This is the peer reviewed author accepted manuscript (post print) version of a published work that appeared in final form in:

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1 Minimising energy usage for domestic cooling with off-peak PCM storage This is the peer reviewed author accepted manuscript (post print) version of a published work that appeared in final form in: Bruno, Francesco, Tay, Nguan Hwee Steven & Belusko, Martin 2014 'Minimising energy usage for domestic cooling with off-peak PCM storage' Energy and buildings, vol. 76, pp This output may not exactly replicate the final published authoritative version for which the publisher owns copyright. It is not the copy of record. This output may be used for non-commercial purposes. This version is licensed under a Creative Commons CC-BY-NC-ND 4.0 license ( The final definitive published version (version of record) is available at: Persistent link to the Research Outputs Repository record: General Rights: Copyright and moral rights for the publications made accessible in the Research Outputs Repository are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognize and abide by the legal requirements associated with these rights. Users may download and print one copy for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the persistent link identifying the publication in the Research Outputs Repository If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

2 NOTICE: This is the author s version of a work that was accepted for publication in Energy and Buildings. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in: Bruno, Frank et al (2014), Minimising energy usage for domestic cooling with off-peak PCM storage, Energy and buildings vol. 76, pp DOI: /j.enbuild

3 Minimising Energy Usage for Domestic Cooling with Off-peak PCM Storage F. Bruno*, N.H.S. Tay and M. Belusko Barbara Hardy Institute, University of South Australia, Mawson Lakes Boulevard, Mawson Lakes, South Australia 5095, Australia Frank.Bruno@UniSA.Edu.Au Abstract Achieving energy savings with domestic off peak air conditioning using phase change materials (PCMs) has always proved a challenge. Although the energy efficiency ratio of an air conditioner is higher during the night, this improvement often does not offset the exergy loss experienced when using thermal storage. Simulations have been conducted using the effectiveness-number of transfer units (ε-ntu) representation of a PCM system to determine the instantaneous heat transfer when coupled to an inverter chiller cooling system. Results show that although 85% of the energy consumption for cooling could be shifted to the off-peak period with an ice based system, the energy demand increased by 7.6%. The investigation demonstrated that by using a PCM with a melting point of 4 C, it is possible to achieve an energy saving for cooling. A savings of around 13.5% can be achieved using a PCM with a melting point of 10 C. Energy usage was increased with a more efficient PCM storage system. This unexpected result was due to which period the storage system was charged. A more efficient storage system charged quicker during the warmer part of the evening. Therefore energy minimisation requires optimal charging during the coldest part of the night. Keywords : Phase change material, Thermal storage, Energy efficiency, Space cooling

4 Abbreviations CFD EER ε-ntu HTF NTU PCM Computational fluid dynamics Energy efficiency ratio Effectiveness-number of transfer units Heat transfer fluid Number of transfer units Phase change material Nomenclature R T δ R HTF R WALL R PCM R i R o R max L H L h f k HTF k w k PCM Total thermal resistance (K/W) Thermal resistance of the HTF (K/W) Thermal resistance of the tube wall (K/W) Thermal resistance of the PCM (K/W) Inner radius of the tube (m) Outer radius of the tube (m) Radius of PCM when point of intersection with neighbouring phase change front (m) Length of the tube (m) Latent heat energy (kj/kg) Heat transfer coefficient of the HTF (W/(m 2 K)) Thermal conductivity of the HTF (W/(m K)) Thermal conductivity of the tube wall (W/(m K)) Thermal conductivity of the PCM (W/(m K)) Δδ Change in phase change fraction (-) Δt Change in time (s) δ Phase change fraction (-)

5 ε δ Heat exchanger effectiveness (-) Mass flow rate of HTF (kg/s) m μ Mass of PCM (kg) Dynamic viscosity of HTF (mpa s) ρ Density of HTF (kg/m 3 ) Cp Q c T htf,in T htf,out T a IP Specific heat of the HTF (kj/(kg K)) Cooling capacity (kw) Inlet temperature of the HTF ( C) Outlet temperature of the HTF ( C) Ambient air temperature ( C) Input Power (kw) I c Load correction factor for input power (-) I hp IP I Heat pump load (% of rated load) Corrected input power for the operating load (kw) 1. INTRODUCTION Worldwide the residential sector is a significant contributor to energy use [1, 2]. A large proportion of electricity consumption in homes is currently consumed for air conditioning, and furthermore there is a tendency for an increasing uptake of air conditioning by households. With the expectation of rising global temperatures in the future, the heavy reliance on the use of air conditioning in the residential sector is expected to continue and increase. Space cooling is also a major contributor to peak electricity load. Energy associated with this can be reduced by minimising the cooling load with better insulation systems [3] and more efficient cooling generating equipment such as indirect evaporative cooling systems [4].

