Parametric investigation of effects of PCM thermal properties on energy demand of SUI building in Toronto.
Energy savings is one of the major concerns in building science and engineering. These requirements/concerns come from strict regulatory rules as well as growing global environ-mental concerns. Practically, the level of indoor air quality or thermal comfort depends heavily on the characteristics of the building envelope (thermal mass, wall and window insulations, air leakage, etc.) and on the outdoor (atmospheric) conditions (solar heat gains, wind velocity, air temperature and humidity, etc). The combinations of all these parameters (external, within the envelope and, internal) control heat exchanges between the interior and the exterior of a building, and consequently affect the overall energy consumption.
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 and space heating or cooling exists 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 daylight hours may be stored for later use during the time between sunset and sunrise (Farid et al. 2004).
Sensible-heat storage and latent-heat storage are two basic types of TES techniques. In sensible-heat storage, the 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 the 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 that 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 change the phase (e.g. melts) 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.
As this paper is a continuation of the TRNS-00216-2011, published in the San Antonio, Texas ASHRAE Conference in July (Poulad and Fung 2012), readers are highly recommended to read the introduction of that paper. This paper mostly discusses the results.
Mathematical Modeling of Latent-Heat TES
Energy analysis is very important in developing a good understanding of the thermodynamic behavior of TES 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 the 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 energy analysis consideration leads to optimal design operation of the thermal system (Verma et al. 2008).
Verma et al. (2008) showed that none of the available analyses cited have treated TES systems that utilize PCM. However, the study showed that the 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. The analysis of heat-transfer problems in the phase-change process (e.g., melting and solidification), called moving boundary problems, is complicated due to the fact that the phase-change boundary (e.g., solid-liquid) moves depending on the speed at which the latent heat is absorbed or lost at the boundary, so that the position of the boundary is not known a priori and forms part of the solution (Verma et al. 2008). In analysing a pure substance, the solidification occurs at a single temperature, while in the opposite case such as with mixtures, alloys, and impure materials, the phase change takes place over a range of temperatures, and therefore it appears as a two-phase zone between the two zones (e.g., solid and liquid zones). In the latter case, it is appropriate to consider the energy equation in terms of enthalpy, which if the advective movements in the inner edge of the liquid are disregarded, is expressed mathematically as:
[rho] [delta]H/[delta]t = [nabla] (k[nabla]T) (1)
[rho] = density
H = total enthalpy
t = time
k = thermal conductivity
T = temperature
Solving this equation requires knowledge of H(T) and k(T) (temperature functional dependency of enthalpy and thermal conductivity, respectively). The strength of this method lies in the fact that the equation is directly applicable to the three phases, the temperature is determined at each point, and the value of thermo-physical properties can be evaluated. Finally, according to the temperature field, it is possible to ascertain the position of two boundaries if so desired, although as indicated above this is not necessary.
PCM is added to the walls and ceilings and mixed with plaster as layers. In each layer (i) covering the building envelope, the heat energy equation is (Kuznik et al. 2010):
[[rho].sub.i] [delta][H.sub.i] / [delta]t = - [delta] / [delta] x ([k.sub.i] [delta]T / [delta]x(2)
[H.sub.i] = enthalpy of the PCM mixture layer i
[[rho].sub.i]= density of the PCM mixture layer i
[k.sub.i]= conductivity of the PCM mixture layer i
For the mixture with total heat capacity of C, Equation 2 can be written as:
[delta][H.sub.i] / [delta]t = [delta][H.sub.i] / [delta]T * [delta]T / [delta]t = [C.sub.T] [delta]T / [delta]t (3)
where [C.sub.T] is the analytical expression of the effective heat capacity.
Net Zero Energy Building (NZEB) Simulation in Toronto
The Toronto NZEB represents an award-winning design initiative that collaborates with the Sustainable Urbanism Initiative (SUI) in 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 the SUI design, the mezzanine is placed between the third floor and ceiling to afford daylight for the house.
Figure 2 shows a computer-generated three-dimensional model of the house. The windows of the building are designed as high-performance double-glazed and its envelope is intended to minimize the heat transfer to the outside, thereby saving energy and contributing to the occupant's thermal comfort.
