of Level Controller Tuning The ‘base case’ model is modified to study the effect of sluggish level (SL) tuning on the composition control performance for the same disturbances as used for the ‘base case’ model (Table 4.1). Sluggish level control is quite commonly used in industry. This 5. Dual Ended Composition Control 78 has the advantage of smooth hydraulics and minimizing disturbance propagation to downstream units. On the other hand, tight level tuning would require lower liquid holdup in reflux drum and reboiler, which is both economical and safer. Overhead Composition for change in Feed Composition Bottoms Composition for change in Feed Composition Overhead Composition for change in Feed flow Bottoms Composition for change in Feed flow IAE for Step Disturbances 25 20 15 10 5 D, V/B-SL D, V/B L, V/B-SL L, V/B L/D, B-SL L/D, B L/D, V-SL L/D, V L/D, V/B-SL L/D, V/B L,B-SL L,B D,V-SL D,V L,V-SL Overhead Composition for change in Feed Composition Bottoms Composition for change in Feed Composition 0.8 0.7 0.6 0.5 0.4 0.3 0.2 D, V/B-SL D, V/B L, V/B-SL L, V/B L/D, B-SL L/D, B L/D, V-SL L/D, V L/D, V/B-SL L/D, V/B L,B-SL L,B D,V-SL D,V 0 L,V-SL 0.1 L,V Max AR for Sinusoidal Disturbance L,V 0 Dual Ended Configurations Figure 5.4: Performance of Various Configurations for Dual Ended Overhead Composition Control with Sluggish Level Tuning compared to Base Case (Tight Tuning) 5. Dual Ended Composition Control 79 0.0054 0.0054 D,V/B-HK 0.0053 D,V/B SL-HK 0.0052 0.0053 0.0052 0.0051 0.0051 0.005 0.005 0.0049 0.0049 0.0048 0.0048 0.0047 0.0047 0 100 200 300 400 0.0055 Heavy Key Composition in Overhead Product D,V-HK D,V SL-HK D,V TS-HK L,V/B-HK 0.0054 L,V/B SL-HK 0.0053 0.0052 0.0051 0.005 0.0049 0.0048 0.0047 0 100 200 0.0053 0.00525 0.0052 0.00515 0.0051 0.00505 0.005 0.00495 0.0049 0.00485 L/D,V SL-HK 100 200 300 400 100 200 L/D,B SL-HK 0 100 200 0.0052 0.00515 0.0051 0.00505 0.005 0.00495 0.0049 0.00485 0.0048 0.00475 L,B-HK 0.0058 L,B SL-HK 0.0056 300 400 L/D,V/B-HK L/D,V/B SL-HK 0 500 400 L/D,B-HK 100 200 0.006 0.0075 0.007 0.0065 0.006 0.0055 0.005 0.0045 0.004 0.0035 0.003 300 0.0051 0.00508 0.00506 0.00504 0.00502 0.005 0.00498 0.00496 0.00494 0.00492 0.0049 300 L/D,V-HK 0 0 500 300 400 500 L,V-HK L,V SL-HK 0.0054 0.0052 0.005 0.0048 0.0046 0.0044 0 100 200 300 400 500 0 100 200 Time (min) Figure 5.5: Comparison of Closed Loop Response between Base Case and Sluggish Level Tuning for Step Disturbance in Feed Composition 5. Dual Ended Composition Control 0.0052 0.00515 0.0051 0.00505 0.005 0.00495 0.0049 0.00485 0.0048 80 0.0055 0.0054 0.0053 0.0052 0.0051 0.005 0.0049 0.0048 0.0047 0.0046 D,V/B-HK D,V/B SL-HK 0 100 200 0.0052 300 400 L,V/B SL-HK 0.0051 Heavy Key Composition in Overhead Product 0.00505 0.005 0.00495 0.0049 0 100 0.0051 0.00508 0.00506 0.00504 0.00502 0.005 0.00498 0.00496 0.00494 0.00492 0 100 0.00508 0.00506 0.00504 0.00502 0.005 0.00498 0.00496 0.00494 0.00492 0.0049 L,V/B-HK 0.00515 DV-HK D,V SL-HK D,V TS-HK 200 L/D,B-HK L/D,B SL-HK 0 100 0.00508 0.00506 0.00504 0.00502 0.005 L/D,V-HK L/D,V SL-HK 200 200 300 400 L/D,V/B-HK L/D,V/B SL-HK 0.00498 0.00496 0.00494 0.00492 0 0.0065 100 200 300 400 500 100 200 0.0058 L,B-HK L,B SL-HK 0.006 0 300 L,V-HK L,V SL-HK 0.0056 0.0054 0.0055 0.0052 0.005 0.005 0.0048 0.0045 0.0046 0.004 0.0044 0 100 200 300 400 500 0 100 200 300 Time (min) Figure 5.6: Comparison of Closed Loop Response between Base Case and Sluggish Level Tuning for Step Disturbance in Feed Flow 5. Dual Ended Composition Control 0.0054 0.0053 0.0052 0.0051 0.005 0.0049 0.0048 0.0047 0.0046 0.0045 0.0044 81 0.0053 D,V/B-LK D,V/B SL-LK 0.0051 0.005 0.0049 0.0048 0.0047 0 100 200 0.0055 L,V/B-LK L,V/B SL-LK 0.0054 0.0053 0 100 0.0058 0.0056 0.0054 200 L/D,B-LK L/D,B SL-LK 0.0052 0.005 0.0048 0.0046 0.0044 0.0042 0.004 0.0052 Light Key Composition in Bottoms Product D,V-LK D,V SL-LK D,V TS-LK 0.0052 0.0051 0.005 0.0049 0.0048 0 100 200 0.0053 300 100 200 0.0054 L/D,V-LK 0.0052 0 L/D,V SL-LK 400 L/D,V/B-LK 0.0053 0.0051 300 L/D,V/B SL-LK 0.0052 0.0051 0.005 0.005 0.0049 0.0049 0.0048 0.0048 0.0047 0.0047 0.0046 0 0.007 100 200 0.006 0.0058 0.0056 0.0054 0.0052 0.005 0.0048 0.0046 0.0044 0.0042 0.004 L,B-LK 0.0065 L,B SL-LK 0.006 0.0055 0.005 0.0045 0.004 0.0035 0.003 0 100 200 0 300 400 500 100 200 300 400 L,V-LK L,V SL-LK 0 100 200 300 Time (min) Figure 5.7: Comparison of Closed Loop Response between Base Case and Sluggish Level Tuning for Step Disturbance in Feed Composition Light Key Composition in Bottoms Product 5. Dual Ended Composition Control 0.00525 0.0052 0.00515 0.0051 0.00505 0.005 0.00495 0.0049 0.00485 0.0048 0.00475 82 0.00508 0.00506 0.00504 0.00502 0.005 D,V/B-LK D,V/B SL-LK DV-LK D,V SL-LK D,V TS-LK 0.00498 0.00496 0.00494 0.00492 0 100 0.00503 0.00502 0.00501 0.005 0.00499 0.00498 0.00497 0.00496 0.00495 0.00494 200 300 400 0 0.0065 L,V/B-LK L,V/B SL-LK 100 200 L/D,B-LK L/D,B SL-LK 0.006 0.0055 0.005 0.0045 0.004 0 100 200 0.00503 0 100 0.00508 0.00506 0.00504 0.00502 0.005 0.00502 0.00501 0.005 0.00499 L/D,V-LK L/D,V SL-LK 0.00496 0 100 200 0.0065 300 400 L,B-LK L,B SL-LK 0.006 0.0055 0.005 0.0045 0.004 0 100 200 300 300 400 500 L/D,V/B-LK L/D,V/B SL-LK 0.00498 0.00496 0.00494 0.00492 0.00498 0.00497 200 400 0 100 200 0.0058 0.0056 0.0054 0.0052 0.005 0.0048 0.0046 0.0044 0.0042 0.004 500 300 400 L,V-LK L,V SL-LK 0 100 200 Time (min) Figure 5.8: Comparison of Closed Loop Response between Base Case and Sluggish Level Tuning for Step Disturbance in Feed Flow 5. Dual Ended Composition Control 83 Figure 5.4 to 5.8 shows that the performance of (L/D,V/B) and (L,V) are significantly improved by sluggish level tuning. Some configurations like (D,V), (L/D,B) and (D,V/B) shows deterioration with sluggish level. Configurations (L,B), (L/D,V), (L,V/B) and (D,V-TS) are unaffected by level tuning. With sluggish level tuning, configurations (L,V), (D,V-TS), (L,V/B), and (L/D,V/B) are stable configurations. TS shows that overhead (reflux drum) level is tight tuned, while bottoms (reboiler) level is sluggish tuned. The improvement in performance for (L,V) is mainly due to better overhead composition control. The reflux drum level is not held tight, which minimizes the interaction between composition and level control. The improvement in (L/D,V/B) is also for similar reasons. The deterioration in (D,V) is due to sluggish control of overheads composition. When D-control is used for overhead composition, the reflux drum level sets the reflux rate which directly affects the composition. For good composition control, the reflux control should be quick. For sluggish level tuning, the response of reflux rate is slow, thus affecting the composition control. Where B-control is used for bottom composition, the control performance is not improved by sluggish level tuning. As explained earlier, for these configurations, the reboiler level will be controlled using V, which requires vaporizing the excess level, and hence creates additional lag in control. 5. Dual Ended Composition Control 5.3 84 Effect of Ratioing with feed flow Skogestad (1997) described that ratioing the manipulated variable with feed flow provides self regulation with respect to feed flow and is equivalent to feed forward control. Similarly, he noted that L/D and V/B configurations have self regulation with respect to feed flow. The ‘base case’ model is modified to study the effect of ratioing the manipulated variables with feed flow on their performance for the same disturbances as used for the ‘base case’ model (Table 4.1). As per Figures 5.9 to 5.13, the performance of (L,V) configuration is substantially improved by flow ratioing. For all other configuration flow ratioing has little effect on the performance. Overall, with flow ratioing, schemes (L,V), (D,V), and (L,V/B) are stable configurations. (L/F,V/F)-control has the advantage of good energy balance and material balance control, the material balance control, which makes this control attractive over other configurations. It is interesting to note that (L/F,V/B) is also attractive scheme as the material balance is set through L/F, while V/B minimizes the propagation of disturbances from bottom to top section of column. As observed earlier, configurations where B-control is used for bottom composition are very sensitive to disturbances and these cannot be improved by flow ratioing. 5. Dual Ended Composition Control Overhead Composition for change in Feed Composition Bottoms Composition for change in Feed Composition Overhead Composition for change in Feed flow Bottoms Composition for change in Feed flow 25 IAE for Step Disturbances 85 20 15 10 5 D/F, V/B D, V/B L/F, V/B L, V/B L/D, B/F L/D, B L/D, V/F L/D, V L/D, V/B L/F, B/F L,B D/F, V/F D,V L/F, V/F Overhead Composition for change in Feed Composition Bottoms Composition for change in Feed Composition 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 D/F, V/B D, V/B L/F, V/B L, V/B L/D, B/F L/D, B L/D, V/F L/D, V L/D, V/B L/F, B/F L,B D/F, V/F D,V 0 L/F, V/F 0.1 L,V Max AR for Sinusoidal Disturbance L,V 0 Dual Ended Configurations Figure 5.9: Performance of Various Configurations for Dual Ended Composition Control with Flow Ratioing compared to Base Case Heavy Key Composition in Overhead Product 5. Dual Ended Composition Control 0.0053 0.0052 0.0051 0.005 0.0049 0.0048 0.0047 0.0046 0.0045 0.0044 86 0.00515 0.0051 0.00505 0.005 0.00495 0.0049 0.00485 D,V/B-HK D/F,V/B-HK D,V-HK D/F,V/F-HK 0.0048 0.00475 0 100 200 0.0055 0.0054 0.0053 0.0052 0.0051 0.005 0.0049 0.0048 0.0047 300 0 0.0052 0.00515 0.0051 0.00505 0.005 L,V/B-HK L/F,V/B-HK 100 200 300 200 300 L/D,B-HK L/D,B/F-HK 0.00495 0.0049 0.00485 0.0048 0 100 200 0.0053 0.00525 0.0052 0.00515 0.0051 0.00505 0.005 0.00495 0.0049 0.00485 0.0075 0.007 0.0065 0.006 0.0055 0.005 0.0045 0.004 0.0035 0.003 L/D,V-HK L/D,V/F-HK 0 100 200 300 0.0059 400 0 500 100 L,B-HK L/F,B/F-HK 0 100 200 300 400 L,V-HK 0.0057 L/F,V/F-HK 0.0055 0.0053 0.0051 0.0049 0.0047 0.0045 0 100 200 300 Time (min) Figure 5.10: Comparison of Closed Loop Response between Base Case and Flow Ratioing for Step Disturbance in Feed Composition 500 5. Dual Ended Composition Control 0.00515 87 0.0051 D,V/B-HK 0.0051 D/F,V/B-HK 0.00505 0.00505 0.005 Heavy Key Composition in Overhead Product 0.005 0.00495 0.00495 0.0049 0.0049 0 100 200 0.0052 300 400 D/F,V/F-HK 0 100 200 0.0051 L,V/B-HK 0.00515 DV-HK L/F,V/B-HK 0.0051 L/D,B-HK L/D,B/F-HK 0.00505 0.00505 300 0.005 0.005 0.00495 0.00495 0.0049 0.0049 0 100 0.00508 200 0.0065 L/D,V-HK 0.00506 0.00504 0 200 300 400 200 300 400 L,B-HK 0.006 L/D,V/F-HK 100 L/F,B/F-HK 0.0055 0.00502 0.005 0.005 0.00498 0.00496 0.0045 0.00494 0.004 0 100 200 0.0058 300 400 0 100 L,V-HK 0.0056 0.0054 L/F,V/F-HK 0.0052 0.005 0.0048 0.0046 0.0044 0 100 200 Time (min) Figure 5.11: Comparison of Closed Loop Response between Base Case and Flow Ratioing for Step Disturbance in Feed Flow 5. Dual Ended Composition Control 0.0056 0.0053 D,V/B-LK 0.0054 Light Key Composition in Bottoms Product 88 D,V-LK 0.0052 D/F,V/B-LK 0.0052 0.0051 0.005 0.005 0.0048 0.0049 0.0046 0.0048 0.0044 D/F,V/F-LK 0.0047 0 100 200 0.0053 L,V/B-LK 0.0052 L/F,V/B-LK 0.0051 0.005 0.0049 0.0048 0.0047 0.0046 0 100 0 0.0054 0.0053 0.0052 0.0051 0.005 0.0049 0.0048 0.0047 0.0046 200 0.0053 0.0052 L/D,V/F-LK 0.0051 0.005 0.0049 0.0048 200 L/D,B-LK L/D,B/F-LK 0 0.007 0.0065 0.006 0.0055 0.005 0.0045 0.004 L/D,V-LK 100 100 200 300 L,B-LK L/F,B/F-LK 0.0035 0.003 