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Energy saving potential of phase change materials in major Australian cities
Energy and Buildings 78 (2014) 192–201
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Energy and Buildings journal homepage: www.elsevier.com/locate/enbuild
Energy saving potential of phase change materials in major Australian cities Morshed Alam ∗ , Hasnat Jamil, Jay Sanjayan, John Wilson Centre for Sustainable Infrastructure, Faculty of Science Engineering and Technology, Swinburne University of Technology, Hawthorn, Victoria 3122, Australia
a r t i c l e
i n f o
Article history: Received 26 November 2013 Received in revised form 17 April 2014 Accepted 21 April 2014 Available online 16 May 2014 Keywords: Phase change materials PCM Building energy modelling EnergyPlus Thermal energy storage Energy savings
a b s t r a c t The potential of phase change materials (PCM) in reducing the heating/cooling energy consumption of residential houses along with several factors influencing the effectiveness of PCM were investigated using EnergyPlus. Simulations were carried out using five different phase change temperature ranges at eight Australian cities which represent six climate zones. It was found that the effectiveness of PCM strongly depends on local weather, thermostat range, PCM layer thickness and surface area. The optimum PCM melting range for lowest energy consumption in each month of the year was found to be far from unique. Different PCM was found to be effective in different times of the year. Depending on local weather, the integration of PCM resulted in 17–23% annual energy savings in the studied house except hot and humid cities like Darwin. For a given amount of PCM, energy saving potential was found to improve further with the increase of applied surface area and decrease of PCM layer thickness up to certain limit beyond which the potential started to decline. The energy saving potential was also found to decrease when the PCM melting point was outside the thermostat range of the corresponding city. The paper also presented the potential effect of climate change on the effectiveness of PCM. © 2014 Elsevier B.V. All rights reserved.
1. Introduction The fast economic development around the globe and high standards of living imposes an ever increasing demand for energy. Over the period 1979–1980 to 2009–2010, there was a 90% increase in Australia’s total energy use, from 3131 PJ to 5925 PJ [1]. Approximately, 95% of Australia’s total energy consumption comes from fossil fuels (coal, oil and gas) [2] which results in harmful greenhouse gas emissions. In 2009–2010, the energy consumption of residential building was around 25% of total energy consumptions and contributed around 13% of total Australia national greenhouse gas emission [1,3]. In recent years, Latent Thermal Energy Storage (LTES) systems in buildings have received serious attention for reducing the dependency on fossil fuels and contributing to a more efficient environmentally benign energy use. Latent heat storage materials, also known as phase change materials (PCM’s), absorb or release the energy equivalent to their latent heat when the temperature of the material undergoes or overpasses the phase change temperature [4]. PCM represent a technology that has the potential to shift peak load and reduce Heating Ventilation and
∗ Corresponding author. Tel.: +61 3 92145463. E-mail addresses: [email protected], [email protected] (M. Alam). http://dx.doi.org/10.1016/j.enbuild.2014.04.027 0378-7788/© 2014 Elsevier B.V. All rights reserved.
Air-conditioning (HVAC) energy consumption in buildings. A large number of research studies on PCM application in buildings have been carried out during the last 30 years which resulted in considerable amount of literature about PCM properties, PCM impregnation methods, locations of application and effect of PCM on thermal energy storage, indoor temperature, energy consumption and peak load shifting of buildings. PCM can be incorporated in wallboards, concretes, plaster, roof, underfloor and insulation of buildings [5–10]. From laboratory experiment, it was reported that the TES of the gypsum wallboard can be increased by ten times through the incorporation of PCM [11]. Oliver [12] observed that a 1.5 cm thick board of gypsum with PCM can store thermal energy equivalent to a 12 cm thick brick wall. Similar phenomenon was also observed by Kuznik et al. [13]. In case of concrete wall with PCM, 30% increase in TES was reported by Hawes et al. [14–16]. Hunger et al. [17] reported energy savings up to 12% through the inclusion of 5% microencapsulated PCM in selfcompacting concrete mix. From theoretical investigation, Neeper [18] indicated that the maximum diurnal energy storage occurred when the PCM melting temperature was close to the average comfort room temperature. After having studied PCM walls in the laboratory, several authors studied their performances in test rooms exposed to outdoor weather conditions. Athienitis et al. [19] observed 4 ◦ C decrease in
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maximum room temperature in Montreal using gypsum board with 25% butyl stearate PCM. Kissock et al. [20] observed a 10 ◦ C reduction in peak daytime temperature of Dayton, Ohio where wallboard imbibed with 30% commercial paraffinic PCM K18 was used. Shilei et al. [21] managed to decrease the room temperature by 1.02 ◦ C in the northeast of China by incorporating a mixture of capric and lauric acid into the wallboard. Chen et al. [22] showed that energy savings can get to 17% or higher if phase transition temperature and enthalpy is set at 23 ◦ C and 60 kJ/kg respectively during winter season in north China. Ahmed et al. [23] observed 20 ◦ C decrease in the indoor temperature amplitude of the test cell through the application of a composite wallboard with vacuum insulation panel and PCM during summer in France. In addition to wall, several studies were carried out by incorporating PCM in roof, floor and plaster of the test room [24–28] and reductions in room temperature fluctuation were observed. With the advent of more accurate computational method, numerical modelling is becoming increasingly popular to test the performance of PCM in buildings. In the numerical studies, the phase change effect has been taken into account through either enthalpy method [29–31] or heat capacity method [32–36]. Kuznik et al. [37] used building simulation software TRNSYS to simulate PCM wall where phase change process was taken into account through effective heat capacity method. The calculated internal wall surface temperature was found to be in good agreement with experimental data [38]. Heim et al. [39] modelled the behaviour of PCM in a three zone building using building simulation software ESP-r. Effect of phase transition was added to the energy equation through effective heat capacity method. Pederson et al. [40] used building simulation software EnergyPlus to simulate buildings with PCM wall in Minneapolis MN, USA. Effect of PCM was modelled through Enthalpy method in EnergyPlus. It was shown that the incorporation of PCM lowers the peak cooling load by 1000 W at that particular simulation environment. Using same software, Tardieu et al. [41] showed that PCM wallboards reduce the daily indoor temperature fluctuation by up to 4 ◦ C on typical summer day in Auckland. Recently, after extensive verification and validation study Tabares-Valesco et al. [42] showed that EnergyPlus can accurately predict the thermal performance of buildings with PCM if several guidelines are met. Hence, “EnergyPlus v7.2” has been adopted as the investigation tool in the present study. From the above literatures, it is evident that integration of PCM in building materials results in an increase in thermal energy storage of building which in turn reduces the indoor temperature fluctuation and energy consumptions of the buildings. It is also observed that efficiency of PCM depends on local climate, types of PCM, amount of PCM and location of application in buildings. The aim of the present study is to investigate the potential of PCM in reducing building energy consumptions and some parameters (i.e. PCM melting ranges, applied surface area, PCM layer thickness, local comfort range etc.) related to the effective application of PCM at different Australian cities. Finally, the potential effect of climate change on the effectiveness of PCM has been explored.
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Fig. 1. Single room house for the simulation.
