Volume 3 solar thermal systems components and applications 3 19 – passive solar architecture

Volume 3 solar thermal systems components and applications 3 19 – passive solar architecture Volume 3 solar thermal systems components and applications 3 19 – passive solar architecture Volume 3 solar thermal systems components and applications 3 19 – passive solar architecture Volume 3 solar thermal systems components and applications 3 19 – passive solar architecture Volume 3 solar thermal systems components and applications 3 19 – passive solar architecture Volume 3 solar thermal systems components and applications 3 19 – passive solar architecture Volume 3 solar thermal systems components and applications 3 19 – passive solar architecture Volume 3 solar thermal systems components and applications 3 19 – passive solar architecture

3.19 Passive Solar Architecture D Kolokotsa, Technical University of Crete, Crete, Greece M Santamouris, A Synnefa, and T Karlessi, National and Kapodistrian University of Athens, Athens, Greece © 2012 Elsevier Ltd All rights reserved 3.19.1 3.19.1.1 3.19.1.2 3.19.1.3 3.19.1.3.1 3.19.1.3.2 3.19.2 3.19.2.1 3.19.2.2 3.19.2.3 3.19.2.4 3.19.2.5 3.19.2.6 3.19.3 3.19.3.1 3.19.3.2 3.19.3.2.1 3.19.3.2.2 3.19.3.2.3 3.19.4 References Introduction Energy and Urbanization Solar Architecture – History and Concepts Solar Architecture – Comprehensive Design and Operation Passive solar heating Passive cooling Role of Solar Architecture in Urban Buildings Development of Cool-Colored Materials Use of Phase Change Materials to Enhance the Performance of Cool-Colored Coatings Development of Thermochromic Coatings Development and Testing of Colored Thin-Film Layers of Asphalt Green Spaces for Urban Buildings Discussion Control Systems for Solar Architecture Controlled Parameters and Control Variables in Passive Solar Architecture Control Strategies in Solar Architecture Conventional control for solar architecture Advanced control Intelligent systems Conclusion and Future Prospects Glossary Cool materials Cool materials are materials with high solar reflectance (high ability to reflect sunlight) and high thermal emittance (high ability to radiate heat) and stay cool in the sun Intelligent control systems in solar architecture Intelligent control systems are defined as intelligence in automation exhibited by an artificial entity Neural networks, genetic programming, fuzzy logic, computer vision, heuristic search, etc and combinations of any of the above are some of the available technologies used to optimize the performance of solar buildings 637 637 638 639 639 642 644 644 646 648 648 651 653 654 655 656 656 657 659 663 663 Urban heat island is a city region which is significantly warmer than its surrounding suburban regions By altering the nature of the city’s surface and generating large amounts of heat, urbanized areas modify the microclimate and air quality The urban heat island serves as a trap for atmospheric pollutants, deteriorates the quality of life and has a direct impact on the energy demand Urbanization The increase of urban population and the physical growth of urban areas as a result of global change Urbanization is also defined by the United Nations as movement of people from rural to urban areas with population growth equating to urban migration 3.19.1 Introduction 3.19.1.1 Energy and Urbanization In recent years, concerns regarding the shortage of traditional energy reserves, the rising demand for energy, fueled partly by the development of new economies, and obvious concerns regarding the effect of irrational energy use and human activity on the environment have made the topic of energy efficiency almost ubiquitous Population growth is commonly assumed to be a key issue of unsustainable consumption The current world population is at around billion people, and is steadily growing by 220 000 each day At the present rate, it is estimated to reach billion by the year 2030 However, energy consumption is not simply determined by population growth, but also by economic activity, technology choices, social values, institutions, and policies Migration of people from rural areas to cities has been on the rise and will likely continue unabated in the so-called less developed countries as a result of increased opportunities being constantly offered in the urban environment and the degradation of the rural Comprehensive Renewable Energy, Volume doi:10.1016/B978-0-08-087872-0.00320-6 637 638 Applications economies and societies Nowadays, approximately 50–60% of the world’s population lives in cities and towns The second half of the last century was a period of more intensive urbanization that our planet had never experienced In fact, urban population has increased from 160 million to about billion in just 100 years, and it is expected to increase to about billion by 2025 This has resulted in the energy consumed in buildings to account for 40% of the energy used worldwide, and it has become a widely accepted fact that measures and changes in the building modus operandi can yield substantial energy savings Evidently, even very modest reductions can have a significant impact Advances in the design, operational optimization, and control of energy-influencing building elements (e.g., building design and services, solar energy, fuel cells, shading, and natural ventilation) unleashed the potential for realization of significant energy savings and efficiencies in the operation of both new and existing building sites worldwide Moreover, buildings constitute a major part of the economic sector in the world and the quality of buildings shapes the life of citizens Although there is an important and substantial increase in the budget allocation toward construction, the United Nations estimates [1] that more than billion urban citizens live in inappropriate houses – mostly in squatter and slum settlements – while in most of the cities in the less developed countries, between one-third and two-thirds of the population live in poor quality and overcrowded housing [2] Even in the developed world, the percentage of people living in low-income households is quite high The average percentage of low-income households in the European Union is close to 15%, while in some countries like Ireland it may go up to 21% Inappropriate housing is characterized by poor indoor environmental conditions such as extremely low or high temperatures and lack of ventilation In parallel, heat-island conditions in dense urban areas increase ambient temperatures and the thermal stress to buildings, especially during the summer period [3] The aforementioned international framework along with the possibility of local energy generation with the exploitation of renewable energy sources has led to the concept of solar architecture [4], that is, the design of buildings that consume less than 15 kWh m−2 energy by applying bioclimatic principles combined with locally installed (renewable) energy-generating sources to produce part of their energy demands This leads to the ‘Passive House concept’, which aims to provide a satisfactory indoor environmental quality in terms of indoor air quality (IAQ) and thermal comfort at minimum energy demand and cost [5] Minimizing energy and costs at the same time is not possible with conventional improvements Significant energy efficiency and energy cost reduction can be achieved by the integration of innovative design and operational aspects that contribute simultaneously to the required balance among indoor quality and energy demand 3.19.1.2 Solar Architecture – History and Concepts Extensive research is recorded in the literature concerning solar techniques for the reduction of energy consumption in buildings The solar techniques can be categorized as passive and active solar systems Active solar systems incorporate electrical or mechanical equipment, such as pumps and fans, to forward the energy produced by the sun to the buildings Active thermal solar systems are systems using solar collectors (either flat or evacuated tubes), solar concentrators (parabolic trough), and so on Active cooling systems are solar devices coupled with chillers, solar-assisted air conditioners, and roof-integrated water or air solar collectors (Figure 1) In any case, the production of electricity is performed via photovoltaics (PV) Solar architecture and passive house concepts are not new The solar insolation and path has always influenced a building’s orientation, location, shape, constructional elements, and materials used Climate is one of the major parameters that influenced Figure Active solar systems incorporated in the building fabric Passive Solar Architecture 639 Figure The solar architectural concepts in Socrates solar house (470–399 BC) the evolution of construction types and buildings’ design techniques One example is the Socrates solar house [6], which incorporates