- Email: [email protected]
Modeling seasonal solar thermal energy storage in a large urban residential building using TRNSYS 16
Energy and Buildings 45 (2012) 28–31
Contents lists available at SciVerse ScienceDirect
Energy and Buildings journal homepage: www.elsevier.com/locate/enbuild
Modeling seasonal solar thermal energy storage in a large urban residential building using TRNSYS 16 L.T. Terziotti, M.L. Sweet, J.T. McLeskey Jr. ∗ Virginia Commonwealth University, Department of Mechanical Engineering, 401 West Main Street, Room E3221, P.O. Box 843015, Richmond, VA 23284-3015, USA
a r t i c l e
i n f o
Article history: Received 27 April 2011 Received in revised form 31 August 2011 Accepted 4 October 2011 Keywords: TRNSYS Solar thermal storage Seasonal storage Urban buildings
a b s t r a c t Space heating, primarily using fossil fuels, is a major component of US energy consumption. Seasonal solar thermal energy storage (SSTES) provides a method to store solar thermal energy collected in the summer to use for heating in the colder months. Solar collectors are used to heat a sand bed, which retains its thermal energy through the winter. That energy is then sent into the building via radiant floors for space heating use. A sand-based storage bed SSTES system for a new five story student housing complex at Virginia Commonwealth University is modeled using TRNSYS Version 16 software. A total of 15 simulations of various storage bed locations and configurations as well as building efficiencies are modeled to determine whether a system is feasible for an urban environment. Substantial energy savings are possible within the small footprint required by city lots. Up to 91% of energy for this large building can be provided by the most efficient SSTES system. © 2011 Elsevier B.V. All rights reserved.
1. Introduction
2. Seasonal solar thermal energy storage systems
Residential space heating makes up a large portion of energy consumption in the United States. It accounts for 48% of energy consumption in residential buildings alone and is responsible for the release of approximately 502 million metric tons of carbon dioxide into the atmosphere each year. In 2005, 97% of U.S. households heated their homes using fossil fuels either directly or indirectly, via electricity derived from such fuels [1,2]. As populations continue to grow, and space and resources become more scarce, the importance of using renewable energy sources is paramount. Solar energy is particularly promising. Every day, 1000 W per square meter of power from the sun reaches the earth [3]. A major challenge is harnessing that massive amount of energy. Large scale energy production from photovoltaics faces the hurdle of intermittent power generation and low efficiencies, thus requiring costly storage mediums [4,5]. On the other hand, converting solar energy to thermal energy via solar collectors has high efficiencies and can be done while also generating electricity via photovoltaic/thermal (PV/T) collectors [6,7]. Therefore, it is important to investigate ways to use solar energy for space heating.
While more solar energy reaches the earth in the summer months, thermal energy is most needed in the winter. Seasonal solar thermal energy storage (SSTES) systems address this fundamental issue by providing a method to store solar energy well into the winter via a thermal storage medium. An SSTES system uses two closed fluid (water) loops. One loop runs through solar collectors to heat the fluid, then into coils inside the storage medium. Fluid in the second loop is heated in the storage medium and then sent through a radiant floor, thus heating the building. The storage medium varies depending on the requirements of the system. A basic SSTES system is shown in Fig. 1. The most common storage medium for an SSTES system is a water tank [8,9]. Water performs well as it has a high specific heat, disperses thermal energy via convection, and flows easily. Generally, the heavily insulated tanks are built above ground or partially above ground to save cost. In large scale projects, the tanks are usually constructed of insulated concrete with a high density liner to prevent permeation [8]. Another method uses the ground itself as a storage medium [10]. A system of boreholes is dug to a depth of 30–200 m, depending on the terrain. Each borehole contains a pipe that carries the fluid to the bottom of the hole and returns it to the surface. The fluid is then sent to the adjacent borehole. A layer of insulation near the surface of the system prevents loss of thermal energy. This method of SSTES is not suitable for all locations. Soil and groundwater conditions may make it impractical [11].
∗ Corresponding author at: 401 West Main Street, Room E3238, P.O. Box 843015, Richmond, VA 23284-3015, USA. Tel.: +1 804 827 7008, fax: +1 804 827 7030. E-mail addresses: [email protected] (L.T. Terziotti), [email protected] (M.L. Sweet), [email protected] (J.T. McLeskey Jr.). 0378-7788/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.enbuild.2011.10.023
L.T. Terziotti et al. / Energy and Buildings 45 (2012) 28–31
29
Fig. 1. Schematic of a basic sand-based SSTES system.
