Parametric investigation of PCM thermal properties on temperature of buildings in Toronto.
Energy storage systems play a key role in improving energy utilization, as many energy sources including solar energy -- are intermittent. Solar energy is available during the day; while a demand for domestic hot water exists, and space heating or cooling during times of low solar radiation. This mismatch of availability and demand can be overcome by the use of efficient thermal energy storage (TES) such that heat collected during sunshine hours may be stored for later use during the hours between sunset and sunrise (Farid et al., 2004).
Generally, four different technologies are involved in TES:
1. Water (sensible): this is mature and the most popular technology in the market.
2. Phase change material or PCM (latent): this technology is in demonstration phase and needs new materials development.
3. Sorption (physical): it is under development.
4. Thermo-chemical materials or TCMs (chemical): this technology is the most promising as they can be charged and discharged so many times. They are under research to develop new materials.
On the average, storage density of the sensible materials is the lowest, PCMs are higher than sensible materials, sorption materials are higher than PCMs, and thermo-chemical materials have the highest storage density. To visualize the importance of latent heat storage (PCM), in the case of water, 80 times more energy is required to melt 1 kg of ice than to raise the temperature of 1 kg of water by 1[degrees]C. This means that a much smaller weight and volume of material is needed for storing a specific amount of energy.
While the sensible heat storage method is the most common, there is much activity in the research of thermal storage for solar energy applications using PCM storage. PCM storage relies on the materials latent heat as the mode of heat transfer as opposed to sensible heat as the transfer mode. Latent heat storage is a new and developing technology which has attracted much attention due to its advantages over sensible heat storage, including smaller temperature fluctuations, smaller size and lower weight to volume ratio (Canbazoglu et al., 2005).
Sensible heat storage and latent heat storage are two basic types of thermal energy storage (TES) techniques. In sensible heat storage, temperature of the storage material varies with the amount of energy stored, for example, in solar heating systems water is used for heat storage in liquid-based systems, while a rock bed is used for air-based systems. Figure 1 illustrates the temperature versus stored amount of energy (as heat) absorbed by a typical ideal PCM material (latent heat source) compared with sensible heat source (e.g. water and concrete). Practically phase change (melting) temperature is not a horizontal line because phase change temperature in heating (melting) and cooling (crystallization) points are slightly different. The length of the horizontal line represents the latent heat of the PCM. Storage of latent heat means storing heat in a material, which undergoes a phase transformation. The most commonly used phase transformation is between the liquid and solid states, but the phase change between two solid states can also be used in principle. However, the latter usually has a much lower storage density. When heat is fed into the storage material, the material begins to melt once the phase change temperature has been reached. Although further heat is applied, the temperature of the material does not increase until it has melted completely. Only then the temperature rises again (Canbazogiu lu et al., 2005).
[FIGURE 1 OMITTED]
PCM storage is an attractive option for thermal storage in solar thermal applications because, given the proper PCM material, a large part of the solar energy available during the day could be stored. When the temperature in a hot water storage tank rises above the melting temperature of the PCM, the PCM begins to melt as it absorbs heat. When the energy stops being supplied, the PCM will release its energy as it solidifies (Whitman et al., 2011).
Phase Change Material Storage
Phase change is always either release or absorb some heat. Latent heat storage is an efficient way of storing thermal energy due to two key factors. In one recent study, it was found that the storage time of hot water, the produced hot water mass and total heat accumulated in the solar water-heating system having a heat storage tank combined with PCMs were 2.59 - 3.45 times that of the conventional solar water-heating system without PCMs. This translates directly into a cost savings as a smaller tank with less insulation could be used in conjunction with PCM storage (Canbazogiu et al., 2005).
Phase change material storage relies on the PCM material to absorb, store, and release energy as they change state utilizing the latent heat of fusion. Ideally, PCMs must have a large latent heat and a high thermal conductivity, have a melting temperature within the range of operation, be chemically stable, low in cost, non-toxic and non-corrosive (Farid et al., 2004).
In solar thermal applications, it is necessary to provide the required storage of solar energy collected during the day and be able to utilize this stored energy for later use.
