Energy conservation and thermal environment analysis of room air conditioner with intermittent supply airflow

Energy conservation and thermal environment analysis of room air conditioner with intermittent... Abstract In zero energy houses, heating load would be reduced sharply during winter, as its building envelope is highly insulated. The normal compressor is triggered by a low load operation leading to more frequent on–off cycling. This paper presents a novel control algorithm named fan intermittent operation, for the indoor unit of room air conditioner removing the compressor on–off cycling under low load condition and to provide stable warm air to satisfy the task of local domain with extremely low compressor frequency. Based on periodic variation control of condensing temperature, a 5% energy saving rate can be established under the winter condition simulation. 1 INTRODUCTION The Japanese government has set stringent target to reduce greenhouse gas emissions by 26% by 2030 and 50% by 2050 [1]. Up to 24% of the energy consumption is attributed to residential house [2], hence, to improve the energy performance in housing is essential to achieving the energy saving goal. Subsequently, in zero energy houses, also known as net zero energy houses, where the heating load is reduced sharply during winter period due to higher insulation incorporated in the building envelope. In the conventional situation, the inverter compressor of the room air conditioner operates on–off cycling automatically during the compressor processing. Often the compressor is operated intermittently due to thermostatic control under the low heating load conditions, and this has a negative effect on the energy saving. The coefficient of performance (COP) could be degraded by ~2.5% while the on–off cycling [3] and rapidly on–off cycling would definitely shorten the compressor life [4]. Furthermore, two basic concepts of typical temperature-based on–off cycling summarized by Koestel [5] were dominant for the compressor cycling control. One is to shut the compressor off and turn it on after additional certain minutes on the basic of timer-based controller but indoor fan would continue running until the set room thermostat temperature is attained. The other is required to substitute for the above timer criteria; the compressor is cut-off when the return air exceed a certain temperate against the set temperature in the heating mode, and cut-in when the return air temperate is below a the set temperature. Due to on–off cycling, indoor thermal environment could suffer large fluctuation, and hence leading to less comfortable level for building occupants [4]. In addition, the heat exchangers (evaporator and condenser) are practically inactive during off-cycles; that the heat generated could exceed the heat exchanger thermal time constant, and this could cause very high-pressure lift during a large portion of the on-cycle and thus produce a low COP efficiency. This article presents a novel control algorithm, a fan intermittent operation (FIO) for an indoor unit of a room air conditioner, to remove the compressor on–off cycling under low heat load condition. In comparison to the conventional compressor on–off cycle, FIO control algorithm would maintain operation of the compressor at limited low frequency consecutively and applying fan cycles on and off intermittently in an indoor unit for establishing the condensing temperature (CT). A 4°C differential between the cut-in and cut-out points was set in our proposed method as detailed in this article. Once the CT exceeds the temperature threshold, the indoor unit fan is set to start. While, when the CT is below the set temperature, the fan of the indoor unit is regulated to stop. This algorithm can provide stable warm air in heating mode with extremely low compressor frequency, compared to the conventional compressor on–off cycling. 2 NON-ISOTHERMAL AIR JET 2.1 Minimum heat capacity for room air conditioner Generally, an air jet is called a non-isothermal jet when the jet temperature differs from the ambient. A common problem for room air conditioner in the heating mode is that supply air (SA) jet, with a high temperature (20°C differs from ambient) and low velocity, unexpectedly rise-up due to the buoyancy effect. However, increase the SA velocity at the same compressor frequency would deteriorate the CT, which would lead to a consequential reduction of the SA temperature. The experimental investigations studied round turbulent vertical buoyant jets were declared by Papanicolaou in [6], as a cognitive understanding, the jet length or terminal velocity of the non-isothermal jet is relevant to supply velocity (SV), and temperature difference between SA and the ambient. A zero energy house