Using a sand, gravel, or soil-based storage medium is attractive due to its low cost and versatility. A pit is dug and lined with a waterproof membrane and insulation. The storage medium is spread inside the pit while coils of tubing for the fluid are distributed throughout the storage medium. The pit is sealed with more insulation and waterproofing and capped with soil. This type of storage medium is advantageous as the land above the storage bed can be used as a parking lot, playground, garden, or for some other purpose.
3. West Grace housing Starting in 2011, Virginia Commonwealth University will be constructing a new student housing project on its Monroe Park Campus. The Monroe Park Campus is located in the heart of Richmond, Virginia, at an elevation of 57 m above sea level in a humid subtropical climate. The project will be a 15,700 m2 (168,500 ft2 ) five story mixed use building with shops and restaurants on the first floor and 457 beds on the upper floors. This building was chosen to be modeled with SSTES to determine the efficacy of this system in a large urban residential building. Implementing SSTES in an urban environment, such as VCU’s Monroe Park Campus, poses unique problems. Space is scarce. All construction must be done to avoid danger to surrounding structures. Past research has examined building sites where space was of less concern [12]. Other research looked at smaller apartment buildings [9]. However, with its urban location, this project must optimize its SSTES system not only for efficiency, but also for geography. The first challenge is determining where to put the solar collectors. Past projects in central Europe have answered this problem adequately by successfully installing the solar collectors on the roofs of the structures to be heated [8]. This allows for the large, contiguous collector areas that have been determined to be most effective [8]. A more pressing issue is determining a location and medium for the storage bed. The above-ground water tanks of past large-scale projects are not feasible in an urban environment where space is scarce. Installing a subterranean water tank is costly, and repairing it is even more so. Also, the utility of the space is still compromised as building over a large water tank presents structural issues that would be costly to address. Thus, other storage mediums must be considered. A borehole system was ruled out as is impractical for Richmond due to its high water table. Using sand as a medium is both cost and space effective. Sand is cheap. A sand-based storage bed is structurally sound enough
to be installed underneath a parking lot or courtyard. Designs for sand-based storage beds are adaptable and easily scalable. For these reasons, sand was chosen as the storage medium for this project. There are two places near the West Grace Housing Project that could be used for the storage bed. The building, located at the intersection of West Grace and Shafer streets, is labeled WG Building. The first site is in the courtyards of the building. A second site is located in a parking lot opposite the building on West Grace Street. It measures 33 by 43 m and is owned by VCU. If feasible, it is preferable to place the storage bed in the building’s courtyards for two reasons. First, it is more cost effective. Using the parking lot would require a second excavation site, thus adding significant cost as designing and installing shoring in a city is quite expensive. The parking lot would then have to be repaved, and pipes would need to be run under West Grace Street, adding further costs and disrupting traffic. Repairs would also be expensive. On the other hand, the excavation required to install the beds in the building’s courtyards is already necessary to construct the building itself, so additional effort is trivial compared to that of the former scenario. The second factor that makes the courtyard a more attractive storage bed location is its permanence. While VCU may choose to sell or build on the parking lot in the future, the courtyards will remain courtyards for the entire lifetime of the West Grace Housing Project.
4. Implementation Building specifications were provided by VCU’s Facilities Management Division. The LEED-NC 2009 Silver 16,657 m2 building was estimated to have a peak-heating load of 18.93 W/m2 (6 BTU/sq.ft h) when using its electric heat pumps. Without ventilation recovery and other energy savings this estimate rises to 37.86 W/m2 (12 BTU/sq.ft h). Simulations were run at both of these heating loads as well as at 28.93 W/m2 (9 BTU/sq.ft h) to represent a building with fewer energy saving features. The system was modeled using TRNSYS Version 16, transient thermal energy modeling software developed at the University of Wisconsin-Madison. The building was constructed in TRNYSY with Type 53 using 6 zones: one for each of the five floors as well as a zone for the plenum above the first floor’s commercial areas. The model was designed to meet the specifications of the American Society of Heating and Air-conditioning Engineers (ASHRAE). Thermal interaction with the ground was modeled with Type 703d (slab on grade). Each of the five 3130 m2 floors had an active layer (radiant floor) with a pipe diameter of 1.8 cm and piping spaced 10 cm
30
L.T. Terziotti et al. / Energy and Buildings 45 (2012) 28–31 Table 2 Heat load of theoretical backup system during the fifth year of the simulation.