Several materials have been investigated to understand their applicability to solar thermal applications. Issues such as the degradation of thermal properties, phase segregation, and stability have been researched to ensure good systemic performance (Farid et al., 2004). Current research indicates that PCMs such as salt hydrates, paraffins (e.g., RT58), and fatty acids are potential candidates for thermal storage in solar applications (Canbazogiu et al., 2005). More specifically, fatty acids including capric, lauric, palmitic, and stearic acids possess good thermal characteristics making them promising PCMs for solar applications (Farid et al., 2004). With a melt-ing range between 30[degrees]C (86[degrees]F) and 65[degrees]C (149[degrees]F) and latent heat of transition varying from 153 to 180 kJ/kg (66 to 77 Btu/ lb), fatty acids could potentially be used in space and domestic hot water applications as they have demonstrated good thermal stability in terms of thermal cycling when used as latent heat storage materials in solar thermal applications (Sari, 2003).
In terms of storage density and the avoidance of large temperature fluctuations, latent heat energy storage is an efficient way to store thermal energy. Other than increased efficiency, advantages to this method of thermal storage compared to sensible heat storage include a higher energy storage density and smaller temperature fluctuations. Once the PCM has reached its melting temperature, the energy added to the storage system is used in the melting process, which prevents large temperature fluctuations. There are however difficulties when using latent heat thermal storage. Also, PCMs may undergo density change, phase segregation, sub-cooling, and lose stability under extended thermal cycling (Farid et al., 2004).
Producing PCM consumes energy and may have some environmental impact. Life cycle assessment (LCA) of PCM was considered in Spanish building industry. Results show that the addition of PCM in the building envelope, although decreasing the energy consumption during operation, does not reduce significantly the global impact throughout the life time of the building. For the hypothetical scenario considering summer conditions all year around and a life time of the building of 100 years, the use of PCM reduces the overall impact by more than 10% (Gracia et al., 2010).
In Canada, most of the houses are made of wood. These buildings are light and inside temperature fluctuates with ambient temperature. Use of PCM in lightweight construction (e.g. a wood house) makes it possible to improve thermal comfort and reduce energy consumption (Kuznik et al., 2010).
Extensive review on dynamic characteristics and energy performance of buildings using PCMs showed that (Zhu et al., 2009):
* PCMs enhance building thermal and energy performance.
* energy performance of buildings using PCMs are not sufficiently studied.
* the research on using optimal control strategies may maximize the potential of using PCMs.
Modeling of Latent Heat Thermal Energy Storage
Exergy analysis is very important in developing a good understanding of the thermodynamic behavior of thermal energy storage systems because it clearly takes into account the loss of availability and temperature of heat in storage applications, and hence it reflects the thermodynamic and economic value of the storage operation. Most of the analyses are based on first law of thermodynamics, which is inadequate as a measure of the energy storage because the temperature of the surroundings and the effect of time duration through which heat is supplied are not considered. The energy analysis might produce a workable design, but not necessarily one with the highest possible thermodynamic efficiency. In contrast an exergy analysis consideration leads to optimal design operation of thermal system (Verma et al., 2008).
Verma et al. (2008) showed that none of the availability analyses cited have treated thermal energy storage systems that utilize PCM. However, the study showed that elimination of the time periods required to heat or to cool the storage material above or below the melting temperature, respectively, can improve the second law efficiency of the system.
Net Zero Energy Building (NZEB) Simulation in Toronto
The Toronto Net Zero Energy house represents an award winning design initiative that collaborates between the Sustainable Urbanism Initiative (SUI) Toronto and a host of architectural and engineering firms, with the objective of increasing public awareness and adoption of energy efficient homes in Canada. More information about the SUI building is given in its website (Siddiqui 2009). NZEB has not yet been built, but it has been the subject of much research as a typical living house in Toronto. In SUI design, mezzanine is placed between second and third floor to afford daylight for the house.
Figure 2 shows a computer generated 3-D model of the house. The building envelope of the SUI House is designed with the intention of minimizing the heat transfer to the outside, thereby saving energy and contributing to occupant thermal comfort.
[FIGURE 2 OMITTED]
The external walls have been insulated with sprayed polyisocyanurate foam insulation, which provides an overall insulation value of R-60 (RSI-10.6). Roof assembly consists of drywall on 19 x 19 mm (0.75 x 0.75 inch) furring and 0.15 mm (5.91 mil) polyethylene vapor retarder attached to the bottom of the 294 mm (11.57 inch) pre-engineered I-joists. Sprayed polyisocyanurate foam is applied between joists as roof insulation. Table 1 shows the various layers used within the wall and floor of the building envelope respectively. Thermo-physical properties of all layers are available in TRNSYS 16, but the PCM. The PCM may be introduced as mass-less inside the envelope or added as a massive layer mixed with other material (e.g. plaster).