2. Methodology 2.1. Building description A single room house was considered for the simulation as shown in Fig. 1. The house consisted of 2 zones: attic space and living area. The dimensions of the living area zone were 4 m × 4 m × 3 m (16 m2 floor area) with one south facing door and one window on each of the west and north wall. The size of each window was 1 m in vertical direction and 2.5 m in horizontal direction and was placed 1 m above the floor surface. Although it was a single room house, all the walls, roof and window materials were selected according to Australian standards. Total window area was 25% of the total floor area which complies with the range recommended by Building Codes of Australia (BCA) [43]. The thickness of windows are 3 mm with solar transmittance = 0.45, visible transmittance = 0.7 and conductivity = 0.9 W/m K. The size of the south facing door was 2 m × 0.8 m and is positioned at an offset of 0.5 m from the left edge. The roof was of hip type with 23 degree pitch on north and south sides and 45 degree pitch on the other two sides and has 0.5 m long eaves on all four sides. The thermophysical properties of all building materials are given in Table 1. The detail constructions of building walls, roof, ceiling and floors are presented in Table 2. The standards described in ICANZ [44] were followed in the constructions. The roof was constructed following the R0100 system-pithed tiled roof with flat ceiling and the external walls were constructed according to W0100 system-clay masonry veneer [44]. Ground level concrete slab was used as floor. Only the living area zone of the building was conditioned to maintain the desired comfort range. 2.2. Simulation details Simulations were carried out using building simulation software EnergyPlus v7.2 for eight different cities of Australia located in six different climate zones: Adelaide, Brisbane, Canberra,
Table 1 Thermophysical properties of building materials. Name
Thickness (m)
Conductivity (W/m K)
Density (kg/m3 )
Specific heat (J/kg K)
Resistance (m2 K/W)
Brick veneer Insulation wall (glass fibre batt) Insulation roof (glass fibre batt) Plasterboard Timber Carpet PCM
0.110 0.07 0.162 0.01 0.035 0.02 0.005
0.547 0.044 0.044 0.17 0.159 0.0465 0.2
1950 12 12 800 721 104 860
840 883 883 1090 1260 1420 1970
0.2 0.63 3.68 0.059 0.22 0.43 0.025
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Table 2 Construction of base case building. Name
Construction (outside to inside layer)
External wall Roof Ceiling Floor Door
Brick veneer, 40 mm air gap, insulation, wall plasterboard Roof tiles Roof insulation ceilings, PCM, plasterboard Concrete, carpet Timber
Table 3 Operating conditions. Parameters
Value
Time step Heating set point (◦ C) Cooling set point (◦ C) Adelaide Melbourne Hobart Canberra Sydney Brisbane Darwin Perth People (person/m2 ) Metabolic rate (W/person) Writing, seating, standing Cooking, cleaning Reading, relaxing Lighting (W/m2 ) Electric equipment (W/m2 )
3 min 20
Schedule HVAC operates from 7 am to 12 am everyday
25 24 23 24 25.5 25.5 26.5 25 0.0625 108 171 108 2.5 1.875
Fig. 2. Enthalpy–temperature graph of PCM 20.
7 am–6 pm 6 pm–8 pm 8 pm–10 pm 6 pm–10 pm 7 am–10 pm
Darwin, Hobart, Melbourne, Perth and Sydney. The standard IWEC weather files of these cities were used for the simulation. All the simulations were run for one year (8760 h) using conduction finite difference algorithm (ConFD) which provides the opportunity to simulate materials with variable properties such as PCM. Table 3 shows the main operating conditions of the simulations. Time step of the simulation was set to 3 min as recommended by TabaresValesco et al. [42]. The thermostat heating and cooling set points for different cities and HVAC schedules were set according to the Australian Building Codes board (ABCB) [45] assuming that the simulated zone is a living room of a house. The metabolic heat generation rates of the occupants were defined from Table 4, Chapter 9 of ASHRAE handbook [46]. The different metabolic heat generation rates represent different activities like seating, writing, cooking, cleaning house etc. The heating and cooling energy consumptions were calculated using ZoneHVAC:IdealLoadsAirSystem module of EnergyPlus [47] which is an ideal Variable Air Volume (VAV) terminal unit with variable supply temperature and humidity. The supply air flow rate varies between zero to maximum and supplies cooling or heating air to the zone in sufficient quantity to satisfy the zone heating and cooling load. The Ideal System was used here instead of any particular HVAC system because the aim of this study was to calculate the total energy requirement of a building under various
operating conditions. All of the building external surfaces were exposed to the outdoors environment except the floor which was in contact with ground. The heat transfer between the building floor and the ground were modelled using the GroundHeatTransfer:Slab module of the EnergyPlus software [47]. Infiltration in the conditioned zone was taken into account through Effective leakage area model available in the software. For each city, simulations were carried out using BioPCM material with six different melting ranges: 20PCM (18–22 ◦ C), 21PCM (19–23 ◦ C), 22PCM (20–24 ◦ C), 23PCM (21–25 ◦ C), 24PCM (22–26 ◦ C) and 25PCM (23–27 ◦ C). The latent heat of the BioPCM was 219 kJ/kg. Phase change was taken into account through enthalpy–temperature graph of BioPCM [48] as shown in Fig. 2. The enthalpy–temperature graphs for all other PCM were obtained by shifting the curve according to the PCM melting ranges. Although BioPCM is available in the form of square pouch, we have assumed it as a constant layer because the PCM module in EnergyPlus allows creation of the PCM material as a continuous layer rather than blocks. BioPCM pouches can be taken as a constant layer of BioPCM by following the procedure described in this thesis [48]. Each simulation was performed twice: (a) with and (b) without HVAC system. 3. Validation In the present study, the algorithm used in EnergyPlus and the performance of the PCM module was verified against the experimental data of Kuznick and Virgone [49]. The building geometry and operating conditions were selected according to the experimental study [49]. Fig. 3 shows that the simulated zone temperatures were in very good agreement with the experimental data with an average percentage of deviation of around 3% for both PCM and no PCM cases. The percentage of deviation is comparable with the study of Kuznik and Virgone [38] where 2.6% deviation was observed between the experimental results and Numerical model.
Table 4 Most efficient PCM at different cities of Australia for the studied house. City
Adelaide Brisbane Canberra Hobart Melbourne Perth Sydney
PCM
22 23 21 20 21 22 23
Energy consumed per conditioned floor area (MJ/m2 )
Annual energy savings (%) 2
No PCM
With PCM (5 mm PCM layer spread to a surface area of 16 m in ceiling)
366 430 481 394 411 422 329
280 357 391 306 332 336 254
23.5 17.1 18.7 22.4 19.3 20.5 22.9
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Fig. 4. Zone mean air temperature from 1st to 4th of April in Melbourne weather.
Fig. 3. Experimental and simulated zone temperature (a) without PCM and (b) with PCM.
Hence, the EnergyPlus PCM module can be used to analyse the thermal performance of studied house and benefits of PCM integration.
4. Results and discussions 4.1. Effect of PCM integration on zone temperature fluctuation Hourly zone temperature data for all cities under investigation were calculated first without including the HVAC system to see the effect of PCM on zone temperature fluctuations. Fig. 4 shows the zone mean air temperature with and without PCM for first 4 days of April in Melbourne. The figure shows that integration of PCM resulted in reduction of daytime zone temperature and increase of night time zone temperature and moved them closer to the comfort range which is 20–24 ◦ C for Melbourne. Here, PCM with 21 ◦ C melting point (melting range 19–23 ◦ C) was used. When the zone temperature reached the melting range, the PCM started to melt and stored energy as latent heat by changing phases from solid to liquid which in turn inhibited the rise in zone ambient temperature. At night time when the temperature fell below 21 ◦ C, the PCM started to solidify by discharging the stored heat and therefore resulted in an increase of zone ambient temperature. On average, the daytime zone temperature was reduced by 1.7 ◦ C and night time zone temperature was increased by 1.3 ◦ C during April in Melbourne through the incorporation of PCM. Moreover, Fig. 4 shows that integration of PCM also reduced the duration of zone temperature outside the comfort zone. For the 4 days shown here, the zone temperature was outside the comfort zone for 76 h without PCM whereas with PCM the duration was reduced to 56 h.