Location
Area (m2 )
Depth (m)
Volume (m3 )
Parking lot Parking lot Two courtyards Parking lot
1430 1430 1240 1430
6.5 5.5 5.0 3.5
9295 7865 6200 5005
apart. The building’s ventilation recovery system was modeled with the Type 91 heat exchanger. The building’s peak heating load was manipulated by varying the efficacy of this heat exchanger to simulate the varying levels of building efficiencies. As previously noted, the peak heating loads were 18.93, 28.93, and 37.86 W/m2 . It is best to have as large a solar collector area as possible [8]. In all, 1930 m2 of flat panel solar collectors (Type 73) were used. This equates to 62% of the roof, allowing ample space for any machinery or architectural features to share the roof while still providing an adequate solar collector area. The storage bed was modeled using Type 342, a module designed to simulate cylindrical water or rock-filled ponds, tanks, and caverns. The fluid in the collector loop is extracted from the bottom of the bed and injected at the top. Conversely, the fluid that goes to the radiant floors is extracted from the top of the bed and reintroduced at the bottom. Type 342 was programmed to use the thermal properties of sand rather than water. A limitation was that Type 342 could only model a cylindrical bed, while the beds at this site are all rectangular. Still, bed depths and volumes were matched to make the simulation as accurate as possible. Storage beds were lined with 10 cm of 0.144 kJ/m3 K insulation (approximately equivalent to R-6.8 rigid board insulation) and topped with 0.5 m of soil. Four storage beds were modeled. The dimensions of the beds are shown in Table 1. Water was allowed to flow from the solar collectors to the storage bed at a rate of two changes per hour when the outlet temperature of the collectors was greater than that of the storage bed. Water flowed to the radiant floors of each story when the ambient temperature of that story dropped below 20 ◦ C, the lowest temperature permitted in a residence by ASHRAE standards, and was shut off when temperatures were greater than 21 ◦ C or if the temperature of the bed was less than that of the building. The flow was such that there was one change per hour. When SSTES was not enough to keep the building at or above 20 ◦ C, a backup theoretical heating system implemented in the TRNBuild software provided just enough energy to reach this temperature. For simulations without an SSTES system, the theoretical system provided all of the heat for the building. This system has an unlimited heating capacity, and only takes into account the heat required to reach 20 ◦ C, not the energy required to transport the heat into the building. Five year simulations were run to determine the heat load of the building by integrating the amount of heat provided by the theoretical system using TRNSYS Type 65a and Type 24. Simulations were run for all combinations of building efficiencies and storage bed dimensions. TRNSYS 16 is unable to simulate a system using Type 342 for more than five years. For this reason, only the fifth year of operation was examined. After conducting several similar studies, it has been found that sand-based SSTES systems reach equilibrium in approximately five years [13]. At this point, all the thermal energy lost during the cold months is regained in the warm months. The term “solar fraction” describes the percentage of total heat load provided by the seasonal solar thermal energy storage system. Fifth year solar fractions were determined by comparing the heat load of the simulations without heat from SSTES to identical building efficiencies with various SSTES implementations.
Store location
High efficiency building
Medium efficiency building
Low efficiency building
Fifth year load met by theoretical backup system (million kJ) 574 1030 No store Parking lot (9295 m3 ) 51.1 294 Parking lot (7865 m3 ) 67.0 331 Two courtyards (6200 m3 ) 78.4 348 3 Parking lot (5005 m ) 124 410
1480 6130 6540 6720 733
Table 3 Heat load of SSTES system during the fifth year of the simulation. Store location
High efficiency building
Fifth year load, SSTES system (million kJ) 523 Parking lot (9295 m3 ) 507 Parking lot (7865 m3 ) 495 Two courtyards (6200 m3 ) 445 Parking lot (5005 m3 )
Med. efficiency building
Low efficiency building
739 702 684 623
870 829 811 750
5. Results and discussion Table 2 shows the total heat load met by the theoretical backup system during the fifth year of operation after the SSTES system has reached a steady state. The first row represents the total heat load of the building without any SSTES and gives a means of comparison for the load values with SSTES implemented. This data is plotted in Fig. 2. As expected, larger storage beds correspond with smaller loads for the theoretical backup system. This demonstrates that larger storage beds are able to provide more heat to the building. In Table 3, the total load met by the SSTES system in the fifth year of operation is given. This is plotted in Fig. 3. The sums of the values in Table 3 and the values of the theoretical backup system load of Table 2 are consistent with the “No Store” values of Table 2. Table 4 compares the load met by the SSTES system to the total load by giving the solar fraction. This is calculated by dividing the values from Table 3 by the “No Store” values from Table 2. This is plotted in Fig. 4. The simulation of the courtyard storage bed (6200 m3 ) shows that considerable energy savings can be made without taking the costly step of excavating the neighboring parking lot. While this
High Efficiency Medium Efficiency
5th Year Heat Load Met by Theorecal Backup System
Low Efficiency
1600 1400
Heat Load (millions of kj)
Table 1 Storage bed dimensions.