Table 1. The Layers of the NZEH Wall (Left) and Floor (Right) (Poulad et al. 2011) Wall Layers Floor Layers Indoor air exposure Boundary with relevant zone PCM Layer 10mm (0.4") PCM Layer 10mm (0.4") Plaster, 13mm (1/2") Plaster, 13mm (1/2") Furring 19mm (3/4") Plaster, 13mm (1/2") Polyethylene Vapor Retarder, Timber floor 25mm (1") 0.15mm (2x6) Wood Studs @600mm (24") O.C Common con 50mm (2") Sprayed Polyisocyanurate closed I-Joist 50mm (2") cell foam 139mm RSI-6.5 OSB Structural Sheathing with STO Rigid insulation-Extruded Gold Coat 13mm Polystyrene 200mm (8")(R-7) Rigid insulation-Extruded Furring 19mm (3/4") Polystyrene 100mm RSI 3.48 Air space 25mm (1") Plywood 10mm (0.4") Face Brick 100mm (4") Boundary with other zone External ambient exposure
The roof has an insulation value of R-76 (RSI-13.4). The windows used in the house have low emissivity and are argon filled with a fiberglass frame and have an overall insulation value of R-4 (RSI-0.7). Walls below grade are of the insulating concrete form and have 2.5 in. of rigid polystyrene board with a waterproof membrane. The overall insulation value of the below grade wall is R-35 (RSI-6.27).
TRNSYS16 Building Simulator
TRNSYS is an acronym for a "transient simulation program" and is a quasi-steady simulation model. This program was developed at the University of Wisconsin by the members of the Solar Energy Laboratory. TRNSYS is comprehensive and powerful building simulation software that can provide whole building simulations with the added capability of easily integrating a variety of renewable energy and HVAC components. It is this software that would be utilized for conducting detailed energy simulations on a variety of building models to assess the impact of integrating thermal mass and phase change materials (PCM) into the building envelope.
TRNSYS is a modular simulation program, based on the FORTRAN programming language. It utilizes standalone components and mathematical modules for a wide variety of applications such as heat pumps and PV panels etc, in a user-friendly graphical interface. Each of these components can be connected together to represents the flow of information during the simulation. The TRNSYS engine calls the system components based on the input file and iterates at each time-step until the system of equations is solved. Weather data is needed to perform the simulations with TRNSYS. TRNSYS runs through hourly values of various weather parameters included in a typical meteorological year (TMY) file. The weather file included with TRNSYS contains detailed weather data for thousands of locations around the world (Klein et al., 1998).
Each component in TRNSYS is defined as a TYPE and contains all the relevant mathematical parameters to integrate it in to the overall TRNSYS model. Building models are defined as TYPE.
TRNSYS Type 204 PCM Components
Prior to the development of the TYPE 204 model in TRNSYS, it was impossible to directly simulate the real effect of heat transfer through a wall containing PCM. While in the past, most of the work was focused on the experimental analysis of building integrated PCM, more recently, with the development of robust building simulation software, it is now possible to investigate in detail the thermal properties of a wide variety of phase change materials without the need for elaborate experimentation. Building simulation also provides a valuable tool for validation of the experimental data.
Prior to the development of the TYPE 204 PCM module in TRNSYS, the only manner in which the effects of PCMs in buildings could be investigated was through the development of an active layer within the building envelope. Ibanez et al. (2005) presented a methodology in TRNSYS whereby, through the definition of an active wall containing tubes through which a fluid was circulated, the overall thermal effect of phase change materials could be determined. Even though this approach did not simulate the real heat transfer process through a PCM wall, the overall impact in terms of energy transfer was quite similar to what would be expected with a PCM integrated wall (Ibanez et al., 2005).