with a relatively smaller temperature difference between SA and the ambient would basically trade-off between the SA temperature and velocity; which is the key to provide a better indoor environment with lower energy consumption. Kubota [7] created the air jet trajectory asymptotic equations on the basic of the air jet momentum conservation; these are shown in Table 1. Table 1. Trajectory asymptotic equations. Momentum and heat conservation equation  dd (sh )(tanθ)=2λArKΔtmΔtosh1cosθ0  um2scosθ=KHouo2cosθo  dd(s)(umΔtms)=−(1+λ)umsdteds  Ar=gβ∆toHouo2  Asymptotic equation for velocity and temperature  umuo= [1+λλKAr ]1/3UΔtmΔto=1+λ2 [λ1+λKAr ]1/3T  U ≅ 1 T≅Y/Yv ( Yv: virtual origin of coordinates)  Trajectory asymptotic equation  Y=415 (Xcosθ )52+tanθoX  xHo= [λ1+λKAr2 ]1/3X,yHo= [λ1+λKAr2 ]1/3Y  Momentum and heat conservation equation  dd (sh )(tanθ)=2λArKΔtmΔtosh1cosθ0  um2scosθ=KHouo2cosθo  dd(s)(umΔtms)=−(1+λ)umsdteds  Ar=gβ∆toHouo2  Asymptotic equation for velocity and temperature  umuo= [1+λλKAr ]1/3UΔtmΔto=1+λ2 [λ1+λKAr ]1/3T  U ≅ 1 T≅Y/Yv ( Yv: virtual origin of coordinates)  Trajectory asymptotic equation  Y=415 (Xcosθ )52+tanθoX  xHo= [λ1+λKAr2 ]1/3X,yHo= [λ1+λKAr2 ]1/3Y  Where g is the gravity force; h is the slot width; K is the outlet constant; S is the coordinates in the direction perpendicular to the central axis of the airflow; te is the airflow temperature; teo is the surrounding temperature; to represents the supply inlet temperature; tm is the mainstream temperature, △tm = te− tm △to = teo− to; U is the velocity; Uo is the original velocity; Um is the mainstream velocity; Ar is the Archimedes number; β is the coefficient of expansion; λ is the diffusion coefficient; and ρ is the density. These equations were based on the following assumptions: the air entrained by the jet is at room air temperature; the only force opposing the downward flow of the heated air or upward flow of the cooled air is a buoyancy force; velocity profile and the temperature difference profile have shapes that can be approximated by an error function-type curve. The direction of the SA jet θ is one of the key factors resulting in the different jet trajectories. In this study, we set the θ as −70° (downwards to the floor). As shown in Figure 1, SA temperature (T, °C) of the warm air jet is fixed at constant value of 35 and 14°C which are different from the ambient (21°C). Along with different air SV (V, m/s), air jet against the buoyancy force is directly proportional to SV and the trajectory of the air jet fall further. Nevertheless the length of air jet trajectory is inversely proportional to SA on the same SV (like Figure 2). The larger the temperature difference between the SA and ambient is, the shorter would be the length of the air jet could reach. Figure 3 indicates the mean temperature of the air jet, which declines sharply with a higher SA. Figure 4 shows the relationship between air jet supply temperature and velocity at different compressor frequency. In this article, we trade off the SA and SV to determine the minimum constant compressor (COMP) frequency for the conventional thermostatic control (stroke volume of testing COMP is 17.2 ml), namely, the appropriate SA temperature is determined on the condition that the air jet is arrived at the floor surface (2 m height). According to KUBOTA equations, a 37°C SA would be different to ambient temperature by ~15°C, which would enable the air jet either more or less to reach a vertical length of 2 m with a constant SA flow rate. Figure 1. View largeDownload slide Air jet trajectories with different supply velocity. Figure 1. View largeDownload slide Air jet trajectories with different supply velocity. Figure 2. View largeDownload slide Air jet trajectories with different supply temperature. Figure 2. View largeDownload slide Air jet trajectories with different supply temperature. Figure 3. View largeDownload slide Air jet temperature distribution with different SA. Figure 3. View largeDownload slide Air jet temperature distribution with different SA. Figure 4. View largeDownload slide Relationship between SA and SV. Figure 4. View largeDownload slide Relationship between SA and SV. 2.2 Fan intermittent operation Compressor cycling, 2–5 min breaks of on and off times, repeating when the inverter compressor approaches the mechanical bottom frequency. In heating mode, since indoor temperature rises around the setting temperature, on–off cycle of the compressor occurs to keep a relatively stable indoor thermal environment, basically we call thermostatic control. The pressure lift (difference between condenser and evaporator saturation pressure) would fluctuate as the results of the on–off cycling. Basically, the higher the pressure lift, the higher the