PNNL 31300 Energy Storage Evaluation Tool September 2021 D Wu D Wang X Ma T Ramachandran S Huang T Fu DISCLAIMER United States Government Neither the United States Government nor any agency thereof, n.
PNNL-31300 Energy Storage Evaluation Tool September 2021 D Wu X Ma S Huang D Wang T Ramachandran T Fu DISCLAIMER United States Government Neither the United States Government nor any agency thereof, nor Battelle Memorial Institute, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute The views and opinions of authors expressed herein not necessarily state or reflect those of the United States Government or any agency thereof PACIFIC NORTHWEST NATIONAL LABORATORY operated by BATTELLE for the UNITED STATES DEPARTMENT OF ENERGY under Contract DE-AC05-76RLO1830 Printed in the United States of America Available to DOE and DOE contractors from the Office of Scientific and Technical Information, P.O Box 62, Oak Ridge, TN 37831-0062; ph: (865) 576-8401 fax: (865) 576-5728 email: reports@adonis.osti.gov Available to the public from the National Technical Information Service, U.S Department of Commerce, 5285 Port Royal Rd., Springfield, VA 22161 ph: (800) 553-6847 fax: (703) 605-6900 email: orders@ntis.fedworld.gov online ordering: http://www.ntis.gov/ordering.htm This document was printed on recycled paper (7/2019) PNNL-31300 Energy Storage Evaluation Tool D Wu X Ma S Huang D Wang T Ramachandran T Fu September 2021 Prepared for the U.S Department of Energy under Contract DE-AC05-76RL01830 Pacific Northwest National Laboratory Richland, Washington 99352 Contents 1.0 Introduction 2.0 ESET Platform 2.1 Platform Architecture 2.2 Getting Started 2.2.1 Registration and Account Management 2.2.2 Dashboard and Project Management 2.2.3 Project Input and Output Pages 3.0 Battery Storage Evaluation Tool 3.1 Input 3.1.1 Use Cases and Functions 3.1.2 Grid and End-user Services 3.1.3 BESS Technical Parameters 3.1.4 Sizing Range and Step Size 3.1.5 BESS Economic Parameters 3.2 Output 3.2.1 Optimal BESS Size 3.2.2 Present-Value Cost and Benefits 3.2.3 Sizing Exploration 3.2.4 Summary of Annual Results 3.2.5 BESS Operation 4.0 Microgrid Asset Sizing Considering Cost and Resilience 4.1 Input 4.1.1 Settings 4.1.2 Load Profile 4.1.3 Tariff Structure 4.1.4 Financial Analysis 4.1.5 DER Selection 4.1.6 PV Parameters 4.1.7 ESS Parameters 4.1.8 DG Parameters 4.2 Output 4.2.1 Sizing Results 4.2.2 Cost Analysis 4.2.3 Monthly Peak Load 4.2.4 Annual Operation in Grid-Connected Mode 5.0 Hydrogen Energy Storage Evaluation Tool 5.1 Input 5.1.1 System Configuration 5.1.2 Financial Analysis 5.1.3 Grid Services 5.1.4 Electrolyzer 5.1.5 Water Cost 5.1.6 Hydrogen Storage 5.1.7 Pathway 1: Tube Compressor 5.1.8 Pathway 1: Hydrogen Sale iii 1.1 2.1 2.1 2.3 2.3 2.4 2.5 3.1 3.3 3.3 3.4 3.6 3.6 3.6 3.7 3.7 3.7 3.8 3.8 3.10 4.1 4.2 4.2 4.3 4.3 4.4 4.4 4.4 4.5 4.5 4.6 4.6 4.6 4.7 4.8 5.1 5.2 5.2 5.2 5.3 5.4 5.4 5.4 5.5 5.5 5.1.9 Pathway 2: Pipeline Injection 5.1.9.1 Optional Components 5.1.9.2 Methanation 5.1.10 Pathway 3: Fuel Cell 5.2 Output 5.2.1 Annual Hours of Operation, Production, and Financial Returns 5.2.2 One-year Simulated Benefits and O&M Costs 5.2.3 HES Hourly Prices, Load/Generation, and Hydrogen Flow 6.0 Pumped Storage Hydropower Evaluation Tool 6.1 Input 6.1.1 System Configuration 6.1.2 PSH Financial Analysis and Economic Parameters 6.1.3 Grid and End-user Services 6.2 Output 6.2.1 Present Value Costs and Benefits 6.2.2 Summary of Annual Results 6.2.3 PSH Operation 7.0 Virtual Battery Assessment Tool 7.1 Navigation Panel 7.2 Setting 7.2.1 Geographical Level 7.2.2 Region and Device Type 7.2.3 Assessment Results 8.0 References iv 5.5 5.6 5.6 5.6 5.7 5.7 5.8 5.9 6.1 6.1 6.1 6.3 6.4 6.6 6.6 6.6 6.7 7.1 7.2 7.3 7.3 7.3 7.5 8.1 Figures Figure ESET platform architecture Figure Database architecture Figure Docker-based deployment Figure Create an account Figure Account