The TYPE 204 component was developed in FORTRAN and integrated into TRNSYS by a team based at the Helsinki University of Technology (Lamberg et al., 2004). Utilizing the finite difference method with a Crank-Nicholson scheme, the model simulates heat transfer through a 3-D PCM composite wall component containing a total of 729 nodes (9 nodes each in the x, y and z directions). At each node the conduction, convection and radiation heat transfer along with the temperature is calculated (Ahmad et al., 2006). The 3-D wall element can be defined precisely to specify the concentration and melting points of the PCM used. The properties of the composite building materials used in conjunction with the PCM can also be easily defined. To account for the changes in the specific heat capacity of the PCM due to temperature variations during phase change, the model uses the effective heat capacity ([C.sub.pe]) method to define the heat capacity at each phase, i.e., liquid or solid as follows:
[C.sub.pe]=[C.sub.p]+Latent Heat/Phase Change Temperature Range (1)
The Type 204 PCM module in TRNSYS has the following input parameters that must be entered into the model to accurately represent a particular phase change material. These properties are described in detail below:
Number of Iterations: This parameter can be given any value between one and infinity and is used primarily for the sake of accuracy. Utilizing any number more than one for iteration would involve the solution of relevant heat transfer equations multiple times and generally provide more accurate solutions. The only drawback is increased computation time. To find a reasonable value for iteration, some preliminary simulations were conducted on ASHRAE Standard 140-2001 (BESTEST) Case 600 in Toronto weather conditions. Total energy demand to keep the indoor air temperature of the Case 600 in range of 21[degrees]C (70[degrees]F) to 24[degrees]C (75[degrees]F) versus the number of iteration is plotted in Figure 3. Three iterations provide reasonably good accuracy in this work. The maximum difference between the maximum number of iteration, 20, and 3 is about 5%. This uncertainty is reasonable in this case because, comparing with 20 iterations; it saves at least four days of simulation time for each run.
[FIGURE 3 OMITTED]
Melting temperature: This characteristic is concerned with the initial temperature during which the phase change material undergoes phase transition.
Crystallization temperature: The crystallization temperature is determined by the point where the PCM changes phase back to a solid. This temperature is always lower than the melting temperature. This is considered one degree lower than melting point.
Range in crystallization temperature: Unlike pure materials such as water, which changes phase at a distinct temperature, most phase changes undergo the phase change process within a temperature range. This parameter could be used to define the phase change range of a particular PCM.
Latent heat of PCM: This parameter measures the total heat storage /release capacity of a particular PCM at the phase change temperature range.
PCM density: The density of the pure PCM can be entered into the model using this parameter. It is 1000 [kg/m.sup.3] (62.4 lb/ [ft.sup.3]) for the PCM.
PCM specific heat capacity [(C.sub.p]): This parameter is concerned with the [C.sub.p] of the PCM. It is an important characteristic since it provides a measure of the energy storage/ release capacity of a particular PCM at a temperature outside the temperature range of phase transition.
Density of other material in PCM node: The density of other material that has been integrated with the PCM can be entered through this parameter. In this simulation, Plaster is used as other material.
[C.sub.p] of other material: The specific heat capacity of any other materials incorporated with the PCM can be entered through this parameter.
Volume fraction of PCM in node: The overall concentration of PCM in a particular specimen can be entered through this parameter. Since most studies characterize the overall concentration of PCM by weight, this value must be converted into volume fraction to reflect the input requirements of the parameter. For mass less simulation, PCM is not mixed; there-fore, volume fraction is 1.
Set point in summer and winter is considered 21[degrees]C (70[degrees]F) and 24[degrees]C (75[degrees]F) respectively. This is only applicable for investigating energy demand. Heating and cooling are off for indoor air temperature investigation.
To add the PCM Type 204 to TRNSYS, the following parameters were fixed in the text file named "ALKU":
The number of nodes (i, j, k), (fixed) 9*9*9 = 729
Dimensions of the wall component, [m]: 0.45, 0.45, 0.2 [meters], height (j), width (i) and depth (k)
Convective heat transfer coefficient of the surface of the wall component, h = 2.0 [W/m.sup.2]K (0.35 [Btu/h.ft.sup.2].[degrees]R) (HILMA).