0.0047 0 100 200 0.006 0 100 200 300 400 L,V-LK L/F,V/F-LK 0.0055 0.005 0.0045 0.004 0 100 200 300 Time (min) Figure 5.12: Comparison of Closed Loop Response between Base Case and Flow Ratioing for Step Disturbance in Feed Composition 500 5. Dual Ended Composition Control 0.0053 89 0.00506 D,V/B-LK 0.0052 D/F,V/B-LK 0.0051 D/F,V/F-LK 0.005 0.00498 0.005 0.0049 0.00496 0.00494 0.0048 0.0047 Light Key Composition in Bottoms Product DV-LK 0.00504 0.00502 0.00492 0 100 200 0.0051 300 0.005 0.00495 0.0048 0.0049 0.0046 0.00485 0.0044 100 0.00506 200 300 L/D,B-LK L/D,B/F-LK 0 100 200 300 0.006 L/D,V-LK L/D,V/F-LK 0.00504 200 0.0052 0.005 0 100 0.0054 L,V/B-LK L/F,V/B-LK 0.00505 0 0.0055 0.00502 0.005 0.005 0.00498 0.0045 0.00496 0.00494 L,B-LK L/F,B/F-LK 0.004 0 100 200 300 400 0 100 200 300 0.006 0.0055 0.005 0.0045 L,V-LK L/F,V/F-LK 0.004 0 100 200 Time (min) Figure 5.13: Comparison of Closed Loop Response between Base Case and Flow Ratioing for Step Disturbance in Feed Flow 400 5. Dual Ended Composition Control 5.4 90 Effect of Turndown The ‘base case’ model is modified to study the effect of turndown (TD) on their performance of the configurations for the same disturbances as used for the ‘base case’ model (Table 4.1). During turndown, the steady state tray temperatures have been adjusted to meet the product specifications, which amounts to 56.45 oC for overhead (base case 55.93 oC) and 95.7 oC for bottoms (base case 96.5 oC) specification. This shows that the steady-state performance requires less energy (per unit feed flow) at turndown compared to the design flow. Refer to Figure 4.20 and Table 4.1, which shows that during turndown, the dynamics could be affected as the time constants have changed substantially, especially for step change in V. In order to review the effect of turndown, the base configuration has been selected between base case and sluggish level tuning which shows better performance. It can be observed from Figure 5.14 to 5.18 that (L/D,V/B), (L/F,V/F) and (L,V/B-SL) controls are nearly unaffected by feed flow rates and are only stable configurations. It is also noted that configurations with V/B control (except D, V/B) also show nearly same response at turndown. These schemes are inherent in feed flow compensation by ratioing the variables, thus show no significant effect on performance with feed flow variation. 5. Dual Ended Composition Control Overhead Composition for change in Feed Composition Bottoms Composition for change in Feed Composition Overhead Composition for change in Feed flow Bottoms Composition for change in Feed flow 25 IAE for Step Disturbances 91 20 15 10 5 D, V/B-TD D, V/B L, V/B-SL TD L, V/B-SL L/D, B-TD L/D, B L/D, V-SL TD L/D, V-SL L/D, V/B-SL TD L/D, V/B-SL L,B-SL TD L,B-SL D,V-TD D,V L,V-SL TD L,V-SL L/F, V/F-TD L/F, V/F 0 Overhead Composition for change in Feed Composition Bottoms Composition for change in Feed Composition 0.7 0.6 0.5 0.4 0.3 0.2 D, V/B-TD D, V/B L, V/B-SL TD L, V/B-SL L/D, B-TD L/D, B L/D, V-SL TD L/D, V-SL L/D, V/B-SL TD L/D, V/B-SL L,B-SL TD L,B-SL D,V-TD D,V L,V-SL TD L,V-SL 0 L/F, V/F-TD 0.1 L/F, V/F Max AR for Sinusoidal Disturbance 0.8 Dual Ended Configurations Figure 5.14: Performance of Various Configurations for Dual Ended Composition Control for Turndown Flow compared with Base Configuration 5. Dual Ended Composition Control 0.00525 92 0.0058 0.0056 0.0054 0.0052 0.005 0.0048 0.0046 0.0044 0.0042 0.004 D,V/B-HK 0.0052 D,V/B TD-HK 0.00515 0.0051 0.00505 0.005 0.00495 0.0049 0.00485 0.0048 0 100 200 0.0054 400 0 L,V/B SL TD-HK 400 L/D,B-HK L/D,B TD-HK 0.0055 0.0053 0.005 0.0051 0.0049 0.0049 0.0048 0.0047 0.0047 0.0045 0 100 200 0.0052 0.005 0.0048 0.0046 L/D,V SL-HK 0.0042 L/D,V SL TD-HK 0.004 0 100 200 300 0.006 0.0055 0.005 0.0045 0.004 L,B SL-HK L,B SL TD-HK 200 300 400 500 300 L/D,V/B SL TD-HK 100 0.0054 0.0053 0.0052 0.0051 0.005 0.0049 0.0048 0.0047 0.0046 0.0045 0.0065 200 L/D,V/B SL-HK 0 400 0.007 100 100 0.0052 0.00515 0.0051 0.00505 0.005 0.00495 0.0049 0.00485 0.0048 0.00475 0.0054 0.0044 0 300 0.0056 0 300 0.0057 0.0051 0.003 D,V TD-HK 200 0.0059 0.0052 0.0035 100 0.0061 L,V/B SL-HK 0.0053 Heavy Key Composition in Overhead Product 300 D,V-HK 200 300 L,V SL-HK L,V SL TD-HK 0 100 200 Time (min) Figure 5.15: Comparison of Closed Loop Response between Base Configuration and Turndown for Step Disturbance in Feed Composition 300 5. Dual Ended Composition Control 0.0054 93 0.0051 D,V/B-HK D,V/B TD-HK 0.0053 0.00505 0.0052 0.0051 0.005 0.005 0.00495 0.0049 0.0049 0.0048 0.0047 0 Heavy Key Composition in Overhead Product DV-HK D,V TD-HK 0.00485 100 0.00506 0.00504 200 300 400 0 L,V/B SL-HK 0.0061 L,V/B SL TD-HK 0.0059 100 200 300 400 L/D,B-HK L/D,B TD-HK 0.0057 0.00502 0.0055 0.005 0.0053 0.00498 0.0051 0.00496 0.0049 0.00494 0.0047 0 100 0.0051 0.00508 0.00506 0.00504 0.00502 0.005 0.00498 0.00496 0.00494 0.00492 200 300 400 L/D,V SL-HK 0 0.00503 L/D,V SL TD-HK 200 300 L/D,V/B SL-HK L/D,V/B SL TD-HK 0.00502 0.00501 0.005 0.00499 0.00498 0 100 200 300 400 0.00497 0 L,B SL-HK L,B SL TD-HK 0.0065 100 0.006 100 200 300 0.00508 L,V SL-HK 0.00506 L,V SL TD-HK 400 0.00504 0.0055 0.00502 0.005 0.005 0.00498 0.0045 0.00496 0.004 0.00494 0 100 200 300 400 0 100 200 300 Time (min) Figure 5.16: Comparison of Closed Loop Response between Base Configuration and Turndown for Step Disturbance in Feed Flow 5. Dual Ended Composition Control 0.0056 94 0.0054 D,V/B-LK D,V/B TD-LK 0.0054 0.0053 0.0052 0.0052 0.0051 0.005 0.005 0.0048 0.0049 0.0046 0.0048 0.0044 0.0047 0 100 200 0.0055 400 0.0053 0 100 D,V TD-LK 200 0.0065 L,V/B SL-LK L,V/B SL TD-LK 0.0054 Light Key Composition in Bottoms Product 300 D,V-LK 300 400 L/D,B-LK 0.006 L/D,B TD-LK 0.0055 0.0052 0.0051 0.005 0.005 0.0045 0.0049 0.004 0.0048 0 100 200 0.008 0.0054 0.0053 0.0052 0.0051 0.005 0.0049 0.0048 0.0047 0.0046 L/D,V SL-LK 0.007 L/D,V SL TD-LK 0.006 0.005 0.004 0.003 0 0 300 100 0.0065 200 L/D,V/B SL TD-LK 100 0.0054 0.0053 0.0052 0.0051 0.006 0.0055 0.005 0.004 L,B SL-LK 0.003 0 100 L,B SL TD-LK 200 300 200 L,V SL-LK L,V SL TD-LK 0.005 0.0049 0.0048 0.0047 0.0046 0.0045 0.0035 300 L/D,V/B SL-LK 0 200 100 400 0 100 Time (min) Figure 5.17: Comparison of Closed Loop Response between Base Configuration and Turndown for Step Disturbance in Feed Composition 200 5. Dual Ended Composition Control 0.0054 95 0.00506 D,V/B-LK D,V/B TD-LK 0.0053 0.00504 0.0052 0.00502 0.0051 0.005 0.005 0.00498 0.0049 0.00496 0.0048 0.00494 0.0047 0.00492 0 Light Key Composition in Bottoms Product DV-LK D,V TD-LK 100 200 300 0 100 0.0065 0.00504 0.00503 0.00502 0.00501 0.005 0.00499 0.00498 0.00497 0.00496 0.00495 200 L/D,B-LK L/D,B TD-LK 0.006 0.0055 0.005 0.0045 L,V/B SL-LK L,V/B SL TD-LK 0 100 0.00503 200 0.004 100 0.00503 L/D,V SL-LK L/D,V SL TD-LK 0.00502 0 300 200 300 L/D,V/B SL-LK L/D,V/B SL TD-LK 0.00502 0.00501 0.00501 0.005 0.005 0.00499 0.00499 0.00498 0.00498 0.00497 0 100 200 L,B SL-LK L,B SL TD-LK 0.0065 0.006 0.005 0.0045 0.004 0.0035 100 200 300 100 200 0.00504 0.00503 0.00502 0.00501 0.005 0.00499 0.00498 0.00497 0.00496 0.00495 0.0055 0 0 400 500 300 L,V SL-LK L,V SL TD-LK 0 100 Time (min) Figure 5.18: Comparison of Closed Loop Response between Base Configuration and Turndown for Step Disturbance in Feed Flow 200 5. Dual Ended Composition Control 5.5 96 Effect of feed tray location The ‘base case’ model is modified to study the effect of changing the feed tray location on the performance of control configurations for the same disturbances as used for the ‘base case’ model (Table 4.1). Simulation models are generated for lower feed tray (LFT, with feed tray located 2 trays below normal feed tray used for above simulations) and higher feed tray (HFT, with feed tray located 2 trays above normal feed tray used for above simulations). Moving the feed tray affects the steady-state and dynamic performance of the column. These effects are described in section 4.5. In order to review the effect of feed tray location, the base configuration has been selected between base case and sluggish level tuning which shows better performance. Figure 5.19 shows that there is no specific trend in the effect of changing feed tray location. The configurations (D,V-TS), (L,B-SL), (L/D,V-SL), and (L/D,B-SL) shows better performance for lower feed tray, while configurations (L,V-SL), (L/D,V/B-SL), (L,V/B), and (D,V/B) shows better performance with higher feed tray. It is interesting to observe that most of the configurations which are recommended earlier fall into the second category, which are improved for higher feed tray location. The results could be attributed to liquid feed effect described earlier in section 4.5. However, it is also recommended to keep options for alternate feed tray location in design and select the best feed tray based on field trials, as simulation cannot completely replicate the plant. 5. Dual Ended Composition Control Overhead Composition for change in Feed Composition Bottoms Composition for change in Feed Composition Overhead Composition for change in Feed flow Bottoms Composition for change in Feed flow 20 15 10 5 D, V/B-HFT D, V/B D, V/B-LFT L, V/B-HFT L, V/B-SL L, V/B-LFT L/D, B-SL HFT L/D, B L/D, B-LFT L/D, V-SL HFT L/D, V-SL L/D, V-SL LFT L/D, V/B-SL HFT L/D, V/B-SL L/D, V/B-SL LFT L,B-SL HFT L,B-SL L,B-SL LFT D,V-TS HFT D,V-SL D,V-TS LFT D,V L,V-SL, LFT L,V-SL, HFT 0 L,V-SL Overhead Composition for change in Feed Composition Bottoms Composition for change in Feed Composition 0.8 0.7 0.6 0.5 0.4 0.3 0.2 D, V/B-HFT D, V/B-LFT D, V/B L, V/B-LFT L, V/B-HFT L, V/B-SL L/D, B-SL HFT L/D, B-LFT L/D, B L/D, V-SL LFT L/D, V-SL HFT L/D, V-SL L/D, V/B-SL LFT L/D, V/B-SL HFT L/D, V/B-SL L,B-SL HFT L,B-SL L,B-SL LFT D,V-TS HFT D,V-TS LFT D,V-SL D,V L,V-SL, LFT 0 L,V-SL, HFT 0.1 L,V-SL IAE for Step Disturbances 25 Max AR for Sinusoidal Disturbance 97 Dual Ended Configurations Figure 5.19: Performance of Various Configurations for Dual Ended Composition Control with lower (LFT) or higher (HFT) Feed Tray Location compared with Base Configuration 5. Dual Ended Composition Control 5.6 98 Summary Each configuration has its own sensitivity to each disturbance and operational changes. Feed flow and feed composition are the most common disturbances a column can be subjected for long time. The effect of these disturbances on single ended configurations for depropaniser has been studied. The magnitude of disturbances used for this study is based on the study by Duvall (1999), except for feed flow, for which +1.5% step disturbance is considered. The performance of ‘base case’ is studied for disturbances in feed flow rates, feed composition, sinusoidal feed composition. Then the performance of changes in base case configurations is compared with the base case. The changes considered are ratioing to feed flow rate, tundown operation, level tuning and feed tray location. Main results of these cases are: Base case (D,V/B), (D,V), (L,V/B), (L/D,V): Stable control (L,B), (L,V), (L/D,B), ), (L/D,V/B): Not Recommended (D,V): Best Configuration Sluggish (L,V), (L/D,V/B): Substantial improvement by sluggish level tuning Level Tuning (L,B), (L/D,V), (L,V/B),(D,V-TS): Nearly independent of level tuning (D,V), (L/D,B), (D,V/B): Adversely affected by sluggish level tuning With sluggish level tuning, configuration (L,V), (D,V-TS), (L,V/B), (L/D,V/B) are the stable configurations. Flow (L,V): Substantial improvement by flow ratioing Ratioing All others: Nearly similar to without flow ratioing With flow ratioing, configuration (L,V), (D,V), and (L,V/B) are stable configurations. Turndown (L/D,V/B-SL), (L/F,V/F), (L,V/B-SL): nearly unaffected by feed flow 5. Dual Ended Composition Control 99 rates, and are only stable configurations. Feed Tray (D,V-TS), (L,B-SL), (L/D,V-SL), (L/D,B-SL): better performance for Location lower feed tray, (L,V-SL), (L/D,V/B-SL), (L,V/B), and (D,V/B): better performance with higher feed tray Considering all above factors, it can be concluded that configurations (L/F,V/FSL), (L,V/B-SL) and (L/D,V/B-SL) are the best configurations considering the range of operations. For these configurations, higher feed tray shows slightly better performance. Duvall (1999) observed that for similar column, the configurations (L,V/B), (L/D,V), and (L/D,V/B) with flow ratioing and sluggish level tuning performed best. Skogestad (1997) concluded that (L/D,V/B) is a good overall choice for all modes of operation. He also observed that (L/D,V) configuration behave somewhere between (L,V) and (L/D,V/B). Hence, the results are directionally in agreement with the earlier studies. The additional learning’s made through this study are: • The turndown flow adversely affects the performance for most of the dual ended control configurations. • Selecting right level tuning is critical for good composition control. • Flow ratioing does not necessarily improve the performance of control loops. • Locating the feed tray suitably can improve the dynamic performance. 