the following features as shown in Figure 2: • • • • • trapezoidal plan with increased south facade, compact form, solar zoning with cool rooms on the north side and warm rooms on the south side, shading protection against solar radiation during the summer period, and utilization of thermal mass 3.19.1.3 Solar Architecture – Comprehensive Design and Operation The basic guidelines for the design and operation of green buildings are as follows: • • • • Enhance living by creating a comfortable environment for the building occupants and users Consume minimum energy and consider the damage that can be caused by the building to the natural environment over its life cycle Minimize the generation of buildings’ waste Use energy from renewable sources to cover the overall energy needs Passive solar architecture is a design-and-operational approach which seeks to make buildings and their adjacent spaces to function in harmony with the environment by taking advantage of the sun’s energy for the heating and cooling of living spaces In this approach, the building itself takes advantage of natural energy characteristics in materials and air created by its exposure to the sun Passive solar features add little or even nothing to the overall cost, are simple, have few moving parts, and require minimal maintenance as usually the mechanical parts are limited The main design-and-operational issues behind passive solar architecture are as follows: • site analysis and building’s form and orientation [7]; • building fabric characteristics [8]; and • appropriate services and control systems [9] Some basic guidelines for passive buildings are as follows: • • • • • The building should be elongated on an east–west axis (Figure 3) Interior spaces that require the most light, heating, and cooling should be along the south face of the building Less used spaces should be located on the north An open floor plan optimizes passive system operation Shading is recommended to prevent summer overheating In the following sections, passive heating and cooling technologies are analyzed 3.19.1.3.1 Passive solar heating For passive solar heating, the building should combine the following characteristics: • increased insulation and air tightness to minimize heat losses, • large south-facing glazing facade, 640 Applications N Worst Good Best Figure Orientation and building’s form • minimization of shading in winter, • thermal mass to store solar heat, and • responsive and efficient heating system Passive solar heating is accomplished via the following procedures: • solar collection, • thermal storage, and • thermal energy distribution Solar collection depends upon the orientation and the surface area of glazings as well as the glazings’ light transmittance Thermal storage systems for passive solar heating are distinguished as direct systems, indirect systems, and sunspaces The direct gain/thermal storage system is the living space which acts as solar collector, heat absorber, and distribution system South-facing glass admits solar energy into the house, where it strikes directly and indirectly thermal mass materials in the house The direct system utilizes almost 60–75% of the sun’s energy striking the windows (Figure 4) In a direct storage system, the thermal mass walls and floors are functional parts of the house It is also possible to use water containers inside the house to store heat However, it is more difficult to integrate water storage containers in the design of the house The thermal mass will absorb and store the heat during the day At night, the thermal mass will radiate the stored heat into the living space Indirect passive solar systems include solar walls A solar wall is a south-facing wall specially designed to collect solar energy and transmit it to the buildings Although a number of configurations are available, the most representative are the mass wall and the Trombe wall The mass wall (Figure 5) is a solid south-facing wall that absorbs solar radiation and transmits it into the building These walls may be of stone, concrete, or other materials, and they have a black mat surface to absorb solar radiation These walls are glazed to the outside to reduce heat losses to the environment Mass walls should be well shaded during summer to protect the building from overheating A Trombe wall, shown in Figure 6, is a mass wall with a vent at its top and bottom to allow air to circulate between the glass-wall gap and the building Vents should be open during the day and closed during the night to avoid reverse circulation, which may reduce the indoor temperature of the heating space Sunspaces are isolated gain systems which are completely separate from the main living area It is a glazed enclosure adjacent in the south facade of the building The isolated gain system will utilize 15–30% of the sunlight striking the glazing toward heating the adjoining living areas Solar energy is also retained in the sunroom itself Sunspaces or solar greenhouses, shown in Figure 7, employ a combination of direct gain and indirect gain system features Sunlight entering the sunroom is retained in the thermal mass and air of the room Sunlight is brought into the house by means of Summer Winter Figure Direct passive solar systems Passive Solar Architecture 641 Summer Winter Figure Mass wall Summer Winter Figure Trombe wall Tsunspace Tindoor Tsunspace > Tindoor Tsunspace Tindoor Tsunspace < Tindoor Figure The sunspaces operation as passive conduction through a shared mass wall in the rear of the sunroom, or by vents that permit the air between the sunroom and living space to be exchanged by convection Recent developments in passive heating include mass walls, solar chimneys (Figure 8), increased insulation [11], innovative glazing systems [12], double-skin facades [13], and so on Passive heating mode Warm air Outdoor air Figure Passive heating via solar chimney [10] Natural ventilation mode Outdoor air Thermal insulation mode 642 Applications 3.19.1.3.2 Passive cooling Passive cooling relies on the use of techniques for solar and heat control, heat amortization, and heat dissipation Solar and heat protection techniques may involve thermal improvement by the use of outdoor and semi-outdoor spaces, layout and external finishing, solar control and shading of building surfaces, thermal insulation, control of internal gains, night ventilation strategies (see Figure 11), radiative cooling, and evaporative cooling Modulation of heat gains deals with the thermal storage capacity of the building structure, while heat dissipation techniques deal with the potential for disposal of excess heat of the building to an environmental sink of lower temperature, like the ground, water, ambient air, or the sky The main passive cooling techniques are tabulated in Table Evaporative cooling is realized by the interaction of hot air with water Water vaporization causes a drop in air temperature and an increase in humidity This effect is maximized by establishing pools or fountains adjacent to the buildings Evaporative cooling is not suitable for humid climates (Figure 9) Ground cooling is a certain procedure where air is cooled before entering the building by passing through underground ducts Since the temperature of the ground below a certain depth is lower than the ambient air temperature, cooling is achieved by convection or even evaporation if the ground is damp (Figure 10) Table Figure Evaporative cooling Figure 10 Ground cooling Main passive cooling techniques Passive cooling technique Heat sink Heat transfer method Radiative cooling Evaporative cooling Ventilation Earth cooling Space Water–air Air Ground Radiation Convection Convection Conduction Passive Solar Architecture 643 Figure 11 Passive cooling via ventilation Ventilation contributes to cooling by forwarding fresh air into the building either naturally (due to pressure or temperature difference) or mechanically Passive cooling via ventilation is performed by (1) side ventilation, where the air cross-ventilation and the pressure difference move the air into the building; (2) cross-ventilation, where the air is passed through the building due to pressure difference between two openings; or (3) stack ventilation, which allows the air to move into the building due to temperature difference [14] (see Figure 11) Radiative cooling occurs when two adjacent masses have different temperatures Therefore, since the sky is usually colder than the various building surfaces, a significant amount of heat which has gathered in the building during the day is radiated to the sky during the night The overall procedure is depicted in Figure 12 State-of-the-art passive cooling technologies incorporate innovative glazing, light-colored walls and roofs, using high-albedo cool materials [15], green roofs [16, 17] and shaded roof [18], cooled ceiling systems [19, 20], passive cooling of the