Time step = 300 second (LASVALI)
Weighting factor of finite-difference method (The Crank-Nicholson method: MENKERROI = 0.5)
Initial temperature of the nodes = 20[degrees]C (68[degrees]F) Indoor temperature (fixed) = 40[degrees]C (104[degrees]F)
Initial value of effective heat capacity [C.sub.pe] = 2.5 kJ/kgK (1.1 Btu/lbK)
Simulation was conducted with TRNSYS using Type 204 PCM module developed in Helsinki, Finland. Interior temperature of the SUI Net Zero House with no PCM was taken as baseline, and then the PCM added to simulate its effect on comfort of the house. The comfort is measured by temperature swing index (TSI). It, in turn, depends on the average hourly temperature fluctuations (AHTF), see Equations (2) and (3). As shown in Table 2, 465 [m.sup.2] of the total wall and ceiling area was covered with PCM of ten millimeters thickness (0.4 inch). This is equal to a latent energy of 409 MJ (114 kWh or 3.9E5 Btu). Therefore, theoretically, PCM can reduce the fluctuation of the inside air temperature by either absorbing or releasing its latent heat. To investigate the effects of PCM on interior temperature, the heating and cooling systems were eliminated from the building zones.
Table 2. The NZEB Zones Descriptions and the PCM Sizes Zone of Window Area, Total Floor Total Wall Zone Vol., the [m.sup.3] House [m.sup.2] Area, Area, (f[t.sup.2]) (f[t.sup.2]) [m.sup.2] [m.sup.2] (f[t.sup.2]) (f[t.sup.2]) Garage 1.03 (9) 11.16 (102) 32.49 (298) 27.2 (757) 1st Floor 10.28 (94) 52.38 (481) 83.18 (764) 146.56 (4078) 2nd Floor 7.39 (68) 58.46 (537) 86.22 (792) 163.57 (4552) 3rd Floor 13.50 (124) 49.3 (453) 92.69 (851) 175.5 (4884) Mezzanine 33.08 (304) 22.85 (210) 86.23 (792) 171.64 (4776) Total 65.28 (599) 194.15 (1783) 380.81 (3497) 684.47 (19046) Zone of Total PCM area the in part, [m.sup.2] (f[t.sup.2]) House Wall Ceiling Total Garage 0 (0) 0 (0) 0 (0) 1st Floor 80 (735) 50 (459) 130 (1194) 2nd Floor 80 (735) 55 (505) 135 (1240) 3rd Floor 85 (781) 45 (413) 130(1194) Mezzanine 50 (459) 20 (184) 70 (643) Total 295 (2709) 170 465 (4270) (1561)
To control the radiation gain inside the building envelope and reduce cooling load in summer and decrease heating load in winter, schedule is illustrated in Table 3. Each year is composed of 8760 hours.
Table 3. Shading Schedule Time of the Year (Hour) % Shading 0 to 2550 0 2550 to 3300 50 3300 to 6560 100 6560 to 8760 0
PCM Material Properties
For the sake of the simulation, a virtual phase change material is used. Table 4 shows the physical property of the PCM that was simulated. The melting point and thermal conductivity were varied from 22[degrees]C (72[degrees]F) to 26[degrees]C (79[degrees]F) and from 0.1 W/mK (0.06 Btu/h.ft.[degrees]R) to 3 W/mK (1.73 Btu/ h.ft.[degrees]R), respectively.
Table 4. PCM Properties PCM Properties Value Density, p: kg/[m.sup.3] (lb/f[t.sup.3]) 800 (50) Thermal conductivity, k: W/mK 0.3 (0.17) (Btu/h.ft.[degrees]R) Specific heat capacity, [C.sub.p]: J/gK (Btu/lb) 1.6 (0.69) Onset phase change temperature upon 22/23 heating/cooling: [T.sub.e] [degrees]C ([degrees]F) (72/73) Latent heat of fusion on heating, L: kJ/kg 110 (0.43) (Btu/lb)
Results are classified in two categories: effects of melting range and effects of thermal conductivity. Melting range is defined as the temperature difference between start of melting point during heating the solid and start of crystallization point during cooling the liquid. Crystallization temperature is always lower than melting point.
Melting Range Sensitivity. Melting point of the PCM is an important factor in absorbing/releasing heat from/to the air. To analyze the sensitivity of melting range, thermal conductivity of the PCM is fixed to a value of 0.3 W/mK (0.17 Btu/ h.ft.[degrees]R). Melting range effects are investigated on indoor air temperature (IAT). To quantify the temperature fluctuation or swing, a dimensionless temperature swing index (TSI) is defined and calculated by taking the average hourly temperature fluctuations (AHTF) of each zone in 200 successive hours (1 to 200 in winter, the first week in January, and 4325 to 4524 in summer, the first week in July) relative to AHTF of outdoor.