1200 1000 800 600 400 200 0 0
2000
4000
6000
8000
10000
Storage Volume (cubic meters) Fig. 2. Fifth year heat load met by the theoretical backup system.
L.T. Terziotti et al. / Energy and Buildings 45 (2012) 28–31
High Efficiency Medium Efficiency
Fih Year Heat Load Met by SSTES System
Low Efficiency
1000
Heat Load (millions of kj)
900 800 700 600 500 400
In some situations, an adjacent courtyard might not be available. For a large residential building such as this housing project, the parking lot simulations demonstrate that a considerable solar fraction can be obtained from a small plot of land. As would be expected, solar fractions are lower for less efficient buildings. A higher solar fraction is preferable as the amount of necessary backup heating machinery would be reduced, potentially saving cost on installation and maintenance. However, the more efficient the building is, the better the performance from the SSTES system. This is because fluid returning from the radiant floors in a high efficiency building to the storage medium retains more heat than the fluid returning from an inefficient building.
300
6. Conclusion
200 100 0 0
2000
4000
6000
8000
10000
Storage Volume (cubic meters) Fig. 3. Fifth year heat load met by SSTES system. Table 4 Solar fraction by storage bed and building model. Store location
Fifth year solar fraction Parking lot (9295 m3 ) Parking lot (7865 m3 ) Two courtyards (6200 m3 ) Parking lot (5005 m3 )
High efficiency building
Med. efficiency building
Low efficiency building
0.910 0.883 0.863 0.784
0.716 0.680 0.663 0.603
0.587 0.559 0.547 0.506
High Efficiency Medium Efficiency
Fih Year Solar Fracon
Low Efficiency
1
Seasonal solar thermal energy storage is a viable heating solution for a building of this size when used with a backup heat source, such as an electric heat pump. This can be done in an urban environment such as VCU’s Monroe Park campus. While neighboring lots can provide enough space for a storage bed, simulations that incorporated storage beds into the building’s courtyards showed that these spaces can also be used with minimal loss in solar fraction. Using the courtyards for storage could potentially minimize costs by reducing the amount of additional engineering and excavation required while also providing a method for taking advantage of an otherwise underutilized area. Acknowledgments This research was funded by Virginia Commonwealth University Honors Summer Undergraduate Research Program. The authors would like to thank David Stets of Richmond BySolar for providing TRNSYS software and computers, as well as Carl Purdin in the VCU Facilities Management Division for providing building specifications. References
0.9 0.8
Solar Fracon
31
0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0
2000
4000
6000
8000
10000
Storage Volume (cubic meters) Fig. 4. Solar fraction compared to bed volume for all simulations performed.
SSTES system was less efficient than those utilizing the parking lot at greater depths, the solar fraction of this system was only 4.74% less efficient than the largest parking lot store (9295 m3 ) and only 1.98% less efficient than the second largest parking lot store (7865 m3 ) when implemented with the high efficiency model. This small loss of efficiency would be outweighed by the economic benefit.