compressor work required for compressing a unit of refrigerant mass. Against this compressor thermostatic cycle, FIO control algorithm is keeping the compressor, operating at limited low frequency consecutively and applying fan cycles on and off intermittently in the indoor unit for establishing the refrigerant CT. This algorithm details the interrelationship between the control of CT and task zone temperature. Once the CT has exceeded a certain temperature threshold, the indoor unit fan would start to operate. While, when the CT is below the set threshold value, indoor unit fan would stop. The algorithm is capable to provide a dynamically adaptable indoor environment to raise thermal comfort of human occupants (Figure 5). Figure 5. View largeDownload slide Schematic of FIO air jet distributions. Figure 5. View largeDownload slide Schematic of FIO air jet distributions. 3 DYNAMIC SIMULATION 3.1 Field test set up The field test was carried out in a 2-storey residential house located in Kanagawa prefecture, Japan. The house was classified as highly insulated dwelling. The floor area of the living room was 69.5 m2, and the height was 2.6 m. Double-glazed windows were installed on the southern wall of the living room. Room air conditioner (Mitsubishi Electric MSZ-ZW805-W) was wall mounted at 2 m height above the floor. The rated capacity of RAC was 8.0 kW for cooling and 9.0 kW for heating. Experimental conditions are illustrated in Table 2. Specifications of the test refrigeration cycle are summarized in Table 3. Table 2. Experimental conditions. Outdoor air temperature [°C]  15.6  Setting temperature [°C]  24  Outdoor fan airflow rate [m3/min]  21.5  Indoor fan airflow rate [m3/min]  11  Outdoor air temperature [°C]  15.6  Setting temperature [°C]  24  Outdoor fan airflow rate [m3/min]  21.5  Indoor fan airflow rate [m3/min]  11  Table 3. Specifications of the test refrigeration cycle. Elements  Specification  Refrigerant  R32  COMP  Type: rotary  Stroke volume: 17.2 ml  Condenser  Type: plate fin and tube  Rated capacity: 9.0 kW  Heat transfer area: m2 (refrigerant side) m2 (air side)  Evaporator  Type: plate fin and tube  Rated capacity: 8.0 kW  Heat transfer area: m2 (refrigerant side) m2 (air side)  Gas pipe  Length: 5 m  Liquid pipe  Length: 5 m  Elements  Specification  Refrigerant  R32  COMP  Type: rotary  Stroke volume: 17.2 ml  Condenser  Type: plate fin and tube  Rated capacity: 9.0 kW  Heat transfer area: m2 (refrigerant side) m2 (air side)  Evaporator  Type: plate fin and tube  Rated capacity: 8.0 kW  Heat transfer area: m2 (refrigerant side) m2 (air side)  Gas pipe  Length: 5 m  Liquid pipe  Length: 5 m  According to KUBOTA equations (as shown in Table 1), in order to provide a 37°C SA, which would enable the air jet to reach a vertical length for 2 m, the compressor frequency hence was set as 23 Hz corresponding to the minimum heating capacity during the on-cycling:   Qref=Gr×(Hin−Hout) (1)  Qair=cp×ρ×(TRA−TSA) (2)  Gr=Vst×Fz×ρ×ηv (3)  COP=QW (4)where Qref is the heat exchange capacity in the refrigerant side, Qair is the heat exchange capacity in the air side, Gr is the refrigerant flow rate, TSA is the SA temperature, TRA is the return air temperature, Hin is the inlet enthalpy, Hout is the outlet enthalpy, Vst is the compressor stroke volume, cp is heating capacity, ρ is the density of refrigerant, Fz is the compressor frequency, ηv is the volumetric efficiency, W is the power consumption and COP is the coefficient of performance. Testing points of the device are illustrated in Table 4. The temperatures, compressor frequency, and power were measured throughout the facility. The air side supply and return temperatures, refrigerant side temperatures were measured by T-type thermocouples. The uncertainty in thermocouple measurement was estimated to be 0.5°C. The temperatures were continuously monitored at 1 min intervals at each testing point. Table 4. Testing points. Elements  Testing item  Unit  COMP  Frequency  Hz  Power consumption  W  Suction temp  °C  Discharge temp  °C  Indoor unit  Supply air temp  °C  Return air temp  °C  Indoor HEX  Condensing temp  °C  Intel temp  °C  Outlet temp  °C  Outdoor HEX  Evaporating temp  °C  Intel temp  °C  Outlet temp  °C  Elements  Testing item  Unit  COMP  Frequency  Hz  Power consumption  W  Suction temp  °C  Discharge temp  °C  Indoor unit  Supply air temp  °C  Return air temp  °C  Indoor HEX  Condensing temp  °C  Intel temp  °C  Outlet temp  °C  Outdoor HEX  Evaporating temp  °C  Intel temp  °C  Outlet temp  °C  3.2 Dynamic simulation Figure 6 illustrates the schematic of a refrigeration system, which consists of: evaporator, compressor, condenser, linear expansion valve (LEV) fans and piping. Refrigeration cycle repeated the evaporation, condensation