management Figure User dashboard Figure Project input page Figure Help text Figure Notification message when an evaluation is completed Figure 10 Project output page Figure 11 Illustration of MPC-based evaluation approach Figure 12 Illustration of bilevel sizing approach Figure 13 BSET Settings panel Figure 14 BSET Grid Service Selection and BTM Service Selection panels Figure 15 BSET Grid Service Inputs panel Figure 16 BSET T&D Deferral Inputs panel Figure 17 BSET BTM Service Inputs panel Figure 18 BSET BESS Technical Parameters panel Figure 19 BSET Sizing Range and Sizing Step Size panels Figure 20 BSET BESS Economic Parameters panel Figure 21 BSET BESS Size and Optimal BESS Size Figure 22 BSET Present-Value Costs and Benefits Figure 23 BSET Sizing Exploration Figure 24 BSET Annual Benefits by Service Figure 25 BSET Number of Hours by Service Figure 26 BSET Annual Electricity Bill Figure 27 BSET Monthly Peak Load Figure 28 BSET BESS Operation Figure 29 Illustration of the two-stage stochastic DER sizing method Figure 30 MASCORE Settings panel with Min net cost selected Figure 31 MASCORE Settings panel with Max survivability selected Figure 32 MASCORE Load Profile panel Figure 33 MASCORE Tariff Structure panel Figure 34 MASCORE Financial Analysis panel Figure 35 MASCORE DER Selection panel Figure 36 MASCORE PV Parameters panel Figure 37 MASCORE ESS Parameters panel Figure 38 MASCORE DG Parameters panel Figure 39 MASCORE Sizing Results Figure 40 MASCORE Cost Analysis Figure 41 MASCORE Monthly Peak Load Figure 42 MASCORE Annual Operation in Grid-Connected Mode Figure 43 HES system scope Figure 44 HES System Configuration panel Figure 45 HES Financial Analysis panel v 2.1 2.2 2.3 2.3 2.4 2.4 2.5 2.6 2.6 2.7 3.2 3.3 3.4 3.4 3.5 3.5 3.5 3.6 3.6 3.7 3.7 3.7 3.8 3.9 3.9 3.10 3.10 3.11 4.2 4.2 4.2 4.3 4.4 4.4 4.4 4.5 4.5 4.6 4.6 4.7 4.7 4.8 5.2 5.2 5.3 Figure 46 HES Services and Value Streams panel Figure 47 HES grid service input panels Figure 48 HES Electrolyzer panel Figure 49 HES Water Cost panel Figure 50 HES Hydrogen Storage panel Figure 51 HES Compressor panel Figure 52 HES Hydrogen Sale panel Figure 53 HES Pathway2: Pipeline Injection panel Figure 54 HES Pathway2: Optional Components panel Figure 55 HES Pathway 2: Methanation panel Figure 56 HES Pathway 3: Fuel Cell panel Figure 57 HES Annual Hours of Operation, Production, and Financial Returns Figure 58 HES PV benefits Figure 59 HES PV cost Figure 60 HES One-year Simulated Benefits and O&M Costs panel Figure 61 HES one-year simulated benefits Figure 62 HES one-year simulated cost Figure 63 HES hourly hydrogen flow Figure 64 HES hourly stored hydrogen Figure 65 PSHET System Configuration panel Figure 66 PSH unit types Figure 67 PSH generator/motor technologies Figure 68 PSHET PSH Unit Parameters panel Figure 69 PSHET Financial Analysis panel Figure 70 PSHET Economic Parameters panel Figure 71 PSHET Energy Arbitrage panel Figure 72 PSHET Frequency Regulation panel Figure 73 PSHET Spinning Reserve panel Figure 74 PSHET Transmission and Distribution (T&D) Upgrade Deferral panel Figure 75 PSHET Capacity Value/Resource Adequacy panel Figure 76 PSHET Power Reliability panel Figure 77 PSHET Present Value Costs and Benefits Figure 78 PSHET Annual Benefits by Service Figure 79 PSHET Number of Hours by Service Figure 80 PSHET grid service prices Figure 81 PSHET unit-level operation Figure 82 PSHET system-level operation and water volume state Figure 83 VBAT assessment procedures Figure 84 VBAT navigation panel Figure 85 VBAT Geographical Level page Figure 86 VBAT Device Type page Figure 87 VBAT Region & Device Type page Figure 88 VBAT Assessment Results page vi 5.3 5.3 5.4 5.4 5.4 5.5 5.5 5.6 5.6 5.6 5.7 5.7 5.7 5.8 5.8 5.9 5.9 5.10 5.10 6.2 6.2 6.2 6.3 6.3 6.4 6.5 6.5 6.5 6.5 6.5 6.6 6.6 6.6 6.7 6.7 6.8 6.8 7.2 7.2 7.3 7.4 7.4 7.5 Tables Table Solution approaches by use case and