The summation of average daytime zone temperature decrease ‘a’ and average night time zone temperature increase ‘b’ in Fig. 4 is termed as average temperature fluctuation reduction (ATFR) in this paper. Fig. 5 shows the monthly ATFR values for different cities of Australia. The figure shows that PCM worked effectively in different cities in different times of the year. In cool temperate zone like Canberra, Melbourne and Hobart, PCM was effective largely during September to April with 3–4 ◦ C reduction in average temperature fluctuation. This occurred because in these periods, the local climate is favourable for regular charging and discharging of PCM. During May to August, the zone temperature in daytime is not warm enough to melt the PCM. As a result, the values of ATFR were less than 1 ◦ C during this period which means PCM was mostly inactive in this period. In mild temperate zone like Adelaide, PCM worked better during March to May (autumn) and September to November (spring). In warm temperate zone like Brisbane, Perth and Sydney, PCM was effective mostly from April to October with ATFR value reaching up to 3.5 ◦ C. In these cities, the outdoor temperature does not drop enough to solidify the PCM during November to March. As a result, the PCM remained in liquid state most of this time period and the effectiveness of PCM was reduced as evident from low values of ATFR which were less than 1.5 ◦ C. In Darwin, the effect of PCM on zone temperature was very little as shown in Fig. 5. The ATFR value crossed 1 ◦ C only for three months during winter in case of 26 and 27 PCM but for all other PCM used the ATFR values were less than 1 ◦ C throughout the year. This occurred due to the hot humid summer and warm winter in Darwin where temperature does not drop enough throughout the year to solidify the PCM. The PCM 26 and 27 reduced the temperature fluctuation a little during winter period when the outside temperature drops enough to solidify these two PCM. Finally, Fig. 5 shows that in all cities, effectiveness of different melting point PCM were different at different times of the year. For example, in Canberra, PCM 25 was most effective from December to March, PCM 23 in April, PCM 20 during May to October and PCM 24 in November. Similarly, in Perth, PCM 25 was most effective from November to April, PCM 22 in May and September, PCM 20 during June to August and PCM 24 during in October. In general, higher melting point PCM resulted in higher ATFR values during summer in contrast with lower melting point PCM which were most effective during winter period. Hence, it can be concluded from above discussion that effectiveness of PCM is strongly dependent on local weather and none of the PCM is equally effective throughout the year. Generally, PCM with higher melting point will be more effective in warm temperate climate zone and PCM with lower melting point will perform better in cold temperate climate zone.
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Fig. 5. (a)–(f) Average temperature fluctuation reduction with PCM in different Australian cities.
4.2. Effect of PCM on annual energy consumption All the simulations that were carried out in Section 4.1 were repeated including the HVAC system to calculate the corresponding energy consumptions. From Figs. 5 and 6, it is evident that the percentages of energy consumption reduction are closely related with ATFR values. The percentage of average consumption energy reductions were calculated using the following formula: % of energy consumption reductions =
In all cities, percentages of energy saving were higher at higher ATFR values. Integration of PCM resulted in greater energy savings during summer in cool temperate zone and during winter in warm temperate zone due to corresponding ATFR values as described in the Section 4.1. Similar to the trend of ATFR values, high melting point PCM worked better during the summer and the low melting point PCM worked better during the winter period in Australian cities. For example, in January at Perth, the PCM 25 reduced the
Energy consumption without PCM − Energy consumption with PCM × 100 Energy consumption without PCM
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Fig. 6. (a)–(f) Energy consumption reductions with PCM in different Australian cities.
temperature fluctuation by 1.75 ◦ C and resulted in about 9% reduction in energy consumption which was the highest in the month of January. In June, the 20 PCM was the most efficient with 3.4 ◦ C decrease in temperature fluctuations and 56% reduction in corresponding energy consumption. However, in Melbourne, the PCM 25 resulted in higher ATFR values during January to March but the corresponding percentage of energy consumption reduction was the lowest among the PCM’s used. This occurred due to the thermostat set point range of
Melbourne. Table 3 shows the thermostat heating and cooling set point for a residential living space at different cities of Australia according to ABCB [48]. The thermostat heating and cooling set point in Melbourne is 20 ◦ C and 24 ◦ C respectively. The PCM 25 is outside the range of thermostat. When the zone temperature was over 25 ◦ C, the PCM 25 was in liquid phase. As the cooling thermostat set point is 24 ◦ C, cooling energy was required to bring the zone temperature down to 24 ◦ C. The liquid 25 PCM had to be solidified in order to bring down the zone temperature to 24 ◦ C which, in turn,
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Table 5 Energy savings for different locations of PCM with constant volume of 0.08 m3 (Results shown for Sydney weather). Location
PCM surface area (m2 )
Thickness of PCM layer (mm)
Annual energy consumption (GJ)
Annual energy savings (%)
No PCM Roof East wall North wall West wall South wall North wall and roof West wall and roof South wall and roof East wall and roof All wall All wall and roof
0 16 12 9.5 9.5 10.4 25.5 25.5 26.4 28 41.4 57.4
0 5 6.7 8.42 8.42 7.7 3.14 3.14 3.03 2.86 2 1.25
5.28 4.07 4.30 4.43 4.48 4.42 3.85 3.89 3.87 3.83 3.72 3.75
0 22.9 18.5 16.1 15.22 16.28 27 26.4 26.75 27.5 29.6 29
resulted in consumption of extra energy and lower efficiency in case of 25 PCM. Similar scenario was also observed in case of Hobart and Canberra. In Hobart, the thermostat range is 20–23 ◦ C. Both the PCM 24 and PCM 25 had higher ATFR values compared with the PCM 20 and PCM 21 but the corresponding energy consumption reduction was the lowest. It can be concluded from the above discussion that selection of a PCM melting range depends on local thermostat set points along with local climate. Higher value of ATFR does not always mean higher energy savings. In addition to that it was also observed that an optimum PCM melting range for highest energy savings at each month of the year is far from unique because different melting point PCM was most efficient at different times of the year. The PCM melting range which provides lowest annual energy consumption for a particular city should be selected. In the present study, the most efficient PCMs at different cities of Australia for the studied house have been identified in terms of highest annual energy savings which are presented in Table 4. The result for Darwin is not presented in Table 4 as it was explained in Section 4.1 that integration of PCM has very little effect in Darwin climate. Further study is required on how to use PCM effectively in hot and humid climate zones like Darwin. 4.3. Effect of PCM surface area and thickness on energy consumption In the previous section, efficacy of PCMs with different melting ranges was investigated by applying a 5 mm layer of PCM on the
ceiling of the house as shown in Table 2. In this section, potential energy savings depending on different surface area, thickness and positions of PCM integration in building have been investigated. The locations of PCM integration are presented in Table 5. To compare the energy savings potential of different combination, total volume of PCM was kept constant throughout the study. Thickness of the PCM layer in each combination was calculated by dividing the PCM volume by the surface area of the applied location. Table 5 shows that percentage of energy savings increased with the increase of surface area and decrease of PCM layer thickness. This was expected because an increase in surface area resulted in an increase of heat transfer rate between PCM and the zone. In addition, as the volume of PCM was constant, an increase in surface area also led to a thinner layer PCM. Consequently, the possibility of effectively charging (melting) and discharging (solidification) of PCM during diurnal temperature variations was increased because the thicker the PCM layer, the lesser is the possibility of effective charging and discharging due to low thermal conductivity of PCM (0.2 W/m K) which increases the time required to melt the PCM completely. If the melting time is not low enough, portion of PCM may remain in solid phase during the daytime charging period. Therefore, the full capacity of PCM was not utilised in case of thicker PCM layer and percentage of energy savings potential decreased. However, Table 5 also shows that percentage of energy saving was maximum in case of “all wall” where the applied PCM surface area was 41.4 m2 and then decreased in spite of an increase in surface area (57.4 m2 ) by incorporating PCM in “all wall and roof”. This occurred due to the thickness of PCM layer in those two
Fig. 7. PCM layer temperatures for different PCM integration combinations (The 23 PCM and Sydney weather was used in the simulation).