of refrigerant to exchange heat between indoors and outdoors. Generally, the dynamic simulation was based on the following conservation equations [8]. Equations (5–8) describe mass balance, energy balance of each control volume such as evaporator, condenser, LEV, pipes (elements required for our dynamic simulation) and the parameters were measured at each point is shown in Figure 6. Figure 6. View largeDownload slide Refrigeration system. Figure 6. View largeDownload slide Refrigeration system. The dynamic simulation would produce convergence when all elements and points become converge independently. The change of evaporator temperature is a function of the air side and refrigerant side heat transfer rate. Our dynamic simulation was based on the following assumptions. The resistance of the copper and aluminum to internal heat conduction was assumed to be small compared to convective resistance of the air side heat transfer. Gravitational potential energy and kinetic energy of refrigerant were ignored in the simulation, namely, the refrigerant thermal energy was generated by enthalpy difference between the inlet and outlet of heat exchanger. Convective heat transfer coefficient and frictional loss were assumed at steady state condition. The momentum change and the acceleration loss were ignored as being assumed to be small compared to frictional loss. The calculation time step in dynamic simulation was one second. Mass conservation equation:   ΔMΔt=Gin−Gout (5) Momentum conservation:   Δ(Mu)Δt=Ginuin−Goutuout+Ap(Pin−Pout−ΔPf) (6) Energy conservation:   ΔEΔt=GinIin−GoutIout−Q (7)where   Q=Aref⋅αref⋅(T−Tw)=Gair⋅(Iwair−Iairin)⋅{1−exp(−αairi⋅AairGair)}Wetcondition=Gair⋅(Tw−Tairin)⋅{1−exp(−αairt⋅AairGairCpair)}Drycondition (8)where M is the refrigerant mass, G is the refrigerant mass flow rate, u is the velocity, A is the heat exchange area, P is the pressure, Q is the heat exchange rate, E is the energy, Iw represents humidity of saturated enthalpy, Tw represents temperature of heat exchanger, αair is the convective heat transfer coefficient of airflow and αref is the convective heat transfer coefficient of refrigerant flow. 3.3 Model validation using the experimental measurements The validity of the model was checked by comparing it with the experimentally obtained condenser and evaporator temperatures during the on and off-cycle. The compressor efficiency and heat exchanger (HEX) conventional heat transfer coefficient were adjusted to match the heating capacity of the real machine. Furthermore, the expansion valve (LEV) pulse and sub cool (SC) and super heat (SH) temperatures were determined by the steady state simulation to match the refrigeration cycle. Then, we modulated the thermal capacity of the heat exchanger and fixed the on and off period (3 min 30 s ON→3 min OFF), according to the on–off cycling testing data. As illustrated in Figure 7, results from our dynamic simulation were in accordance with the field test data, which were taken into full consideration, as the condensing pressure and the evaporate pressure were matched to on-cycling field test data during the operation period. Regarding the variable-capacity compressors, we redefined the baseline of compressors frequency, such as 23 Hz as appropriate in this case. The COMP efficiency was adjusted to as 0.757. To avoid the divergence during the off-cycle, 1 Hz is fixed in the dynamic simulation. The average heating capacity was 1.4 kW per period and energy consumption was 197.6 W per period. Figure 7. View largeDownload slide On–off cycling model validations (field testing vs simulation). Figure 7. View largeDownload slide On–off cycling model validations (field testing vs simulation). 3.4 Evaluating FIO performance As illustrated in Section 2.2, FIO control algorithm would keep the compressor operating at limited low frequency (nearly half of the COMP frequency of conventional thermostatic cycling), consecutively and provide sequential warm air by interrogating the CT which was established as a result of the indoor fan on and off intermittent operation. In order to keep the same assessment premise for comparison with conventional thermostatic model, our dynamic simulation for the FIO control algorithm was modulated with the compressor frequency to realize the same heating capacity (~1.4 kW). The FIO simulation conditions are presented in Table 5. The conditions of elements are as shown in Table 3 Table 5. FIO simulation conditions. Compressor frequency [Hz]  11  Condensing temperature oscillations [°C]  39.0 ⇔ 35.0 (≒37)  Heating capacity [kW]  1.4  Outdoor air temperature [°C]  15.6  Indoor air temperature [°C]  24.3  Outdoor fan airflow rate [m3/min]  21.5  Indoor fan airflow rate [m3/min]  11  Compressor frequency [Hz]  