[1] EIA, Total Energy Consumption, EIA, 2005. [2] EIA, US Carbon Dioxide Emissions from Energy and Industry, EIA, 2005. [3] NREL, Annual Average Daily Solar Radiation, 1990, Available from: http://rredc.nrel.gov/solar/old data/nsrdb/redbook/atlas/serve.cgi. [4] D. Coiante, L. Barra, Can photovoltaics become an effective energy option? Solar Energy Materials and Solar Cells 27 (1992) 79–89. [5] M. Green, J. Zhao, A. Wang, S.R. Wenham, Progress and outlook for highefficiency crystalline silicon solar cells, Solar Energy Materials and Solar Cells 65 (2001) 9–16. [6] S. Dubey, G.N. Tiwari, Thermal modeling of a combined system of photovoltaic thermal (PV/T) solar water heater, Solar Energy 82 (2008) 602–612. [7] E. Zambolin, D. Del Col, Experimental analysis of thermal performance of flat plate and evacuated tube solar collectors in stationary standard and daily conditions, Solar Energy 84 (2010) 1382–1396. [8] T. Schmidt, D. Mangold, H. Muller-Steinhagen, Central solar heating plants with seasonal storage in Germany, Solar Energy 76 (2004) 165–174. [9] A. Simons, S.K. Firth, Life-cycle assessment of a 100% solar fraction thermal supply to a European apartment building using water-based sensible heat storage, Energy and Buildings (2011), doi:10.1016/j.enbuild.2010.12.029. [10] Brunger et al., The Drake Landing Solar Community Project – Early Results, 2007. [11] D. Pahud, B. Matthey, Comparison of the thermal performance of double U-pipe borehole heat exchangers measured in situ, Energy and Buildings 33 (2001) 5. [12] M.N. Fisch, M. Guigas, J.O. Dalenback, A review of large-scale solar heating systems in Europe, Solar Energy 63 (1998) 355–366. [13] M.L. Sweet, Numerical Simulation of Underground Seasonal Solar Thermal Energy Storage, M.S. Thesis, Virginia Commonwealth University, 2010.
Contents lists available at SciVerse ScienceDirect
Energy and Buildings journal homepage: www.elsevier.com/locate/enbuild
Modeling seasonal solar thermal energy storage in a large urban residential building using TRNSYS 16 L.T. Terziotti, M.L. Sweet, J.T. McLeskey Jr. ∗ Virginia Commonwealth University, Department of Mechanical Engineering, 401 West Main Street, Room E3221, P.O. Box 843015, Richmond, VA 23284-3015, USA
a r t i c l e
i n f o
Article history: Received 27 April 2011 Received in revised form 31 August 2011 Accepted 4 October 2011 Keywords: TRNSYS Solar thermal storage Seasonal storage Urban buildings
a b s t r a c t Space heating, primarily using fossil fuels, is a major component of US energy consumption. Seasonal solar thermal energy storage (SSTES) provides a method to store solar thermal energy collected in the summer to use for heating in the colder months. Solar collectors are used to heat a sand bed, which retains its thermal energy through the winter. That energy is then sent into the building via radiant floors for space heating use. A sand-based storage bed SSTES system for a new five story student housing complex at Virginia Commonwealth University is modeled using TRNSYS Version 16 software. A total of 15 simulations of various storage bed locations and configurations as well as building efficiencies are modeled to determine whether a system is feasible for an urban environment. Substantial energy savings are possible within the small footprint required by city lots. Up to 91% of energy for this large building can be provided by the most efficient SSTES system. © 2011 Elsevier B.V. All rights reserved.
1. Introduction
2. Seasonal solar thermal energy storage systems
Residential space heating makes up a large portion of energy consumption in the United States. It accounts for 48% of energy consumption in residential buildings alone and is responsible for the release of approximately 502 million metric tons of carbon dioxide into the atmosphere each year. In 2005, 97% of U.S. households heated their homes using fossil fuels either directly or indirectly, via electricity derived from such fuels [1,2]. As populations continue to grow, and space and resources become more scarce, the importance of using renewable energy sources is paramount. Solar energy is particularly promising. Every day, 1000 W per square meter of power from the sun reaches the earth [3]. A major challenge is harnessing that massive amount of energy. Large scale energy production from photovoltaics faces the hurdle of intermittent power generation and low efficiencies, thus requiring costly storage mediums [4,5]. On the other hand, converting solar energy to thermal energy via solar collectors has high efficiencies and can be done while also generating electricity via photovoltaic/thermal (PV/T) collectors [6,7]. Therefore, it is important to investigate ways to use solar energy for space heating.
While more solar energy reaches the earth in the summer months, thermal energy is most needed in the winter. Seasonal solar thermal energy storage (SSTES) systems address this fundamental issue by providing a method to store solar energy well into the winter via a thermal storage medium. An SSTES system uses two closed fluid (water) loops. One loop runs through solar collectors to heat the fluid, then into coils inside the storage medium. Fluid in the second loop is heated in the storage medium and then sent through a radiant floor, thus heating the building. The storage medium varies depending on the requirements of the system. A basic SSTES system is shown in Fig. 1. The most common storage medium for an SSTES system is a water tank [8,9]. Water performs well as it has a high specific heat, disperses thermal energy via convection, and flows easily. Generally, the heavily insulated tanks are built above ground or partially above ground to save cost. In large scale projects, the tanks are usually constructed of insulated concrete with a high density liner to prevent permeation [8]. Another method uses the ground itself as a storage medium [10]. A system of boreholes is dug to a depth of 30–200 m, depending on the terrain. Each borehole contains a pipe that carries the fluid to the bottom of the hole and returns it to the surface. The fluid is then sent to the adjacent borehole. A layer of insulation near the surface of the system prevents loss of thermal energy. This method of SSTES is not suitable for all locations. Soil and groundwater conditions may make it impractical [11].