AHTF=[[SIGMA].sub.i=1.sup.200] | Z[T.sub.i]-Z[T.sub.i+1]]/200 (2)
where ZT is the zone temperature in [degrees]C and i is the specific hour of year (could be any value from 1 to 8559). Then,
TSI=Average of AHTF for the Zone/Average of AHTF for Outdoor (3)
For this investigation, heating and cooling are off. Mezzanine has the highest fluctuation in temperature out of all zones in NZEB (Table 2) because it has the maximum window area; therefore, its average temperature is investigated.
Figure 4 illustrates the mezzanine temperature on a typical summer (July [2.sup.nd]) and winter (Jan. [2.sup.nd]) day. Curves of "10-12" and "15-17" overlap each other and the closest to "No PCM" curve. On the other side, "20-21" and "21-22" curves provide more comfortable temperature (i.e., closer to set point, 24[degrees]C) than the others in summer.
[FIGURE 4 OMITTED]
Daily fluctuation in indoor temperature changes from 7.6[degrees]C (13.7[degrees]F) and 6.5[degrees]C (11.7[degrees]F) to 5.3[degrees]C (9.5[degrees]F) and 4.9[degrees]C (8.8[degrees]F) in the typical winter and summer day, respectively, by using PCM (see Figure 5). Simulation results for other days of the year show the same trend, i.e., No PCM has the maximum swing and swing is lower in summer than winter days. Additionally, other zones have lower temperature fluctuations than the mezzanine.
[FIGURE 5 OMITTED]
Effects of Thermal Conductivity on IAT. For this investigation, heating and cooling are off. The thermal conductivity was changed from 0.1 to 3 W/mK. The average temperature of the mezzanine zone is investigated. Analysis of data (Figure 6) clarifies that the indoor average temperature is not sensitive to the PCM thermal conductivity, but the presence of the PCM keeps the zone temperatures comfortable (between 21[degrees]C and 24[degrees]C). Although "k=2" shows better performance in summer and winter, all plots with different thermal conductivities are almost overlapping each other in a narrow band. Other days of the year show the same trend, i.e., No PCM has the maximum distance from set points (in summer days, the temperature is the furthest from 24[degrees]C, and in winter days, it is the furthest from 21[degrees]C).
[FIGURE 6 OMITTED]
SUMMARY AND DISCUSSION
It is worth mentioning that, for investigating thermal conductivity effect, the melting range was fixed to the value given in Table 4 (i.e., 22-23[degrees]C). To investigate the melting range effects, thermal conductivity was fixed and taken from Table 4.
The analysis of all simulations is quite difficult, due to the amount of data generated. Therefore, only the main points are highlighted here.
As Figure 5 shows, the minimum temperature fluctuation is seen for PCM with melting range of 21[degrees]C to 23[degrees]C. It should be mentioned that if there is enough PCM to store/release heat there should be no temperature fluctuation. In summer, during the day ambient temperature is above set point range; there-fore, inside the house PCM absorb energy until it changes the phase completely. At night, ambient temperature is lower than set point range; the heat that already stored inside the PCM is released to keep the IAT around its melting range. In winter, ambient temperature is almost always lower than set point range; therefore the heater should work to keep IAT above 21[degrees]C.
As shown in the last column of Table 5, the TSI of the mezzanine is higher in winter than summer (0.91 and 0.62, respectively). This is due to the direct radiation of sun through the windows during the day in winter and cold night in Toronto. In summer, shading (Table 3) reduces the radiation into the mezzanine; therefore, the indoor temperature fluctuation is lower with respect to the outdoor temperature fluctuation (TSI). Analysis of the data in Table 5 proves that using the PCM reduces the AHTF by 16% and 15% (comparing AHTF in No PCM and mezzanine columns) in winter and summer, respectively. As it is expected, by increasing the window areas, the difference between winter and summer AHTF increases. This difference is about 0.03 for first and second floors and increases up to 0.16 for the mezzanine. The maximum difference goes to No PCM condition, which proves that by using PCM, the temperature fluctuation between winter and summer decreases. Regarding temperature fluctuations in all zones, the PCM is more effective in winter than summer. Due to the large window area of the mezzanine, when PCM is not used, the mezzanine has a higher temperature fluctuation than the outdoor in winter. In summer, due to the shading and thermal inertia of the building envelope, outdoor has a higher AHTF.