6 Thermal storage can potentially reduce cooling energy in buildings by allowing the equipment that generates the cooling to operate during times when they run more efficiently. They can also be used to store cooling from air conditioning equipment when operating from a renewable energy source. Thermal storage also has financial benefits when the electricity is more costly during the peak as compared to the non-peak hours and it can also serve as a backup in the event of a breakdown of the cooling plant [5, 6]. Many countries are making use of thermal storage to shift the peak load to off-peak hours for air-conditioning demands [7 10]. These systems mostly use water or ice as the thermal storage media and are limited to commercial applications. A major drawback of ice based systems is they often do not achieve an energy saving [11]. Other phase change material (PCM) applications are limited due to the high cost of these systems, and the lack of clarity as to any energy savings achieved. Without extensive simulation it is not clear if off-peak storage can achieve an energy saving with PCMs. In previous research the authors have developed an effectiveness-number of transfer units (ε-ntus) method which can be used to characterise the heat transfer within PCM storage systems [6,12]. This method has the principle advantage of readily identifying the thermal performance of a PCM system in terms of heat exchange effectiveness. In previous research [13-15], the authors have extensively investigated a PCM storage system with a tube-in-tank type arrangement. Bulk storage of PCM generally achieves higher energy storage density and lower cost than encapsulated PCM. The effectiveness was demonstrated to be a function of the phase change fraction based on a one dimensional heat transfer between the heat transfer fluid (HTF) and the PCM at the phase change boundary. A computational fluid dynamics (CFDs) model of a tube-in-tank PCM system has been developed and validated through experimental results by Tay et al. [15,16]. This model confirmed that the heat transfer through the PCM is essentially one dimensional. Therefore, a mathematical model was developed by Tay et al. [12] and experimentally validated based on the average ε-ntu technique

7 for tubes in a phase change thermal energy storage system. This characterisation has been used to design a suitable PCM storage system for cooling a commercial building [17]. This analysis was based on determining the system size for a given phase change fraction. However, as presented by Belusko et al. [18], the effectiveness can determine the heat transfer at any phase change fraction, and therefore can be used to simulate the heat exchange over time. Consequently, it will be possible to investigate and design an off-peak cooling system which can achieve an energy saving, using the instantaneous effectiveness. A particular advantage of the ɛ-ntu method is that the impact of heat transfer improvements can be quickly identified. PCMs have a low thermal conductivity, and heat transfer improvements such as fins can improve heat transfer, however it has been difficult to identify whether the PCM system is actually better. Using the ɛ-ntu the impact of heat transfer improvements can be shown by applying an effective thermal conductivity to the PCM. A new concept of heat transfer enhancement for a tube-in-tank phase change thermal energy storage system has been investigated by the authors [19]. Melted paths in the frozen PCM are created using pre-melt tubes. This melted PCM is then recirculated using a pump. The flow of the melted PCM causes mixing and increases the overall heat transfer. This method achieves an effective conductivity of twice that of the liquid PCM. The ε-ntu method determines the thermal resistance independent of temperature. Natural convection is a function of the temperature difference experienced in the PCM liquid. However, over small temperature ranges a constant effective thermal conductivity is possible. Bedecarrats et al. [20] demonstrated this effect by determining an effective thermal conductivity for liquid water, when modelling the heat transfer of a thermal storage system with PCM encapsulated in spheres. A constant effective thermal conductivity of 1.1 W/m K was found.

8 This paper investigates the tube-in-tank PCM storage system for domestic space cooling applications. The ε-ntu technique is used along with building load, weather and chiller thermal performance data to carry out simulations to evaluate the thermal performance of a space cooling system with off-peak PCM thermal storage, investigating the conditions under which energy savings can be achieved. 2. Effectiveness-NTU technique A tube-in-tank thermal storage system is where the bulk of the PCM is in the tank and heat transfer fluid transfers the heat to the PCM through the tubes that are in the tank (Fig. 1). This arrangement of PCMs maximises the volume of PCM. When operating as an off-peak storage system, energy is stored in the PCM during the solidification or charging of the PCM and released from the PCM during the melting or discharging process. A PCM thermal storage system can be described as a heat exchanger with varying heat exchange effectiveness over the phase change process. The ε-ntu representation developed by Tay et al. [12, 15] was used to design the tube-in-tank phase change thermal energy storage system. This design has the advantage over traditional sphere in tank systems of having a high compactness factor. The compactness factor is the ratio of the PCM to total tank volume and typically is around 0.9 for shell and tube designs compared to 0.6 for sphere in tank designs [14]. The tube-in-tank PCM system under analysis is analysed as a single straight tube surrounded by a cylindrical volume of PCM with HTF flowing through the tube (Fig. 2). This is a one dimensional mathematical representation of the heat flow between the HTF and the PCM at the phase change profile. The number of transfer units (NTU) is determined from the thermal resistance to the heat flow within the HTF and the section of the PCM which has undergone phase change. The mathematical representation defines that the resistance in the PCM is assumed to be uniform along the length of the