∗ Corresponding author at: 401 West Main Street, Room E3238, P.O. Box 843015, Richmond, VA 23284-3015, USA. Tel.: +1 804 827 7008, fax: +1 804 827 7030. E-mail addresses: [email protected] (L.T. Terziotti), [email protected] (M.L. Sweet), [email protected] (J.T. McLeskey Jr.). 0378-7788/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.enbuild.2011.10.023
L.T. Terziotti et al. / Energy and Buildings 45 (2012) 28–31
29
Fig. 1. Schematic of a basic sand-based SSTES system.
Using a sand, gravel, or soil-based storage medium is attractive due to its low cost and versatility. A pit is dug and lined with a waterproof membrane and insulation. The storage medium is spread inside the pit while coils of tubing for the fluid are distributed throughout the storage medium. The pit is sealed with more insulation and waterproofing and capped with soil. This type of storage medium is advantageous as the land above the storage bed can be used as a parking lot, playground, garden, or for some other purpose.
3. West Grace housing Starting in 2011, Virginia Commonwealth University will be constructing a new student housing project on its Monroe Park Campus. The Monroe Park Campus is located in the heart of Richmond, Virginia, at an elevation of 57 m above sea level in a humid subtropical climate. The project will be a 15,700 m2 (168,500 ft2 ) five story mixed use building with shops and restaurants on the first floor and 457 beds on the upper floors. This building was chosen to be modeled with SSTES to determine the efficacy of this system in a large urban residential building. Implementing SSTES in an urban environment, such as VCU’s Monroe Park Campus, poses unique problems. Space is scarce. All construction must be done to avoid danger to surrounding structures. Past research has examined building sites where space was of less concern [12]. Other research looked at smaller apartment buildings [9]. However, with its urban location, this project must optimize its SSTES system not only for efficiency, but also for geography. The first challenge is determining where to put the solar collectors. Past projects in central Europe have answered this problem adequately by successfully installing the solar collectors on the roofs of the structures to be heated [8]. This allows for the large, contiguous collector areas that have been determined to be most effective [8]. A more pressing issue is determining a location and medium for the storage bed. The above-ground water tanks of past large-scale projects are not feasible in an urban environment where space is scarce. Installing a subterranean water tank is costly, and repairing it is even more so. Also, the utility of the space is still compromised as building over a large water tank presents structural issues that would be costly to address. Thus, other storage mediums must be considered. A borehole system was ruled out as is impractical for Richmond due to its high water table. Using sand as a medium is both cost and space effective. Sand is cheap. A sand-based storage bed is structurally sound enough
to be installed underneath a parking lot or courtyard. Designs for sand-based storage beds are adaptable and easily scalable. For these reasons, sand was chosen as the storage medium for this project. There are two places near the West Grace Housing Project that could be used for the storage bed. The building, located at the intersection of West Grace and Shafer streets, is labeled WG Building. The first site is in the courtyards of the building. A second site is located in a parking lot opposite the building on West Grace Street. It measures 33 by 43 m and is owned by VCU. If feasible, it is preferable to place the storage bed in the building’s courtyards for two reasons. First, it is more cost effective. Using the parking lot would require a second excavation site, thus adding significant cost as designing and installing shoring in a city is quite expensive. The parking lot would then have to be repaved, and pipes would need to be run under West Grace Street, adding further costs and disrupting traffic. Repairs would also be expensive. On the other hand, the excavation required to install the beds in the building’s courtyards is already necessary to construct the building itself, so additional effort is trivial compared to that of the former scenario. The second factor that makes the courtyard a more attractive storage bed location is its permanence. While VCU may choose to sell or build on the parking lot in the future, the courtyards will remain courtyards for the entire lifetime of the West Grace Housing Project.