buildings [21], natural ventilation [22], solar control of buildings such as shading with plants and proper tree plantation [23], and insulating envelopes and external surfaces of the buildings [24, 25], which are effective ways for reducing cooling loads of the buildings Moreover, advanced materials are used in the building fabric This varies from the application of Fresnel lenses for temperature and illumination control [26] to the incorporation of cool materials and green spaces [15, 23, 27–29] The Fresnel lenses are incorporated into the building as transparent material to separate the direct from the diffuse solar radiation and can be combined Figure 12 Passive cooling via radiation 644 Applications with solar radiation absorbers (T), PV, or hybrid PV/T The application of cool materials and green spaces in the building fabric has become the object of serious research during the very last period Integrated solar systems that combine heating and cooling are also proposed [30] The solution combines solar collectors with a hot water storage tank and a gas boiler backup to provide hot water, which is used either for space heating or to drive an absorption chiller for space cooling Based on the above analysis, this chapter focuses on the recent technological developments in the improvement of the building fabric and control systems for the solar architecture The state of the art in the urban fabric and dynamic facade materials including cool materials, thermochromic coatings, and green spaces are analyzed in Section 3.19.2 The evolution of control systems in the solar architecture is discussed in Section 3.19.3 Section 3.19.4 analyzes the research trends and the state of the art is concluded 3.19.2 Role of Solar Architecture in Urban Buildings Increased urban temperatures have an important impact on the energy consumption of buildings, mainly during the summer period Heat island is the most documented phenomenon of climatic change Heat island is related to the increase of urban temperatures compared to the suburban areas because of the positive heat balance Hundreds of studies have been performed all over the world, and data for many European, American, and other cities are available [3] Higher urban temperatures increase the peak electricity demand for cooling and the concentration of pollutants in cities Several techniques have been proposed to mitigate heat islands, of which two appear to be especially significant: the use of green spaces and the use of appropriate materials in buildings and the urban fabric Heat island intensity can be considerably reduced by decreasing the amount of solar radiation absorbed by the urban fabric The use of proper materials for buildings and the urban fabric that present high reflectivity to solar radiation may contribute significantly to a decrease in the temperature of cities These ‘cool materials’ have become the subject of much research recently [31, 32] In parallel, the development of dynamic facade materials, like the thermochromic coatings, may contribute to reduce the cooling load of buildings and, in parallel, decrease the corresponding heating needs This section analyzes the role of passive cooling in the urban buildings and focuses on the techniques used to increase albedo, such as the use of cool materials and green spaces in the urban structure 3.19.2.1 Development of Cool-Colored Materials The use of cool materials for heat-island mitigation has gained a lot of interest during the past few years Cool materials are characterized by high solar reflectance (SR) and infrared emittance values These two properties mainly affect the temperature of a surface Increasing the reflectance and/or the emittance of the covering contributes to lower the surface temperature, which in turn decreases the heat penetrating into the building, if it is a surface of the building envelope, or contributes to decrease the temperature of the ambient air as heat convection intensity from a cooler surface is lower During the last year, the development of cool-colored materials has gained increasing acceptance, because in many cases the aesthetics of darker colors is preferred Cool nonwhite coatings absorb light in the visible range in order to appear having a specific color, but they should be highly reflective in the near-infrared (NIR) part of the electromagnetic spectrum to maintain a high SR This is very important considering the fact that about half of all solar power arrives as invisible NIR radiation Specialized, complex inorganic color pigments that are dark in color but have the ability to reflect strongly the NIR portion of the solar spectrum have been created by pigment manufacturers and they are used in order to develop cool-colored coatings with higher SR compared to conventionally pigmented coatings Cool-colored coatings can be applied on building envelopes and other surfaces of the urban environment as exterior finishes and paints or they can be used to manufacture building materials that reflect more sunlight than conventionally pigmented products City-scale application of cool materials will increase surface albedo This means that surface temperatures will be lower as well as near-surface air temperatures Ten prototype cool-colored coatings were created at the National and Kapodistrian University of Athens using special NIR reflective color pigments and were tested in comparison to color-matched, conventionally pigmented coatings [27] All coatings tested are acryl-based coatings and they can be applied on building envelopes (roofs and walls) and other surfaces of the urban environment The coatings were applied on white concrete pavement tiles The tiles had a size of 40  40 cm In order to study the optical properties and the thermal performance of the coatings, the following parameters were measured: The surface temperature of the samples on a 24 h basis The basic experimental equipment consists of surface temperature sensors (thermocouples type K) connected to a data logging system Instantaneous values were measured and saved on a computer hard disk every 10 The temperature sensors were placed on the center of the surface of each tile The infrared emittance of the samples, with the use of the Devices & Services emissometer model AE This emittance device determines the total thermal emittance, in comparison with standard high- and low-emittance materials The spectral reflectance of the samples, using UV/VIS/NIR spectrophotometer (Varian Cary 5000) fitted with a 150 mm-diameter integrating sphere (Labsphere DRA 2500) that collects both specular and diffuse radiation The reference standard reflectance material used for the measurement was a polytetrafluoroethylene (PTFE) plate (Labsphere) Passive Solar Architecture 645 Table SR of cool and color-matched standard coatings and % increase in SR between them SR (%) Color Cool Standard % Increase in SR(cool-standard) Orange Light blue Blue Green Black (1) Anthracite Brown Chocolate brown Light brown Black (2) 63 42 33 27 12 26 34 27 36 27 53 40 18 20 23 22 19 83 35 100 271 48 200 64 440 SR, solar reflectance During the experimental period, the ambient meteorological conditions were characterized by high temperatures, low relative humidity, low wind speeds, and clear sky The samples were placed on a horizontal platform, insulated from below in order to eliminate the heat transfer effects between the platform and the samples The experimental procedure took place during the months of August to October of 2005 Based on the results of the spectrophotometric measurements, the SR of each sample was calculated The calculation was done by the weighted averaging method, using a standard solar spectrum as the weighting function The spectrum employed is that suggested by American Society for Testing and Materials (ASTM) (ASTM E903-96, ASTM G159-98)) The values of SR for each sample are shown in Table All the coatings containing infrared reflective pigments have SR values higher than those of the standard coatings The highest difference in the SR was observed between cool black (2) coating (SR = 27%) and standard black (2) (SR = 5%) The percentage increase of SR was 440% In contrast, the smaller difference in the SR was observed between cool light blue coating (SR = 42%) and standard light blue (SR = 40%), with a percentage increase of SR of only 5% In general, the increase in SR varies with the color of the coating, but it appears to be higher for dark colors Spectral reflectance measurements showed that the reflectance curves for each standard and its corresponding cool coating coincide in the visible range, indicating that the coatings are color-matched, that is, they appear to have the same color Furthermore, almost all of the standard coatings exhibit low or modest reflectance in the NIR range, while the cool-colored coatings exhibit a more selective absorption band, reflecting