9 tube (Fig. 2 (a)). The HTF flows inside the tubes of radius, Ri. Fig. 2 (b) shows the thermal circuit for the models. {Fig. 1} {Fig. 2} In order to formulate the effectiveness, the total thermal resistance, R T δ, needs to be determined and is given in Eqs. (1) and (2) where R HTF is the resistance of the HTF, defined by forced internal convection, R WALL is the resistance of the tube wall and R PCM is the resistance in the PCM, defined by conduction and the relevant conduction shape factor. The shape factor refers to the conduction between two concentric cylinders, representing heat flowing from the tube to the phase change front at the phase change temperature. This front will vary with time beginning at the tube wall and increasing to the maximum radius (R max ). This R max defines when the phase change front from one tube intersects the phase change front from a neighboring tube. (1) (2) Therefore, the heat exchanger effectiveness can be written in terms of R T δ : (3)

10 To determine the change in the phase change fraction and be able to simulate the instantaneous heat flow with time the phase change fraction can be related to the heat flow by Eq. (4). (4) Experiments using small and large shell and tube PCM tanks have been conducted by Tay et al. [12, 15] to validate the ε-ntu technique and a CFD analysis [15, 16]. The research demonstrated that the heat transfer in a shell and tube PCM tank is predominately a one-dimensional heat flow and the dominant resistance to heat transfer is in the PCM. The average ε-ntu technique was validated for the freezing and melting processes where natural convection is negligible. 3. Mathematical model The domestic cooling system in this study comprised of a chiller, PCM thermal storage unit and fan coil units (Fig. 3). The chiller provides cooling via a chilled heat transfer fluid to either the building through fan coil units or the PCM thermal storage unit. Cooling was assumed to be required in the building when the building load was greater than 2 kw, as smaller loads would be tolerable in the home. During the day cooling was provided by the PCM thermal storage unit, unless the PCM was fully melted in which case the cooling was provided directly by the chiller. If the PCM thermal storage unit was providing the cooling and the temperature of the heat transfer fluid returning from the building was more than 15 C then the chiller also cooled the building directly. During the off-peak hours between 22:00 and 07:00 hrs, if cooling was required by the building then the chiller would provide this directly. If cooling was not required during the off-peak hours then the chiller was used to charge the PCM storage unit.

11 {Fig. 3} The house considered was a newly built typical single storey Australian house. The house was located in Adelaide which has a semi mediterranean climate. The house has a concrete slab floor, with external brick walls internally insulated. The roof is pitched with insulation on the attic floor. The house is a 4-bedroom, 2-bathroom home with two living areas with a total floor area of 211 m 2, and a conditioned floor area of 169 m 2, 101 m 2 being the living zone. The house includes foil insulation in the roof, fans in the living zone, low emissivity (low-e) single glazed windows throughout the house, R4 (R value in m 2 K/W) insulation in the roof, R2 insulation within the external wall and R1.5 insulation in the internal walls. Hourly building load data for this house was obtained using the AccuRate TM household energy rating software [21]. Through preliminary simulations, it was found that a chiller with a rated cooling capacity of 12 kw was able to meet the cooling demand of the building. Cooling capacity and input power data for various operating conditions was obtained for a commercially available chiller with an inverter scroll compressor which matched this specification. This data was used to develop the following equations to calculate cooling capacity and power input: Q c = a + bt htf,out + ct a + d (T htf,out ) 2 + f(t a ) + g T htf,out T a (5) where a = 1.099E+01 b = 1.498E-01 c = E-01 d = 4.411E-03

12 f = E-04 g = 5.289E-03 and IP = a + bt htf,out + ct a + d (T htf,out ) 2 + f(t a ) + g T htf,out T a (6) where a = 4.424E-01 b = 1.219E-02 c = 9.690E-02 d = 3.411E-03 f = E-04 g = E-04 Since the chiller had an inverter compressor, a relationship needed to be developed to account for the variation in input power at different compressor loads. The following equation was developed from Tab. 3 in reference [22]: l c = a + b l hp + c l 2 hp (7) where a = 7.06E-01 b= 1.29E-02 c = -9.88E-05