11  Condensing temperature oscillations [°C]  39.0 ⇔ 35.0 (≒37)  Heating capacity [kW]  1.4  Outdoor air temperature [°C]  15.6  Indoor air temperature [°C]  24.3  Outdoor fan airflow rate [m3/min]  21.5  Indoor fan airflow rate [m3/min]  11  As the basic concept of FIO control algorithm, compressor frequency was fixed at 11 Hz then indoor fan was set to on–off operation. Here we assumed the supply temperate was equivalent to the CT. The mean CT per whole cycle was kept the same as the conventional thermostatic control, in which the average on-cycling was ~37°C, at the CT. Figure 8 shows the dynamic simulation results of FIO control algorithm. The average heating capacity was 1406 W per period and energy consumption was 197.2 W per period. Figure 8. View largeDownload slide Dynamic simulation results of FIO control algorithm. Figure 8. View largeDownload slide Dynamic simulation results of FIO control algorithm. 4 RESULTS AND DISCUSSION Figure 9 shows the comparison between conventional on–off cycling and FIO control. A 5% energy saving was yielded from a 2°C difference between the ET generated from the FIO control algorithm and the conventional control algorithm. In case of the conventional control, refrigerant flow rate (Gr) was proportional to COMP frequency (Fz) base on equation (3), and also had positive relationship with heating capacity according to equation (1), hence, the 23 Hz COMP frequency would provide a larger heat exchange capacity in the on-cycling, which resulted in a larger temperature difference between ET and outdoor temperature. Different saturation pressure of the evaporator between the conventional on–off cycling and FIO control was resulted from the different compressor frequency (refrigerant flow rate). Figure 9. View largeDownload slide Comparison between conventional on–off cycling and FIO. Figure 9. View largeDownload slide Comparison between conventional on–off cycling and FIO. The expansion valve (LEV) would ensure even pressure condition during the off-cycle, which mix thermal energy to trigger the entropy increase and had resulted in energy loss in the conventional on–off refrigeration cycling. In addition, the refrigerant was unevenly and inappropriately distributed at each part of the conventional on–off cycling, compared to sequence operation by FIO control algorithm. To re-move stagnate refrigerant and reprocess pressure difference at the start of the on-cycle, an addition work is needed in quantifying cyclic loss in the refrigeration system. Furthermore, the mean CT of the on-cycle is different from the mean CT of the whole cycle; which depends on the thermal capacitance of the heat exchangers. Since the SA temperature follows the oscillations of the refrigerant saturation temperatures (CT), thus, the FIO control algorithm can provide relatively higher and successive SA to maintain a better well-being of occupants and a more comfortable environment for the task zone as compared to the conventional thermal on–off control algorithm. Table 6 summarizes the comparison between conventional thermostatic control and FIO control algorithm. The energy consumption of FIO control algorithm was 197.2 W per period base on fixed compressor frequency (11 Hz), and the energy consumption of conventional control algorithm was 197.6 W per period (on–off cycling 23 Hz ⇔ 1 Hz), and a total of 5% energy saving rate for the whole unit can be yielded. Table 6. Comparison between conventional thermostatic control and FIO control algorithm. Item  Normal symbols  Unit  Conventional control algorithm  FIO control algorithm  COMP frequency  Hz  Hz  23.0 ⇔ 1.0  11.0  Indoor fan airflow rate  V  m3/min  11.0  11.0 → 0.1  Condensing temperature  CT  °C  38.6 → 22.9 (≒37 on-cycling)  39.0 ⇔ 35.0 (≒37)  COMP ON–OFF period  COMP—ON/OFF    3 min 30 s ON → 3minOFF  –  Indoor fan ON–OFF period  FAN—ON/OFF    –  50 s ON→ 45 s OFF  Cycle period   Heating capacity  Q  W  1400  1406   Power consumption of COMP  Pcomp  W  198  197   Power consumption of indoor fan  Pfan_in  W  14  7   Power consumption of outdoor fan  Pfan_out  W  15  15   Total power consumption  P  W  227  218   Energy saving rate  –  %  –  5%  Item  Normal symbols  Unit  Conventional control algorithm  FIO control algorithm  COMP frequency  Hz  Hz  23.0 ⇔ 1.0  11.0  Indoor fan airflow rate  V  m3/min  11.0  11.0 → 0.1  Condensing temperature  CT  °C  38.6 → 22.9 (≒37 on-cycling)  39.0 ⇔ 35.0 (≒37)  COMP ON–OFF period  COMP—ON/OFF    3 min 30 s ON → 3minOFF  –  Indoor fan ON–OFF period  FAN—ON/OFF    –  50 s ON→ 45 s OFF  Cycle period   Heating capacity  Q  W  1400  1406   Power consumption of COMP  Pcomp  W  198  197   Power consumption of indoor fan  Pfan_in  W  14  7   Power consumption of outdoor fan  Pfan_out  W  15  15   Total