significantly the NIR radiation During the day, it was found that all the cool-colored coatings had surface temperatures lower than those of the color-matched standard coatings The best performing cool coatings were black (2), chocolate brown, blue, and anthracite, which maintained a difference in mean daily surface temperature from their standard color-matched coatings by 5.2, 4.7, 4.7, and 2.8 °C, respectively, for the month of August The highest temperature difference was observed between cool and standard black (2) and was equal to 10.2 °C, corresponding to a difference in their SR of 22 The lowest temperature difference was observed between cool and standard green (2) and was equal to 1.6 °C (for August), corresponding to a difference in their SR of 7% This temperature difference between the cool and the standard coatings can easily be explained If a coating appears, for example, black, this means that it must absorb in the entire range of the visible spectrum The light energy that is absorbed is converted to heat energy, resulting in an increase in the surface temperature of the sample The same applies for the cool and standard black coatings that both have strong absorptance in the visible range In the NIR range, the standard black coating continues to show very low reflectance, absorbing not only all the visible light that enters its surface but also the infrared part of the solar energy In contrast, a coating containing infrared reflective pigments exhibits a more selective absorption band (like the cool black) Therefore, although it still absorbs all of the visible wavelengths, a large part of the NIR radiation is reflected rather than absorbed If we consider the fact that almost half of the solar energy that arrives to earth is infrared, it becomes evident that the black coating that absorbs this part will become hotter than the coating that reflects it The temperature difference between the cool and standard coatings decreases from August to October, as the monthly average daily global solar radiation decreases too, and the impact of the infrared reflective pigments in the coatings becomes less evident It was found that the coatings with higher values of SR demonstrated lower surface temperatures A strong correlation (R2 = 0.92) was found between the maximum daily surface temperature and the SR of the samples We can therefore assume that the main factor affecting the thermal performance of the samples during the day is their SR During the night when there is no solar radiation, the surface temperature of the samples was found to be quite uniform due to the fact that all the coatings have an emissivity of about 0.88 However, cool-colored coatings remain cooler (by 0.1–1.6 °C) than the standard color-matched coatings, probably because they have absorbed smaller amounts of solar radiation during the day Small variations in the measured emissivity explain the variations in the night surface temperature 646 3.19.2.2 Applications Use of Phase Change Materials to Enhance the Performance of Cool-Colored Coatings Phase change materials (PCMs) may store heat in their mass under the form of latent heat PCMs are widely used in solar applications as well as in building materials, like plaster, to absorb the excess heat in buildings Microencapsulated PCMs are commercially developed and are available at a particle size ranging between 17 and 20 μm Microparticles include a phase change ingredient, usually paraffins, in their core and a polymer or a plastic in the exterior shell The melting temperature may vary according to the specific needs Phase change microparticles have been used to further enhance the performance of cool color coatings They have been used to develop coatings based on infrared reflective pigments doped with PCMs [33] Six different colored pigments have been tested while investigations have been performed regarding the melting temperature of the microcapsules and the weight percentage of the materials The PCM-doped coatings as well as the conventional infrared reflective and the common coatings have been used to paint concrete tiles, and their surface temperature has been measured during the summer of 2008 (Figure 13) Surface temperature sensors and infrared thermography techniques have been used Measurements have shown that the PCM-doped materials present a peak daily temperature of up to °C lower compared to conventional infrared reflective coatings and up to °C compared to common coatings Figure 14 shows the daily variation of the surface temperature of black tiles, coated with PCM-doped, conventional infrared reflective, and common black coatings, for 10 consecutive days of measurements As shown, during the whole measurement period, the peak surface temperature of PCM-doped coatings was in all cases 2–4 °C lower than that of the conventional infrared reflective Figure 13 Picture of the tested cool phase change coatings 75 Common Cool PCM Temperature (°C) 65 55 45 35 25 15 10 Period of measurements (days) Figure 14 Daily variation of the surface temperature of black tiles coated with phase change material (PCM)-doped, conventional infrared reflective, and common black coatings Passive Solar Architecture 651 Table Mean maximum daily surface temperatures (°C) for thermochromic, cool, and common coatings in August Mean maximum daily surface temperature (°C) in August Thermochromic Green Yellow Brown Black Blue Gray Cool Common With TiO2 Without TiO2 With TiO2 Without TiO2 Light Dark 44.2 42.5 40.2 50.3 42.7 44.3 49.5 43.8 57.0 44.0 54.9 63.8 52.3 56.1 61.1 46.7 63.6 49.3 59.2 69.8 51.5 49.6 46.7 64.4 59.2 63.0 52.8 64.3 68.0 62.6 Table Mean nocturnal surface temperatures (°C) for thermochromic, cool, and common coatings in August Mean nocturnal surface temperature (°C) in August Thermochromic Green Yellow Brown Black Blue Gray 3.19.2.5 Cool Common With TiO2 Without TiO2 With TiO2 Without TiO2 Light Dark 18.0 18.5 18.6 21.3 20.0 21.0 17.8 18.0 20.2 17.6 21.0 20.4 20.7 20.2 21.6 20.5 20.2 20.2 20.6 20.7 21.1 20.6 20.5 20.6 20.5 20.8 20.9 20.3 21.1 20.2 Green Spaces for Urban Buildings The importance of green spaces to mitigate urban heat island has been stressed by many researchers Trees create a favorable thermal balance for humans and enhance outdoor thermal comfort [49] Papadakis et al [29] have conducted measurements to investigate the ability of trees to control solar radiation on vertical facades in Greece It is reported that almost 70–85% of the incident radiation was intercepted by the trees while the ambient temperature behind the shaded area was relatively lower than those without the trees Building-integrated green spaces are mainly green rooftops A typical green roof consists of a soil mixture and a drainage layer (see Figure 23) Green roofs can be categorized as intensive and extensive, depending upon the use, the depth of plantation, and the required maintenance Intensive green roofs are usually traditional roof gardens that require a relatively thick soil to grow large plants and they require increased irrigation, feeding, and other maintenance They are normally accessible as a recreation space for residents and so incorporate areas of paving, seating, and other architectural features In contrast, extensive green roofs feature a lightweight growing medium and self-generative plants They are designed to be self-sustaining and require only a minimum of maintenance, perhaps a once-yearly weeding or an application of slow-release fertilizer to boost growth Extensive roofs are usually only accessed for maintenance Planted roofs can contribute highly to mitigate heat island Planted roofs present much lower temperatures than hard surfaces and contribute to decrease the ambient temperature through convection and evapotranspiration Eumorfopoulou and Aravantinos have simulated various planted roof elements with different heights of plants and different drainage and they have performed comparisons between a bare roof and a planted roof It is concluded that the planted roof contributes highly to the thermal protection of buildings but cannot replace the thermal insulation layer [50] Niachou et al have reported extensive measurements of a planted roof in Greece and they concluded that it contributes to reduce seriously the cooling load of buildings The application of the green roof reduced the percentage of maximum indoor air temperature exceeding 30 °C to 15% from 68% without the green rooftop The energy efficiency due to green roofs for a noninsulated building was 37–48%, while for an insulated building it was quite low (5%) [22] The benefits of an intensive rooftop garden installation in a tropical environment were investigated by Wong et al through field measurements carried out in Singapore The analysis reveals that the temperature measured under the vegetation depends upon the plants’ leaf area index Lower temperatures