13 The input power corrected for the operating load could then be calculated as follows: IP l = IP / l c (8) The load on the chiller will either come from the fan coil units in the building or the PCM tank. The outlet temperature of the HTF from the chiller when cooling the building is 7 C, and was fixed at 5 C lower than the PCM melting point when charging the PCM. The HTF used was a low temperature fluid used in chiller systems and has the following properties: specific heat, C p =2.68 kj/kg K, thermal conductivity, k HTF =0.495 W/m K, viscosity, µ=3.8 mpa s and density, ρ=1345 kg/m 3 [15]. The reference PCM was assumed to have properties of latent energy of 220 kj/kg, density of 1200 kg/m 3 and thermal conductivity of the solid PCM of 1.5 W/m K. An effective thermal conductivity of the liquid PCM of 1.2 W/m K was applied, which assumed that the storage system incorporated dynamic melting [19]. The tubes in the PCM unit were assumed to have an inner radius of m and outer radius of m. A total length of 250 m of tube was assumed for the base case. The energy for pumping the HTF through the fan coil units of the home was assumed to be 200 W. Simulations were carried out and a number of parameters were varied for the PCM, namely the melting point, mass, effective thermal conductivity of the liquid PCM and the thermal conductivity of solid PCM. The commencement time of the off-peak period was also varied as well as the mass flow rate of the HTF. 4. RESULTS AND DISCUSSION The total annual energy consumption was first determined for a base case using the 12 kw chiller with

14 no PCM storage unit. The heat transfer fluid from the chiller (T htf,out ) was assumed to be at 7 C. With the base case, anytime the building load was above 2 kw the chiller would be operating to meet the load. Once the base case was evaluated, simulations were first carried out for different melting temperatures, assuming a total PCM mass of 1500 kg. Results from these simulations are presented in Tab. 1. {Tab. 1} The first row shows the annual energy consumption for the cooling system with no thermal storage unit, being kwh. For the simulations incorporating thermal storage, the off-peak rate was from 22:00 to 07:00 hrs, and the peak rate all other hours. The design of the appropriate heat transfer area to achieve sufficient heat transfer was based on varying the tube length. The tube length in the PCM storage unit was determined by increasing it until most of the cooling load could be generated by the chiller during the off-peak period. A minimum tube length of approximately 250 m was required to do this, and so this was set as the reference tube length. After the annual energy consumption of the base case was determined, simulations were carried out with the PCM thermal storage system incorporated with the cooling system. The results in the second row of Tab. 1 correspond to the cooling system using ice for thermal storage. The energy consumption is higher (712.1 kwh) than the base case as the chiller needs to provide lower temperature HTF to freeze the ice, and this was not offset by the increased energy efficiency ratio (EER) through charging at lower outdoor temperatures during the night.

15 Tab. 1 shows that for a fixed tube length of 250 m in the thermal storage unit, as the melting or freezing temperature of the PCM is increased, the energy consumption is reduced. This is because the chiller is able to provide higher HTF temperature to freeze the PCM, resulting in a higher EER. A PCM with a melting point of 4 C or above will save energy in comparison to the base case which has no storage. A larger tube length increases the charging and discharging average effectiveness. However, surprisingly, for the 10 C PCM, increasing the tube length from 250 to 400 m was found to increase energy usage from to kwh, representing an increase of around 4.2%. Upon detailed inspection of the hourly data it was identified that with the more effective PCM system, the chiller was able to charge the PCM much faster in the earlier part of the off-peak period. This period coincides with higher ambient temperatures relative to later periods in the off-peak period, resulting in lower average EER. Fig. 4 presents an example period. This figure shows the expected increase in EER as ambient temperatures reduce from 21:00 until 06:00 hrs. With a more effective PCM system, it is clear that the average EER is lower. The figure also shows the state of charge of the PCM unit for 250 and 400 m tubes, where 0 and 1 represents a fully melted and frozen state, respectively. It can be seen that with 400 m of tubes, the PCM is fully frozen at 03:00 hrs. With 250 m of tubes, the PCM is fully frozen later at approximately 06:00 hrs. This result demonstrates that a more efficient PCM thermal storage unit with a higher effectiveness does not necessarily translate to a more energy efficient cooling system overall. The annual energy consumption of the cooling system could be minimised by modifying the control system for charging the PCM to take advantage of cooler outdoor conditions during the night. Tab. 2 shows the effect of starting the charge process from 22:00, 23:00 and 00:00 hrs. The total energy consumption reduces as the starting time is delayed, as more of the cooling is generated during the morning hours when ambient temperatures are lower. This demonstrates that if the state of charge is known at the end of the peak period, the energy consumption