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Fig. 9. Thermal zones of single storey house [50].
surface area was smaller for the latter case. Finally, Table 5 shows that energy saving potential for “north wall” case was higher than that of “west wall” case although the surface area and PCM layer thickness were equal in both cases. Similar phenomenon was also observed for “north wall and roof” and “west wall and roof”. The reason might be the variation in the amount of solar radiation received by these surfaces. Study is ongoing to understand this phenomenon. 4.4. Effect of climate change on PCM efficiency
Fig. 8. Effect of climate change on PCM energy saving efficiency.
combinations and is explained with the help of Fig. 7. The temperature of PCM layer for four different cases in Sydney weather has been presented in Fig. 7. The PCM 23 was used in each case. The PCM layer thickness for each case is mentioned in Table 5. The PCM layer in case of “east wall” was the thickest among the four cases plotted in Fig. 7. The maximum PCM layer temperature in case of “east wall” during charging was within the melting range of PCM which suggest that PCM was not completely melted. Hence, the corresponding percentage of energy saving was the lowest as explained earlier this section. In case of “east wall and roof”, PCM was relatively thinner compared with east wall. The PCM layer temperature was increased but still within the melting range of 23 PCM. Thus, the PCM was not completely melted but the fraction of molten phase was higher than the east wall case which, in turn, resulted in higher energy saving potential compared with “east wall” case. The temperature of PCM layer in case of “all wall” reached 25 ◦ C during daytime which illustrates that the thickness of PCM layer in case of “all wall” were thin enough to achieve complete melting of PCM. Consequently, the energy saving potential of the “all wall” increased compared with the previous two cases. However, if the thickness of PCM layer is below certain limit, the temperature of the PCM layer rises quickly during daytime due to shorter melting period which was the situation for “all wall and roof” case where the PCM layer thickness was 1.25 mm. The PCM was completely melted within a short period time in case of “all wall and roof” and the temperature of the PCM layer rose sharply after phase transition as shown in Fig. 7. As a result, the thin layer of PCM in this case could not hold the zone temperature inside the comfort zone (20–25 ◦ C for Sydney) for longer period of time and extra energy was required to bring down the temperature to comfort zone which, in turn, resulted in lower energy saving potential compared to “all wall” case although
The sections above have demonstrated that the efficiency of PCM highly dependent on local climate. Wang et al. [50] reported a 2.3 ◦ C increase (A1FI emission scenario) in average temperature of Australia by 2050 with warming of around 2.3–3.36 ◦ C in inland and 1.32–2.3 ◦ C in coastal areas due to the greenhouse effect. Therefore, in this section, the effect of climate change by 2050 on the efficiency of PCM has been investigated for two cities: Melbourne and Sydney. The weather data files for the year 2050 were composed from the study of Wang et al. [50]. The projected energy consumption reduction through the application of PCM using present and 2050 weather data files are presented in Fig. 8. In case of Melbourne and Sydney, PCM 21 and PCM 23 were used respectively because they resulted in highest energy consumption reduction for these two cities at present weather as reported in Table 4. The figure shows that in Melbourne, the effectiveness of PCM will increase during May to October and decrease during November to April due to global warming. The projected percentage of annual energy consumption reduction in 2050 is around 19.2% which is similar to the calculated present value of 19.3% as reported in Table 4. On the other hand, in Sydney, PCM effectiveness is predicted to increase during June to August and decrease during September. The projected percentage of annual energy consumption reduction in 2050 will be around 12.4% which is almost half of the present value of 22.9%. Hence, it is observed that global warming will have negligible effect on the annual energy saving efficiency of PCM in Melbourne but will significantly influence the effectiveness of PCM in Sydney. However, other PCM melting point whose efficiency is lower at present weather might become the highest by 2050. Investigation is underway on this subject and will be reported in detail in our future article. It should be noted that the local comfort range may also change by 2050 which will also influence the PCM effectiveness as discussed in Section 4.2. However, in the present study, the same thermostat settings, as presented in Table 3, were used for the year 2050 due to the lack of available guidelines regarding thermal comfort range for 2050.
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factors on the effectiveness of PCM have been investigated using building simulation software EnergyPlus. Five different melting ranges PCM have been used to identify the optimum PCM melting range for each city. From the present investigation, following preliminary conclusions have been reached:
Fig. 10. Energy saving potential of PCM in both the single room house and typical house.
4.5. Comparison with a typical house A modern typical single storey Australian house was modelled with and without PCM to investigate the PCM effectiveness. The floor area of the house is 232 m2 and has a five star energy rating according to NatHERS (Nationwide house energy rating system) energy rating system. NatHERS is an Australian house energy rating scheme that rates the potential energy efficiency of Australian homes in a scale of 0–10 stars. Fig. 9 shows the different thermal zones of the house. The construction details of the house can be found in this paper [50]. Simulations were carried out for Melbourne and Sydney weather using five different PCM mentioned in Section 2.2. Similar to single room house of Section 2.2, a 5 mm layer of PCM was applied in the ceilings of the real house. The energy saving potential of PCM with different melting point has been presented in Fig. 10 for both cases. The figure shows that in both the single room house and real house, 21 PCM and 23 PCM resulted in highest energy savings among the PCM used for Melbourne and Sydney respectively. Hence, it can be said that the single room model can be used to decide which PCM will result in highest energy savings at a particular climate. However, Fig. 10 shows that actual percentage of energy savings was different for the single room house and real house in both climates. It was expected because each house has different internal thermal condition depending on size, axis orientation, location, number of windows, types of window glass, wall and roof materials and consequently, energy requirements will be different. Therefore, the simulation results regarding percentage of energy reduction at a particular climate region is not applicable for every house in that region. But the effect of PCM on energy consumptions will follow similar trend as shown in Fig. 10. As our primary goal of this study was to find out suitable PCM melting range for different climate region and investigate how different factors influence the performance of PCM in reducing energy consumption, a single room house was considered for the simulation rather than a real house which also results in lower simulation time. Although the 21 PCM and 23 PCM was found to be the most efficient PCM in Melbourne and Sydney region, its efficiency for the studied real house was only 3.3% and 10.3% respectively which can be increased by placing the PCM at different configurations descried in Section 4.3. 5. Conclusions The potential of PCM in reducing the building energy consumption at different climate zones of Australia and influence of several
• PCM has the potential to reduce the building energy consumption in Australian cities under cold temperate, mild temperate and warm temperate zones. The integration of PCM has very minor effect on the energy consumption of houses which are in hot and humid climate zone. • Effectiveness of a PCM depends on local climate, thermostat range, PCM layer thickness, surface area and location of application in buildings. • An optimum PCM melting range for lowest energy consumption in each month of the year is far from unique. Lowest annual energy consumption may be used as a criterion for the selection of PCM for a particular city. • Comparison between a real house and a single room house demonstrated that the optimum PCM temperature is the same for both however the percentage PCM required is different. Hence, for the purposes of calculating optimum PCM temperature, single room house simulation can be used. • 21 PCM is the most efficient PCM for Melbourne and Canberra. For Perth and Adelaide, 22 PCM is the most efficient. For Brisbane and Sydney, 23 PCM is the most efficient PCM. Finally, 20 PCM is most effective for Hobart region. • PCM with melting point outside the comfort range does not provide efficient energy reductions irrespective of large reduction in temperature fluctuations. • At constant volume, effectiveness of PCM increases with increasing surface area until an optimum level beyond which further increase in surface area reduces the energy saving potential of PCM. • Climate change will have an adverse influence on the energy saving potential of PCM which are optimised for current climate. Future research needs to include more detailed analysis on how to utilise PCM more effectively in Australian buildings under different climate zones. Use of night ventilation during summer needs to be investigated as it was reported by Cabeza et al. [51] that the night ventilation is very important to achieve full PCM cycle during summer. The positions of PCM layer in the external and internal wall of a building can be varied to examine the effect on the effectiveness of PCM. Finally, the impacts of PCM in cutting down the greenhouse gas emission need to be investigated. Acknowledgements Authors wish to acknowledge the “Climate Adaptation Technology and Engineering for Extreme Events” funded by CSIRO climate adaptation flagship for supporting this project. References [1] ABS, Year Book Australia, vol. 92, Australian Bureau of Statistics, Canberra, 2012, pp. 600. [2] ABARES, Energy in Australia, Australian Bureau of Agricultural and Resource Economics and Sciences, Canberra, 2011. [3] X. Wang, D. Chen, Z. Ren, Global warming and its implication to emission reduction strategies for residential buildings, Building and Environment 46 (2011) 871–883. [4] H.G. Lorsch, K.W. Kauffman, J.C. Denton, Thermal energy storage for solar heating and off-peak air conditioning, Energy Conversion 15 (1975) 1–8. [5] E. Rodriguez-Ubinas, et al., Applications of phase change material in highly energy-efficient houses, Energy and Buildings 50 (2012) 49–62. [6] A.M. Khudhair, M.M. Farid, A review on energy conservation in building applications with thermal storage by latent heat using phase change materials, Energy Conversion and Management 45 (2004) 263–275.