were measured under vegetation with increased leaf area index The cooling effect of plants was also confirmed by the ambient air temperature reduction observed at different heights A maximum temperature difference of 4.2 °C was obtained between the locations with and without the plants [51] 652 Applications (a) Common Cool Tamb Thermochromic 80 with TiO2 Temperature (°C) 70 60 50 40 30 20 10 0:00 4:48 9:36 14:24 19:12 0:00 Time (hh:mm) (b) Common Cool Tamb Thermochromic 80 without TiO2 70 Temperature (°C) 60 50 40 30 20 10 0:00 4:48 9:36 14:24 19:12 0:00 Time (hh:mm) Figure 19 Mean daily surface temperature profile of ambient temperature (Tamb) and of green-colored thermochromic, cool, and common coatings with TiO2 (a) and without TiO2 (b) in August 80 Reflectivity SR (%) Whitish 60 Yellow Black 40 Green 20 Natural 300 Red 800 1300 1800 2300 Wave Length (nm) Figure 20 Spectral reflectance of various colored asphalt surfaces and of the conventional black asphalt Wong et al also carried out energy simulations to estimate the energy savings for a commercial building in Singapore with an intensive green roof The annual energy savings were estimated to be around 15% Increase of soil thickness contributes to the increase of energy savings and more than 60% of heat gain was intercepted by the rooftop system [52] It is therefore more than obvious that green spaces and green rooftops constitute a feasible mitigation strategy for urban heat island leading to a substantial decrease in energy consumption Passive Solar Architecture Table materials 653 Measured reflectivity of colored and conventional asphalt Product SR (%) SRUV (%) SRVIS (%) SRNIR (%) Whitish Yellow Green Black conventional Natural Red 55 40 27 45 27 10 8 10 45 26 10 31 10 63 51 39 56 40 Maximum daily surface temperature (°C) SR, solar reflectance; SRNIR, solar reflectance in the near-infrared region; SRUV, solar reflectance in the ultraviolet region; SRVIS, solar reflectance in the visible region 80 70 ΔT = 16.5 60 ΔT = 11.2 ΔT = 11.7 Natural Yellow ΔT = 6.3 ΔT = 5.6 Green Red 50 40 30 20 10 Black Whitish Figure 21 Maximum daily surface temperature of colored and conventional black asphalt pavements Black Whitish Natural Yellow Green Red 80 Surface temperature (°C) 70 60 50 40 30 20 10 0:00 4:48 9:36 14:24 19:12 0:00 Time (hh : mm) Figure 22 Daily variation of the surface temperature of representative colored and black asphalt materials 3.19.2.6 Discussion The mitigation of the heat-island effect can be achieved by decreasing the thermal gains in the urban environment, and in particular, the amount of the absorbed solar radiation This can be done by increasing the albedo of cities using materials for buildings and the urban fabric that have high SR values In order to meet the building market’s aesthetic preferences, cool nonwhite materials are needed The results of the relevant research indicate significant success in developing cool-colored coatings doped or not with PCM microcapsules, thermochromic materials, and cool asphalt coatings that have the same visible reflectance as the standard coatings, 654 Applications Vegetation layer Growing media (soil) Drainage layer Protection layers Figure 23 A green roof structure [17] appearing to have the same color, but for the colored coatings they exhibit a more selective absorption band in the infrared part of the spectrum, reflecting large parts of the solar energy that arrives as infrared radiation rather than absorbing it This results in lower surface temperatures for all the coatings The use of cool coatings is not limited to their direct application on building envelopes, resulting in the reduction of surface temperatures and leading to lower cooling energy consumption for air-conditioned buildings and increased thermal comfort for unconditioned building; they can also be used to manufacture other cool building and paving materials The use of cool coatings is a passive solution that combines energy efficiency and the aesthetic appeal of the products Therefore, solar architecture techniques in the building fabric that can contribute simultaneously to the mitigation of the urban heat island and to the reduction of the energy consumption are as follows: • Improvement of the urban microclimate and increased vegetation – urban greening Many studies have been carried out on the cooling benefits of trees and vegetation within the cities Surface peak temperature reductions of up to 20 °C may be possible on hot, sunny days Vegetation augmentation and reduction of impervious surface cover in urban environments can be accomplished through residential and municipal tree planting programs, addition or expansion of ecoroofs (or green roofs), and implementation of pervious pavements While many studies focus on the evapotranspiration benefits of urban trees, it is important to note that trees also affect wind patterns within cities Thus, by changing wind patterns, trees may alter the effectiveness of cooling breezes and can play an important role in dispersion processes as well as pollutant removal by deposition • Increase of surface albedo by the use of cool materials and coatings The primary surfaces in the urban environment that are amenable to albedo increase are rooftops In order to assess potential for albedo modification, various studies have estimated the composition of the urban fabric This composition varies for different land use subtypes within a city and depends on whether one is concerned with the plan view data (as seen from a plane) or with the actual composition under the canopy With respect to the plan view composition of cities, these studies typically find that roughly 20% of a city’s surface is rooftop 30% is pavement, and the remainder is a combination of vegetation canopy and other surfaces It is this underlying composition that limits the potential effectiveness of any albedo-related mitigation strategy 3.19.3 Control Systems for Solar Architecture The main challenge in the design of control systems for energy performance of buildings is to find the balance between implementation costs, operation costs, energy consumption, indoor climate quality, users’ satisfaction, and contribution to sustainable building Intelligently designed buildings are those that involve environmentally responsive design, taking into account the surroundings and building usage and involving the selection of appropriate building services and control systems to further enhance building operation with a view to the reduction of energy consumption and environmental impact over its lifetime This procedure requires advanced control techniques to establish a balance among the following (see Figure 24): • • • • • user comfort requirements, energy consumption, passive solar design concepts, solar heating and cooling technologies, and PV Passive Solar Architecture Earth cooling Visual comfort Radiative cooling Indoor air quality Evaporative cooling Thermal comfort 655 Shading control Daylighting control Passive solar design Solar heating Window control Solar systems Solar cooling Photovoltaics Energy and power meters Figure 24 The advanced control systems in solar buildings Various control strategies are used for the regulation of the above The combined control of active and passive systems, as, for example, night ventilation for cooling and mechanical cooling or hybrid ventilation, generally requires the use of the so-called ‘logic control’ implemented by various rules in order to determine which of the passive or active systems should be operated Many digital controllers offer this possibility to implement logic control rules as well as ON–OFF or proportional–integral– derivative (PID) control [53, 54] Modern control systems provide optimized operation of the energy systems while satisfying indoor comfort Recent technological developments based on artificial intelligence techniques offer several advantages compared with the classical control systems The use of fuzzy logic and artificial neural networks (ANNs) in various building-related applications has been growing significantly over the years [55–62] The results have revealed the potential usefulness of the advanced control strategies for the energy management of houses and buildings Evolutionary computing techniques, namely, genetic algorithms (GAs), are employed in buildings since they have proved to be robust and efficient in finding near-optimal solutions in complex problem spaces [63, 64] Predictive control techniques are also applied [65] Finally, optimization methods such as dynamic programming [66], multiobjective techniques [67], and simulation-assisted multicriteria analysis [68] are widely adopted due to buildings’ nonlinearity 3.19.3.1 Controlled Parameters and Control Variables in Passive Solar Architecture Passive solar architecture cannot be implemented without taking into account the various controlled