functionality vii 3.3 In this panel, users can also specify whether generator/motor technology can operate at a fixed speed or adjustable speed, as shown in Figure 67 With fixed-speed technology, both the motor and generator can operate at a synchronous speed In comparison, the adjustable-speed technology allows the motor to rotate at a non-synchronous speed By varying motor speed, the pump curve can be shifted, so that the improved efficiency can be achieved over a range of flow rates PSHET also supports the modeling of hydraulic short circuit (HSC) at both unit and plant level The unit-level HSC pairs pumps and turbines, connecting inlets of turbines to discharges of pumps The plant-level HSC allows inlets of turbines and discharges of pumps for all units, regardless of technology selected, to be connected The HSC modes increase the PSH operation flexibility by allowing variable flows to be pumped to the upper reservoir Note that a ternary unit must have unit-level HSC selected and a unit with reversible pump/turbine must have unitlevel HSC unselected The PSH Unit Parameters panel allows users to define the minimum and maximum generating/pumping power (in MW) and the corresponding generating/pumping water discharge (in cfs, i.e., cubic feet per second) per unit, as shown in Figure 68 Figure 68 PSHET PSH Unit Parameters panel 6.1.2 PSH Financial Analysis and Economic Parameters The Financial Analysis panel allows users to define the time horizon (in years) for evaluation and the real discount rate, as shown Figure 69 The real discount rate is used to calculate the present-value net benefit of a PSH plant Figure 69 PSHET Financial Analysis panel The Economic Parameters panel allows users to define PSH cost parameters as shown in Figure 70 Note that the power cost is the equivalent investment cost, including both the capital cost and operation and maintenance (O&M) cost in present value The power cost is modeled using 6.3 a linear function of PSH power capacity, where a constant term is used to represent the fixed costs for installation, electrical, IT, etc The PSH operational cost includes the fixed and variable O&M cost, as well as each unit’s start-up cost for generating/pumping Figure 70 PSHET Economic Parameters panel 6.1.3 Grid and End-user Services PSHET enables users to bundle multiple services and capture stacked value streams Inputs such as service prices, tariff structure, and load profile are required for PSH evaluation analysis Screenshots for grid service inputs are provided in Figures 71–75 Each service is selected by checking the corresponding checkbox Grid service inputs include hourly energy price, regulation price, spinning reserve price, Transmission and Distribution (T&D) deferral events and upgrade cost, capacity events and price The hourly prices in historical or representative year can be used as inputs for evaluating energy arbitrage, frequency regulation, and spinning reserve • Most markets have implemented pay-for-performance to calculate rewarding credit based on regulation capacity, regulation mileage, and performance factor/score The capacity payment is calculated based on the capacity prices and regulation capacity In some markets, the performance factor is used to adjust the capacity payment The mileage payment is calculated based on the mileage prices, regulation mileage, and performance score The inputs for regulation services include capacity and mileage prices and performance score, as shown in Figure 72 • The inputs for the economic assessment of T&D deferral include existing load profile, load growth rate, existing infrastructure capacity, and planned upgrade cost, as shown in Figure 74 Based on the existing load profile and load growth rate, the peak demand for future years is calculated and compared with the existing infrastructure capacity to determine the year when T&D investment needs to