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Contents lists available at ScienceDirect
Energy and Buildings journal homepage: www.elsevier.com/locate/enbuild
Energy saving potential of phase change materials in major Australian cities Morshed Alam ∗ , Hasnat Jamil, Jay Sanjayan, John Wilson Centre for Sustainable Infrastructure, Faculty of Science Engineering and Technology, Swinburne University of Technology, Hawthorn, Victoria 3122, Australia
a r t i c l e
i n f o
Article history: Received 26 November 2013 Received in revised form 17 April 2014 Accepted 21 April 2014 Available online 16 May 2014 Keywords: Phase change materials PCM Building energy modelling EnergyPlus Thermal energy storage Energy savings
a b s t r a c t The potential of phase change materials (PCM) in reducing the heating/cooling energy consumption of residential houses along with several factors influencing the effectiveness of PCM were investigated using EnergyPlus. Simulations were carried out using five different phase change temperature ranges at eight Australian cities which represent six climate zones. It was found that the effectiveness of PCM strongly depends on local weather, thermostat range, PCM layer thickness and surface area. The optimum PCM melting range for lowest energy consumption in each month of the year was found to be far from unique. Different PCM was found to be effective in different times of the year. Depending on local weather, the integration of PCM resulted in 17–23% annual energy savings in the studied house except hot and humid cities like Darwin. For a given amount of PCM, energy saving potential was found to improve further with the increase of applied surface area and decrease of PCM layer thickness up to certain limit beyond which the potential started to decline. The energy saving potential was also found to decrease when the PCM melting point was outside the thermostat range of the corresponding city. The paper also presented the potential effect of climate change on the effectiveness of PCM. © 2014 Elsevier B.V. All rights reserved.
1. Introduction The fast economic development around the globe and high standards of living imposes an ever increasing demand for energy. Over the period 1979–1980 to 2009–2010, there was a 90% increase in Australia’s total energy use, from 3131 PJ to 5925 PJ [1]. Approximately, 95% of Australia’s total energy consumption comes from fossil fuels (coal, oil and gas) [2] which results in harmful greenhouse gas emissions. In 2009–2010, the energy consumption of residential building was around 25% of total energy consumptions and contributed around 13% of total Australia national greenhouse gas emission [1,3]. In recent years, Latent Thermal Energy Storage (LTES) systems in buildings have received serious attention for reducing the dependency on fossil fuels and contributing to a more efficient environmentally benign energy use. Latent heat storage materials, also known as phase change materials (PCM’s), absorb or release the energy equivalent to their latent heat when the temperature of the material undergoes or overpasses the phase change temperature [4]. PCM represent a technology that has the potential to shift peak load and reduce Heating Ventilation and
∗ Corresponding author. Tel.: +61 3 92145463. E-mail addresses: [email protected], [email protected] (M. Alam). http://dx.doi.org/10.1016/j.enbuild.2014.04.027 0378-7788/© 2014 Elsevier B.V. All rights reserved.
Air-conditioning (HVAC) energy consumption in buildings. A large number of research studies on PCM application in buildings have been carried out during the last 30 years which resulted in considerable amount of literature about PCM properties, PCM impregnation methods, locations of application and effect of PCM on thermal energy storage, indoor temperature, energy consumption and peak load shifting of buildings. PCM can be incorporated in wallboards, concretes, plaster, roof, underfloor and insulation of buildings [5–10]. From laboratory experiment, it was reported that the TES of the gypsum wallboard can be increased by ten times through the incorporation of PCM [11]. Oliver [12] observed that a 1.5 cm thick board of gypsum with PCM can store thermal energy equivalent to a 12 cm thick brick wall. Similar phenomenon was also observed by Kuznik et al. [13]. In case of concrete wall with PCM, 30% increase in TES was reported by Hawes et al. [14–16]. Hunger et al. [17] reported energy savings up to 12% through the inclusion of 5% microencapsulated PCM in selfcompacting concrete mix. From theoretical investigation, Neeper [18] indicated that the maximum diurnal energy storage occurred when the PCM melting temperature was close to the average comfort room temperature. After having studied PCM walls in the laboratory, several authors studied their performances in test rooms exposed to outdoor weather conditions. Athienitis et al. [19] observed 4 ◦ C decrease in
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maximum room temperature in Montreal using gypsum board with 25% butyl stearate PCM. Kissock et al. [20] observed a 10 ◦ C reduction in peak daytime temperature of Dayton, Ohio where wallboard imbibed with 30% commercial paraffinic PCM K18 was used. Shilei et al. [21] managed to decrease the room temperature by 1.02 ◦ C in the northeast of China by incorporating a mixture of capric and lauric acid into the wallboard. Chen et al. [22] showed that energy savings can get to 17% or higher if phase transition temperature and enthalpy is set at 23 ◦ C and 60 kJ/kg respectively during winter season in north China. Ahmed et al. [23] observed 20 ◦ C decrease in the indoor temperature amplitude of the test cell through the application of a composite wallboard with vacuum insulation panel and PCM during summer in France. In addition to wall, several studies were carried out by incorporating PCM in roof, floor and plaster of the test room [24–28] and reductions in room temperature fluctuation were observed. With the advent of more accurate computational method, numerical modelling is becoming increasingly popular to test the performance of PCM in buildings. In the numerical studies, the phase change effect has been taken into account through either enthalpy method [29–31] or heat capacity method [32–36]. Kuznik et al. [37] used building simulation software TRNSYS to simulate PCM wall where phase change process was taken into account through effective heat capacity method. The calculated internal wall surface temperature was found to be in good agreement with experimental data [38]. Heim et al. [39] modelled the behaviour of PCM in a three zone building using building simulation software ESP-r. Effect of phase transition was added to the energy equation through effective heat capacity method. Pederson et al. [40] used building simulation software EnergyPlus to simulate buildings with PCM wall in Minneapolis MN, USA. Effect of PCM was modelled through Enthalpy method in EnergyPlus. It was shown that the incorporation of PCM lowers the peak cooling load by 1000 W at that particular simulation environment. Using same software, Tardieu et al. [41] showed that PCM wallboards reduce the daily indoor temperature fluctuation by up to 4 ◦ C on typical summer day in Auckland. Recently, after extensive verification and validation study Tabares-Valesco et al. [42] showed that EnergyPlus can accurately predict the thermal performance of buildings with PCM if several guidelines are met. Hence, “EnergyPlus v7.2” has been adopted as the investigation tool in the present study. From the above literatures, it is evident that integration of PCM in building materials results in an increase in thermal energy storage of building which in turn reduces the indoor temperature fluctuation and energy consumptions of the buildings. It is also observed that efficiency of PCM depends on local climate, types of PCM, amount of PCM and location of application in buildings. The aim of the present study is to investigate the potential of PCM in reducing building energy consumptions and some parameters (i.e. PCM melting ranges, applied surface area, PCM layer thickness, local comfort range etc.) related to the effective application of PCM at different Australian cities. Finally, the potential effect of climate change on the effectiveness of PCM has been explored.
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Fig. 1. Single room house for the simulation.