parameters that the overall system will regulate The most widely used in the literature concern occupants’ thermal, visual, and acoustic comfort as well as the IAQ The building’s occupants have a direct impact on the passive design operation and the effectiveness of passive solar architecture For example, the influence of occupants’ behavior on the energy consumption is studied by Foster et al [69] In this chapter, the interaction between the occupants and the venetian blinds is examined as blinds are the key element in the passive control of glare, daylighting, and overheating, all of which affect both the occupants’ comfort and the energy consumption The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Standard 55 describes thermal comfort as ‘the condition of mind which expresses satisfaction with the thermal environment’ The environmental variables that influence thermal comfort are the air temperature, the mean radiant temperature, the air velocity, and the water vapor pressure in ambient air Two other important variables are the person’s activity level and clothing Most of the above are combined in the predicted mean vote 656 Applications (PMV), which provides information on the degree of discomfort experienced in a thermal environment with an extra invocator, the percentage of people dissatisfied (PPD) [70, 71] Regarding thermal comfort, the controlled parameters found in the literature involve • • • • • PMV [72–74], the PPD [75], indoor temperature [76], maximum daily discomfort in degree hours [77], and zone operative temperature [75] Regarding visual comfort, the control involves passive shading targeting the regulation of workplane illuminance [65, 78] Additionally, the daylight glare index regulated through the adjustment of shading and electric lighting is proposed as the controlled variable for visual comfort [79] Regarding the solar system operation, the following controlled parameters are found: • tank water temperature for solar collectors for the simultaneous control of indoor environment and water circuit [76] and • supply and return temperature of passive solar systems’ collector [75] In terms of energy consumption, the controlled variables may be • seasonal building load profiles [77], • buildings’ heating or cooling balance points (i.e., the temperature above or below which cooling or heating is necessary) [77], and • building load coefficient [67] Other parameters that are taken into account in the formulation of the control strategy include • climatic conditions either measured or predicted [80] and • presence of detectors The control variables differ according to the passive system The most representative are the following [74, 76, 81]: • • • • • • • • heating, ventilating, and air conditioning (HVAC) ON–OFF, boilers or chillers, coils and valves, water pumps, supply and exhaust fans, electric lighting control, shading control, and window motors All the above environmental parameters and control variables are integrated into the various control strategies described in the next section targeting to minimize the energy consumption and create a comfortable and qualitative environment for the building users 3.19.3.2 Control Strategies in Solar Architecture The control theory for linear systems has been considered for quite a long time as a well-established scientific discipline with different techniques for analyzing and designing controllers The main problems in applying the linear control theory for solar architecture are caused by the fact that (1) linear mathematical models are needed and cannot be straightforwardly extracted, (2) the developed mathematical models of such complicated processes cannot take into account all aspects of reality and therefore simplifications and assumptions are necessary, (3) most processes for solar architecture techniques are not linear, and (4) due to continuous changes of the climatic conditions, solar system processes vary dynamically with time The control techniques used for solar architecture can be divided into different categories (tabulated in Table 8) [82, 83], and these are explained below 3.19.3.2.1 Conventional control for solar architecture Conventional control strategies for solar architecture include the widely used ON–OFF and conventional PID methods [84] The conventional control strategies are still very attractive when they involve a small number of environmental parameters’ regulation and a limited number of solar techniques For example, active ON–OFF control is proposed by Tzempelikos and Athienitis [78] for the regulation of electric lighting consumption in a simulation-based thermal and daylight analysis for office spaces The ON–OFF system is based on occupancy sensors, while the buildings are designed to exploit the daylight availability via window sizing, orientation, and window-to-wall ratio Passive Solar Architecture Set points + 657 e(k) – PI u(pi) e(k–1) z –1 + Actuators (k) + + Building + y(k) – D + z–1 u(d ) Figure 25 The proportional–integral–derivative control diagram Due to the dynamic characteristics of the technologies involved in the solar architecture, it is quite difficult to obtain a satisfactory performance when an integrated approach is established where a combination of passive heating and cooling techniques is considered The use of PID controllers (Figure 25) with fixed gains KP, KI, KD although applied in numerous cases [85] cannot deal with nominal operation of the various components without including a feedforward term in the control loop to account for the effect of the quite significant disturbances and time variations Gain scheduling proportional–integral (PI) controllers, adaptive PID controllers, and fuzzy logic- or neural network (NN)-based PID controllers are some examples of PID feedforward actions and adaptations to buildings’ dynamic characteristics [86] Classical PID as well as ON–OFF control has been proved to be energy ‘inefficient’ due to the fact that the controlled variable creates overshootings and oscillations once the reference signal is reached [85] Overshootings and oscillations are the main cause of energy waste 3.19.3.2.2 Advanced control Based on the categorization in Table 8, advanced control for solar architecture includes model-based predictive control and adaptive control Predictive control in solar architecture uses a model to estimate and predict the optimum control strategy to be implemented (Figure 26) While the online control systems can react only to the actual building conditions, a model-based predictive control can move forward in time to predict the buildings’ reaction to alternative control schemes Therefore, different control scenarios can be evaluated based on suitable objective functions and create a control state space that corresponds to a building’s performance space A model can be either a ‘black box’ or a ‘physical’ model In the ‘black box’ or nonphysical model approaches, self-learning algorithms, reinforced learning [87], or NNs [88] are some of the methodologies found in the literature The benefits of the mentioned approaches are low computational time and the fact that they not require any specific building modeling expertise, while their limitations are that, on the one hand, NNs require reliable training data that may not be available and, on the other hand, self-learning algorithms cannot move beyond the limits of their experience When physical models are utilized, the expert has the opportunity to understand the cause-and-effect relationship between the various building components, the control strategies, and the climatic conditions The physical models approach can use stochastic mathematical models [89] or simulation-assisted predictive control [90] Some physical models, though, require high computational skills and effort For this reason, integration of Table Control strategies for solar architecture Control category Control strategies Conventional control ON–OFF Proportional–integral–derivative control Feedforward control Model-based predictive control Adaptive control Optimal control Fuzzy logic Neural network Advanced control Intelligent techniques 658 Applications Model ym (k) Adaptation techniques x3 Controller u(k) Building y(k) Figure 26 Model-based predictive control whole-building thermal models with (cognitive-based) control is quite interesting and with significant potential – see References 91 and 92 for some efforts Adaptive control has been developed for decades, and now it has become a rigorous and mature discipline which mainly focuses on dealing with uncertainties in control systems Since adaptive control usually involves adaptive estimation algorithms, it can deal with relatively large uncertainties and gain flexibility to fit the unknown system, therefore playing a role of ‘learning’ in some sense The adaptive control systems in solar buildings are used to modify the