The external walls have been insulated with sprayed polyiso-cyanurate 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 in.) furring and 0.15 mm (0.00591 in.) polyethylene vapor retarder attached to the bottom of the 294 mm (11.57 in.) pre-engineered I-joists. Sprayed polyisocyanurate foam is applied between joists as roof insulation. Table 1 shows the various layers used within the walls and floors of the building envelope, respectively. Thermo-physical properties of all layers are available in TRNSYS 16, except the PCM. The PCM may be introduced as massless inside the envelope or added as a massive layer mixed with other material (e.g., plaster) (Siddiqui et al. 2008).
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). The walls below grade are of an 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).
Table 1. Layers of the NZEHWall and Floor (Poulad etal. 2011) Wall Layers Floor Layers Indoor air exposure PCM layer 10 mm (0.4 in.) Boundary with relevant zone Plaster, 13 mm (0.5 in.) PCM layer, 10 mm (0.4 in.) Furring, 19 mm (0.75 in.) Plaster, 13 mm (0.5 in.) Polyethylene vapor retarder, Timber floor, 25 mm (1in.) 0.15 mm (0.0059 in.) 2 x 6 wood studs at 600 mm (24 Common con, 50 mm (2 in.) in.) O.C. Sprayed polyisocyanurate I-joist, 50 mm (2 in.) closed-cell foam, 139 mm (5.47 in) (RSI-6.5) OSB structural sheathing with Rigid insulation-extruded STO gold coat, 13 mm (0.51 polystyrene, 200 mm (8 in.) in.) (R-7) Rigid insulation-extruded Furring, 19 mm (0.75 in.) polystyrene, 100 mm (4 in.) (RSI-3.48) Air space, 25 mm (1 in.) Plywood, 10 mm (0.4 in.) Face brick, 100 mm (4 in.) Boundary with other zone External ambient exposure Note: OSB = oriented strand board; STO gold coat = ready-mixed flexible waterproof coating for use under adhesive wall claddings.
The simulation was conducted with TRNSYS using the Type 204 PCM module developed in Helsinki, Finland (Lamberg et al. 2004). Energy consumption of the SUI NZEB with no PCM was taken as a baseline, and then the PCM was added to simulate its effect on the comfort of the house. As shown in Table 2, 465 [m.sup.2] (4270 ft) of the total wall and ceiling area was covered with PCM of 10 mm (0.4 in.) thickness. This is equal to a latent energy of 409 MJ (114 kWh [3.9E5 Btu]). To investigate the effects of PCM on the energy demand, the heating and cooling systems were set to unlimited to keep the building zones inside the setpoints.
Table 2. NZEB Zone Descriptions and PCM Sizes Zone of the Window Area, Total Floor Total Zone Volume, House m[m.sup.2] Area, WallArea, [m.sup.3] (f[t.sup.2]) [m.sup.2] [m.sup.2] (f[t.sup.3]) (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 the Total PCM Area House in Part, [m.sup.2] (f[t.sup.2]) 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 (1561) (4270)
To control the radiation gain inside the building envelope, and to reduce cooling load in summer and decrease heating load in winter, the shading schedule is introduced. It is illustrated in Figure 3. Each year was composed of 8760 hours. It started at midnight January (hour 1) and ended at midnight December (hour 8760).
PCM Material Properties
For the sake of the simulation, a virtual PCM was used. Table 3 shows the physical property of the PCM that was simulated. The melting point and thermal conductivity are the parameters under investigation; therefore, they are varied from 20[degrees]C-26[degrees]C (68[degrees]F-79[degrees]F) and from 0.1-3.0 W/m*K (0.06-1.73 Btu/h*ft.*[degrees]R) to, respectively.
Table 3. PCM Properties PCM Property Value Density, [rho]: kg/[m.sup.3] (lb/f[t.sup.3]) 800 (50) Thermal conductivity, k W/m-K (Btu/h*ft*[degrees]R) 0.3 (0.17) Specific heat capacity, [C.sub.p]: J/g*K (Btu/lb) 1.6 (0.69) Onset phase-change temperature upon heating/cooling 22/23 [T.sub.e]: [degrees]C ([degrees]F) (72/73) Latent heat of fusion on heating, L: kJ/kg (Btu/lb) 110 (0.43)
Results are classified in two categories: effects of melting range and effects of thermal conductivity. Melting range is defined as the temperature difference between the start of the melting point during heating of the solid and the start of the crystallization point during cooling of the liquid. Crystallization temperature is always lower than the melting point. PCM was considered massless in all simulations.