2. Methodology 2.1. Building description A single room house was considered for the simulation as shown in Fig. 1. The house consisted of 2 zones: attic space and living area. The dimensions of the living area zone were 4 m × 4 m × 3 m (16 m2 floor area) with one south facing door and one window on each of the west and north wall. The size of each window was 1 m in vertical direction and 2.5 m in horizontal direction and was placed 1 m above the floor surface. Although it was a single room house, all the walls, roof and window materials were selected according to Australian standards. Total window area was 25% of the total floor area which complies with the range recommended by Building Codes of Australia (BCA) [43]. The thickness of windows are 3 mm with solar transmittance = 0.45, visible transmittance = 0.7 and conductivity = 0.9 W/m K. The size of the south facing door was 2 m × 0.8 m and is positioned at an offset of 0.5 m from the left edge. The roof was of hip type with 23 degree pitch on north and south sides and 45 degree pitch on the other two sides and has 0.5 m long eaves on all four sides. The thermophysical properties of all building materials are given in Table 1. The detail constructions of building walls, roof, ceiling and floors are presented in Table 2. The standards described in ICANZ [44] were followed in the constructions. The roof was constructed following the R0100 system-pithed tiled roof with flat ceiling and the external walls were constructed according to W0100 system-clay masonry veneer [44]. Ground level concrete slab was used as floor. Only the living area zone of the building was conditioned to maintain the desired comfort range. 2.2. Simulation details Simulations were carried out using building simulation software EnergyPlus v7.2 for eight different cities of Australia located in six different climate zones: Adelaide, Brisbane, Canberra,
Table 1 Thermophysical properties of building materials. Name
Thickness (m)
Conductivity (W/m K)
Density (kg/m3 )
Specific heat (J/kg K)
Resistance (m2 K/W)
Brick veneer Insulation wall (glass fibre batt) Insulation roof (glass fibre batt) Plasterboard Timber Carpet PCM
0.110 0.07 0.162 0.01 0.035 0.02 0.005
0.547 0.044 0.044 0.17 0.159 0.0465 0.2
1950 12 12 800 721 104 860
840 883 883 1090 1260 1420 1970
0.2 0.63 3.68 0.059 0.22 0.43 0.025
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Table 2 Construction of base case building. Name
Construction (outside to inside layer)
External wall Roof Ceiling Floor Door
Brick veneer, 40 mm air gap, insulation, wall plasterboard Roof tiles Roof insulation ceilings, PCM, plasterboard Concrete, carpet Timber
Table 3 Operating conditions. Parameters
Value
Time step Heating set point (◦ C) Cooling set point (◦ C) Adelaide Melbourne Hobart Canberra Sydney Brisbane Darwin Perth People (person/m2 ) Metabolic rate (W/person) Writing, seating, standing Cooking, cleaning Reading, relaxing Lighting (W/m2 ) Electric equipment (W/m2 )
3 min 20
Schedule HVAC operates from 7 am to 12 am everyday
25 24 23 24 25.5 25.5 26.5 25 0.0625 108 171 108 2.5 1.875
Fig. 2. Enthalpy–temperature graph of PCM 20.
7 am–6 pm 6 pm–8 pm 8 pm–10 pm 6 pm–10 pm 7 am–10 pm
Darwin, Hobart, Melbourne, Perth and Sydney. The standard IWEC weather files of these cities were used for the simulation. All the simulations were run for one year (8760 h) using conduction finite difference algorithm (ConFD) which provides the opportunity to simulate materials with variable properties such as PCM. Table 3 shows the main operating conditions of the simulations. Time step of the simulation was set to 3 min as recommended by TabaresValesco et al. [42]. The thermostat heating and cooling set points for different cities and HVAC schedules were set according to the Australian Building Codes board (ABCB) [45] assuming that the simulated zone is a living room of a house. The metabolic heat generation rates of the occupants were defined from Table 4, Chapter 9 of ASHRAE handbook [46]. The different metabolic heat generation rates represent different activities like seating, writing, cooking, cleaning house etc. The heating and cooling energy consumptions were calculated using ZoneHVAC:IdealLoadsAirSystem module of EnergyPlus [47] which is an ideal Variable Air Volume (VAV) terminal unit with variable supply temperature and humidity. The supply air flow rate varies between zero to maximum and supplies cooling or heating air to the zone in sufficient quantity to satisfy the zone heating and cooling load. The Ideal System was used here instead of any particular HVAC system because the aim of this study was to calculate the total energy requirement of a building under various
operating conditions. All of the building external surfaces were exposed to the outdoors environment except the floor which was in contact with ground. The heat transfer between the building floor and the ground were modelled using the GroundHeatTransfer:Slab module of the EnergyPlus software [47]. Infiltration in the conditioned zone was taken into account through Effective leakage area model available in the software. For each city, simulations were carried out using BioPCM material with six different melting ranges: 20PCM (18–22 ◦ C), 21PCM (19–23 ◦ C), 22PCM (20–24 ◦ C), 23PCM (21–25 ◦ C), 24PCM (22–26 ◦ C) and 25PCM (23–27 ◦ C). The latent heat of the BioPCM was 219 kJ/kg. Phase change was taken into account through enthalpy–temperature graph of BioPCM [48] as shown in Fig. 2. The enthalpy–temperature graphs for all other PCM were obtained by shifting the curve according to the PCM melting ranges. Although BioPCM is available in the form of square pouch, we have assumed it as a constant layer because the PCM module in EnergyPlus allows creation of the PCM material as a continuous layer rather than blocks. BioPCM pouches can be taken as a constant layer of BioPCM by following the procedure described in this thesis [48]. Each simulation was performed twice: (a) with and (b) without HVAC system. 3. Validation In the present study, the algorithm used in EnergyPlus and the performance of the PCM module was verified against the experimental data of Kuznick and Virgone [49]. The building geometry and operating conditions were selected according to the experimental study [49]. Fig. 3 shows that the simulated zone temperatures were in very good agreement with the experimental data with an average percentage of deviation of around 3% for both PCM and no PCM cases. The percentage of deviation is comparable with the study of Kuznik and Virgone [38] where 2.6% deviation was observed between the experimental results and Numerical model.
Table 4 Most efficient PCM at different cities of Australia for the studied house. City
Adelaide Brisbane Canberra Hobart Melbourne Perth Sydney
PCM
22 23 21 20 21 22 23
Energy consumed per conditioned floor area (MJ/m2 )
Annual energy savings (%) 2
No PCM
With PCM (5 mm PCM layer spread to a surface area of 16 m in ceiling)
366 430 481 394 411 422 329
280 357 391 306 332 336 254
23.5 17.1 18.7 22.4 19.3 20.5 22.9
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Fig. 4. Zone mean air temperature from 1st to 4th of April in Melbourne weather.
Fig. 3. Experimental and simulated zone temperature (a) without PCM and (b) with PCM.
Hence, the EnergyPlus PCM module can be used to analyse the thermal performance of studied house and benefits of PCM integration.
4. Results and discussions 4.1. Effect of PCM integration on zone temperature fluctuation Hourly zone temperature data for all cities under investigation were calculated first without including the HVAC system to see the effect of PCM on zone temperature fluctuations. Fig. 4 shows the zone mean air temperature with and without PCM for first 4 days of April in Melbourne. The figure shows that integration of PCM resulted in reduction of daytime zone temperature and increase of night time zone temperature and moved them closer to the comfort range which is 20–24 ◦ C for Melbourne. Here, PCM with 21 ◦ C melting point (melting range 19–23 ◦ C) was used. When the zone temperature reached the melting range, the PCM started to melt and stored energy as latent heat by changing phases from solid to liquid which in turn inhibited the rise in zone ambient temperature. At night time when the temperature fell below 21 ◦ C, the PCM started to solidify by discharging the stored heat and therefore resulted in an increase of zone ambient temperature. On average, the daytime zone temperature was reduced by 1.7 ◦ C and night time zone temperature was increased by 1.3 ◦ C during April in Melbourne through the incorporation of PCM. Moreover, Fig. 4 shows that integration of PCM also reduced the duration of zone temperature outside the comfort zone. For the 4 days shown here, the zone temperature was outside the comfort zone for 76 h without PCM whereas with PCM the duration was reduced to 56 h.