6. Conclusions and Recommendations 100 Chapter 6 Conclusions and Recommendations 6.1 Conclusions This study specifically deals with the composition control of distillation columns. A rigorous steady state and dynamic model for an industrial depropaniser is developed using the commercial software, Hysys. The column design is similar to that defined in the doctoral thesis of Duvall (1999). It consists of 50 real trays (excluding condenser reboiler) with saturated liquid feed containing ethane, propane (LK), i-butane (HK), n-butane, npentane and n-hexane. The product requirements are 0.5 mole% i-butane in overheads and 0.5 mole% propane in bottoms. Optimum feed tray is calculated as 28 from bottom, to minimise the reflux and boil-up ratios. Tray temperatures (tray 16 for bottoms composition and tray 40 for overhead composition) are controlled to maintain the products composition; temperature controllers are periodically reset by the measured product composition. This calculated number of trays matches with the base case design used by Duvall (1999). Moreover, the open loop time constants obtained are close to that obtained by Duvall et al (2000) which validates the present design. The RGA for various configurations indicates that dual ended configurations (L, B); (L/D, B) and (L/D, V/B) are preferred while the worst scheme is (D, B). The performance of several control configurations is evaluated using Hysys dynamics for small disturbances in feed flow rate, feed composition and sinusoidal feed composition. 6. Conclusions and Recommendations 101 The IAE is used as the performance indicator for step disturbances, and peak amplitude ratio (AR) for the sinusoidal disturbance. The model is then modified to study the effect of ratioing manipulated variables to feed flow, turndown operation, tuning of level controllers and feed tray location, on the performance of control configurations. Both single ended and dual ended configurations are evaluated using this procedure. The key observations from the evaluation of single ended configurations for the depropaniser are: 1. For tight level tuning, D-control performs significantly better than L-control. Dcontrol is adversely affected by sluggish level tuning, while L-control is unaffected. During turndown operation, D-control is very sensitive to sinusoidal disturbances, while L-control shows improvement. 2. The performance of V-control is significantly improved by sluggish level tuning; its performance improves for turndown operation also. However, B configuration is unstable with both tight and sluggish level tuning, and it does not improve by flow ratioing; hence it is not recommended for control. 3. Ratioing L and V to feed flow provide control performance similar to that of L/D and V/B configurations. D-control is unaffected by flow ratioing. 4. L/D and V/B configurations are least sensitive to level tuning and turndown. 5. In general, higher feed tray location slightly improves the control performance. Overall, (L/D, V/B) configurations performed best for single ended control of the depropaniser. However, this requires additional measurements, which makes it more 6. Conclusions and Recommendations 102 complex and expensive. If a simple configuration is preferred, (D, V) is a good alternative with tight level tuning for D and sluggish level tuning for V. The only disadvantage with D-control is the sensitivity to sinusoidal disturbances in feed composition at significantly lower feed flow rates (i.e., turndown operation). Compared to single ended control, the configuration selection with dual ended controls is quite limited as many configurations are very sensitive to disturbances and unstable. The stable configurations for dual ended composition control are: 1. Base case : (D,V/B), (D,V), (L,V/B), (L/D,V) 2. Sluggish Level Tuning: (L,V), (D,V-TS), (L,V/B), (L/D,V/B) 3. Flow Ratioing: (L,V), (D,V), and (L,V/B) 4. Turndown: (L/D,V/B-SL), (L/F,V/F), (L,V/B-SL). In general, higher feed tray location slightly improves the control performance. Configurations (L/F,V/F-SL), (L,V/B-SL) and (L/D,V/B-SL) are the best options, where SL means sluggish level tuning for both overhead and bottoms. (For L/F, V/F), SL is considered to improve performance due to better performance on (L,V) with sluggish level tuning. It can be concluded that for dual ended configurations, ratioing schemes outperform the schemes where no ratioing is considered. It can be observed that all the stable configurations with tight level tuning (base case) are unstable at turndown, hence it is concluded that tight level tuning is not preferred for dual ended control (except with feed flow ratioing). Thus, turndown performance is a critical parameter in selection of control configuration. Further, except for (L/D, V/B), the conclusions made through RGA analysis do not match with that using rigorous dynamic simulation. Skogestad (2001) observed that (L, V) configuration is almost independent of 6. Conclusions and Recommendations 103 level tuning. This study shows the validity of this statement, which is nearly applicable to flow ratioing schemes. For single ended L-control, the performance is nearly independent of level tuning, while V-control show marked improvement in performance by using sluggish level control. For dual ended configurations, (L,V) configuration show significant improvement by sluggish level tuning. Considering all above factors, it can be concluded that rigorous dynamic simulation is needed for evaluating/selecting a control configuration including flow ratioing, sluggish and/or tight level tuning. Figure 6.1 gives a simplified flowchart for evaluating the optimum composition control scheme. This requires many simulations; however, based on experience gained through this study and other similar studies, some of the steps and configurations can be skipped. The performance should be evaluated for the expected disturbances in the selected process. 6. Conclusions and Recommendations 104 START Select a (another) Composition Control Configuration Evaluate the control performance for expected disturbances and turndown performance for various configurations for the flowing choices: - Sluggish or tight level - With or without flow ratioing List the option which gives best performance under this configuration Any other configuration to be evaluated Yes No Select the best configuration Figure 6.1: Flowchart for evaluation and selection of optimum control configuration 6.2 Recommendations for Future Work Several recommendations for future study are outlined below: 1. The dynamic studies for distillation columns presently available in literature are mainly carried out using simple models. For obtaining meaningful and reliable conclusions, rigorous simulation models should be utilized. This study has been done for an industrial depropaniser; similar studies can be carried out for a range of 6. Conclusions and Recommendations 105 columns for generalizing the findings of this study. The simulation model, where possible, should be validated using column operating data before utilizing for control studies. The magnitude of disturbances used for performance evaluation should be based on the disturbances expected during the plant operation, like feed flow/composition variation, utility conditions and rates, changes in ambient conditions, start-up etc. 2. Measuring feed flow is not always possible especially if the feed is multi-phase fluid or if flashing saturated liquid feed across the measuring device can affect the flow measurement. Moreover, using flow ratioing schemes introduces a bottleneck for future modifications, where the feed heating will be limited. Hence, future studies on column control should be targeted to enhance simple schemes. 3. Tight tuning of level controllers lowers equipment size and cost; however, limited research focuses on this aspect. Studies can be carried out to quantify the possible reduction in equipment size/cost, and to develop effective control schemes which can still provide stable and good control. 4. The effect of alternate feed tray location was not found to be significant for the depropaniser, perhaps due its medium number (50) of trays. However, similar studies should be done for shorter columns (with 10-20 trays), where this aspect could be important. 5. Except for (L/D, V/B), the conclusions made through RGA analysis do not match with that using rigorous dynamic simulation. Studies can be carried out using other, recent loop-pairing methods such as the one proposed by Xiong et al. (2005) to test their validity through rigorous simulation. 106 References [1] Alsop, N., Ferrer, J.M.: What dynamic simulation brings to a Process Control Engineer : Applied case study to a Propylene/Propane Splitter, ERTC Computing, London, UK, May 2004. [2] Alsop, N., Ferrer, J.M.: Step-test free APC implementation using dynmic simulation, AIChE Process Control 2006 Spring National Meeting, Orlando, FL, Apr 2006. [3] Amrithalingham, R., Sung, S.W., Lee, Jay H.: Two-Step procedure for Data-Based Modeling for Inferential Control Applications, AIChE Journal, Vol. 46, N0. 10, 1974-1988, Oct. 1999. [4] Anderson, J. J.: Vacuum Distillation Control, a PhD theses, Texas Tech University, December 1998. [5] Buckley, P.S., Luyben, W.L., Shunta, J.S.: Design of Distillation Column Control Systems, Instrument Society of America, 1985 [6] Deshpande, P.B.: Distillation Dynamics and Control, Instrument Society of America, 1985. [7] Dhole, V.R., Linnhoff, B.: Distillation Column targets, Comp. Chem. Eng., Vol 17, No 5/6, 549-560, 1993. [8] Duvall, P.M.: On Control of High Relative volatility Distillation Columns, a PhD theses, Texas Tech University, December 1999. [9] Duvall, M., Riggs, J.B., Lee, P.: Multi-model decoupled Generic Model Control, Control Engineering Practice, Vol. 9, 471-481, 2000. [10] Engelien, H.K., Larsson, T., and Skogestad S.: Implementation of optimal operation for heat integrated distillation columns, Trans IChemE, , Vol 81, Part A, 277-281, Feb 2003. [11] Engelien, H.K., Skogestad, S.: Minimum energy diagrams for multieffect distillation arrangements, AIChE J, Vol. 51, No. 6, 1714-1725, 2005. [12] Foley, M.W., Ramharack, N.R., Copeland, B.R.: Comparison of PI Controller Tuning Methods, Ind. Eng. Chem. Res., 6741-6750, 2005. [13] Green, J., Bullen, S., Martins, F.: Excel 2000 VBA, Programmer’s Reference, Wiley Publishing, 2003. 