Simulation of domestic heat demand management using sensible and latent heat storage.

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1 Simulation of domestic heat demand management using sensible and latent heat storage. Joynal Abedin 1, a, Steven K. Firth 1, b, Philip C. Eames 2, c 1* School of Civil and Building Engineering, Loughborough University, UK. LE11 3TU. 2 Centre for Renewable Energy Systems Technology, Loughborough University, UK. LE11 3TU. a J.Abedin@lboro.ac.uk, b S.K.Firth@lboro.ac.uk, c P.C.Eames@lboro.ac.uk, ABSTRACT Approximately one third of the energy consumption and CO 2 emission in the United Kingdom is in domestic buildings. Around 80% of the energy is used for space and water heating. Therefore, removing the CO 2 emission from heating is essential for meeting the 2050 target of reducing the overall CO 2 emission by 80% from a 1990 baseline. This could be done by using electricity for heating from renewable sources and low or decarbonised electricity generators. However, this could result in large disparity between the daily and seasonal peak to offpeak electricity demand, imposing tough challenges in the form of matching supply to demand. Thermal Energy Storage (TES) could help overcome these challenges, by de-coupling the temporal link between demand and supply, enabling demand shifting in time. To do this effectively, large uptake of the TES will be necessary. This research provides an insight into the heat demand shifting capability of domestic scale TES and the benefits it could deliver. This is done by dynamic modelling of a 1990 s building with typical occupancy scenarios. The model simulates active and passive heat storage by using models of a hot water storage tank and Phase Change Material (PCM) based ceiling insulation. The results show that water tank size typically installed in homes and PCM wall layers can shift the heat demand by 3 hours whilst maintaining adequate level of thermal comfort. This research provides a good starting point for gaining greater understanding of the techno-economic benefits of TES, and how it could make domestic buildings more sustainable. KEYWORDS: Heat demand management, Building simulation, Heat demand shifting. 1. INTRODUCTION The Climate Change Act 2008 (H.M. Government, 2008) sets legally binding targets for the UK to reduce its carbon dioxide (CO 2 ) emissions by 34% by 2020 and 80% by 2050, against a 1990 baseline. The domestic building sector is the second largest energy consuming sector. It is responsible for over 30% of the total UK energy needs and produces over 28% of the overall CO2 emission (Martiskainen, 2007). Therefore, this sector requires high de-carbonization and demand reduction priority. Energy efficiency improvement, demand side management and micro-renewable energy generation and decarbonised mains electricity are some of the methods available for use in this sector. This will reduce the heavy use of fossil fuels in favour of renewables. Mass penetration of these will lead to an energy system with a diverse energy generation mix, and greater electrification of the energy demand sectors. The results will be lower power quality due to the high aggregation of energy from Renewable Energy Technologies (RET), and large variability in electricity supply due to the intermittency in renewable generation (ERP, 2011), (Hall, 2008). These are challenges which will impact the security and resilience of the future energy system, and will need to be mitigated. Further, the UK domestic building sector comprises of over 26 million homes and predominantly heated by natural gas, resulting in a relatively large contribution to the overall CO2 emission. Removing CO2 emission from heating is vital in order to ensure that the UK has chance of meeting its CO2 emission obligations, especially as heating (space and water heating) accounts for approximately 80% of the total energy use in domestic buildings (HM Government, 2009). This could be done by meeting the heating needs using renewable sources such as solar thermal systems, or by using electricity from low or zero carbon electricity generators such as nuclear power and plants utilising carbon capture and storage. A study by the Energy Research Partnership (ERP, 2011) shows that a large scale deployment of heat pumps will deliver the heating needs, and is predicted to attain over 50% household penetration by 2030 and over 75% by This would exert additional challenges in the form of larger electricity demand variation between the winter and the summer seasons. Greater number of power stations may be needed for meeting the winter demand, whilst during the summer time they will need to operate at a lower power factor due to the low demand.