4. Implementation Building specifications were provided by VCU’s Facilities Management Division. The LEED-NC 2009 Silver 16,657 m2 building was estimated to have a peak-heating load of 18.93 W/m2 (6 BTU/sq.ft h) when using its electric heat pumps. Without ventilation recovery and other energy savings this estimate rises to 37.86 W/m2 (12 BTU/sq.ft h). Simulations were run at both of these heating loads as well as at 28.93 W/m2 (9 BTU/sq.ft h) to represent a building with fewer energy saving features. The system was modeled using TRNSYS Version 16, transient thermal energy modeling software developed at the University of Wisconsin-Madison. The building was constructed in TRNYSY with Type 53 using 6 zones: one for each of the five floors as well as a zone for the plenum above the first floor’s commercial areas. The model was designed to meet the specifications of the American Society of Heating and Air-conditioning Engineers (ASHRAE). Thermal interaction with the ground was modeled with Type 703d (slab on grade). Each of the five 3130 m2 floors had an active layer (radiant floor) with a pipe diameter of 1.8 cm and piping spaced 10 cm
30
L.T. Terziotti et al. / Energy and Buildings 45 (2012) 28–31 Table 2 Heat load of theoretical backup system during the fifth year of the simulation.
Location
Area (m2 )
Depth (m)
Volume (m3 )
Parking lot Parking lot Two courtyards Parking lot
1430 1430 1240 1430
6.5 5.5 5.0 3.5
9295 7865 6200 5005
apart. The building’s ventilation recovery system was modeled with the Type 91 heat exchanger. The building’s peak heating load was manipulated by varying the efficacy of this heat exchanger to simulate the varying levels of building efficiencies. As previously noted, the peak heating loads were 18.93, 28.93, and 37.86 W/m2 . It is best to have as large a solar collector area as possible [8]. In all, 1930 m2 of flat panel solar collectors (Type 73) were used. This equates to 62% of the roof, allowing ample space for any machinery or architectural features to share the roof while still providing an adequate solar collector area. The storage bed was modeled using Type 342, a module designed to simulate cylindrical water or rock-filled ponds, tanks, and caverns. The fluid in the collector loop is extracted from the bottom of the bed and injected at the top. Conversely, the fluid that goes to the radiant floors is extracted from the top of the bed and reintroduced at the bottom. Type 342 was programmed to use the thermal properties of sand rather than water. A limitation was that Type 342 could only model a cylindrical bed, while the beds at this site are all rectangular. Still, bed depths and volumes were matched to make the simulation as accurate as possible. Storage beds were lined with 10 cm of 0.144 kJ/m3 K insulation (approximately equivalent to R-6.8 rigid board insulation) and topped with 0.5 m of soil. Four storage beds were modeled. The dimensions of the beds are shown in Table 1. Water was allowed to flow from the solar collectors to the storage bed at a rate of two changes per hour when the outlet temperature of the collectors was greater than that of the storage bed. Water flowed to the radiant floors of each story when the ambient temperature of that story dropped below 20 ◦ C, the lowest temperature permitted in a residence by ASHRAE standards, and was shut off when temperatures were greater than 21 ◦ C or if the temperature of the bed was less than that of the building. The flow was such that there was one change per hour. When SSTES was not enough to keep the building at or above 20 ◦ C, a backup theoretical heating system implemented in the TRNBuild software provided just enough energy to reach this temperature. For simulations without an SSTES system, the theoretical system provided all of the heat for the building. This system has an unlimited heating capacity, and only takes into account the heat required to reach 20 ◦ C, not the energy required to transport the heat into the building. Five year simulations were run to determine the heat load of the building by integrating the amount of heat provided by the theoretical system using TRNSYS Type 65a and Type 24. Simulations were run for all combinations of building efficiencies and storage bed dimensions. TRNSYS 16 is unable to simulate a system using Type 342 for more than five years. For this reason, only the fifth year of operation was examined. After conducting several similar studies, it has been found that sand-based SSTES systems reach equilibrium in approximately five years [13]. At this point, all the thermal energy lost during the cold months is regained in the warm months. The term “solar fraction” describes the percentage of total heat load provided by the seasonal solar thermal energy storage system. Fifth year solar fractions were determined by comparing the heat load of the simulations without heat from SSTES to identical building efficiencies with various SSTES implementations.