The summation of average daytime zone temperature decrease ‘a’ and average night time zone temperature increase ‘b’ in Fig. 4 is termed as average temperature fluctuation reduction (ATFR) in this paper. Fig. 5 shows the monthly ATFR values for different cities of Australia. The figure shows that PCM worked effectively in different cities in different times of the year. In cool temperate zone like Canberra, Melbourne and Hobart, PCM was effective largely during September to April with 3–4 ◦ C reduction in average temperature fluctuation. This occurred because in these periods, the local climate is favourable for regular charging and discharging of PCM. During May to August, the zone temperature in daytime is not warm enough to melt the PCM. As a result, the values of ATFR were less than 1 ◦ C during this period which means PCM was mostly inactive in this period. In mild temperate zone like Adelaide, PCM worked better during March to May (autumn) and September to November (spring). In warm temperate zone like Brisbane, Perth and Sydney, PCM was effective mostly from April to October with ATFR value reaching up to 3.5 ◦ C. In these cities, the outdoor temperature does not drop enough to solidify the PCM during November to March. As a result, the PCM remained in liquid state most of this time period and the effectiveness of PCM was reduced as evident from low values of ATFR which were less than 1.5 ◦ C. In Darwin, the effect of PCM on zone temperature was very little as shown in Fig. 5. The ATFR value crossed 1 ◦ C only for three months during winter in case of 26 and 27 PCM but for all other PCM used the ATFR values were less than 1 ◦ C throughout the year. This occurred due to the hot humid summer and warm winter in Darwin where temperature does not drop enough throughout the year to solidify the PCM. The PCM 26 and 27 reduced the temperature fluctuation a little during winter period when the outside temperature drops enough to solidify these two PCM. Finally, Fig. 5 shows that in all cities, effectiveness of different melting point PCM were different at different times of the year. For example, in Canberra, PCM 25 was most effective from December to March, PCM 23 in April, PCM 20 during May to October and PCM 24 in November. Similarly, in Perth, PCM 25 was most effective from November to April, PCM 22 in May and September, PCM 20 during June to August and PCM 24 during in October. In general, higher melting point PCM resulted in higher ATFR values during summer in contrast with lower melting point PCM which were most effective during winter period. Hence, it can be concluded from above discussion that effectiveness of PCM is strongly dependent on local weather and none of the PCM is equally effective throughout the year. Generally, PCM with higher melting point will be more effective in warm temperate climate zone and PCM with lower melting point will perform better in cold temperate climate zone.
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Fig. 5. (a)–(f) Average temperature fluctuation reduction with PCM in different Australian cities.
4.2. Effect of PCM on annual energy consumption All the simulations that were carried out in Section 4.1 were repeated including the HVAC system to calculate the corresponding energy consumptions. From Figs. 5 and 6, it is evident that the percentages of energy consumption reduction are closely related with ATFR values. The percentage of average consumption energy reductions were calculated using the following formula: % of energy consumption reductions =
In all cities, percentages of energy saving were higher at higher ATFR values. Integration of PCM resulted in greater energy savings during summer in cool temperate zone and during winter in warm temperate zone due to corresponding ATFR values as described in the Section 4.1. Similar to the trend of ATFR values, high melting point PCM worked better during the summer and the low melting point PCM worked better during the winter period in Australian cities. For example, in January at Perth, the PCM 25 reduced the
Energy consumption without PCM − Energy consumption with PCM × 100 Energy consumption without PCM
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Fig. 6. (a)–(f) Energy consumption reductions with PCM in different Australian cities.
temperature fluctuation by 1.75 ◦ C and resulted in about 9% reduction in energy consumption which was the highest in the month of January. In June, the 20 PCM was the most efficient with 3.4 ◦ C decrease in temperature fluctuations and 56% reduction in corresponding energy consumption. However, in Melbourne, the PCM 25 resulted in higher ATFR values during January to March but the corresponding percentage of energy consumption reduction was the lowest among the PCM’s used. This occurred due to the thermostat set point range of
Melbourne. Table 3 shows the thermostat heating and cooling set point for a residential living space at different cities of Australia according to ABCB [48]. The thermostat heating and cooling set point in Melbourne is 20 ◦ C and 24 ◦ C respectively. The PCM 25 is outside the range of thermostat. When the zone temperature was over 25 ◦ C, the PCM 25 was in liquid phase. As the cooling thermostat set point is 24 ◦ C, cooling energy was required to bring the zone temperature down to 24 ◦ C. The liquid 25 PCM had to be solidified in order to bring down the zone temperature to 24 ◦ C which, in turn,
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Table 5 Energy savings for different locations of PCM with constant volume of 0.08 m3 (Results shown for Sydney weather). Location
PCM surface area (m2 )
Thickness of PCM layer (mm)
Annual energy consumption (GJ)
Annual energy savings (%)
No PCM Roof East wall North wall West wall South wall North wall and roof West wall and roof South wall and roof East wall and roof All wall All wall and roof
0 16 12 9.5 9.5 10.4 25.5 25.5 26.4 28 41.4 57.4
0 5 6.7 8.42 8.42 7.7 3.14 3.14 3.03 2.86 2 1.25
5.28 4.07 4.30 4.43 4.48 4.42 3.85 3.89 3.87 3.83 3.72 3.75
0 22.9 18.5 16.1 15.22 16.28 27 26.4 26.75 27.5 29.6 29
resulted in consumption of extra energy and lower efficiency in case of 25 PCM. Similar scenario was also observed in case of Hobart and Canberra. In Hobart, the thermostat range is 20–23 ◦ C. Both the PCM 24 and PCM 25 had higher ATFR values compared with the PCM 20 and PCM 21 but the corresponding energy consumption reduction was the lowest. It can be concluded from the above discussion that selection of a PCM melting range depends on local thermostat set points along with local climate. Higher value of ATFR does not always mean higher energy savings. In addition to that it was also observed that an optimum PCM melting range for highest energy savings at each month of the year is far from unique because different melting point PCM was most efficient at different times of the year. The PCM melting range which provides lowest annual energy consumption for a particular city should be selected. In the present study, the most efficient PCMs at different cities of Australia for the studied house have been identified in terms of highest annual energy savings which are presented in Table 4. The result for Darwin is not presented in Table 4 as it was explained in Section 4.1 that integration of PCM has very little effect in Darwin climate. Further study is required on how to use PCM effectively in hot and humid climate zones like Darwin. 4.3. Effect of PCM surface area and thickness on energy consumption In the previous section, efficacy of PCMs with different melting ranges was investigated by applying a 5 mm layer of PCM on the
ceiling of the house as shown in Table 2. In this section, potential energy savings depending on different surface area, thickness and positions of PCM integration in building have been investigated. The locations of PCM integration are presented in Table 5. To compare the energy savings potential of different combination, total volume of PCM was kept constant throughout the study. Thickness of the PCM layer in each combination was calculated by dividing the PCM volume by the surface area of the applied location. Table 5 shows that percentage of energy savings increased with the increase of surface area and decrease of PCM layer thickness. This was expected because an increase in surface area resulted in an increase of heat transfer rate between PCM and the zone. In addition, as the volume of PCM was constant, an increase in surface area also led to a thinner layer PCM. Consequently, the possibility of effectively charging (melting) and discharging (solidification) of PCM during diurnal temperature variations was increased because the thicker the PCM layer, the lesser is the possibility of effective charging and discharging due to low thermal conductivity of PCM (0.2 W/m K) which increases the time required to melt the PCM completely. If the melting time is not low enough, portion of PCM may remain in solid phase during the daytime charging period. Therefore, the full capacity of PCM was not utilised in case of thicker PCM layer and percentage of energy savings potential decreased. However, Table 5 also shows that percentage of energy saving was maximum in case of “all wall” where the applied PCM surface area was 41.4 m2 and then decreased in spite of an increase in surface area (57.4 m2 ) by incorporating PCM in “all wall and roof”. This occurred due to the thickness of PCM layer in those two
Fig. 7. PCM layer temperatures for different PCM integration combinations (The 23 PCM and Sydney weather was used in the simulation).