2 Grid Load (MW) SB13 Dubai Paper Comparison of TES Top-Up, Demand shift period and a diurnal grid load curve for a November weekday Grid Off-Peak Grid Peak TES Topup period Demand shift period :00 04:00 08:00 12:00 16:00 20:00 Time of day (Hrs) Figure 1. Illustration of a real diurnal grid load curve for a November weekday, the daily peak and off-peak periods, and the potential heat demand shift period. Currently, in the winter days, the daily electricity demand peaks during 4pm and 6pm (See Figure 1). Evening heating demand mostly occurs between 4pm and 8pm, and largely coincides in time, throughout all the dwellings in the UK. Transferring this demand over to the electricity grid could lead to an unsustainable disparity between the daily peak and off-peak demands. This, together with the increasing quantity of intermittent generation from RETs, has the potential to become extremely difficult and expensive to match the daily supply to the daily demand (ERP, 2011). One way of mitigating this is by removing the heating demand from the peak period (Demand Shift Period) and spreading it over an off-peak period (Top-up Period) as can be seen in Figure 1. To do this effectively, some form of Thermal Energy Storage (TES) capability in the dwellings will be required. Such TES capability could also absorb surplus energy generated by intermittent macro and micro RETs, providing economic benefits as well as the short term grid load balancing ability, thereby enabling the electricity generation networks to accommodate greater deployment of RETs. Successful deployment of effective TES is therefore critical to ensuring greater penetration of heat pumps and RETs, without which the domestic decarbonisation and renewable energy targets could become unachievable. The UK domestic building sector has over 13.7 million homes fitted with hot water storage tank (ERP, 2011), presenting us with a great opportunity to apply TES, to decouple the temporal link between the heating energy supply and demand, enabling the demand to be shifted in time. This will allow asynchronous management of the supply and demand, providing options for mitigating the challenges. There are many ways of incorporating TES in buildings (Arteconi A, et. al., 2011). This research looked into two methods; 1) Passive TES where a Phase Change Material (PCM), a latent heat storage material that can store or release relatively large amount of heat energy as it s physical state changes with temperature, for example from solid to liquid (Sharma et. al, 2009), is attached to the surface of the ceilings, to store and release heat as the room temperature rises and falls past it s phase change temperature, and 2) Active sensible TES where water in a hot water storage tank is actively heated up to a temperature below the boiling point, and the heat energy stored in the water is used to service the space heating and DHW needs. To apply TES effectively it is necessary to understand how the building occupancy and operational dynamics interact with TES, and what the key parameters are that define and improve the usefulness of domestic scale TES. Using dynamic building modelling and simulation, this research intended to contribute towards understanding these issues better by exploring the energy performance, thermal transient responses and the potential benefits of active and passive TES application in a two bedroom detached property, when operated under dynamic operational scenarios. The study explores the heat demand shifts achievable with a 0.5m 3 hot water storage tank size and a simple PCM layer attached to the ceilings. The model identifies the time and duration of the space temperature drop below a commonly acceptable level of 18, which is a key parameter that affects the level of thermal comfort achievable (Yohanis et al., 2010), during the demand shift period. This study provides a guide to developing of more accurate and effective models of domestic scale TES, which could be used to assess the techno-economic feasibility and the effectiveness of TES application in domestic buildings. 2. METHODOLOGY This research is based on a dynamic building modelling case study investigating the thermal performance and heat energy demand management capability within a two bedroom detached dwelling. The building is located on the Loughborough University campus (Figure 2), and comprises of standard brick construction materials, and built to the 1990 s building regulation standards.