Melting-Range Sensitivity: The melting point of the PCM is an important factor in absorbing/releasing heat from/to the building envelope. To analyze the sensitivity of the melting range, the conductivity of the PCM is fixed to a value of 0.3 W/m*K (0.17 Btu/h*ft*[degrees]R)Melting-range effects are investigated on energy demand.
To simulate the energy demand of the NZEB, the heating and cooling are considered unlimited to make the indoor air temperature (IAT) inside the setpoints (21[degrees]C [70[degrees]F], to start heating and 24[degrees]C [75[degrees]F], to start cooling). Figure 4 illustrates the effect of the melting range of the PCM on heating and total (cooling plus heating) energy demand of the NZEH. The range of 22[degrees]C-23[degrees]C (71.6[degrees]F-73.4[degrees]F (22-23) provides the minimum demand (about 35% savings with respect to no PCM), i.e., it is the best range. To investigate the effect of the amount of PCM, the PCM was eliminated from the mezzanine zone in the melting range of 23-24 (23-24 NM). This increased the energy by 22.11 kWh/yr (75,442 Btu/yr). Also, to check the reproducibility of the TRNSYS simulation, the 23-24 NM simulation was repeated (marked as Repeat on Figure 4) and the results were almost the same (less than 0.5% difference). Having said that heating, ventilation, and air conditioning (HVAC) systems keep the interior temperature of the zones between setpoints, the melting range of 25-26 is outside the setpoint range (21-24); therefore PCM acts as sensible material. When the sun shines, solar energy (heat) is stored in PCM as latent heat only if the melting range is inside the setpoints. This heat is released at night, which reduces the heating demand.
Figure 5 illustrates that peak power is not sensitive to melting range; although, reducing the amount of PCM reduces the cooling peak and increases the heating peak power (as simulation 23-24 NM stipulates). Conveniently, peak should be reduced by adding PCM into the envelope. Repetition of the simulation for no PCM reveals that peak is between 5 and 5.5 kW, and it always occurs at hour 7022 (mid-October) when there is no shading on windows.
Investigations of the daily power demand in summer (Figure 6) and winter (Figure 7) shows that the energy (hourly power) demand reduces by adding PCM. In addition, the energy demands per hour (power) fluctuations are closely related to ambient temperature fluctuations. The hourly power of PCM with 22-23 is completely overlapped with 21-22 and 23-24 in summer (Figure 6) and winter, respectively. That is why it is not shown as a separate plot in Figures 6 and 7.
In the winter, when the ambient temperature decreases to -6[degrees]C (21[degrees]F) the power demand (heating load per hour) increases to 2.3 kW (7848 Btu/h) (No PCM), showing a negative correlation (Figure 7). On the other hand, in the summer when the ambient temperature increases to 25[degrees]C (77[degrees]F) the power demand (cooling load per hour) increases to 2.6 kW (8872 Btu/h) (no PCM), showing a positive correlation (Figure 6). Practically, the simulations were run for no PCM and a different melting range from 20-26 (e.g., 21-22, 22-23). In Figures 6 and 7, only a few of the temperature ranges are shown because other ranges overlapped each other.
Thermal Conductivity Sensitivity: The thermal property of PCM (Table 3) was used to simulate the effects of thermal conductivity on energy demand and peak power of the NZEB (SUI). The NZEB was designed with high-quality materials. Because of the good insulation of the building, the temperature does fluctuate much in the garage (with no PCM).
Neither peak power nor annual load are sensitive to the thermal conductivity (Figure 8). Comparing the total annual load demand for the building with PCM of conductivity 0.14 W/m*K (0.08 Btu/h*ft*[degrees]R) with 1.39 W/m*K (increasing the thermal conductivity by about ten times) shows a reduction of about 2% load demand (Figure 9). The total energy demand (y) can be expressed as a function of the PCM conductivity (x) employing the best fit using the least squares method (y = 548[e.sup.-4.2x] + 7525). The best fit prediction of energy demand has a maximum difference of 0.3% from the true value.