16 can be minimized by optimally charging during the night when ambient temperatures are at their minimum. {Fig. 4} {Tab. 2} Fig. 5 shows the effect of increasing the mass of PCM for tube lengths of 250 m and 400 m. A PCM with melting and freezing point of 10 C was assumed. As the mass of the PCM increases, the total annual energy consumption reduces however the reduction is minimal after 1000 kg of PCM. The figure also shows that as the tube length is increased from 250 to 400 m, more of the cooling load is shifted to the off-peak hours. These results are consistent with the expected impact of the effectiveness of the PCM system. With larger PCM volumes, the thermal resistance of the PCM increases, reducing the effectiveness. Therefore at some point, the additional storage capacity cannot be accessed as the effectiveness is very low delivering very low heat transfer rates. With an increased heat transfer area, the effectiveness increases, and therefore more heat transfer can be used within the PCM storage vessel. As a result the amount of cooling achieved through off-peak charging of the PCM system is higher for the 400 m tube than the 250 m tube. {Fig. 5} Fig. 6 shows the effect of increasing the effective thermal conductivity of the liquid PCM, assuming 1000 kg of PCM. As the liquid thermal conductivity is increased up to 1.2 W/m K, the total annual energy is reduced from kwh down to kwh, representing a reduction of approximately 6.2%. Increasing the thermal conductivity further has little effect on the electricity consumption. This

17 figure also shows that the liquid thermal conductivity has a significant effect on the ratio of peak to off-peak electrical load. With a liquid thermal conductivity of 0.6 W/m K, the off-peak and peak electricity consumption was and kwh, respectively, and with a liquid thermal conductivity of 1.5 W/m K the off-peak and peak electricity consumption was and kwh, respectively. Hence the off-peak energy increased by 14.4% and the peak electricity consumption reduced by 36.6%. Increasing the liquid thermal conductivity reduces the thermal resistance in the PCM, therefore increasing the overall effectiveness. A higher effectiveness during discharging results in more of the cooling load being met by the PCM storage system. With more discharging, conversely more charging will occur during off peak. {Fig. 6} Fig. 7 shows that increasing the thermal conductivity of the solid PCM increases the total annual energy consumption. Increasing the solid thermal conductivity increases the effectiveness during charging. Consequently, similar to an increased tube length, more of the charging occurs during the earlier part of the off-peak period when ambient temperatures are higher and the EER of the chiller is lower. With a solid thermal conductivity of 1.5W/m K, the off-peak and peak electricity consumption was and kwh respectively, and with a solid thermal conductivity of 4.0 W/m K the off-peak and peak electricity consumption was and kwh, respectively. So the peak electricity usage reduced by 2.9%, the off-peak electricity increased by 8.2% and the total electricity increased by 5.6%. Similarly to an increased liquid thermal conductivity, an increased solid thermal conductivity increased the amount of charging, enabling more discharging to occur during the day, shifting more of the cooling to off peak. {Fig. 7}

18 Fig. 8 shows the effect of increasing the mass flow rate of the HTF. As the mass flow rate is increased, the total energy consumption reduces. An increased mass flow rate increases the amount of charging and discharging that can be achieved. It is expected that higher mass flow rates reduce the heat exchange effectiveness, which ultimately would result in higher discharge outlet temperatures from the PCM unit going into the building. At temperatures above 15 C, additional cooling is required by the chiller which would increase energy consumption. Over the range considered this effect was limited, and energy consumption consistently reduced. A mass flow rate of less than 0.75 kg/s results in a large amount of electricity to be consumed during the peak period. At these low mass flow rates, insufficient discharging was occurring and therefore the PCM storage system was being underutilised. {Fig. 8} 4. CONCLUSION A simulation was conducted of a domestic chiller with an inverter driven scroll compressor incorporating an off-peak PCM thermal storage unit. The PCM was successfully modelled using the ε-ntu technique to determine the instantaneous heat transfer. The model was able to identify the factors which affect the day-time peak demand and energy savings that can be achieved with off-peak PCM storage. In this study it was found that although 85% of the energy consumption for cooling could be shifted to the off-peak period with an ice based system, the energy demand increased by 7.6%. The investigation demonstrated that by using a PCM with a melting point of 4 C, it is possible to achieve an energy saving for cooling. A savings of around 13.5% can be achieved with a melting point of 10 C. It was demonstrated that charging during the coldest part of the night is critical to minimizing the energy consumption of the system. Increasing the thermal conductivity of the

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