Table 5. AHTF of Different Zones and Outdoor Temperature in the First Week of Jan. (Winter) and July (Summer) Garage 1st 2nd 3rd Mezzanine No Outdoor TSI Floor Floor Floor PCM AHTF 0.19 0.34 0.21 0.35 0.69 0.82 0.76 0.91 (Winter) AHTF 0.15 0.31 0.19 0.2 0.53 0.62 0.86 0.62 (Summer) Difference 0.04 0.03 0.02 0.15 0.16 0.2 0.1 0.29
In the mezzanine, due to the thermal inertia, the peak occurs 2 to 4 hours after the outdoor temperature is in its maxi-mum point (Figure 6) in summer; and in winter, due to the steady state of outside conditions, the peak occurs almost at the same time that ambient temperature is in its minimum.
The Net-Zero House was simulated using TRNSYS incorporated with PCM module of the TYPE 204. The best melting range and thermal conductivity of the PCM were sought to make the lowest IAT swing. Considering the set points of 21[degrees]C (70[degrees]F) and 24[degrees]C (75[degrees]F), the best melting range for the PCM was found to be 21[degrees]C (68[degrees]F) to 23[degrees]C (71.6[degrees]F), which is in lower section of the set points range. In terms of thermal conductivity, the higher is the better. Although IAT swing is neither sensitive to the melting range nor to the thermal conductivity, the swing is lower when the PCM is added.
As energy demand and peak power of buildings have direct impact on economy, these effects must be studied. Moreover, the effects of the thermal conductivity are better to be investigated by applying some small layers of PCM on the envelope instead of one thick layer (e.g., 10 layers of one mm instead of one layer of 10mm).
This work was funded in part by the Solar Buildings Research Network under the Strategic Network Grants Program and Discovery Grant of the Natural Sciences and Engineering Research Council (NSERC) of Canada.
AHTF = Average hourly temperature fluctuations ([degrees]C,
[C.sub.p] = Heat capacity (J/g.K, Btu/lb.[degrees]R)
[C.sub.pe] = Effective heat capacity (J/g.K, Btu/lb.[degrees]R)
h = Convective Heat Transfer Coefficient (W/m2K, Btu/h.f[t.sup.2]
H = Enthalpy
HVAC = Heating, Ventilation, and Air Conditioning
IAT = Indoor air temperature
L = Latent heat of fusion on heating (kJ/kg, Btu/lb)
k = Thermal conductivity (W/mK, Btu/h.ft.[degrees]R)
NZEB = Net Zero Energy Building
PCM = Phase change material
SUI = Sustainable Urbanism Initiative
T = Temperature ([degrees]C, [degrees]F)
TCM = Thermo-Chemical Material
TES = Thermal energy storage
TMY = Typical meteorological year
TSI = Temperature swing index
ZT = Zone temperature
[pho] = Density (kg/[m.sup.3])
p = Specific
Mehdi Shahrestani, University of Reading, Reading, Berkshire, UK: 1) Is it sustainable to use some kinds of PCM? 2) Is it possible to change the melting point of a specific PCM?
M. Ebrahim Poulad: 1) Yes, PCM is sustainable because it is not exhaustive. So, many labs are producing different PCMs for different applications. They don't lose their properties in storing energy by the number of iterations they have been used. 2) It is not easy to change the melting range of a current PCM, but we can produce a PCM with a different melting range that fits any specific demand. Please feel free to contact me if you need more explanation.
Ahmad, Maha, Andre Bontemps, He'bert Sallee, and Daniel Quenard. "Thermal testing and numerical simulation of a prototype cell using light wallboards coupling vacuum isolation panels and phase change material." Energy and Buildings, 2006: 38 673-681.
Canbazogiu, Suat, Abdulmuttalip Sahinaslan, Ahmet Ekmekyapar, Gokhan Y. Aksoya, and Akarsu, Fatih. "Enhancement of solar thermal energy storage performance using sodium thiosulfate pentahydrate of a conventional solar water-heating system." Energy and Buildings, 2005: 37 235-242.
Castellon, C., A. Castell, M. Medrano, I. Martorell, and L. F. Cabeza. "Experimental Study of PCM Inclusion in Dif-ferent Building Envelopes." Journal of Solar Energy Engineering, Nov. 2009: 131 (4) 041006 (6 pages).