3 Dept. of Civil & Building Engineering N N Test_House Figure 2. Location and orientation of the subject building. Figure 3. Screen shot of the TRNSYS building model. Transient System (TRNSYS), a dynamic modular simulation program, was used to model the building and the associated system components (Crawley et. al, 2005). Developed by the University of Wisconsin, TRNSYS involves interconnecting different modules or TYPES representing different system components or building materials, for example a radiator or TYPE 1231 and a multi-zone building or TYPE 56. All the components, boundary conditions and the simulation parameter are configured in the TRNSYS Simulation Studio. The simulation engine solves algebraic and differential equations that represent the entire system. Outputs can be analysed graphically or printed to external files in various formats for further analysis. The study involved developing three model cases of the building, heating and the TES systems (see Table 1); Table 1. Building fabric construction and the heating system details for the three model cases considered. Building part Base Case Active TES Case Combines TES Case Ground Floor Synthetic carpet & Underlay, Timber flooring, Air gap, Cast concrete, Dam proof, Clay U-Value = 0.93W/m 2 K External Wall Gypsum Plaster, Block inner skin, Cavity insulation, Facing brick outer U-Value: 0.36 W/m 2 K Roof Slate tiles, Ashfelt U-value = 3.97W/m 2 K (Double glazed) Pilkington glass, Cavity, External Windows Pilkington glass PVC U-value = 1.76 W/m 2 K External Doors Double glazed FF floor/gf ceiling Loft floor/ff ceiling Heating System U-value = 2.95 W/m 2 K Carpet & Underlay, Timber flooring, Cavity, Gypsum plasterboard U-value = 1.33 W/m 2 K Insulation, Gypsum plasterboard U-value = 0.22 W/m 2 K Wet instantaneous central heating & DHW Wet central heating & DHW with hot water storage at mm PCM layer Melting point = mm PCM layer Melting point = 18 Wet central heating & DHW with hot water storage at The modelling approach The Base Case The Base Case building model consists of a Type-56 multi-zone building. The building has two thermal zones, Ground Floor (GF) and First floor (FF), each having specific internal gain, and connection to the heating system via a radiator (see Table 2). The loft was not connected to the heating system and had no direct internal gains. Temperature sensors are located on both zones to enable independent control of the space temperature and minimise energy use. Configuration of the DHW and the heating system components are shown in figure 4. A hot water storage tank modelled as a 0.5m 2 stratified cylindrical hot water storage tank (Type-4) provides hot water for both DHW and space heating. The tank has an internal 20kW electrical heating element heating the water to a temperature of 70. The hot water is circulated through heat exchangers which transfer energy for meeting the DHW

4 and space heating demand. The energy removed from the tank is immediately replaced by the electric heating element simulating the operation of typical storage tank backed DHW and heating system. The hot water tank has a six stage stratification. The heating element is fixed at the lowest stratified zone, and the hot water output delivered from the top most zone. The dimensions of the TES tank are such that the stratified zone heights are 0.3m giving an overall tank height and diameter of 1.8m and 0.6m respectively. These are dimensions of commercially available tanks of the 0.5 m 2 volume, which can be installed in most of the existing building stock. The tank loss coefficient is set to 0.7W/m 2.K, and the heating dead band is 5. The system comprises of three hot water loops (see figure 4); 1) Primary loop: isolating the water tank from both the DHW and heating loops, 2) Intermediate loop: isolating DHW from the heating loop, and, 3) Heating loop: circulating water around the heating system. Heat from the primary loop is transferred to the intermediate loop via a heat exchanger (Type 657). If the primary loop temperature drops below the set-point all the water flows through the heat exchanger in order to achieve maximum heat transfer to the intermediate loop. The space heating loop consists of two 8kW radiators (Type 1231) serving the two thermal zones, a constant flow rate pump (Type 114) and a heat exchanger (Type 657) as in figure 4. The heat exchanger transfers heat from the intermediate loop to the heating loop. The pump circulates water through the heat exchanger and a bypass in appropriate proportions to ensure a water temperature of 70. If the heating loop water temperature falls below the set-point, all of the water is pumped through the heat exchanger ensuring maximum heat transfer to the heating loop. The radiator and the pump sizes are based on the thermal zone size, type and how they connect to other spaces, as determined by commercially available radiator sizing calculators. DHW demand is primarily