be made Annual peak minimization problems are formulated and solved repeatedly to determine the year when the T&D upgrade must be made Based on the upgrade cost and the years when T&D investment needs to be made with and without a PSH, present-value costs are calculated and T&D deferral benefits are estimated • The value of generation capacity is primarily derived from a PSH plant’s contribution to resource adequacy and system reliability The input file contains information for forecast dates and hours when the capacity will be called by the system operator and how much capacity (in percentage) is required from the PSH plant The capacity price is assumed to 6.4 be a yearly value, as shown in Figure 75 Figure 71 PSHET Energy Arbitrage panel Figure 72 PSHET Frequency Regulation panel Figure 73 PSHET Spinning Reserve panel Figure 74 PSHET Transmission and Distribution (T&D) Upgrade Deferral panel Figure 75 PSHET Capacity Value/Resource Adequacy panel The screenshot for power reliability (an end-user service) inputs is provided in Figure 76 These inputs include outage scenarios and outage mitigation price 6.5 Figure 76 PSHET Power Reliability panel 6.2 6.2.1 Output Present Value Costs and Benefits The Present Value Costs and Benefits panel lists costs, benefits, and net benefits in present value, as shown in Figure 77 Figure 77 PSHET Present Value Costs and Benefits 6.2.2 Summary of Annual Results PSHET provides annual benefits by service and PSH usage in hours by service, as shown in Figures 78 and 79, respectively Figure 78 PSHET Annual Benefits by Service 6.6 Figure 79 PSHET Number of Hours by Service 6.2.3 PSH Operation PSHET also enables users to view detailed wholesale market prices and PSH operation (both at the unit- and system-level) throughout a year, as shown in Figures 80–82, respectively The scheduled and/or actual PSH operation as well as its water volume state profile are plotted and synchronized in time Note that a positive PSH power means discharging and corresponds to a decreased water volume state Figure 80 PSHET grid service prices 6.7 Figure 81 PSHET unit-level operation Figure 82 PSHET system-level operation and water volume state 6.8 7.0 Virtual Battery Assessment Tool Exploiting flexibility from demand-side resources represents an innovative solution for solving a multitude of issues in today’s rapidly evolving electric power grid Among various demand-side resources, buildings consume about 75% of the total electricity in the U.S The massive electric energy consumption and enormous thermal storage capability of buildings provide great potential for various grid services When control properly, buildings with an inherent ability to store heat in thermal mass can vary their power consumption and shift the electric energy consumption to an earlier or later time with little impact on customers’ comfort and convenience Flexible building loads represent a significant and largely untapped resource for the grid Conventional control methods are based on detailed dynamic models and consider operational constraints for individual buildings and devices When scheduling a large group of building loads for grid services, it is computationally expensive yet unnecessary to model and consider detailed dynamics and constraints of individual devices To coordinate flexible building assets with generators and energy storage systems over a large area, it is impractical for grid operators to incorporate thousands of detailed dynamic building load models into their daily scheduling and dispatch systems Therefore, simplified models are needed to represent the aggregate building load flexibility from a large number of buildings To better understand the flexibility potential from building loads and enable scheduling, dispatch, and control of flexible loads at the system, community, building, and device levels, advanced methods are