power consumption  P  W  227  218   Energy saving rate  –  %  –  5%  5 CONCLUSION This article presents a novel control algorithm FIO for the indoor unit of the room air conditioner, to remove the compressor on–off cycling under low load condition. The results show that FIO control algorithm can provide a better well-being of occupants and a more comfortable environment for the task zone compared to conventional thermal on–off control algorithm. A 5% energy saving would be yielded in the heating mode from an ~2°C difference in the evaporating temperature due to the smaller refrigerant flow by FIO control algorithm. In addition, cycling loss would basically occur during COMP cut-in and cut-out running, and refrigerant would become unevenly and inappropriately distributed at each part of the conventional on–off cycling, compared to sequence operation by FIO control algorithm. In the dynamic simulation, the cycling loss such as the overshot of the starting current was not taken into account. The total power consumption could effectively be increased in the real operation. Finally, FIO control algorithm can provide relatively higher and successive SA to maintain a better well-being of occupants and a more comfortable environment for the task zone compared to conventional thermal on–off control algorithm. REFERENCES 1 Strategy for energy conservation of Japan 2016. Ministry of Economy, Trade and Industry. Renewable Energy Department (in Japanese). 2 International Panel on Climate Change (IPCC) 2013. 3 Coulter WH, Bullard CW. An experimental analysis of cycling losses in domestic refrigerator-freezers. ASHRAE Trans  1997; 103: 587– 96. 4 Llic SM, Bullard CW. Effect of Shorter Compressor On/Off Cycle Times on A/C System Performance. Air Conditioning and Refrigeration Center CR-43, 2001. http://hdl.handle.net/2142/13401. 5 Koestel A. Computing temperatures and velocities in vertical jet of hot and coal air. Trans Am Soc Heat Ventilat Eng  1954; 1512: 385– 410. 6 Papanicolaou NP, List E. Investigations of round vertical turbulent buoyant jets. J Fluid Mech  1988; 195: 341– 91. Google Scholar CrossRef Search ADS   7 Kubota H. Analysis of inclined buoyant jets. Int J Trans Soc Heat Air-Condition Sanitary Eng  1987; 2: 85– 95. (in Japanese). 8 Unezaki F, Matsuoka F. A dynamic model of a vapor compression refrigeration cycle using zeotropic refrigerant mixtures—1st report: a versatile model for zeotropic refrigerant mixtures. Int J Trans Jpn Soc Refrig Air-Condition Eng  2001; 18: 321– 30. (in Japanese). © The Author(s) 2018. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Low-Carbon Technologies Oxford University Press

Energy conservation and thermal environment analysis of room air conditioner with intermittent supply airflow

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Abstract

Abstract In zero energy houses, heating load would be reduced sharply during winter, as its building envelope is highly insulated. The normal compressor is triggered by a low load operation leading to more frequent on–off cycling. This paper presents a novel control algorithm named fan intermittent operation, for the indoor unit of room air conditioner removing the compressor on–off cycling under low load condition and to provide stable warm air to satisfy the task of local domain with extremely low compressor frequency. Based on periodic variation control of condensing temperature, a 5% energy saving rate can be established under the winter condition simulation. 1 INTRODUCTION The Japanese government has set stringent target to reduce greenhouse gas emissions by 26% by 2030 and 50% by 2050 [1]. Up to 24% of the energy consumption is attributed to residential house [2], hence, to improve the energy performance in housing is essential to achieving the energy saving goal. Subsequently, in zero energy houses, also known as net zero energy houses, where the heating load is reduced sharply during winter period due to higher insulation incorporated in the building envelope. In the conventional situation, the inverter compressor of the room air conditioner operates on–off cycling automatically during the compressor processing. Often the compressor is operated intermittently due to thermostatic control under the low heating load conditions, and this has a negative effect on the energy saving. The coefficient of performance (COP) could be degraded by ~2.5% while the on–off cycling [3] and rapidly on–off cycling would definitely shorten the compressor life [4]. Furthermore, two basic concepts of typical temperature-based on–off cycling summarized by Koestel [5] were dominant for the compressor cycling control. One is to shut the compressor off and turn it on after additional certain minutes on the basic of timer-based controller