107 [14] Huang, H., Riggs, J.B.: Comparison of PI and MPC for GRU, Journal of Process Control , Vol 12, 167-173, 2002. [15] Hurowitz, S.E., Philip M.: Superfractionator Process Control, a PhD theses, Texas Tech University, August 1998. [16] Hurowitz, S., Anderson, J., Duvall, M., Riggs, J.B.: Distillation control configuration selection, Journal of Process Control, Vol.13, 357-362, 2003. [17] Kano, M., Showchaiya, N., Hasebe, S., Hashimoto, I.: Inferential control of distillation compositions: Selection of model and control configurations, Control Eng. Prac., Vol. 11, 927-933, 2003. [18] Kister, H.Z.: Distillation Operation, McGraw Hill, 1990 [19] Lek, C.M., Rangaiah, G.P., Hidajat, K.: Distillation: Revisiting some rules of thumb, Chemical Engineering, 50-55, September 2004. [20] Ludwig, E.E.: Applied Process Design for Chemical and Petrochemical Plants, Vol 2, 1997. [21] Lundstrom, P., Skogestad, S.: Opportunities and difficulties with 5 X 5 distillation control, Journal of Process Control, Vol 5, No. 4, 249-261, 1995. [22] Luyben, W.L.: Process Modelling, Simulation, and Control for Chemical Engineers, 2nd Edition, McGraw Hill, 1990. [23] Luyben, W.L.: Evaluation of criteria for selecting temperature control trays in distillation columns, Journal of Process Control, Vol. 16, 115-134, 2006. [24] Mahoney, D.P., Fruehauf ,P.S.: An integrated approach for distillation column control design using steady state and dynamic simulation, website: www.aspentech.com/publication_files , cited on 01 Jan 2007 [25] Mathur, U.: Successful multivariable control without plant tests, Hydrocarbon Processing, June 2003. [26] McAvoy T.J.: Connection between relative gain and control loop stability and design, AIChE Journal, Volume 27, Issue 4, 613 – 619, 1981. [27] Mukherjee, S.: Tray Column Design: Keep control of the details, Chemical Engineering, 52-58, Sep 2005. [28] Ogunnaike, B.A., Ray, W.H: Process Dynamics, Modelling, and Control, Oxford University Press, 1994. 108 [29] Riggs, J.B.: Improve distillation column control, Chemical Engineering Progress, 31-47, October 1998. [30] Riggs, J.B., Huang H.: Comparison of PI and MPC for GRU, Journal of Process Control, Vol. 12, 163-173, 2002. [31] Ross, R., Perkins J.D., Pistikopoulos, E.N., Koot, G.L.M., Van Schijndel J.M.G..: Optimal design and control of high purity industrial distillation columns, Comp. Chem. Eng., Vol. 25, 141-150, Jan 2001. [32] Segovia-Hernandez, J.G., Hernandez, S., Rico-Ramirez, V., Jimenez, A.: A comparison of feedback control behavior between thermally coupled and conventional distillation schemes, Comp. Chem. Eng., Vol. 28, 811-819, 2004. [33] Shinskey, F.G.: Distillation Control for productivity and energy conservation, 2nd Edition, McGraw Hill, 1984. [34] Shinskey, F.G.: Process Control – As taught Vs as practiced, Ind. Eng. Chem. Research, Vol. 41, 3745-3750, 2002. [35] Skogestad, S.: Control Structure design for complete chemical plants, Comp. and Chem. Eng., Vol. 28, 219-234, 2004. [36] Skogestad, S., Govatsmark, M.S.: Optimal no of stages in distillation with respect to controllability, European symposium on computer aided process engineering, Computer-aided chemical engineering, 499-504, October 2002. [37] Skogestad, S., Morari, M.: Understanding the dynamic behavior of distillation columns, Ind. Eng. Chem. Res, Vol. 27, 1848-1862, 1988. [38] Skogestad, S.: Dynamics and control of distillation columns – a tutorial introduction, Trans IChemE, Vol 75, Part A, Sep. 1997. [39] Skogestad, S: Probably the best simple PID tuning rules in the world, AIChE annual meeting, Reno, NV, USA, Paper no. 276h, Nov 2001 [40] Skogestad, S: Modelling and Dynamic Simulation for Process Control, Lecture notes at seminar at NTH, Trondheim, Aug 1991. [41] Teo, T.M., Lakshminarayan, S., and Rangaiah, G.P.: Performance Assessment of Cascade Control Systems, 27-38, Journal of The Institute of Engineers, Singapore, Vol 45, Issue 6, 2005. [42] Xiong Q., Cai W., He M.: A practical loop pairing criteria for multivariable processes, Journal of Process Control, Vol. 15, Issue 7, 741-747, Oct. 2005 109 Appendix A Macro for Step Changes in Single Ended Composition Controller This macro is used to calculate the Integral Absolute Error (IAE) for step changes in product composition and disturbances in feed composition and feed flow rate. It has been developed in excel and serves as an interface with hysys and excel. The steps involved in this macro are: 1. Define variables 2. Start simulation and Initialise parameters 3. For each detuning factor: Change controller tuning parameter Reset temperature control set point at each sampling period Collect output and calculate IAE for each step change or disturbance Close and Restart simulation for next detuning factor, and re-initialize parameters 110 Option Explicit Public hyController As Controller Public hyGain As Double Public hyTiValue As Double Public feedHK As Double, feedLK As Double Public feedStream As String Public hyfeedStream As ProcessStream Public hyfeedCompFrac As Variant Public l As Integer Public hyApp As HYSYS.Application Public hyCase As SimulationCase Public hyFlowsheet As Flowsheet Public hySubFlowsheets As Flowsheets Public hySubFlowsheet As Flowsheet Public hyOvhdStream As ProcessStream Public hyBtmStream As ProcessStream Public hyComponents As Components Public hyOvhdCompFrac As Variant Public hyBtmCompFrac As Variant Public j As Integer Public k As Integer Public PVValue As Double Public SP As Double, PV As Double, SPb As Double, PVb As Double Public y As Double, yb As Double Public Detuning(100) As Double, IAE(100) As Double, IAEb(100) As Double Public m As Double, A As Double, B As Double, trayT As Double Public Tset As Variant, Tset1 As Variant, Tset2 As Variant Public h As Integer, I As Double, Integral As Double, Ib As Double, Integralb As Double Public compInitial As Variant Public strCase As String Public j1 As Integer, jj1 As Integer, jj As Integer Public j2 As Integer, jj2 As Integer Public SP1 As Double, SP2 As Double Public ovhdCompIndicator As String, btmCompIndicator As String, tempController As String Public initialRun As Double Sub controller_tuning() 'this macro is used for step change in product composition, feed composition and feed flow 'start simulation case Set hyApp = CreateObject("HYSYS.Application") strCase = Range("B2") Set hyCase = hyApp.SimulationCases.Open(strCase) hyCase.Visible = True 'set simulation objects Set hyFlowsheet = hyCase.Flowsheet 111 Set hySubFlowsheets = hyFlowsheet.Flowsheets Set hySubFlowsheet = hySubFlowsheets.Item(0) tempController = "TIC-100" ovhdCompIndicator = "XIC-100" btmCompIndicator = "XIC-101" Set hyController = hySubFlowsheet.Operations.Item(tempController) 'Initialise parameters Detuning(1) = Range("M2") hyGain = hyController.GainValue hyTiValue = hyController.TiValue h = Range("J2") * 60 'Step size for integration SP = Range("B3") SP1 = Range("B4") SP2 = Range("B5") SPb = Range("G5") A = Range("B6") initialRun = Range("G4") * 60 'Initial set points Range("B10") = hyGain Range("B11") = hyTiValue Range("B12") = hySubFlowsheet.Operations.Item(ovhdCompIndicator).SPValue Range("B13") = hySubFlowsheet.Operations.Item(btmCompIndicator).SPValue 'run simulation and calculate IAE for different tuning factors For m = 1 To Range("G6") 'Change controller tuning parameters hyGain = hyGain / Detuning(m) hyTiValue = hyTiValue * Detuning(m) hyController.GainValue = hyGain hyController.TiValue = hyTiValue 'run case to stabilise the control hyCase.Solver.Integrator.RunUntil (initialRun) k = hyCase.Solver.Integrator.CurrentTime 'Initialise Integral = 0 Integralb = 0 For jj = 1 To Range("J3") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue B = (Log(PV) - A) * (trayT + 273) Tset = (B / (Log(SP) - A)) - 273 112 For j = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SPb) Ib = h * yb Integralb = Ib + Integralb Next j ' composition output If Detuning(m) > Range("M4") And Detuning(m) < Range("M5") Then Cells(88 + jj, 4) = k / 60 Cells(88 + jj, 5) = PV Cells(88 + jj, 6) = PVb Cells(88 + jj, 7) = Tset Cells(88 + jj, 8) = B Cells(88 + jj, 9) = trayT End If Next jj For jj1 = 1 To Range("J4") - Range("J3") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue B = (Log(PV) - A) * (trayT + 273) Tset1 = (B / (Log(SP1) - A)) - 273 For j1 = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset1 k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP1) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue 113 yb = Abs(PVb - SPb) Ib = h * yb Integralb = Ib + Integralb Next j1 ' composition output If Detuning(m) > Range("M4") And Detuning(m) < Range("M5") Then Cells(88 + jj - 1 + jj1, 4) = k / 60 Cells(88 + jj - 1 + jj1, 5) = PV Cells(88 + jj - 1 + jj1, 6) = PVb Cells(88 + jj - 1 + jj1, 7) = Tset1 Cells(88 + jj - 1 + jj1, 8) = B Cells(88 + jj - 1 + jj1, 9) = trayT End If Next jj1 For jj2 = 1 To Range("J5") - Range("J4") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue B = (Log(PV) - A) * (trayT + 273) Tset2 = (B / (Log(SP2) - A)) - 273 For j2 = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset2 k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP2) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SPb) Ib = h * yb Integralb = Ib + Integralb Next j2 ' composition output If Detuning(m) > Range("M4") And Detuning(m) < Range("M5") Then Cells(88 + jj - 2 + jj1 + jj2, 4) = k / 60 Cells(88 + jj - 2 + jj1 + jj2, 5) = PV Cells(88 + jj - 2 + jj1 + jj2, 6) = PVb Cells(88 + jj - 2 + jj1 + jj2, 7) = Tset2 Cells(88 + jj - 2 + jj1 + jj2, 8) = B Cells(88 + jj - 2 + jj1 + jj2, 9) = trayT End If 114 Next jj2 'IAE=Total area divided by the time IAE(m) = Integral Cells(18 + m, 2) = Detuning(m) Cells(18 + m, 3) = IAE(m) 'Bottom composition IAEb(m) = Integralb Cells(18 + m, 4) = IAEb(m) 'Close simulation case (in order to start next case from same point) hyCase.Close 'Open simulation case Set hyCase = hyApp.SimulationCases.Open(strCase) hyCase.Visible = True 'reset simualtion case objects Set hyFlowsheet = hyCase.Flowsheet Set hySubFlowsheets = hyFlowsheet.Flowsheets Set hySubFlowsheet = hySubFlowsheets.Item(0) Set hyController = hySubFlowsheet.Operations.Item(tempController) hyGain = hyController.GainValue hyTiValue = hyController.TiValue 'Change detuning factor If m < Range("G6") Then Detuning(m + 1) = Detuning(m) - Range("M3") End If Next m hyCase.Close End Sub 115 Appendix B Macros for Sinusoidal Disturbance in Single Ended Composition Controller This macro is used to calculate the Amplitude Ratio (AR) for sinusoidal disturbance in feed composition at various frequencies. It has been developed in excel and serves as an interface with hysys and excel. The steps involved in this macro are: 1. Define variables 2. Start simulation and Initialise parameters 3. For each frequency: Reset temperature control set point at each sampling period Collect the data and calculate AR Stop and Restart