SUMMARY AND DISCUSSION
For investigating the thermal conductivity effect, the melting range was fixed to the value given in Table 3 (i.e., 22[degrees]C-23[degrees]C). To investigate the melting-range effects, thermal conductivity was fixed and taken from Table 3.
The analysis of all simulations is quite difficult due to the amount of data generated. Therefore, only the main points are highlighted here.
Adding the PCM into the building envelope stores the solar energy during the day (as the latent heat) and releases it at night when the temperature goes lower than the melting temperature of the PCM (Figure 1). To take advantage of the latent-heat storage, the PCM melting range should be inside the setpoints range. Figure 4 shows that when the melting range is in the middle of the setpoints, the energy demand of the building is the lowest of all other options. Moreover, the amount of PCM has the effect on the energy demand. Comparing 23-24 with 23-24 NM shows that by decreasing the amount of PCM, the energy demand increases due to the lower storage capacity. While PCM has the melting range above or below the setpoints, it acts as sensible materials with constant specific heat capacity because the interior temperature is kept within setpoints. Figure 4 shows that annual energy demand in increasing order is: 22-23, 21-22, 23-24, 25-26, and 24-25.
Peak power is extracted from the maximum power demand in the whole year (8760 hours). Figure 5 reveals:
* Heating peak is higher when PCM is not used or is eliminated from the mezzanine.
* Cooling peak is reduced when the PCM is eliminated from mezzanine because in this zone there are about 33 [m.sup.2] (300 f[t.sup.2]) of windows that could have stored solar energy during the day and would increase the cooling load. In this zone with no PCM, 23-24 NM, not only the cooling peak but also the cooling load (see Figure 4) is the lowest of all. It seems that the no PCM case has the cooling peak slightly lower than PCM-incorporated envelope with the same reason.
* With the stated conditions, peak power is not sensitive to melting range.
In Toronto, the heating demand period (87% of the time in a year the ambient temperature is less than 20[degrees]C [68[degrees]F]) is longer than the cooling demand period; therefore, there is a chance of having higher heating peak increases while reducing the amount of PCM.
Although about a 2% reduction in energy consumption is seen with increasing thermal conductivity, when the condition PCM is added to the envelope (i.e., 10 mm [0.4 in.], in one layer), energy demand is not sensitive to thermal conductivity. In Figure 8, energy/peak versus PCM thermal conductivity is almost a horizontal line for k > 0.14 W/m*K (representative of lightweight plasters).
The Net-Zero Energy House was simulated using TRNSYS incorporated with PCM module of Type 204. The best melting range and thermal conductivity of the PCM were sought to determine the lowest energy demand. Considering the setpoints 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 22[degrees]C-23[degrees]C (71.6[degrees]F-73.4[degrees]F), which is in the middle section of the setpoints range. This provides 35% saving in the total annual energy demand. Although it is not worthwhile to work on thermal conductivity to achieve a maximum of 2% reduction in energy demand, higher thermal conductivity is preferred.
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., ten layers of 1 mm instead of one layer of 10mm).
This work was funded in part by the Smart Net-zero Energy Buildings Research Network (SNEBRN) under the Strategic Network Grants Program and Discovery Grant of the Natural Sciences and Engineering Research Council (NSERC) of Canada.
[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/[m.sup.2]K (Btu/h*f[t.sup.2]*[degrees]R)
H = total enthalpy
L = latent heat of fusion on heating, kJ/kg (Btu/lb)
k = thermal conductivity, W/m*K (Btu/h*ft*[degrees]R)
T = temperature, [degrees]C ([degrees]F)
[rho] = density, kg/[m.sup.3](lb/f[t.sup.3])
p = specific
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M. Ebrahim Poulad
Student Member ASHRAE
Alan S. Fung, PhD, PE
M. Ebrahim Poulad is a doctoral candidate and Alan S. Fung is an associate professor in the Mechanical and Industrial Engineering Department, Ryerson University, Toronto, Ontario, Canada.
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|Author:||Poulad, M. Ebrahim; Fung, Alan S.|
|Date:||Jan 1, 2013|
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