required to characterize, quantify, and utilize flexibility in buildings for various grid services One approach is to characterize aggregate flexibility from a collection of building loads using battery-equivalent models or virtual batteries (VBs) A VB is a scalar linear system that resembles simplified battery dynamics parameterized by charging/discharging power limits, energy limits, and self-discharging rate The generalized VB model is convenient for quantifying aggregated flexibility or designing coordination algorithms, because all different types of resources can be represented using the same model and there is no need to consider diversified characteristics and dynamics for different types of loads Different characterization methods have been proposed to construct VB models for building loads, such as analytical methods [Hao et al., 2015], optimization-based methods [Hao et al., 2018], and simulation-based methods [Huang and Wu, 2019, Huang et al., 2020] Various VBbased scheduling and control methods can be found in [Wu et al., 2020b, Wang et al., 2020b, Wang et al., 2020a] Based on these methods, PNNL has developed a tool named VBAT to enable industry, regulators, and other stakeholders to quantify technical potential and economic benefits from flexible building loads Housing, population, weather station, and climate zone information have been collected and used for VB potential estimation [Wu et al., 2018] Specifically, we have collected various information at different geographical levels (county, state, and census region) in the U.S., including housing, population, building asset penetration rate, outdoor temperature, to estimate VB potential for four types of residential thermostatically controlled loads (TCL), three types of commercial refrigeration, and heating, ventilation, and air conditioning (HVAC) systems in commercial offices We are currently working to integrate VB scheduling methods into VBAT for bundling grid services and plan to make them available to the public in future versions The remainder of this section details how to use VBAT for regional 7.1 flexibility assessment for different types of building loads 7.1 Navigation Panel Users follow three steps to generate regional flexibility from different types of building loads, as illustrated in Figure 83 • Select geographical level • Select region and device type • View assessment results There is a navigation panel to enable users to switch between different steps Depending on the selected geographical level, the navigation panel may appear slightly different, as shown in Figure 84 Figure 83 VBAT assessment procedures Figure 84 VBAT navigation panel 7.2 7.2 Setting 7.2.1 Geographical Level A screenshot of the Geographical Level page is provided in Figure 85 Regional building load characteristics depend on factors such as climate, population, and housing, which vary much from one U.S region to another Therefore, different regions could exhibit quite different VB potential from building loads On the Geographical Level page, users can specific the geographical level at which the flexibility assessment to be performed, including U.S., Census Region and Division, State, and County In particular, Census Region and Division used in VBAT is defined by the U.S Census Bureau [United States Census Bureau, 2010] Figure 85 VBAT Geographical Level page 7.2.2 Region and Device Type Based on the geographical level selected, users can specify region, state, or county accordingly The characteristics and flexibility also vary by building load type In the existing version of VBAT, the following building loads available: • Residential TCLs: air conditioners, heat pump, water heaters, refrigerators • Commercial refrigerators: display case, food preparation, and walk-in refrigerators The geographical diversity of device parameters is built into the model Depending on the