linked to the number of occupiers residing in the building at a point in time. The temperature usually varies from 10 to 60, and the range of uses includes bath/shower, hand washing, dish washing and clothe washing (Yao. et al., 2005). Vast majority of the DHW used is at a temperature around 45, which is also recommended in order to minimise the risks of scalding (Hewitt, N. J., 2012). Therefore, a combination of tampering (Type 11h,) mixing (Type 11d) and diverter (Type 647) valves are used in the model to ensure a water delivery temperature of 45. Water in the intermediate loop is mixed with cold water to feed the DHW outlets. If the primary loop and/or the intermediate loop water temperature fall below the DHW temperature set-point then it is only delivered from the intermediate loop without mixing with cold water. The average DHW consumption per capita is around 67.4lt/day (Yao. et al., 2005). The model reflected this by supplying hot water at a rate of 5.6lt/hour. The timing of the DHW delivery is linked to the times when occupants are present in the building, which is assumed to be approximately 12 hours per day, thus resulting in approximately 67.4lt/ person /day. The building occupancy schedule comprised of two adults and one school age child. The Building Research Establishment Domestic Energy Model (BREDEM), which is the most commonly used building energy model UK, and on which the Standard Assesment Procedure (SAP) is based, assumes that the living room is heated to 21 for 9 hours on weekdays, to and to (Heating-On periods). Thus, the room temperature set-point and the heating duration are set to coincide with BREDEM. The daytime occupancy profiles for the occupants also coincides with the BREDEM heating assumption, whilst the night time occupancy is from to The night time internal gain from the occupant is set to 50% of the day time gain, and only applicable to the relevant thermal zones. For simplicity the temperature set point and the duration is kept identical for both of the thermal zones, and the weekdays and weekends respectively, although BREDEM assumes a bedroom temperature of 18 and weekend heating duration of 16 hours (07.00 to 23.00). This study also assumes that additional, portable or otherwise, heating devices are not used in the building. DHW Load Ground Floor First Floor Primary HX/Isolator Secondary HX/Isolator Pump Radiator Radiator Primary Loop Intermediate Loop Heating Loop TES Tank Cold Water Supply Thermostat Thermostat Control Figure 4. The DHW and the space heating system configuration. The internal gains comprise of people (adults: Sensible = 90W, Latent = 60W; child: sensible = 60W, latent = 40W), lighting during occupied hours only (5W/m2), cooking lighting during occupied hours (sensible =

5 1000W, latent = 100W), and a TV (sensible = 200W, Latent = 50W). These are assumed to be the most dominant sources of internal gain. The thermal zone air infiltration level is set to 0.5ACH as per the requirement of the Part L building regulation (CIBSE Guide A., 2006). The loft infiltration is set to 1 ACH. Ventilation is set at 0.5 ACH during the daytime occupied hours only. The weather data used is based on a location approximately 5 miles north the building site. Simulations were performed for 60 days from the 1 st of January, when heating dominates the domestic energy consumption, creating extreme scenarios in terms of supply and demand. The simulation time resolution was 5 minute Active TES Case Sensible heat storage using hot water storage tank The Active TES Case comprised of the building and the heating system models as per the Base Case with the exception that the hot water tank is configured to store water at a temperature of 95. The tank initially heats the water between 0.00 and hours. The stored heat is later used to provide heating and the DHW during the demand shift period (16.00 to hours) when the main heating system is switched off. This simulated heating energy demand shifting in time, from the electricity grid peak-time of to hours to an off-peak time between to hours (see Figure 1) Combined TES Case Sensible & latent heat storage using PCM and hot water storage tank The Combined TES Case comprised of the building and the heating system models as per the Base Case and the Active TES Case with the exception that a PCM material layer (Type 1270) is inserted at the surface of the entire ground floor and first floor ceilings (see Table 1). The PCM material specification is set such that the melting and solidification occurs at 18. The specific heat of the PCM material is 3 kj/kgk for both solid and liquid phases. The specific heat of fusion is 1000 kj/kg. Kruznik, et. Al, (2010) described the development and validation of Type The model simulates a pure PCM layer from a physical view point, for example the PCM is not encapsulated and impregnated into some gypsum material, as is the case with many existing commercially available products. The model assumes that the material phase change process occurs at a constant temperature and also has a constant specific heat in both the solid and the liquid phase. 