controller dynamically during its operation, that is, adjusting the controller to building users’ preferences, modifying the control actions so as to fit to specific operational, usually predefined, performance (Figure 27) Therefore, the main advantage of adaptive control comes from the fact that adaptive controllers can adjust themselves to modify the control law based on estimation of unknown parameters by identification algorithms Consequently, the adaptive control field is very closely connected to the systems’ (in our case, building components) identification algorithms, in which an area is aiming at providing and investigating mathematical tools and algorithms that build dynamical models from measured data Typically, in system identification, a certain model structure which contains some unknown parameters is selected by the user and then by the use of some recursive algorithms which are based on specific model characteristics, statistical data, and noise, these unknown parameters are extracted The methods or algorithms developed in system identification are borrowed in adaptive control in order to estimate the unknown parameters in the closed loop For convenience, the parameter estimation methods or algorithms adopted in adaptive control are often referred to as adaptive estimation methods Adaptive estimation and system identification share many similar characteristics; for example, both of them originate and benefit from the development of statistics One typical example is the least-squares algorithm that is applied to system identification, statistics, or adaptive control and gives parameter estimation by minimizing the sum of squared errors As an example of the above, a bilinear model-based predictive control is proposed by Kolokotsa et al [65], so as to achieve optimum indoor environmental conditions while minimizing energy costs by the prioritization of natural ventilation for cooling, shading regulation for optimum daylight utilization, and window operation for a building energy management system The control diagram depicted in Figure 28 includes the actuators (A) and the overall installation (P), where k is the sample time, x(k) the state vector, y(k) the measurements vector, n(k) the unknown noise for the measurements, u(k) the control vector, d(k) the disturbances vector (casual gains, door opening, people smoking, etc.), and xs the set point vector Bilinear models are developed for the thermal comfort, visual comfort, and IAQ where the indoor temperature, relative humidity, indoor carbon dioxide concentration, and indoor illuminance behavior are modeled The least-squares estimation is Adaptation/ identifier xs Figure 27 Self-tuning controller + – e(k) Controller Building y(k) Passive Solar Architecture 659 d(k) Xs y(k) Controller u(k) A P x(k + 1) Δ–1 x(k) n(k) x(k) y(k) f (x(k),u(k),d(k)) Figure 28 Model-based predictive control for indoor comfort and energy efficiency regulation [65] performed separately for each actuator that influences the corresponding environmental parameter by putting the building energy management systems (BEMS) in continuous operation mode for at least 48 h Following the identification procedure, the BEMS controller is designed to minimize the performance index J(k) which aims to keep the environmental variables as close as possible to the defined set points xs and simultaneously minimize the energy consumption J(k) is defined as JðkÞ ẳ xin k ỵ 1ị xs Q ỵ ukịR 2 ½1Š where Q and R are weight matrices corresponding to the set points’ proximity and the actuators’ electric energy cost, respectively The bilinear model-based predictive control’s response to fluctuations in the environmental variables is found to be fast and stable Finally, the controller’s performance is tested by an installation in specific building where comfort, weather data, and prediction model are integrated into a common architecture (Figure 29); the controller’s performance is found to be quite satisfactory and selects the optimum solutions based on the energy consumption and the set point proximity by satisfying the performance index J (Figure 30) 3.19.3.2.3 Intelligent systems Recent research in building-related artificial intelligence topics has shown that artificial intelligence techniques such as fuzzy systems and NNs can contribute to a significant reduction of energy consumption while maintaining indoor comfort in acceptable margins by regulating the operation of the various building-integrated solar systems or by giving priority to passive means in order to cover the comfort or energy requirements Fuzzy logic (Figure 31) is based on the way the human brain deals with inexact information Fuzzy systems are structured numerical estimators They start from formalized insights about the structure of categories that exist in the real world and then formulate the fuzzy IF–THEN rules that represent expert knowledge They combine fuzzy sets with fuzzy rules and they produce complex nonlinear behavior Fuzziness is often confused with probability The main difference between fuzzy logic and probability is that fuzziness deals with deterministic plausibility while probability concerns the likelihood of nondeterministic and stochastic events Fuzziness expresses the uncertainty in the definition of phenomena such as ‘tall person’ and ‘large room’ The major feature of fuzzy logic is its ability to express the ambiguity in human thinking, subjectivity, and knowledge in a comparatively accurate manner As a result of the above, the use of fuzziness in buildings’ solar architecture systems and components is applicable for the following reasons: • A fuzzy description of the operational characteristics under study fits naturally to the problem • The systems to be controlled are usually nonlinear ANNs imitate the operation of the human brain’s neurons They are composed of a number of elements/neurons operating in parallel and are inspired by the biological nervous systems A schematic diagram of typical multilayer feedforward ANN architecture is shown in Figure 32 The network as depicted in Figure 32 usually consists of an input layer, the hidden layers, and an output layer The number of hidden layers depends on the complexity of the problem under study Each neuron is connected to other neurons of a previous layer through adaptable synaptic weights Usually, the biggest challenge faced when designing an NN is to find the right number of neurons in the hidden layer This depends on the number of inputs and outputs and also on the number of training cases The GAs are adaptive search and optimization algorithms that work by mimicking the principles of natural genetics GAs are very different from traditional search and optimization methods used in engineering design problems [93] Fundamental ideas of genetics are borrowed and used artificially to construct search algorithms that are robust and require minimal problem information PC RS 485 to RS 232 RS 232 RS 485 Energy meter electrex kilo Indoor humidity sensor QFA2000 Outdoor humidity sensor QFA3160 Universal I/O module 5WG1 670-1AB03 EIB power supply 5WG1 125-1AB21 RS 232 interface 5WG1 148-1AB04 Indoor Co2 sensor QPA63.2 Energy and power meter 5KT1 165 Air-conditioning Window Universal I/O module 5WG1 670-1AB03 Shading Shading 3-phase power supply Shading Motor control relay 5WG1 524-1AB01 Binary outputs 5WG1 561-1AB01 Devices installed at the rail BUS Power supply 24C DC 4a max Indoor temperature sensor 5WG1 256-4AB01 Indoor brightness sensor 5WG1 253-4AB01 Rain detector 5WG1 258-3AB41 Weather station 5WG1 257-3AB11 EIB-Gateway DALI 5WG1 141-4AB01 Temperature sensor 5WG1 258-3AB21 Brightness sensor 5WG1 258-3AB31 Wind speed sensor 5WG1 258-7AB12 Electronic ballast DALI TRIDONIC 2/58 EXCELL Lamb Figure 29 The bilinear model-based predictive control BEMS architecture [65] Lamb Electronic ballast DALI TRIDONIC 2/58 EXCELL Lamb Lamb 51 Electronic ballast DALI TRIDONIC 2/58 EXCELL Lamb Lamb AC 230 V Passive Solar Architecture 661 100 90 80 70 60 50 Men Women 40 30 20 10 Very good Good Bad Very bad Figure 30 Perception of indoor thermal comfort based on occupants’ responses [65] e(k) xs + – Fuzzification Fuzzy rules Defuzzification Δu(k) Z–1 Z–1 y(k) Building u(k) Figure 31 The fuzzy control system A typical unconstrained, single variable optimization problem can be outlined as follows: maximize f ðxÞ xmin ≤ x ≤ xmax ½2Š The GA, as any evolution program, for a particular problem must have the following five components: • • • • • a generic representation for potential solutions to the problem; a way to create an initial population of potential solutions; an evaluation function that plays the role of the environment, rating solutions in terms of their ‘fitness’; genetic operators (such as crossover and mutation) that alter the composition of children; and applying genetic operators, and so on Indicatively, artificial