simulation for next frequency and re-initialize parameters 116 Option Explicit Public PVValue As Double Public SP As Double, PV As Double, SPb As Double, PVb As Double Public hyTransferFunction As Operations Public hySpreadsheet As SpreadsheetOp Public Period(100) As Double, Frequency(100) As Double, step As Double Public hyFeedComp As Double, hyOvhdComp As Double, hyBtmComp As Double Public hyFeedCompb As Double, hyOvhdCompb As Double, hyBtmCompb As Double Public maxOvhdComp As Double, maxBtmComp As Double, maxFeedComp As Double Public maxOvhdCompb As Double, maxBtmCompb As Double, maxFeedCompb As Double Public norOvhdComp As Double, norBtmComp As Double, norFeedComp As Double Public norOvhdCompb As Double, norBtmCompb As Double, norFeedCompb As Double Public minOvhdComp As Double, minBtmComp As Double, minFeedComp As Double Public minOvhdCompb As Double, minBtmCompb As Double, minFeedCompb As Double Public hyFeedAmp As Double, hyOvhdAmp As Double, hyBtmAmp As Double Public hyFeedAmpb As Double, hyOvhdAmpb As Double, hyBtmAmpb As Double Public maxFeedAmp As Double, maxOvhdAmp As Double, maxBtmAmp As Double Public maxFeedAmpb As Double, maxOvhdAmpb As Double, maxBtmAmpb As Double Sub sinusoidal_disturbance() 'start simulation case Set hyApp = CreateObject("HYSYS.Application") strCase = Range("B2") Set hyCase = hyApp.SimulationCases.Open(strCase) hyCase.Visible = True 'set simulation objects Set hyFlowsheet = hyCase.Flowsheet Set hySubFlowsheets = hyFlowsheet.Flowsheets Set hySubFlowsheet = hySubFlowsheets.Item(0) tempController = "TIC-100" ovhdCompIndicator = "XIC-100" btmCompIndicator = "XIC-101" Set hyController = hySubFlowsheet.Operations.Item(tempController) Set hySpreadsheet = hyFlowsheet.Operations.Item("SPRDSHT") hyFeedComp = hySpreadsheet.Cell("D6").CellValue hyOvhdComp = hySpreadsheet.Cell("D1").CellValue hyBtmComp = hySpreadsheet.Cell("D2").CellValue hyFeedCompb = hySpreadsheet.Cell("D7").CellValue hyOvhdCompb = hySpreadsheet.Cell("D3").CellValue hyBtmCompb = hySpreadsheet.Cell("D4").CellValue 'Initialise parameters Detuning(1) = Range("M2") hyGain = hyController.GainValue hyTiValue = hyController.TiValue h = Range("J2") * 60 'Step size for integration SP = Range("B3") 117 SPb = Range("G5") A = Range("B6") initialRun = Range("G4") * 60 Period(1) = Range("B4") step = Range("B5") hySpreadsheet.Cell("A1").CellValue = Period(1) Frequency(1) = 2 * 3.14 / Period(1) norFeedComp = hyFeedComp norOvhdComp = hyOvhdComp norBtmComp = hyBtmComp norFeedCompb = hyFeedCompb norOvhdCompb = hyOvhdCompb norBtmCompb = hyBtmCompb 'Initial set points Range("B10") = hyGain Range("B11") = hyTiValue Range("B12") = hySubFlowsheet.Operations.Item(ovhdCompIndicator).SPValue Range("B13") = hySubFlowsheet.Operations.Item(btmCompIndicator).SPValue Range("B88") = hySubFlowsheet.Operations.Item(tempController).SPValue Range("C88") = hySubFlowsheet.Operations.Item(tempController).PVValue Range("F11") = norFeedComp Range("D11") = norOvhdComp Range("E11") = norBtmComp Range("F14") = norFeedCompb Range("D14") = norOvhdCompb Range("E14") = norBtmCompb 'run simulation and calculate IAE for different tuning factors For m = 1 To Range("G6") 'Change controller tuning parameters hyGain = hyGain / Detuning(m) hyTiValue = hyTiValue * Detuning(m) hyController.GainValue = hyGain hyController.TiValue = hyTiValue 'run case to stabilise the control hyCase.Solver.Integrator.RunUntil (initialRun) k = hyCase.Solver.Integrator.CurrentTime 'Initialise Integral = 0 Integralb = 0 For jj = 1 To Range("J3") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue 118 PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue B = (Log(PV) - A) * (trayT + 273) Tset = (B / (Log(SP) - A)) - 273 For j = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue Next j Next jj hyFeedComp = hySpreadsheet.Cell("D6").CellValue hyOvhdComp = hySpreadsheet.Cell("D1").CellValue hyBtmComp = hySpreadsheet.Cell("D2").CellValue hyFeedCompb = hySpreadsheet.Cell("D7").CellValue hyOvhdCompb = hySpreadsheet.Cell("D3").CellValue hyBtmCompb = hySpreadsheet.Cell("D4").CellValue maxFeedAmp = 0 maxOvhdAmp = 0 maxBtmAmp = 0 maxFeedComp = 0 maxOvhdComp = 0 maxBtmComp = 0 minFeedComp = 1 minOvhdComp = 1 minBtmComp = 1 maxFeedAmpb = 0 maxOvhdAmpb = 0 maxBtmAmpb = 0 maxFeedCompb = 0 maxOvhdCompb = 0 maxBtmCompb = 0 minFeedCompb = 1 minOvhdCompb = 1 minBtmCompb = 1 If Range("G3") * 60 < Period(m) Then jj2 = Round(1.5 * Period(m) / (Range("G3") * 60), 0) Else: jj2 = 1 End If 'If jj2 < Range("J4") Then 'l = Round((Range("J4") / jj2), 0) 'Else: l = 1 'End If 119 If m = 1 Then l = Round((Range("J4") / jj2), 0) Else: l = 1 End If Range("J5") = jj2 For jj1 = 1 To l For j2 = 1 To jj2 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue B = (Log(PV) - A) * (trayT + 273) Tset = (B / (Log(SP) - A)) - 273 For j1 = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset If k > Range("G7") * 60 Then Exit For k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue hyFeedComp = hySpreadsheet.Cell("D6").CellValue hyOvhdComp = hySpreadsheet.Cell("D1").CellValue hyBtmComp = hySpreadsheet.Cell("D2").CellValue hyFeedCompb = hySpreadsheet.Cell("D7").CellValue hyOvhdCompb = hySpreadsheet.Cell("D3").CellValue hyBtmCompb = hySpreadsheet.Cell("D4").CellValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SPb) Ib = h * yb Integralb = Ib + Integralb ' composition output 'If m = Round(Range("G6") / 2, 0) Then If m = 1 Then Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 1) = k / 60 Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 2) = Tset Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 3) = trayT 120 Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 4) = PV Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 5) = PVb Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 6) = hyFeedComp Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 7) = hyOvhdComp Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 8) = hyBtmComp Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 9) = hyFeedCompb Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 10) = hyOvhdCompb Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 11) = hyBtmCompb Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 12) = B End If If hyOvhdComp > maxOvhdComp Then maxOvhdComp = hyOvhdComp End If If hyBtmComp > maxBtmComp Then maxBtmComp = hyBtmComp End If If hyFeedComp > maxFeedComp Then maxFeedComp = hyFeedComp End If If hyOvhdComp < minOvhdComp Then minOvhdComp = hyOvhdComp End If If hyBtmComp < minBtmComp Then minBtmComp = hyBtmComp End If If hyFeedComp < minFeedComp Then minFeedComp = hyFeedComp End If If hyOvhdCompb > maxOvhdCompb Then maxOvhdCompb = hyOvhdCompb End If If hyBtmCompb > maxBtmCompb Then maxBtmCompb = hyBtmCompb End If If hyFeedCompb > maxFeedCompb Then maxFeedCompb = hyFeedCompb End If If hyOvhdCompb < minOvhdCompb Then minOvhdCompb = hyOvhdCompb End If If hyBtmCompb < minBtmCompb Then minBtmCompb = hyBtmCompb End If 121 If hyFeedCompb < minFeedCompb Then minFeedCompb = hyFeedCompb End If Next j1 Next j2 hyOvhdAmp = (maxOvhdComp - minOvhdComp) / 2 hyBtmAmp = (maxBtmComp - minBtmComp) / 2 hyFeedAmp = (maxFeedComp - minFeedComp) / 2 If hyOvhdAmp > maxOvhdAmp Then maxOvhdAmp = hyOvhdAmp End If If hyBtmAmp > maxBtmAmp Then maxBtmAmp = hyBtmAmp End If If hyFeedAmp > maxFeedAmp Then maxFeedAmp = hyFeedAmp End If hyOvhdAmpb = (maxOvhdCompb - minOvhdCompb) / 2 hyBtmAmpb = (maxBtmCompb - minBtmCompb) / 2 hyFeedAmpb = (maxFeedCompb - minFeedCompb) / 2 If hyOvhdAmpb > maxOvhdAmpb Then maxOvhdAmpb = hyOvhdAmpb End If If hyBtmAmpb > maxBtmAmpb Then maxBtmAmpb = hyBtmAmpb End If If hyFeedAmpb > maxFeedAmpb Then maxFeedAmpb = hyFeedAmpb End If Next jj1 'IAE=Total area divided by the time IAE(m) = Integral Cells(18 + m, 2) = Detuning(m) Cells(18 + m, 3) = IAE(m) 'Bottom composition IAEb(m) = Integralb Cells(18 + m, 4) = IAEb(m) Cells(18 + m, 5) = Frequency(m) Cells(18 + m, 6) = Period(m) Cells(18 + m, 7) = maxOvhdAmp Cells(18 + m, 8) = maxBtmAmp 122 Cells(18 + m, 9) = maxFeedAmp Cells(18 + m, 10) = maxOvhdAmpb Cells(18 + m, 11) = maxBtmAmpb Cells(18 + m, 12) = maxFeedAmpb 'Close simulation case (in order to start next case from same point) hyCase.Close 'Open simulation case Set hyCase = hyApp.SimulationCases.Open(strCase) hyCase.Visible = True 'reset simualtion case objects Set hyFlowsheet = hyCase.Flowsheet Set hySubFlowsheets = hyFlowsheet.Flowsheets Set hySubFlowsheet = hySubFlowsheets.Item(0) Set hyController = hySubFlowsheet.Operations.Item(tempController) hyGain = hyController.GainValue hyTiValue = hyController.TiValue step = Range("B5") Set hyfeedStream = hySubFlowsheet.MaterialStreams.Item("feed") Set hyOvhdStream = hySubFlowsheet.MaterialStreams.Item("ovhdliq") Set hyBtmStream = hySubFlowsheet.MaterialStreams.Item("btmliq") Set hySpreadsheet = hyFlowsheet.Operations.Item("SPRDSHT") 'Initialise parameters h = Range("J2") * 60 'Step size for integration SP = Range("B3") SPb = Range("G5") A = Range("B6") initialRun = Range("G4") * 60 If m < Range("G6") Then Period(m + 1) = 10 ^ (WorksheetFunction.Log10(Period(m)) + step) hySpreadsheet.Cell("A1").CellValue = Period(m + 1) Frequency(m + 1) = 2 * 3.14 / Period(m + 1) Detuning(m + 1) = Detuning(m) End If Next m hyCase.Close End Sub 123 Appendix C Macros for Step Changes in Dual Ended Composition Controller This macro is used to calculate the Integral Absolute Error (IAE) for step changes in product composition and disturbances in feed composition and feed flow rate. It has been developed in excel and serves as an interface with hysys and excel. The steps involved in this macro are: 1. Define variables 2. Start simulation and Initialise parameters 3. For each detuning factor: Change controller tuning parameter Reset temperature control set point at each sampling period Collect output and calculate IAE for each step change or disturbance Close and Restart simulation for next detuning factor, and re-initialize parameters 124 Option Explicit Public hyController As Controller, hyControllerb As Controller Public hyGain As Double, hyGainb As Double Public hyTiValue As Double, hyTiValueb As Double Public feedHK As Double, feedLK As Double Public feedStream As String Public hyfeedStream As ProcessStream Public hyfeedCompFrac As Variant Public l As Integer Public hyApp As HYSYS.Application Public hyCase As SimulationCase Public hyFlowsheet As Flowsheet Public hySubFlowsheets As Flowsheets Public hySubFlowsheet As Flowsheet Public hyOvhdStream As ProcessStream Public hyBtmStream As ProcessStream Public hyComponents As Components Public hyOvhdCompFrac As Variant Public hyBtmCompFrac As Variant Public j As Integer Public k As Integer Public PVValue As Double Public SP As Double, PV As Double, SPb As Double, PVb As Double Public y As Double, yb As Double Public Detuning(100) As Double, IAE(100) As Double, IAEb(100) As Double Public IAEa(100) As Double, IAEab(100) As Double Public m As Double, A As Double, B As Double, trayT As Double, Ab As Double, Bb As Double, trayTb As Double Public m1 As Double, m2 As Double, k1 As Double Public Tset As Variant, Tset1 As Variant, Tset2 As Variant Public Tsetb As Variant, Tset1b As Variant, Tset2b As Variant Public h As Integer, I As Double, Integral As Double, Ib As Double, Integralb As Double Public compInitial As Variant Public strCase As String Public j1 As Integer, jj1 As Integer, jj As Integer Public j2 As Integer, jj2 As Integer, j3 As Integer, jj3 As Integer, j4 As Integer, jj4 