3. RESULTS & DISCUSSION 3.2 Base Case Results and validation There is good agreement between the base case space temperature and the range of heat demands observed during this study and a previous similar study (Abedin, et. al, 2013) involving the same building and different tools, Integrated Environmental Solution and TRNSYS, providing confidence that the models operated with a reasonable level of accuracy. The ground floor, having larger overall window area and due to the buoyancy effect, is the worst in retaining heat compared to the first floor (see figure 3), and more likely to pose thermal comfort issues. Therefore, the subsequent temperature analyses are based on the ground floor data unless specifically stated. The transient space heating response (after the heating system turns on) is such that it takes roughly 15 to 20 minutes to reach the set-point of 21, as shown in the example in figure 3. This is maintained throughout the heating-on period. As the heating system turns off at the end of the heating-on period, the temperature rapidly drops to roughly 14, taking around 20 minutes, then gradually drops further until the next heating-on period is reached. This transient heating and cooling characteristics are important as they describe the rate at which the space heats up and cools down, and therefore the power rating and the capacity requirement of the heating system and the TES system to be used. The lowest unoccupied time room temperature is 6.8 and the overall daily average temperature is The ventilation rate included in the model is a factor (in addition to the building fabric) contributing to the rapid rise and fall of the space temperature. Reducing this to zero improves the temperature up to 2, indicating a variable which could be used to ensure more acceptable room temperature during the demand shift period. The heat energy demand during the simulation period for space heating and DHW are in the range 42.16kWh to 49.58kWh and 5.89kWhr to 6.03kWh respectively (see Table 2). These are comparable to the previous study involving the same building, and are also in line with what can be expected of a building of its type and size (Arteconi A, et. al., 2011). The combined heat and DHW demand during the demand shift period (i.e. from 4pm to 8pm) varies from 20.84kWh to 25.35kWh. This is the amount of energy the TES system will have to deliver and at an appropriate

6 rate in order to ensure that the room temperature remains at the set-point and that the DHW demand is met. The corresponding space heating only energy demand varies from 9.74kWh and 19.76kWh. Figure 3. Example of the thermal response and the heating load on 7 th January for the Base Case. Figure 4. Example of the thermal response and the heating load on 7 th January for the Active TES Case. Figure 5. Example of the thermal response and the heating load on 7 th January for the Combined Case. 3.3 Impact of active and passive TES When the heating system is switched off during the demand shift period, stored heat from the hot water tank is transferred into the room. The energy delivered varies from 18.01kWh to 21.23kWh over the simulation period (see Table 2). As the water tank energy is depleted, the room temperature drops below the set point as illustrated in figure 4 for the example day of January 7 th. The lowest room temperature during the demand shift period (i.e. during occupied hours) is (see Table 2). The room temperature remains below 18 for hours during the occupied hours over the simulation period. This indicates that the room temperature would remain at lower than 18 for about 2 hours each day during the demand shift period, reaching the lowest temperature of This will affect the thermal comfort level and is unlikely to be acceptable to most occupants. One way of addressing this is by reducing the demand shift period, for example when it is reduced to 3 hours (i.e. 4.30pm to 7.30pm) the temperature duration below 18 drops to 42.6 hours or roughly 40 minutes per day. The lowest temperature value also rises by about 1, which could improve the perception of thermal comfort in the room. A further improvement to this aspect could be achieved by reducing the ventilation rate during the demand shift period. Storing water at 70, instead of 95, reduces the lowest room temperature by about 3, and the temperature remains lower than 18 for virtually the entire 4 hour demand shift period. This indicates the importance of having high temperature fluid in the storage tank. Using other high temperature fluid in the primary loop may be advantageous and worth investigating, although safety issues relating to high temperature storage will arise and need to be taken into account. The active TES in the hot water storage tank was expected to provide bulk of the energy needed for the heat demand shift whilst the passive PCM TES help to prolong the demand shift and flatten the heating load curve. This is demonstrated in figure 5 where the unoccupied period temperature drop remains 1 to 2 higher than for