geographical level select, different pages appear for selecting region/state/county and device type Figure 86 and Figure 87 are examples corresponding to cases where U.S and Census Region and Division are selected, respectively 7.3 Figure 86 VBAT Device Type page Figure 87 VBAT Region & Device Type page 7.4 7.2.3 Assessment Results Based on the geographical level, specific region/state/county, and device type selected, hourly VB power and energy limits are generated, as shown in Figure 88 Users can click the Run button to view the results Users can select a particular area to zoom in and explore the results in detail and click the Reset Zoom button to exit a zoom-in mode and return to the original axes limits The Download button enables users to download the numerical data for a record or customized analysis Figure 88 VBAT Assessment Results page 7.5 8.0 References [Feldt, 2020] Feldt R 2020 https://github.com/robertfeldt/BlackBoxOptim.jl [Hao et al., 2015] Hao H, BM Sanandaji, K Poolla, and TL Vincent 2015 “Aggregate Flexibility of Thermostatically Controlled Loads.” IEEE Transactions on Power Systems 30(1):189– 198 [Hao et al., 2018] Hao H, D Wu, J Lian, and T Yang 2018 “Optimal Coordination of Building Loads and Energy Storage for Power Grid and End User Services.” IEEE Transactions on Smart Grid 9(5):4335–4345 [Huang and Wu, 2019] Huang S and D Wu 2019 “Validation on aggregate flexibility from residential air conditioning systems for building-to-grid integration.” Energy and Buildings 200:58–67 [Huang et al., 2020] Huang S, Y Ye, D Wu, and W Zuo 2020 “An assessment of power flexibility from commercial buildings in the United States.” Energy [United States Census Bureau, 2010] United States Census Bureau 2010 Census Regions and Divisions of the United States [Wang et al., 2020a] Wang J, S Huang, D Wu, and N Lu 2020a “Operating a Commercial Building HVAC Load as a Virtual Battery through Airflow Control.” IEEE Transactions on Sustainable Energy [Wang et al., 2020b] Wang P, D Wu, and K Kalsi 2020b “Flexibility Estimation and Control of Thermostatically Controlled Loads with Lock Time for Regulation Service.” IEEE Transactions on Smart Grid 11(4):3221–3230 [Wu et al., 2018] Wu D, H Hao, T Fu, and K Kalsi 2018 “Regional Assessment of Virtual Battery Potential from Building Loads.” In Proceedings of the IEEE Power and Energy Society Transmission and Distribution Conference and Exposition, pp 1–5 [Wu et al., 2015] Wu D, C Jin, P Balducci, and M Kintner-Meyer 2015 “An Energy Storage Assessment: Using Optimal Control Strategies to Capture Multiple Services.” In Proceedings of the IEEE Power and Energy Society General Meeting, pp 1–5 Denver, CO [Wu et al., 2016] Wu D, M Kintner-Meyer, T Yang, and P Balducci 2016 “Economic Analysis and Optimal Sizing for behind-the-meter Battery Storage.” In Proceedings of the IEEE Power and Energy Society General Meeting, pp 1–5 Boston, MA [Wu et al., 2020a] Wu D, X Ma, S Huang, T Fu, and P Balducci 2020a “Stochastic Optimal Sizing of Distributed Energy Resources for a Cost-effective and Resilient Microgrid.” Energy 198 117284 [Wu et al., 2020b] Wu D, P Wang, X Ma, and K Kalsi 2020b “Scheduling and Control of Flexible Building Loads for Grid Services based on Virtual Battery Models.” In IFAC World Congress 8.1 ... including battery energy storage, storage- enabled microgrid, hydrogen energy storage, pumpedstorage hydropower, and thermal storage in building mass • Battery Energy Storage Evaluation Tool (BSET)... 4.8 5.0 Hydrogen Energy Storage Evaluation Tool Batteries and pumped storage hydroelectric are bidirectional electrical storage systems, which absorb electric energy, store that energy for a period... limits 2.6 Figure 10 Project output page 2.7 3.0 Battery Storage Evaluation Tool Among various energy storage technologies, battery energy storage systems (BESSs) have the best controllability and