Store location
High efficiency building
Medium efficiency building
Low efficiency building
Fifth year load met by theoretical backup system (million kJ) 574 1030 No store Parking lot (9295 m3 ) 51.1 294 Parking lot (7865 m3 ) 67.0 331 Two courtyards (6200 m3 ) 78.4 348 3 Parking lot (5005 m ) 124 410
1480 6130 6540 6720 733
Table 3 Heat load of SSTES system during the fifth year of the simulation. Store location
High efficiency building
Fifth year load, SSTES system (million kJ) 523 Parking lot (9295 m3 ) 507 Parking lot (7865 m3 ) 495 Two courtyards (6200 m3 ) 445 Parking lot (5005 m3 )
Med. efficiency building
Low efficiency building
739 702 684 623
870 829 811 750
5. Results and discussion Table 2 shows the total heat load met by the theoretical backup system during the fifth year of operation after the SSTES system has reached a steady state. The first row represents the total heat load of the building without any SSTES and gives a means of comparison for the load values with SSTES implemented. This data is plotted in Fig. 2. As expected, larger storage beds correspond with smaller loads for the theoretical backup system. This demonstrates that larger storage beds are able to provide more heat to the building. In Table 3, the total load met by the SSTES system in the fifth year of operation is given. This is plotted in Fig. 3. The sums of the values in Table 3 and the values of the theoretical backup system load of Table 2 are consistent with the “No Store” values of Table 2. Table 4 compares the load met by the SSTES system to the total load by giving the solar fraction. This is calculated by dividing the values from Table 3 by the “No Store” values from Table 2. This is plotted in Fig. 4. The simulation of the courtyard storage bed (6200 m3 ) shows that considerable energy savings can be made without taking the costly step of excavating the neighboring parking lot. While this
High Efficiency Medium Efficiency
5th Year Heat Load Met by Theorecal Backup System
Low Efficiency
1600 1400
Heat Load (millions of kj)
Table 1 Storage bed dimensions.
1200 1000 800 600 400 200 0 0
2000
4000
6000
8000
10000
Storage Volume (cubic meters) Fig. 2. Fifth year heat load met by the theoretical backup system.
L.T. Terziotti et al. / Energy and Buildings 45 (2012) 28–31
High Efficiency Medium Efficiency
Fih Year Heat Load Met by SSTES System
Low Efficiency
1000
Heat Load (millions of kj)
900 800 700 600 500 400
In some situations, an adjacent courtyard might not be available. For a large residential building such as this housing project, the parking lot simulations demonstrate that a considerable solar fraction can be obtained from a small plot of land. As would be expected, solar fractions are lower for less efficient buildings. A higher solar fraction is preferable as the amount of necessary backup heating machinery would be reduced, potentially saving cost on installation and maintenance. However, the more efficient the building is, the better the performance from the SSTES system. This is because fluid returning from the radiant floors in a high efficiency building to the storage medium retains more heat than the fluid returning from an inefficient building.
300
6. Conclusion
200 100 0 0
2000
4000
6000
8000
10000
Storage Volume (cubic meters) Fig. 3. Fifth year heat load met by SSTES system. Table 4 Solar fraction by storage bed and building model. Store location
Fifth year solar fraction Parking lot (9295 m3 ) Parking lot (7865 m3 ) Two courtyards (6200 m3 ) Parking lot (5005 m3 )
High efficiency building
Med. efficiency building
Low efficiency building
0.910 0.883 0.863 0.784
0.716 0.680 0.663 0.603
0.587 0.559 0.547 0.506
High Efficiency Medium Efficiency
Fih Year Solar Fracon
Low Efficiency
1
Seasonal solar thermal energy storage is a viable heating solution for a building of this size when used with a backup heat source, such as an electric heat pump. This can be done in an urban environment such as VCU’s Monroe Park campus. While neighboring lots can provide enough space for a storage bed, simulations that incorporated storage beds into the building’s courtyards showed that these spaces can also be used with minimal loss in solar fraction. Using the courtyards for storage could potentially minimize costs by reducing the amount of additional engineering and excavation required while also providing a method for taking advantage of an otherwise underutilized area. Acknowledgments This research was funded by Virginia Commonwealth University Honors Summer Undergraduate Research Program. The authors would like to thank David Stets of Richmond BySolar for providing TRNSYS software and computers, as well as Carl Purdin in the VCU Facilities Management Division for providing building specifications. References
0.9 0.8
Solar Fracon
31
0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 0
2000
4000
6000
8000
10000
Storage Volume (cubic meters) Fig. 4. Solar fraction compared to bed volume for all simulations performed.
SSTES system was less efficient than those utilizing the parking lot at greater depths, the solar fraction of this system was only 4.74% less efficient than the largest parking lot store (9295 m3 ) and only 1.98% less efficient than the second largest parking lot store (7865 m3 ) when implemented with the high efficiency model. This small loss of efficiency would be outweighed by the economic benefit.
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