7 the case without the PCM (Figure 4). As a result, the peak heating load at the beginning of the heating-on period is marginally lower, and therefore this would have a slight flattening effect on the overall heating load profile. The combined effects of active and passive TES demonstrated an appreciable improvement to the minimum room temperature reached during both the occupied and the unoccupied hours (see Table 2). Interestingly, however, the duration of the below 18 temperature in the demand shift period got slightly worse from hours to hours. An explanation for this could be that the material melting temperature is also set at 18 resulting in the heat energy being stored in the PCM without raising the space temperature. PCM material clearly had some positive impact. However, the full potential of the PCM material could not be simulated as the material melting point and the room temperature duration did not result in a complete phase change to occur. This limited the latent heat storage and release during the demand shift period. Lowering the PCM melting point to 15degC, enabling most of the material to change phase, was seen to keep the unoccupied hour room temperature even higher, therefore demanding even less energy for raising it to the set-point. This suggested that, if the PCM was to go through the phase change around the set-point temperature then it would help to maintain higher room temperature during the demand shift period. Table 2. Summary of the daily energy demands and room temperatures over a 60 day simulation period from 1 st January. Base Case Active TES Case Combined Case Min Max Min Max Min Max Daily DHW Energy demand (kwh) Daily space heating Energy demand (kwh) Heat & DHW energy demand 4-8pm (kwh) Heat demand 4-8pm (kwh) GF temperature over 24 hours ( ) Minimum & Mean 6.82 & & & Lowest room temperature. (4pm-8pm) ( ) Space temperature duration < 18 (Hours) Heat demand shifting of 4 hours has been shown to be unachievable, whilst maintaining adequate level of thermal comfort, with a 0.5m 2 hot water storage tank, storing water at 95. The addition of PCM helps in keeping the room temperature above 13 for the entire duration, but remains below 18 for over two hours (or 53%) of the demand shift period, which may be unacceptable to many occupants. Reducing the demand shift period to 3 hours shows a much more acceptable space temperature level, and only stays below 18 for about 23% or 43 minutes of the demand shift period. Further research following this study could include investigating how a more realistic PCM would affect the space temperature and the demand shifting ability. Also, the effectiveness of the TES methods investigated needs to be simulated within different building size, type, location, and larger and more variable occupancy scenarios. The impact of applying PCM based TES on the building thermal performance, particularly cooling during the summer season, has been ignored during this study. This is an aspect which is becoming more and more significant with the increasing temperature due to global warming, and needs to be understood. A further, and an important, research area is investigating the adverse impact on the electricity supply and distribution, which could result as a consequence of a large scale TES uptake in domestic buildings. For example, could shifting the heating load of the period 4pm-8pm to an off-peak time simply result in a new peak occurring at 12am, and would this be sustainable, in terms of generation capacity and distribution, if replicated throughout all the UK domestic buildings? Also, the peak demand at 7am could become unsustainable for the same reason. Therefore, to explore these concerns, the model could be simulated to provide heating, initially to both of the heating demand periods (7am-9am and 4pm-11pm) from the TES system, to dampen the peak load. The TES system could be recharged during all other times of low electricity demand from the grid, but at a slower rate to avoid sudden peaking in demand. In addition, the release of the stored heat into the space could be combined with heating from the grid at the time of demand, and replenishing the store when the grid load is low, thereby further spreading the stored heat use and the demand of energy from the grid. This would mean shifting most of the heat demand to the off-peak times, and spreading the remainder over an extended demand shift period, resulting in a flattened overall heating load curve. The models developed during this research, with further enhancement, will enable greater exploration and understanding of these scenarios, which is essential for formulating a viable future heat demand management strategy.