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Fig. 9. Thermal zones of single storey house [50].
surface area was smaller for the latter case. Finally, Table 5 shows that energy saving potential for “north wall” case was higher than that of “west wall” case although the surface area and PCM layer thickness were equal in both cases. Similar phenomenon was also observed for “north wall and roof” and “west wall and roof”. The reason might be the variation in the amount of solar radiation received by these surfaces. Study is ongoing to understand this phenomenon. 4.4. Effect of climate change on PCM efficiency
Fig. 8. Effect of climate change on PCM energy saving efficiency.
combinations and is explained with the help of Fig. 7. The temperature of PCM layer for four different cases in Sydney weather has been presented in Fig. 7. The PCM 23 was used in each case. The PCM layer thickness for each case is mentioned in Table 5. The PCM layer in case of “east wall” was the thickest among the four cases plotted in Fig. 7. The maximum PCM layer temperature in case of “east wall” during charging was within the melting range of PCM which suggest that PCM was not completely melted. Hence, the corresponding percentage of energy saving was the lowest as explained earlier this section. In case of “east wall and roof”, PCM was relatively thinner compared with east wall. The PCM layer temperature was increased but still within the melting range of 23 PCM. Thus, the PCM was not completely melted but the fraction of molten phase was higher than the east wall case which, in turn, resulted in higher energy saving potential compared with “east wall” case. The temperature of PCM layer in case of “all wall” reached 25 ◦ C during daytime which illustrates that the thickness of PCM layer in case of “all wall” were thin enough to achieve complete melting of PCM. Consequently, the energy saving potential of the “all wall” increased compared with the previous two cases. However, if the thickness of PCM layer is below certain limit, the temperature of the PCM layer rises quickly during daytime due to shorter melting period which was the situation for “all wall and roof” case where the PCM layer thickness was 1.25 mm. The PCM was completely melted within a short period time in case of “all wall and roof” and the temperature of the PCM layer rose sharply after phase transition as shown in Fig. 7. As a result, the thin layer of PCM in this case could not hold the zone temperature inside the comfort zone (20–25 ◦ C for Sydney) for longer period of time and extra energy was required to bring down the temperature to comfort zone which, in turn, resulted in lower energy saving potential compared to “all wall” case although
The sections above have demonstrated that the efficiency of PCM highly dependent on local climate. Wang et al. [50] reported a 2.3 ◦ C increase (A1FI emission scenario) in average temperature of Australia by 2050 with warming of around 2.3–3.36 ◦ C in inland and 1.32–2.3 ◦ C in coastal areas due to the greenhouse effect. Therefore, in this section, the effect of climate change by 2050 on the efficiency of PCM has been investigated for two cities: Melbourne and Sydney. The weather data files for the year 2050 were composed from the study of Wang et al. [50]. The projected energy consumption reduction through the application of PCM using present and 2050 weather data files are presented in Fig. 8. In case of Melbourne and Sydney, PCM 21 and PCM 23 were used respectively because they resulted in highest energy consumption reduction for these two cities at present weather as reported in Table 4. The figure shows that in Melbourne, the effectiveness of PCM will increase during May to October and decrease during November to April due to global warming. The projected percentage of annual energy consumption reduction in 2050 is around 19.2% which is similar to the calculated present value of 19.3% as reported in Table 4. On the other hand, in Sydney, PCM effectiveness is predicted to increase during June to August and decrease during September. The projected percentage of annual energy consumption reduction in 2050 will be around 12.4% which is almost half of the present value of 22.9%. Hence, it is observed that global warming will have negligible effect on the annual energy saving efficiency of PCM in Melbourne but will significantly influence the effectiveness of PCM in Sydney. However, other PCM melting point whose efficiency is lower at present weather might become the highest by 2050. Investigation is underway on this subject and will be reported in detail in our future article. It should be noted that the local comfort range may also change by 2050 which will also influence the PCM effectiveness as discussed in Section 4.2. However, in the present study, the same thermostat settings, as presented in Table 3, were used for the year 2050 due to the lack of available guidelines regarding thermal comfort range for 2050.
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factors on the effectiveness of PCM have been investigated using building simulation software EnergyPlus. Five different melting ranges PCM have been used to identify the optimum PCM melting range for each city. From the present investigation, following preliminary conclusions have been reached:
Fig. 10. Energy saving potential of PCM in both the single room house and typical house.
4.5. Comparison with a typical house A modern typical single storey Australian house was modelled with and without PCM to investigate the PCM effectiveness. The floor area of the house is 232 m2 and has a five star energy rating according to NatHERS (Nationwide house energy rating system) energy rating system. NatHERS is an Australian house energy rating scheme that rates the potential energy efficiency of Australian homes in a scale of 0–10 stars. Fig. 9 shows the different thermal zones of the house. The construction details of the house can be found in this paper [50]. Simulations were carried out for Melbourne and Sydney weather using five different PCM mentioned in Section 2.2. Similar to single room house of Section 2.2, a 5 mm layer of PCM was applied in the ceilings of the real house. The energy saving potential of PCM with different melting point has been presented in Fig. 10 for both cases. The figure shows that in both the single room house and real house, 21 PCM and 23 PCM resulted in highest energy savings among the PCM used for Melbourne and Sydney respectively. Hence, it can be said that the single room model can be used to decide which PCM will result in highest energy savings at a particular climate. However, Fig. 10 shows that actual percentage of energy savings was different for the single room house and real house in both climates. It was expected because each house has different internal thermal condition depending on size, axis orientation, location, number of windows, types of window glass, wall and roof materials and consequently, energy requirements will be different. Therefore, the simulation results regarding percentage of energy reduction at a particular climate region is not applicable for every house in that region. But the effect of PCM on energy consumptions will follow similar trend as shown in Fig. 10. As our primary goal of this study was to find out suitable PCM melting range for different climate region and investigate how different factors influence the performance of PCM in reducing energy consumption, a single room house was considered for the simulation rather than a real house which also results in lower simulation time. Although the 21 PCM and 23 PCM was found to be the most efficient PCM in Melbourne and Sydney region, its efficiency for the studied real house was only 3.3% and 10.3% respectively which can be increased by placing the PCM at different configurations descried in Section 4.3. 5. Conclusions The potential of PCM in reducing the building energy consumption at different climate zones of Australia and influence of several
• PCM has the potential to reduce the building energy consumption in Australian cities under cold temperate, mild temperate and warm temperate zones. The integration of PCM has very minor effect on the energy consumption of houses which are in hot and humid climate zone. • Effectiveness of a PCM depends on local climate, thermostat range, PCM layer thickness, surface area and location of application in buildings. • An optimum PCM melting range for lowest energy consumption in each month of the year is far from unique. Lowest annual energy consumption may be used as a criterion for the selection of PCM for a particular city. • Comparison between a real house and a single room house demonstrated that the optimum PCM temperature is the same for both however the percentage PCM required is different. Hence, for the purposes of calculating optimum PCM temperature, single room house simulation can be used. • 21 PCM is the most efficient PCM for Melbourne and Canberra. For Perth and Adelaide, 22 PCM is the most efficient. For Brisbane and Sydney, 23 PCM is the most efficient PCM. Finally, 20 PCM is most effective for Hobart region. • PCM with melting point outside the comfort range does not provide efficient energy reductions irrespective of large reduction in temperature fluctuations. • At constant volume, effectiveness of PCM increases with increasing surface area until an optimum level beyond which further increase in surface area reduces the energy saving potential of PCM. • Climate change will have an adverse influence on the energy saving potential of PCM which are optimised for current climate. Future research needs to include more detailed analysis on how to utilise PCM more effectively in Australian buildings under different climate zones. Use of night ventilation during summer needs to be investigated as it was reported by Cabeza et al. [51] that the night ventilation is very important to achieve full PCM cycle during summer. The positions of PCM layer in the external and internal wall of a building can be varied to examine the effect on the effectiveness of PCM. Finally, the impacts of PCM in cutting down the greenhouse gas emission need to be investigated. Acknowledgements Authors wish to acknowledge the “Climate Adaptation Technology and Engineering for Extreme Events” funded by CSIRO climate adaptation flagship for supporting this project. References [1] ABS, Year Book Australia, vol. 92, Australian Bureau of Statistics, Canberra, 2012, pp. 600. [2] ABARES, Energy in Australia, Australian Bureau of Agricultural and Resource Economics and Sciences, Canberra, 2011. [3] X. Wang, D. Chen, Z. Ren, Global warming and its implication to emission reduction strategies for residential buildings, Building and Environment 46 (2011) 871–883. [4] H.G. Lorsch, K.W. Kauffman, J.C. Denton, Thermal energy storage for solar heating and off-peak air conditioning, Energy Conversion 15 (1975) 1–8. [5] E. Rodriguez-Ubinas, et al., Applications of phase change material in highly energy-efficient houses, Energy and Buildings 50 (2012) 49–62. [6] A.M. Khudhair, M.M. Farid, A review on energy conservation in building applications with thermal storage by latent heat using phase change materials, Energy Conversion and Management 45 (2004) 263–275.
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