but indoor fan would continue running until the set room thermostat temperature is attained. The other is required to substitute for the above timer criteria; the compressor is cut-off when the return air exceed a certain temperate against the set temperature in the heating mode, and cut-in when the return air temperate is below a the set temperature. Due to on–off cycling, indoor thermal environment could suffer large fluctuation, and hence leading to less comfortable level for building occupants [4]. In addition, the heat exchangers (evaporator and condenser) are practically inactive during off-cycles; that the heat generated could exceed the heat exchanger thermal time constant, and this could cause very high-pressure lift during a large portion of the on-cycle and thus produce a low COP efficiency. This article presents a novel control algorithm, a fan intermittent operation (FIO) for an indoor unit of a room air conditioner, to remove the compressor on–off cycling under low heat load condition. In comparison to the conventional compressor on–off cycle, FIO control algorithm would maintain operation of the compressor at limited low frequency consecutively and applying fan cycles on and off intermittently in an indoor unit for establishing the condensing temperature (CT). A 4°C differential between the cut-in and cut-out points was set in our proposed method as detailed in this article. Once the CT exceeds the temperature threshold, the indoor unit fan is set to start. While, when the CT is below the set temperature, the fan of the indoor unit is regulated to stop. This algorithm can provide stable warm air in heating mode with extremely low compressor frequency, compared to the conventional compressor on–off cycling. 2 NON-ISOTHERMAL AIR JET 2.1 Minimum heat capacity for room air conditioner Generally, an air jet is called a non-isothermal jet when the jet temperature differs from the ambient. A common problem for room air conditioner in the heating mode is that supply air (SA) jet, with a high temperature (20°C differs from ambient) and low velocity, unexpectedly rise-up due to the buoyancy effect. However, increase the SA velocity at the same compressor frequency would deteriorate the CT, which would lead to a consequential reduction of the SA temperature. The experimental investigations studied round turbulent vertical buoyant jets were declared by Papanicolaou in [6], as a cognitive understanding, the jet length or terminal velocity of the non-isothermal jet is relevant to supply velocity (SV), and temperature difference between SA and the ambient. A zero energy house with a relatively smaller temperature difference between SA and the ambient would basically trade-off between the SA temperature and velocity; which is the key to provide a better indoor environment with lower energy consumption. Kubota [7] created the air jet trajectory asymptotic equations on the basic of the air jet momentum conservation; these are shown in Table 1. Table 1. Trajectory asymptotic equations. Momentum and heat conservation equation  dd (sh )(tanθ)=2λArKΔtmΔtosh1cosθ0  um2scosθ=KHouo2cosθo  dd(s)(umΔtms)=−(1+λ)umsdteds  Ar=gβ∆toHouo2  Asymptotic equation for velocity and temperature  umuo= [1+λλKAr ]1/3UΔtmΔto=1+λ2 [λ1+λKAr ]1/3T  U ≅ 1 T≅Y/Yv ( Yv: virtual origin of coordinates)  Trajectory asymptotic equation  Y=415 (Xcosθ )52+tanθoX  xHo= [λ1+λKAr2 ]1/3X,yHo= [λ1+λKAr2 ]1/3Y  Momentum and heat conservation equation  dd (sh )(tanθ)=2λArKΔtmΔtosh1cosθ0  um2scosθ=KHouo2cosθo  dd(s)(umΔtms)=−(1+λ)umsdteds  Ar=gβ∆toHouo2  Asymptotic equation for velocity and temperature  umuo= [1+λλKAr ]1/3UΔtmΔto=1+λ2 [λ1+λKAr ]1/3T  U ≅ 1 T≅Y/Yv ( Yv: virtual origin of coordinates)  Trajectory asymptotic equation  Y=415 (Xcosθ )52+tanθoX  xHo= [λ1+λKAr2 ]1/3X,yHo= [λ1+λKAr2 ]1/3Y  Where g is the gravity force; h is the slot width; K is the outlet constant; S is the coordinates in the direction perpendicular to the central axis of the airflow; te is the airflow temperature; teo is the surrounding temperature; to represents the supply inlet temperature; tm is the mainstream temperature, △tm = te− tm △to = teo− to; U is the velocity; Uo is the original velocity; Um is the mainstream velocity; Ar is the Archimedes number; β is the coefficient of expansion; λ is the diffusion coefficient; and ρ is the density. These equations were based on the following assumptions: the air entrained by the jet is at room air temperature; the only force opposing the downward flow of the heated air or upward flow of the cooled air is a buoyancy force; velocity profile and the temperature difference profile have shapes that can be approximated by an error function-type curve. The direction of the SA jet θ is one of the key factors resulting in