Farid, M.M., A.M. Khudhair, A.K. Razack, and Said Al-Hal-laj. "A review on phase change energy storage: materials and applications." Energy Conversion and Management, 2004: 45 1597-1615.
Gracia, Alvaro de, et al. "Life cycle assessment of the inclusion of phase change materials (PCM) in experimental buildings." Energy and Buildings, 2010.
Ibanez, Manuel, Ana Lazaro, Zalba Belen, and F. Cabeza Luisa. "An approach to the simulation of PCMs in building applications using TRNSYS." Applied Thermal Engineering, Vol, 2005: 25 1796-1807.
Jokisalo, Juha, Piia Lamberg, and Kai Siren. Suitability of Building Construction Materials in Short-Term Energy Storage - Office Room Simulations. Helsinki, Finland: Helsinki University of Technology, 1999.
Jokisalo, Juha, Piia Lamberg, and Kai Siren. SUITABILITY OF BUILDING CONSTRUCTION MATERIALS IN SHORT-TERM ENERGY STORAGE - OFFICE ROOM SIMULATIONS. Helsinki, Finland: Helsinki University of Technology, 1999.
Kuznik, Frederic, Joseph Virgone, and Kevyn Johannes. "Development and validation of a new TRNSYS type for the simulation of external building walls containing PCM." Energy and Buildings, 2010: 42 1004-1009.
Lamberg, Piia, Reijo Lehtiniemi, and Anna-Maria Henell. "Numerical and experimental investigation of melting and freezing Numerical and experimental investigation of melting and freezing." International Journal of Thermal Sciences, 2004: 43 277-287.
Poulad, M.E., A. Fung, and D. Naylor. "Effect of PCM Thermal Conductivity on Energy Demand and Temperature of the Net-Zero Building in Toronto." CANCAM Pro-ceedings. Vancouver, B.C., 2011.
Schranzhofer, H., P. Puschnig, A. Heinz, and W. Streicher. Validation of a TRNSYS Simulation Model for PCM Energy Storages and PCM Wall Construction Elements.
Graz, Austria: Institute of Thermal Engineering, University of Technology Graz, 2006.
Sharma, Atul, V.V. Tyagi, C.R. Chen, and D. Buddhi. "Review on thermal energy storage with phase change materials and applications." Renewable and Sustainable Energy Reviews, 2009: 13 318-345.
Siddiqui, Omar. "Thermophysical characteristics of building integrated phase change materials (PCM) and their applicability to energy efficient homes." MASc. Thesis. Ryerson University, 2009.
Siddiqui, Omar, Alan Fung, Humphrey Tse, and Dahai Zhang. "Modelling of the Net Zero town house in Toronto using TRNSYS, and an analysis of the impact using thermal mass." Energy Sustainability. Jacksonville, Florida USA, 2008.
Sustainable Urbanism Initiative. Toronto: Sustainable Design in Toronto's Annex Net Zero Energy Healthy Housing Proposal, 2007.
Verma, Prashant, Varun, and S.K. Singal. "Review of mathematical modeling on latent heat thermal energy storage systems using phase-change material." Renewable and Sustainable Energy Reviews, 2008: Vol. 12, pp. 999-1031.
Whitman, C. A., M.B. Johnson, and M. A. White. "Characterization of Thermal Performance of a Solid-Solid Phase Change." Thermochimica Acta, 2011.
Zhu, Na, Zhenjun Ma, and Shengwei Wang. "Dynamic characteristics and energy performance of buildings using phase change materials: A review." Energy Conversion and Management, 2009: 3169-3181.
M. Ebrahim Poulad
Student Member ASHRAE
Alan S. Fung, PhD, PE
M. Ebrahim Poulad is a PhD candidate and Alan S. Fung is an associate professor in the Department of Mechanical and Industrial Engineering at Ryerson University in Toronto, Ontario.
|Printer friendly Cite/link Email Feedback|
|Author:||Poulad, M. Ebrahim; Fung, Alan S.|
|Date:||Jul 1, 2012|
|Previous Article:||Thermal performance of building envelope details for mid- and high-rise buildings.|
|Next Article:||Field measurements of thermal conditions during surgical procedures for the development of CFD boundary conditions.|