intelligence in solar buildings control is found in the following applications: • Lah et al designed a fuzzy control system for the regulation of a movable shade roller blind, targeting the harmonization of thermal and optical flows They aimed to combine minimization of energy use with comfortable living and working conditions The control algorithm consisted of thermal and lighting parts, each one containing conventional and fuzzy controllers The impact on thermal light behavior was analyzed with adaptable window geometry The controller is designed and adjusted so as to adjust the inside daylight illumination level with moderate continuous movement of the roller blind The overheating is reduced by the roller blind regulation and the desired illuminance is reached [94] • In the same route of the regulation of thermal and visual comfort is the work proposed by Kristl et al [95] A fuzzy controller for the regulation of a roller blind is tested and tuned in an experimental chamber A thermal comfort loop and an illumination loop are developed and then these loops are merged to harmonize the results 662 Applications Input layers Hidden layers Output layers Figure 32 The artificial neural network architecture • A quasi-adaptive fuzzy controller for space heating in passive solar buildings that is responsive to the lagging effects of solar energy inputs is proposed by Gouda et al [96] The controller is divided into two main modules: a conventional static fuzzy controller and feedforward NN with a singular value decomposition (SVD) algorithm An estimation of the internal air temperature at least h ahead in time and within typical measurement uncertainty is provided by an ANN Experimental results of the fuzzy controller are compared to simulations of the conventional PI heating system The fuzzy controller follows the variable set point more accurately without overshootings, thus reducing the afternoon overheating and the energy costs significantly, compared to the conventional control problems • An NN model is proposed by Kazanasmaz et al to predict daylighting levels in office buildings The input parameters used in the model included date, hour, outdoor temperature, solar radiation, humidity, UV index, distance to windows, number of windows, orientation of rooms, floor identification, room dimensions, and point identification The model was tested for specific office buildings, providing quite satisfactory results The specific model can be used by architects and designers to determine illuminance and light distribution in solar architecture without the need for a detailed model development [97] • A fuzzy and feedforward controller for operating a hybrid thermal energy storage system (HTESS) is presented by LeBreux et al [98] The storage system accumulates solar energy during daytime and releases it during the night or during cloudy days and, simultaneously, it stores electrical energy during off-peak periods and releases it later during on-peak hours The control strategy takes into account the weather forecasts for solar radiation and outdoor air temperature, and optimizes the off-peak and the on-peak periods for electrical heating The thermal comfort of the room is maintained in all situations and at all times Finally, the electricity consumption for space heating is minimized and 95% of this electricity is consumed during off-peak hours • Guillemin and Morel developed a self-adaptive integrated system for building energy and comfort management The fuzzy expert system consists of a shading device controller, an artificial lighting controller, and a heating controller When the user is present, priority is given to visual comfort, and when absent, priority is given to thermal aspects (heating/cooling energy saving) The models used in the controller are adapted regularly in order to meet the requirements of the building and of the environment A process of adaptation is performed each night using GAs in order to identify the most appropriate parameters of the controller The operation of the controller is compared to that of a conventional controller (no automatic blind control and artificial lighting control, and a Passive Solar Architecture 663 proportional controller for heating) The energy consumption of the fuzzy controller is 20–25% less than that of a conventional controller Additionally, Guillemin and Morel presented a controller with inputs of the users’ set points and the weather data of the room The ANNs are included for the prediction of room temperature The thermal comfort level is kept high and the visual comfort is improved by the fuzzy control system An energy efficiency of 19% is estimated, compared to conventional control [74] • Kubota et al developed a prediction system based on genetic programming and fuzzy inference systems Genetic programming is applied for the feature extraction and selection, and fuzzy inference is used for the building energy load prediction The method is compared to the Kalman filtering algorithm and a feedforward NN with four layers Although the NN is better for load prediction, the proposed method can extract meaningful information from the measured data and can predict the building energy load corresponding to the next day [99] The application of advanced control strategies in passive solar buildings has a significant impact on the energy consumption compared to conventional techniques In all cases, the energy consumption is reduced by at least 18–20%, when an optimal control strategy is applied [100] 3.19.4 Conclusion and Future Prospects Buildings are increasingly expected to meet higher and potentially more complex levels of performance They should be sustainable, use zero net energy, be healthy and comfortable, grid-friendly, yet economical to build and maintain Ensuring any one of these is challenging in itself, but achieving all would seem to be overwhelming Various technologies are mature and can be considered for the improvement of the energy efficiency and indoor comfort in buildings These technologies may be distinguished into the following basic categories: • measures for the improvement of the building’s envelope (addition or improvement of insulation, change of color, placement of heat-insulating door and window frames, increase of thermal mass, building shaping, superinsulated building envelopes, etc.); • incorporation of high-efficiency heating and cooling equipment, for example, air-conditioning equipment with higher energy efficiency ratio (EER) and high-efficiency condensing boilers; • use of renewables (solar thermal systems, building’s integrated photovoltaics, hybrid systems, etc.); • use of ‘intelligent’ energy management, that is, advanced sensors, energy control (zone heating and cooling), and monitoring systems; • measures for the improvement of the indoor comfort conditions in parallel with minimization of the energy requirements (increase in the ventilation rate, use of mechanical ventilation with heat recovery, improvement of boilers and air-conditioning efficiency, use of multifunctional equipment, i.e., integrated water heating with space cooling, etc.); and • use of energy-efficient appliances, including compact fluorescent lighting, light emitting diode (LED) lighting, and so on Nowadays, passive solar design is moving toward zero- or even positive-energy buildings Zero-energy buildings have become a high priority for architects and multidisciplinary researchers related to building engineering and physics A zero-energy building refers to a building with a net energy consumption of zero over a typical year [101] It implies that the energy demand for heat and electrical power is reduced, and this reduced demand is met on an annual basis from renewable energy supply The renewable energy supply can be either integrated into the building design or specifically provided for the building, for example, as part of a community renewable energy supply system Additionally, this normally implies that the grid is used to supply electrical power when there is no renewable power available, and the building will export power back to the grid when it has excess power generation This ‘two-way’ flow should result in a net 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(thermocolored-common) 51 33 78 70 55 40 40 59 41 55 34 73 45 81 73 76 53 47 71 54 73 40 43 36 4 38 33 18 20 32 33 18 41 27 73 69 41 17 12 53 32 44 25 24 22 34 135 233 11 28 25 36 18 64 64 18 3 51 21 13 13 1 83 725... TiO2 Light Dark 33 .2 32 .2 31 .0 37 .6 33 .1 34 .1 36 .0 32 .5 40.9 34 .4 40.2 44.6 38 .7 40.4 43. 8 35 .3 44.6 36 .4 42 .3 48.5 38 .4 37 .4 35 .5 45.2 42.4 44.4 39 .0 45.1 47.5 43. 9 Passive Solar Architecture 651... Section 3. 19. 2 The evolution of control systems in the solar architecture is discussed in Section 3. 19 .3 Section 3. 19. 4 analyzes the research trends and the state of the art is concluded 3. 19. 2