As Integer Public ja As Integer, ja1 As Integer, jja1 As Integer, jja As Integer Public ja2 As Integer, jja2 As Integer, ja3 As Integer, jja3 As Integer, ja4 As Integer, jja4 As Integer Public SP1 As Double, SP2 As Double, SP1b As Double, SP2b As Double Public ovhdCompIndicator As String, btmCompIndicator As String, tempController As String, tempControllerb As String Public initialRun As Double, initialRun2 As Double Sub controller_tuning() 125 'this macro is used for step change in product composition, feed composition and feed flow 'start simulation case Set hyApp = CreateObject("HYSYS.Application") strCase = Range("B2") Set hyCase = hyApp.SimulationCases.Open(strCase) hyCase.Visible = True 'set simulation objects Set hyFlowsheet = hyCase.Flowsheet Set hySubFlowsheets = hyFlowsheet.Flowsheets Set hySubFlowsheet = hySubFlowsheets.Item(0) tempController = "TIC-100" ovhdCompIndicator = "XIC-100" btmCompIndicator = "XIC-101" Set hyController = hySubFlowsheet.Operations.Item(tempController) tempControllerb = "TIC-101" Set hyControllerb = hySubFlowsheet.Operations.Item(tempControllerb) 'Initialise parameters Detuning(1) = Range("M2") hyGain = hyController.GainValue hyTiValue = hyController.TiValue h = Range("J2") * 60 'Step size for integration SP = Range("B3") SP1 = Range("B4") SP2 = Range("B5") A = Range("B6") initialRun = Range("G4") * 60 hyGainb = hyControllerb.GainValue hyTiValueb = hyControllerb.TiValue SPb = Range("C3") SP1b = Range("C4") SP2b = Range("C5") Ab = Range("C6") 'Initial set points Range("B10") = hyGain Range("B11") = hyTiValue Range("B12") = hySubFlowsheet.Operations.Item(ovhdCompIndicator).SPValue Range("B13") = hySubFlowsheet.Operations.Item(btmCompIndicator).SPValue Range("C10") = hyGainb Range("C11") = hyTiValueb 'initial simulation values Range("B88") = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue Range("C88") = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue Range("D88") = hySubFlowsheet.Operations.Item(tempController).SPValue 126 Range("E88") = hySubFlowsheet.Operations.Item(tempControllerb).SPValue Range("H88") = hySubFlowsheet.Operations.Item(tempController).PVValue Range("I88") = hySubFlowsheet.Operations.Item(tempControllerb).PVValue 'run simulation and calculate IAE for different tuning factors For m = 1 To Range("G6") 'Change controller tuning parameters hyGain = hyGain / Detuning(m) hyTiValue = hyTiValue * Detuning(m) hyController.GainValue = hyGain hyController.TiValue = hyTiValue hyGainb = hyGainb / Detuning(m) hyTiValueb = hyTiValueb * Detuning(m) hyControllerb.GainValue = hyGainb hyControllerb.TiValue = hyTiValueb 'run case to stabilise the control hyCase.Solver.Integrator.RunUntil (initialRun) k = hyCase.Solver.Integrator.CurrentTime 'Initialise Integral = 0 Integralb = 0 For jj = 1 To Range("J3") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue B = (Log(PV) - A) * (trayT + 273) Tset = (B / (Log(SP) - A)) - 273 trayTb = hySubFlowsheet.Operations.Item(tempControllerb).PVValue PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue Bb = (Log(PVb) - Ab) * (trayTb + 273) Tsetb = (Bb / (Log(SPb) - Ab)) - 273 For j = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset hySubFlowsheet.Operations.Item(tempControllerb).SPValue = Tsetb k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP) I=h*y 127 Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SPb) Ib = h * yb Integralb = Ib + Integralb Next j ' composition output If Detuning(m) > Range("M4") And Detuning(m) < Range("M5") Then Cells(88 + jj, 1) = k / 60 Cells(88 + jj, 2) = PV Cells(88 + jj, 3) = PVb Cells(88 + jj, 4) = Tset Cells(88 + jj, 5) = Tsetb Cells(88 + jj, 6) = B Cells(88 + jj, 7) = Bb Cells(88 + jj, 8) = trayT Cells(88 + jj, 9) = trayTb End If Next jj For jj1 = 1 To Range("J4") - Range("J3") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue B = (Log(PV) - A) * (trayT + 273) Tset1 = (B / (Log(SP1) - A)) - 273 trayTb = hySubFlowsheet.Operations.Item(tempControllerb).PVValue Bb = (Log(PVb) - Ab) * (trayTb + 273) Tsetb = (Bb / (Log(SPb) - Ab)) - 273 For j1 = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset1 hySubFlowsheet.Operations.Item(tempControllerb).SPValue = Tsetb k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP1) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SPb) Ib = h * yb 128 Integralb = Ib + Integralb Next j1 ' composition output If Detuning(m) > Range("M4") And Detuning(m) < Range("M5") Then Cells(87 + jj + jj1, 1) = k / 60 Cells(87 + jj + jj1, 2) = PV Cells(87 + jj + jj1, 3) = PVb Cells(87 + jj + jj1, 4) = Tset1 Cells(87 + jj + jj1, 5) = Tsetb Cells(87 + jj + jj1, 6) = B Cells(87 + jj + jj1, 7) = Bb Cells(87 + jj + jj1, 8) = trayT Cells(87 + jj + jj1, 9) = trayTb End If Next jj1 For jj2 = 1 To Range("J5") - Range("J4") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue B = (Log(PV) - A) * (trayT + 273) Tset2 = (B / (Log(SP2) - A)) - 273 trayTb = hySubFlowsheet.Operations.Item(tempControllerb).PVValue Bb = (Log(PVb) - Ab) * (trayTb + 273) Tsetb = (Bb / (Log(SPb) - Ab)) - 273 For j2 = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset2 hySubFlowsheet.Operations.Item(tempControllerb).SPValue = Tsetb k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP2) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SPb) Ib = h * yb Integralb = Ib + Integralb Next j2 ' composition output If Detuning(m) > Range("M4") And Detuning(m) < Range("M5") Then Cells(86 + jj + jj1 + jj2, 1) = k / 60 129 Cells(86 + jj + jj1 + jj2, 2) = PV Cells(86 + jj + jj1 + jj2, 3) = PVb Cells(86 + jj + jj1 + jj2, 4) = Tset2 Cells(86 + jj + jj1 + jj2, 5) = Tsetb Cells(86 + jj + jj1 + jj2, 6) = B Cells(86 + jj + jj1 + jj2, 7) = Bb Cells(86 + jj + jj1 + jj2, 8) = trayT Cells(86 + jj + jj1 + jj2, 9) = trayTb End If Next jj2 For jj3 = 1 To Range("K4") - Range("J5") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue B = (Log(PV) - A) * (trayT + 273) Tset2 = (B / (Log(SP2) - A)) - 273 trayTb = hySubFlowsheet.Operations.Item(tempControllerb).PVValue Bb = (Log(PVb) - Ab) * (trayTb + 273) Tset1b = (Bb / (Log(SP1b) - Ab)) - 273 For j3 = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset2 hySubFlowsheet.Operations.Item(tempControllerb).SPValue = Tset1b k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP2) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SP1b) Ib = h * yb Integralb = Ib + Integralb Next j3 ' composition output If Detuning(m) > Range("M4") And Detuning(m) < Range("M5") Then Cells(85 + jj + jj1 + jj2 + jj3, 1) = k / 60 Cells(85 + jj + jj1 + jj2 + jj3, 2) = PV Cells(85 + jj + jj1 + jj2 + jj3, 3) = PVb Cells(85 + jj + jj1 + jj2 + jj3, 4) = Tset2 Cells(85 + jj + jj1 + jj2 + jj3, 5) = Tset1b Cells(85 + jj + jj1 + jj2 + jj3, 6) = B Cells(85 + jj + jj1 + jj2 + jj3, 7) = Bb 130 Cells(85 + jj + jj1 + jj2 + jj3, 8) = trayT Cells(85 + jj + jj1 + jj2 + jj3, 9) = trayTb End If Next jj3 For jj4 = 1 To Range("K5") - Range("K4") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue B = (Log(PV) - A) * (trayT + 273) Tset2 = (B / (Log(SP2) - A)) - 273 trayTb = hySubFlowsheet.Operations.Item(tempControllerb).PVValue Bb = (Log(PVb) - Ab) * (trayTb + 273) Tset2b = (Bb / (Log(SP2b) - Ab)) - 273 For j4 = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset2 hySubFlowsheet.Operations.Item(tempControllerb).SPValue = Tset2b k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP2) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SP2b) Ib = h * yb Integralb = Ib + Integralb Next j4 ' composition output If Detuning(m) > Range("M4") And Detuning(m) < Range("M5") Then Cells(84 + jj + jj1 + jj2 + jj3 + jj4, 1) = k / 60 Cells(84 + jj + jj1 + jj2 + jj3 + jj4, 2) = PV Cells(84 + jj + jj1 + jj2 + jj3 + jj4, 3) = PVb Cells(84 + jj + jj1 + jj2 + jj3 + jj4, 4) = Tset2 Cells(84 + jj + jj1 + jj2 + jj3 + jj4, 5) = Tset2b Cells(84 + jj + jj1 + jj2 + jj3 + jj4, 6) = B Cells(84 + jj + jj1 + jj2 + jj3 + jj4, 7) = Bb Cells(84 + jj + jj1 + jj2 + jj3 + jj4, 8) = trayT Cells(84 + jj + jj1 + jj2 + jj3 + jj4, 9) = trayTb End If Next jj4 131 'IAE=Total area divided by the time IAE(m) = Integral Cells(18 + m, 2) = Detuning(m) Cells(18 + m, 3) = IAE(m) 'Bottom composition IAEb(m) = Integralb Cells(18 + m, 4) = IAEb(m) 'Close simulation case (in order to start next case from same point) hyCase.Close 'Open simulation case Set hyCase = hyApp.SimulationCases.Open(strCase) hyCase.Visible = True 'reset simualtion case objects Set hyFlowsheet = hyCase.Flowsheet Set hySubFlowsheets = hyFlowsheet.Flowsheets Set hySubFlowsheet = hySubFlowsheets.Item(0) Set hyController = hySubFlowsheet.Operations.Item(tempController) hyGain = hyController.GainValue hyTiValue = hyController.TiValue Set hyControllerb = hySubFlowsheet.Operations.Item(tempControllerb) hyGainb = hyControllerb.GainValue hyTiValueb = hyControllerb.TiValue k1 = k 'Change detuning factor If m < Range("G6") Then Detuning(m + 1) = Detuning(m) - Range("M3") End If Next m hyCase.Close 'start simulation case Set hyApp = CreateObject("HYSYS.Application") strCase = Range("B7") Set hyCase = hyApp.SimulationCases.Open(strCase) hyCase.Visible = True 'set simulation objects Set hyFlowsheet = hyCase.Flowsheet Set hySubFlowsheets = hyFlowsheet.Flowsheets Set hySubFlowsheet = hySubFlowsheets.Item(0) tempController = "TIC-100" ovhdCompIndicator = "XIC-100" btmCompIndicator = "XIC-101" 132 Set hyController = hySubFlowsheet.Operations.Item(tempController) tempControllerb = "TIC-101" Set hyControllerb = hySubFlowsheet.Operations.Item(tempControllerb) 'Initialise parameters Detuning(1) = Range("M2") hyGain = hyController.GainValue hyTiValue = hyController.TiValue h = Range("J2") * 60 'Step size for integration SP = Range("B3") SP1 = Range("B4") SP2 = Range("B5") A = Range("B6") initialRun2 = Range("G7") * 60 hyGainb = hyControllerb.GainValue hyTiValueb = hyControllerb.TiValue SPb = Range("C3") SP1b = Range("C4") SP2b = Range("C5") Ab = Range("C6") 'Initial set points Range("B10") = hyGain Range("B11") = hyTiValue Range("B12") = hySubFlowsheet.Operations.Item(ovhdCompIndicator).SPValue Range("B13") = hySubFlowsheet.Operations.Item(btmCompIndicator).SPValue Range("C10") = hyGainb Range("C11") = hyTiValueb For m2 = 1 To Range("G6") 'Change controller tuning parameters hyGain = hyGain / Detuning(m2) hyTiValue = hyTiValue * Detuning(m2) hyController.GainValue = hyGain hyController.TiValue = hyTiValue hyGainb = hyGainb / Detuning(m2) hyTiValueb = hyTiValueb * Detuning(m2) hyControllerb.GainValue = hyGainb hyControllerb.TiValue = hyTiValueb 'run case to stabilise the control hyCase.Solver.Integrator.RunUntil (initialRun2) 133 k = hyCase.Solver.Integrator.CurrentTime 'Initialise Integral = 0 Integralb = 0 For jja = 1 To Range("J8") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue B = (Log(PV) - A) * (trayT + 273) Tset = (B / (Log(SP) - A)) - 273 trayTb = hySubFlowsheet.Operations.Item(tempControllerb).PVValue PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue Bb = (Log(PVb) - Ab) * (trayTb + 273) Tsetb = (Bb / (Log(SPb) - Ab)) - 273 For ja = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset hySubFlowsheet.Operations.Item(tempControllerb).SPValue = Tsetb k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SPb) Ib = h * yb Integralb = Ib + Integralb Next ja ' composition output If Detuning(m2) > Range("M4") And Detuning(m2) < Range("M5") Then Cells(83 + jj + jj1 + jj2 + jj3 + jj4 + jja, 1) = (k1 + k) / 60 Cells(83 + jj + jj1 + jj2 + jj3 + jj4 + jja, 2) = PV Cells(83 + jj + jj1 + jj2 + jj3 + jj4 + jja, 3) = PVb Cells(83 + jj + jj1 + jj2 + jj3 + jj4 + jja, 4) = Tset Cells(83 + jj + jj1 + jj2 + jj3 + jj4 + jja, 5) = Tsetb Cells(83 + jj + jj1 + jj2 + jj3 + jj4 + jja, 6) = B Cells(83 + jj + jj1 + jj2 + jj3 + jj4 + jja, 7) = Bb Cells(83 + jj + jj1 + jj2 + jj3 + jj4 + jja, 8) = trayT Cells(83 + jj + jj1 + jj2 + jj3 + jj4 + jja, 9) = trayTb End If 134 Next jja For jja1 = 1 To Range("J9") - Range("J8") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue B = (Log(PV) - A) * (trayT + 273) Tset1 = (B / (Log(SP1) - A)) - 273 trayTb = hySubFlowsheet.Operations.Item(tempControllerb).PVValue Bb = (Log(PVb) - Ab) * (trayTb + 273) Tsetb = (Bb / (Log(SPb) - Ab)) - 273 For ja1 = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset1 hySubFlowsheet.Operations.Item(tempControllerb).SPValue = Tsetb k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP1) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SPb) Ib = h * yb Integralb = Ib + Integralb Next ja1 ' composition output If Detuning(m2) > Range("M4") And Detuning(m2) < Range("M5") Then Cells(82 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1, 1) = (k1 + k) / 60 Cells(82 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1, 2) = PV Cells(82 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1, 3) = PVb Cells(82 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1, 4) = Tset1 Cells(82 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1, 5) = Tsetb Cells(82 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1, 6) = B Cells(82 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1, 7) = Bb Cells(82 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1, 8) = trayT Cells(82 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1, 9) = trayTb End If Next jja1 For jja2 = 1 To Range("J10") - Range("J9") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue B = (Log(PV) - A) * (trayT + 273) 135 Tset2 = (B / (Log(SP2) - A)) - 273 trayTb = hySubFlowsheet.Operations.Item(tempControllerb).PVValue Bb = (Log(PVb) - Ab) * (trayTb + 273) Tsetb = (Bb / (Log(SPb) - Ab)) - 273 For ja2 = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset2 hySubFlowsheet.Operations.Item(tempControllerb).SPValue = Tsetb k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP2) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SPb) Ib = h * yb Integralb = Ib + Integralb Next ja2 ' composition output If Detuning(m2) > Range("M4") And Detuning(m2) < Range("M5") Then Cells(81 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2, 1) = (k1 + k) / 60 Cells(81 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2, 2) = PV Cells(81 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2, 3) = PVb Cells(81 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2, 4) = Tset2 Cells(81 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2, 5) = Tsetb Cells(81 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2, 6) = B Cells(81 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2, 7) = Bb Cells(81 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2, 8) = trayT Cells(81 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2, 9) = trayTb End If Next jja2 For jja3 = 1 To Range("K9") - Range("J10") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue B = (Log(PV) - A) * (trayT + 273) Tset2 = (B / (Log(SP2) - A)) - 273 trayTb = hySubFlowsheet.Operations.Item(tempControllerb).PVValue Bb = (Log(PVb) - Ab) * (trayTb + 273) Tset1b = (Bb / (Log(SP1b) - Ab)) - 273 136 For ja3 = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset2 hySubFlowsheet.Operations.Item(tempControllerb).SPValue = Tset1b k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP2) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SP1b) Ib = h * yb Integralb = Ib + Integralb Next ja3 ' composition output If Detuning(m2) > Range("M4") And Detuning(m2) < Range("M5") Then Cells(80 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3, 1) = (k1 + k) / 60 Cells(80 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3, 2) = PV Cells(80 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3, 3) = PVb Cells(80 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3, 4) = Tset2 Cells(80 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3, 5) = Tset1b Cells(80 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3, 6) = B Cells(80 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3, 7) = Bb Cells(80 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3, 8) = trayT Cells(80 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3, 9) = trayTb End If Next jja3 For jja4 = 1 To Range("K10") - Range("K9") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue B = (Log(PV) - A) * (trayT + 273) Tset2 = (B / (Log(SP2) - A)) - 273 trayTb = hySubFlowsheet.Operations.Item(tempControllerb).PVValue Bb = (Log(PVb) - Ab) * (trayTb + 273) Tset2b = (Bb / (Log(SP2b) - Ab)) - 273 For ja4 = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset2 hySubFlowsheet.Operations.Item(tempControllerb).SPValue = Tset2b k=k+h hyCase.Solver.Integrator.RunUntil (k) 137 PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP2) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SP2b) Ib = h * yb Integralb = Ib + Integralb Next ja4 ' composition output If Detuning(m2) > Range("M4") And Detuning(m2) < Range("M5") Then Cells(79 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3 + jja4, 1) = (k1 + k) / 60 Cells(79 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3 + jja4, 2) = PV Cells(79 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3 + jja4, 3) = PVb Cells(79 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3 + jja4, 4) = Tset2 Cells(79 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3 + jja4, 5) = Tset2b Cells(79 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3 + jja4, 6) = B Cells(79 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3 + jja4, 7) = Bb Cells(79 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3 + jja4, 8) = trayT Cells(79 + jj + jj1 + jj2 + jj3 + jj4 + jja + jja1 + jja2 + jja3 + jja4, 9) = trayTb End If Next jja4 'IAE=Total area divided by the time IAEa(m2) = Integral Cells(18 + m2, 5) = Detuning(m2) Cells(18 + m2, 6) = IAEa(m2) 'Bottom composition IAEab(m2) = Integralb Cells(18 + m2, 7) = IAEab(m2) 'Close simulation case (in order to start next case from same point) hyCase.Close 'Open simulation case Set hyCase = hyApp.SimulationCases.Open(strCase) hyCase.Visible = True 'reset simualtion case objects Set hyFlowsheet = hyCase.Flowsheet Set hySubFlowsheets = hyFlowsheet.Flowsheets Set hySubFlowsheet = hySubFlowsheets.Item(0) Set hyController = hySubFlowsheet.Operations.Item(tempController) hyGain = hyController.GainValue 138 hyTiValue = hyController.TiValue Set hyControllerb = hySubFlowsheet.Operations.Item(tempControllerb) hyGainb = hyControllerb.GainValue hyTiValueb = hyControllerb.TiValue 'Change detuning factor If m < Range("G6") Then Detuning(m2 + 1) = Detuning(m2) - Range("M3") End If Next m2 hyCase.Close End Sub 139 Appendix D Macros for Sinusoidal Disturbance in Dual Ended Composition Controller This macro is used to calculate the Amplitude Ratio (AR) for sinusoidal disturbance in feed composition at various frequencies. It has been developed in excel and serves as an interface with hysys and excel. The steps involved in this macro are: 1. Define variables 2. Start simulation and Initialise parameters 3. For each frequency: Reset temperature control set point at each sampling period Collect the data and calculate AR Stop and Restart simulation for next frequency and re-initialize parameters 140 Option Explicit Public PVValue As Double Public SP As Double, PV As Double, SPb As Double, PVb As Double Public hyTransferFunction As Operations Public hySpreadsheet As SpreadsheetOp Public Period(100) As Double, Frequency(100) As Double, step As Double Public hyFeedComp As Double, hyOvhdComp As Double, hyBtmComp As Double Public hyFeedCompb As Double, hyOvhdCompb As Double, hyBtmCompb As Double Public maxOvhdComp As Double, maxBtmComp As Double, maxFeedComp As Double Public maxOvhdCompb As Double, maxBtmCompb As Double, maxFeedCompb As Double Public norOvhdComp As Double, norBtmComp As Double, norFeedComp As Double Public norOvhdCompb As Double, norBtmCompb As Double, norFeedCompb As Double Public minOvhdComp As Double, minBtmComp As Double, minFeedComp As Double Public minOvhdCompb As Double, minBtmCompb As Double, minFeedCompb As Double Public hyFeedAmp As Double, hyOvhdAmp As Double, hyBtmAmp As Double Public hyFeedAmpb As Double, hyOvhdAmpb As Double, hyBtmAmpb As Double Public maxFeedAmp As Double, maxOvhdAmp As Double, maxBtmAmp As Double Public maxFeedAmpb As Double, maxOvhdAmpb As Double, maxBtmAmpb As Double Sub sinusoidal_disturbance() 'start simulation case Set hyApp = CreateObject("HYSYS.Application") strCase = Range("B2") Set hyCase = hyApp.SimulationCases.Open(strCase) hyCase.Visible = True 'set simulation objects Set hyFlowsheet = hyCase.Flowsheet Set hySubFlowsheets = hyFlowsheet.Flowsheets Set hySubFlowsheet = hySubFlowsheets.Item(0) tempController = "TIC-100" ovhdCompIndicator = "XIC-100" btmCompIndicator = "XIC-101" Set hyController = hySubFlowsheet.Operations.Item(tempController) Set hySpreadsheet = hyFlowsheet.Operations.Item("SPRDSHT") tempControllerb = "TIC-101" Set hyControllerb = hySubFlowsheet.Operations.Item(tempControllerb) hyFeedComp = hySpreadsheet.Cell("D6").CellValue hyOvhdComp = hySpreadsheet.Cell("D1").CellValue hyBtmComp = hySpreadsheet.Cell("D2").CellValue hyFeedCompb = hySpreadsheet.Cell("D7").CellValue hyOvhdCompb = hySpreadsheet.Cell("D3").CellValue hyBtmCompb = hySpreadsheet.Cell("D4").CellValue 'Initialise parameters Detuning(1) = Range("M2") 141 hyGain = hyController.GainValue hyTiValue = hyController.TiValue h = Range("J2") * 60 'Step size for integration SP = Range("B3") SPb = Range("G5") A = Range("B6") initialRun = Range("G4") * 60 Period(1) = Range("B4") step = Range("B5") hySpreadsheet.Cell("A1").CellValue = Period(1) Frequency(1) = 2 * 3.14 / Period(1) hyGainb = hyControllerb.GainValue hyTiValueb = hyControllerb.TiValue Ab = Range("C6") norFeedComp = hyFeedComp norOvhdComp = hyOvhdComp norBtmComp = hyBtmComp norFeedCompb = hyFeedCompb norOvhdCompb = hyOvhdCompb norBtmCompb = hyBtmCompb 'Initial set points Range("B10") = hyGain Range("B11") = hyTiValue Range("B12") = hySubFlowsheet.Operations.Item(ovhdCompIndicator).SPValue Range("B13") = hySubFlowsheet.Operations.Item(btmCompIndicator).SPValue Range("B88") = hySubFlowsheet.Operations.Item(tempController).SPValue Range("C88") = hySubFlowsheet.Operations.Item(tempController).PVValue Range("F11") = norFeedComp Range("D11") = norOvhdComp Range("E11") = norBtmComp Range("F14") = norFeedCompb Range("D14") = norOvhdCompb Range("E14") = norBtmCompb Range("C10") = hyGainb Range("C11") = hyTiValueb 'run simulation and calculate IAE for different tuning factors For m = 1 To Range("G6") 'Change controller tuning parameters hyGain = hyGain / Detuning(m) hyTiValue = hyTiValue * Detuning(m) hyController.GainValue = hyGain hyController.TiValue = hyTiValue 142 hyGainb = hyGainb / Detuning(m) hyTiValueb = hyTiValueb * Detuning(m) hyControllerb.GainValue = hyGainb hyControllerb.TiValue = hyTiValueb 'run case to stabilise the control hyCase.Solver.Integrator.RunUntil (initialRun) k = hyCase.Solver.Integrator.CurrentTime 'Initialise Integral = 0 Integralb = 0 For jj = 1 To Range("J3") 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue B = (Log(PV) - A) * (trayT + 273) Tset = (B / (Log(SP) - A)) - 273 trayTb = hySubFlowsheet.Operations.Item(tempControllerb).PVValue PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue Bb = (Log(PVb) - Ab) * (trayTb + 273) Tsetb = (Bb / (Log(SPb) - Ab)) - 273 For j = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset hySubFlowsheet.Operations.Item(tempControllerb).SPValue = Tsetb k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue Next j Next jj hyFeedComp = hySpreadsheet.Cell("D6").CellValue hyOvhdComp = hySpreadsheet.Cell("D1").CellValue hyBtmComp = hySpreadsheet.Cell("D2").CellValue hyFeedCompb = hySpreadsheet.Cell("D7").CellValue hyOvhdCompb = hySpreadsheet.Cell("D3").CellValue hyBtmCompb = hySpreadsheet.Cell("D4").CellValue maxFeedAmp = 0 maxOvhdAmp = 0 maxBtmAmp = 0 maxFeedComp = 0 maxOvhdComp = 0 maxBtmComp = 0 143 minFeedComp = 1 minOvhdComp = 1 minBtmComp = 1 maxFeedAmpb = 0 maxOvhdAmpb = 0 maxBtmAmpb = 0 maxFeedCompb = 0 maxOvhdCompb = 0 maxBtmCompb = 0 minFeedCompb = 1 minOvhdCompb = 1 minBtmCompb = 1 If Range("G3") * 60 < Period(m) Then jj2 = Round(1.5 * Period(m) / (Range("G3") * 60), 0) Else: jj2 = 1 End If 'If jj2 < Range("J4") Then 'l = Round((Range("J4") / jj2), 0) 'Else: l = 1 'End If If m = 1 Then l = Round((Range("J4") / jj2), 0) Else: l = 1 End If Range("J5") = jj2 For jj1 = 1 To l For j2 = 1 To jj2 'reset temperature control set point trayT = hySubFlowsheet.Operations.Item(tempController).PVValue PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue B = (Log(PV) - A) * (trayT + 273) Tset = (B / (Log(SP) - A)) - 273 trayTb = hySubFlowsheet.Operations.Item(tempControllerb).PVValue PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue Bb = (Log(PVb) - Ab) * (trayTb + 273) Tsetb = (Bb / (Log(SPb) - Ab)) - 273 For j1 = 1 To Range("J6") hySubFlowsheet.Operations.Item(tempController).SPValue = Tset 144 hySubFlowsheet.Operations.Item(tempControllerb).SPValue = Tsetb If k > Range("G7") * 60 Then Exit For k=k+h hyCase.Solver.Integrator.RunUntil (k) PV = hySubFlowsheet.Operations.Item(ovhdCompIndicator).PVValue hyFeedComp = hySpreadsheet.Cell("D6").CellValue hyOvhdComp = hySpreadsheet.Cell("D1").CellValue hyBtmComp = hySpreadsheet.Cell("D2").CellValue hyFeedCompb = hySpreadsheet.Cell("D7").CellValue hyOvhdCompb = hySpreadsheet.Cell("D3").CellValue hyBtmCompb = hySpreadsheet.Cell("D4").CellValue 'Trapezoidal rule for Numerical Integration y = Abs(PV - SP) I=h*y Integral = I + Integral 'Bottom composition PVb = hySubFlowsheet.Operations.Item(btmCompIndicator).PVValue yb = Abs(PVb - SPb) Ib = h * yb Integralb = Ib + Integralb ' composition output 'If m = Round(Range("G6") / 2, 0) Then If m = 1 Then Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 1) = k / 60 Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 2) = Tset Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 3) = trayT Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 4) = PV Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 5) = PVb Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 6) = hyFeedComp Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 7) = hyOvhdComp Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 8) = hyBtmComp Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 9) = hyFeedCompb Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 10) = hyOvhdCompb Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 11) = hyBtmCompb Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 12) = B Cells(88 + (jj1 - 1) * Range("J6") * jj2 + (j2 - 1) * Range("J6") + j1, 13) = Bb End If 145 If hyOvhdComp > maxOvhdComp Then maxOvhdComp = hyOvhdComp End If If hyBtmComp > maxBtmComp Then maxBtmComp = hyBtmComp End If If hyFeedComp > maxFeedComp Then maxFeedComp = hyFeedComp End If If hyOvhdComp < minOvhdComp Then minOvhdComp = hyOvhdComp End If If hyBtmComp < minBtmComp Then minBtmComp = hyBtmComp End If If hyFeedComp < minFeedComp Then minFeedComp = hyFeedComp End If If hyOvhdCompb > maxOvhdCompb Then maxOvhdCompb = hyOvhdCompb End If If hyBtmCompb > maxBtmCompb Then maxBtmCompb = hyBtmCompb End If If hyFeedCompb > maxFeedCompb Then maxFeedCompb = hyFeedCompb End If If hyOvhdCompb < minOvhdCompb Then minOvhdCompb = hyOvhdCompb End If If hyBtmCompb < minBtmCompb Then minBtmCompb = hyBtmCompb End If If hyFeedCompb < minFeedCompb Then minFeedCompb = hyFeedCompb End If Next j1 Next j2 hyOvhdAmp = (maxOvhdComp - minOvhdComp) / 2 hyBtmAmp = (maxBtmComp - minBtmComp) / 2 hyFeedAmp = (maxFeedComp - minFeedComp) / 2 If hyOvhdAmp > maxOvhdAmp Then maxOvhdAmp = hyOvhdAmp End If If hyBtmAmp > maxBtmAmp Then maxBtmAmp = hyBtmAmp 146 End If If hyFeedAmp > maxFeedAmp Then maxFeedAmp = hyFeedAmp End If hyOvhdAmpb = (maxOvhdCompb - minOvhdCompb) / 2 hyBtmAmpb = (maxBtmCompb - minBtmCompb) / 2 hyFeedAmpb = (maxFeedCompb - minFeedCompb) / 2 If hyOvhdAmpb > maxOvhdAmpb Then maxOvhdAmpb = hyOvhdAmpb End If If hyBtmAmpb > maxBtmAmpb Then maxBtmAmpb = hyBtmAmpb End If If hyFeedAmpb > maxFeedAmpb Then maxFeedAmpb = hyFeedAmpb End If Next jj1 'IAE=Total area divided by the time IAE(m) = Integral Cells(18 + m, 2) = Detuning(m) Cells(18 + m, 3) = IAE(m) 'Bottom composition IAEb(m) = Integralb Cells(18 + m, 4) = IAEb(m) Cells(18 + m, 5) = Frequency(m) Cells(18 + m, 6) = Period(m) Cells(18 + m, 7) = maxOvhdAmp Cells(18 + m, 8) = maxBtmAmp Cells(18 + m, 9) = maxFeedAmp Cells(18 + m, 10) = maxOvhdAmpb Cells(18 + m, 11) = maxBtmAmpb Cells(18 + m, 12) = maxFeedAmpb 'Close simulation case (in order to start next case from same point) hyCase.Close 'Open simulation case Set hyCase = hyApp.SimulationCases.Open(strCase) hyCase.Visible = True 'reset simualtion case objects Set hyFlowsheet = hyCase.Flowsheet Set hySubFlowsheets = hyFlowsheet.Flowsheets Set hySubFlowsheet = hySubFlowsheets.Item(0) 147 Set hyController = hySubFlowsheet.Operations.Item(tempController) hyGain = hyController.GainValue hyTiValue = hyController.TiValue step = Range("B5") Set hyfeedStream = hySubFlowsheet.MaterialStreams.Item("feed") Set hyOvhdStream = hySubFlowsheet.MaterialStreams.Item("ovhdliq") Set hyBtmStream = hySubFlowsheet.MaterialStreams.Item("btmliq") Set hySpreadsheet = hyFlowsheet.Operations.Item("SPRDSHT") Set hyControllerb = hySubFlowsheet.Operations.Item(tempControllerb) hyGainb = hyControllerb.GainValue hyTiValueb = hyControllerb.TiValue 'Initialise parameters h = Range("J2") * 60 'Step size for integration SP = Range("B3") SPb = Range("G5") A = Range("B6") Ab = Range("C6") initialRun = Range("G4") * 60 If m < Range("G6") Then Period(m + 1) = 10 ^ (WorksheetFunction.Log10(Period(m)) + step) hySpreadsheet.Cell("A1").CellValue = Period(m + 1) Frequency(m + 1) = 2 * 3.14 / Period(m + 1) Detuning(m + 1) = Detuning(m) End If Next m hyCase.Close End Sub [...]... the operation away from constraints A distillation unit may have a large number of measurements However, there are some critical parameters which need to be controlled Lundstrom and Skogestad (1995) explained that a one-feed two-product distillation column has five manipulated variables (flow of reflux, distillates and bottoms, and duty of reboiler and condenser) and at least five controlled variables... is vast literature available on various aspects of distillation design and control, viz steady-state and dynamic modeling, design and control objectives, control structure design, controllability and control loop interactions, tuning of controllers, and various tools available for design However, it is observed that some key design and operational aspects need further research The performance of control. .. dynamics (Deshpande, 1985) Skogestad (1997) explained some fundamentals of steady state and dynamic behavior of distillation columns He provided some short-cut formulas for estimating RGA for different configurations, and various types of control configuration and their selection based on Closed Loop Disturbance Gain (CLDG) Mahoney and Fruehauf1 highlighted the importance of dynamic simulation to assess... (CCC) The starting point for a dynamic simulation is a sound steady-state simulation, as this forms a basis for any control study (Alsop and Ferrer, 2004) Skogestad (1988, 1997) gave insight into column behavior using fundamentals and short-cut methods in steady state and dynamics of distillation column He explained some concepts related to modeling of distillation column for dynamic performance Shinskey... consistent gap between industry and academia on column modeling and control such as usage of unrealistic linear models, assumption of minimum phase dynamics, assumption of constant time delay, missing interacting lags in columns and arbitrary objective functions by academics The latest generation of process simulators is quite easy to use, flexible, thermodynamically sound, and can provide more realistic... Amrithalingham et al (1999) used Hysys as a dynamic simulation software and interfaced it with Matlab for building an inferential control model for a depropaniser Ross et al (2000) analyzed operating problems of a highly non-linear industrial column using mixedinteger dynamic optimization (MIDO) as the dynamic optimization tool to design the 2 Literature Survey 11 system via simultaneous design and control approach... Performance of Various Configurations for Dual Ended 97 Composition Control with lower (LFT) or higher (HFT) Feed Tray Location compared with Base Configuration xiv List of Tables Table 3.1 Steady State Design Data and Assumptions 17 Table 3.2 Design Parameters for Dynamic Simulation 19 Table 3.3 Data for and Results from Short-cut Distillation 21 Table 3.4: Possible Pairings of Controlled and Manipulated... systematically takes the reader through understanding distillation concepts, steady-state design and various control strategies Kister (1990) presented operational aspects of distillation units and provided practical recommendations for troubleshooting distillation problems Luyben (1990) describes the concept of mathematical modeling and simulation of process systems and describes the concepts of advanced... has been a shift in the academia using more industrially acceptable simulators Hysys® and Aspen Plus from Aspentech, and Pro-II from Scimsci are such simulators which can be used for steady-state modeling Hysys can give a smooth transition from steady state to dynamic simulation Visual Basic (VB) can be used as an interface of HYSYS with Excel (John Green, 2003 and VBA Tutorials from HYSYS) Amrithalingham... and non-linear, and have major impact on the utilities consumption and product quality Thus selection of proper controls for distillation columns is both challenging and critical The dynamic behavior of a column is a combination of steady state design, control structure selected and the column integration with the rest of the plant This makes each column unique in terms of its overall performance So, ... Design, Simulation and Control of a Depropaniser 17 Chapter Design, Simulation and Control of a Depropaniser 3.1 Basis and Method A depropaniser column design similar to that defined in the doctoral... academia on column modeling and control such as usage of unrealistic linear models, assumption of minimum phase dynamics, assumption of constant time delay, missing interacting lags in columns and arbitrary... HYSYS) Amrithalingham et al (1999) used Hysys as a dynamic simulation software and interfaced it with Matlab for building an inferential control model for a depropaniser Ross et al (2000) analyzed