8 6. CONCLUSIONS A 1990 s two bedroom detached building model was created in TRNSYS, consisting of a Base Case, Active (hot water storage tank) TES Case and a Combined (hot water storage tank and PCM ceiling layer) TES Case scenario. Simulations were carried out with a typical occupancy schedule for two adults and a child, and the thermal transient responses and the heat energy consumption were analysed. Hot water tank based sensible TES system model was used to shift the DHW and space heating demand from the peak period of 4pm-8pm to an offpeak period of 12am-7am. The full benefits of latent heat storage and release by the PCM are not realized due the slow and insufficient volume of material changing phase during the heating and cooling cycle, even when the melting point is set as low as 18. Therefore, the value of using PCM for heat demand shifting in domestic building is considered questionable. A 4 hour heat demand shift does not seem to be possible with a 0.5m 3 hot water tank, storing water at 95, whilst still maintaining an adequate level of thermal comfort. However, a 3 hour heat demand shift may be achieved, which maintains the room temperature at 18 or higher for approximately 137 minutes or 76% of the demand shift period. Storing sensible heat at higher temperatures, which does not have the complications of thermal conductivity and heat exchange as is the case with latent heat storage, for heat demand shifting appeared effective. Therefore, research into other media for heat storage at temperatures beyond 100, which are still suitable for domestic heat demand management is recommended. ACKNOWLEDGEMENT This research was made possible by EPSRC support for the London-Loughborough Centre for Doctoral Research in Energy Demand, grant number EP/H009612/1. REFERENCES Abedin, J., Firth, S. K., Eames, P. C., Simulation of heat demand shifting using short-term thermal storage, 13 th International IBPSA Conference, Building Simulation 2013, IBPSA. Arteconi A, et. al., State of the art of thermal storage for demand-side management, Applied Energy 93 (2012) Crawley, D. B. et al.,2005. Contrasting the capabilities of building energy performance simulation programs, Ninth International IBPSA Conference, Building Simulation 2005, IBPSA. CIBSE GUIDE A, Environmental Design, 7 th Edition, The Chartered Institution of Building Services Engineers, CIBSE Publications, London. ERP, The future role for energy storage in the UK, Main Report, The Energy Research Partnership, Technology Report. June Hall, P.J., Energy storage: the route to liberation from the fossil fuel economy? Energy Policy, 36(12), p Hewitt, N.J., Heat pumps and energy storage The challenges of implementation. Applied Energy, 89(1), p HM Government (2008). Climate Change Act. Retrieved from available at: acts/acts2008/pdf/ukpga_ _en.pdf HM Government, The UK Low Carbon Transition Plan: National strategy for climate and energy. HM Government, UK. Kuznik, F., Virgone, J. & Johannes, K., Development and validation of a new TRNSYS type for the simulation of external building walls containing PCM. Energy and Buildings, 42(7), pp Martiskainen, M., Affecting consumer behaviour on energy demand. Energy, 81(March) Sharma, A. et al., Review on thermal energy storage with phase change materials and applications. Renewable and Sustainable Energy Reviews, 13(2), p Yohanis, Y.G. & Mondol, J.D., Annual variations of temperature in a sample of UK dwellings. Applied Energy, 87(2), p Yao, R. et al, A method of formulating energy load profile for domestic buildings in the UK, Energy and Buildings, 37(6), p