the different jet trajectories. In this study, we set the θ as −70° (downwards to the floor). As shown in Figure 1, SA temperature (T, °C) of the warm air jet is fixed at constant value of 35 and 14°C which are different from the ambient (21°C). Along with different air SV (V, m/s), air jet against the buoyancy force is directly proportional to SV and the trajectory of the air jet fall further. Nevertheless the length of air jet trajectory is inversely proportional to SA on the same SV (like Figure 2). The larger the temperature difference between the SA and ambient is, the shorter would be the length of the air jet could reach. Figure 3 indicates the mean temperature of the air jet, which declines sharply with a higher SA. Figure 4 shows the relationship between air jet supply temperature and velocity at different compressor frequency. In this article, we trade off the SA and SV to determine the minimum constant compressor (COMP) frequency for the conventional thermostatic control (stroke volume of testing COMP is 17.2 ml), namely, the appropriate SA temperature is determined on the condition that the air jet is arrived at the floor surface (2 m height). According to KUBOTA equations, a 37°C SA would be different to ambient temperature by ~15°C, which would enable the air jet either more or less to reach a vertical length of 2 m with a constant SA flow rate. Figure 1. View largeDownload slide Air jet trajectories with different supply velocity. Figure 1. View largeDownload slide Air jet trajectories with different supply velocity. Figure 2. View largeDownload slide Air jet trajectories with different supply temperature. Figure 2. View largeDownload slide Air jet trajectories with different supply temperature. Figure 3. View largeDownload slide Air jet temperature distribution with different SA. Figure 3. View largeDownload slide Air jet temperature distribution with different SA. Figure 4. View largeDownload slide Relationship between SA and SV. Figure 4. View largeDownload slide Relationship between SA and SV. 2.2 Fan intermittent operation Compressor cycling, 2–5 min breaks of on and off times, repeating when the inverter compressor approaches the mechanical bottom frequency. In heating mode, since indoor temperature rises around the setting temperature, on–off cycle of the compressor occurs to keep a relatively stable indoor thermal environment, basically we call thermostatic control. The pressure lift (difference between condenser and evaporator saturation pressure) would fluctuate as the results of the on–off cycling. Basically, the higher the pressure lift, the higher the compressor work required for compressing a unit of refrigerant mass. Against this compressor thermostatic cycle, FIO control algorithm is keeping the compressor, operating at limited low frequency consecutively and applying fan cycles on and off intermittently in the indoor unit for establishing the refrigerant CT. This algorithm details the interrelationship between the control of CT and task zone temperature. Once the CT has exceeded a certain temperature threshold, the indoor unit fan would start to operate. While, when the CT is below the set threshold value, indoor unit fan would stop. The algorithm is capable to provide a dynamically adaptable indoor environment to raise thermal comfort of human occupants (Figure 5). Figure 5. View largeDownload slide Schematic of FIO air jet distributions. Figure 5. View largeDownload slide Schematic of FIO air jet distributions. 3 DYNAMIC SIMULATION 3.1 Field test set up The field test was carried out in a 2-storey residential house located in Kanagawa prefecture, Japan. The house was classified as highly insulated dwelling. The floor area of the living room was 69.5 m2, and the height was 2.6 m. Double-glazed windows were installed on the southern wall of the living room. Room air conditioner (Mitsubishi Electric MSZ-ZW805-W) was wall mounted at 2 m height above the floor. The rated capacity of RAC was 8.0 kW for cooling and 9.0 kW for heating. Experimental conditions are illustrated in Table 2. Specifications of the test refrigeration cycle are summarized in Table 3. Table 2. Experimental conditions. Outdoor air temperature [°C]  15.6  Setting temperature [°C]  24  Outdoor fan airflow rate [m3/min]  21.5  Indoor fan airflow rate [m3/min]  11  Outdoor air temperature [°C]  15.6  Setting temperature [°C]  24  Outdoor fan airflow rate [m3/min]  21.5  Indoor fan airflow rate [m3/min]  11  Table 3. Specifications of the test refrigeration cycle. Elements  Specification  Refrigerant  R32  COMP  Type: rotary  Stroke volume: 17.2 ml  Condenser  Type: plate fin and tube  Rated capacity: 9.0 kW  Heat transfer area: m2 (refrigerant side) m2 (air side)  Evaporator  Type: plate fin and tube  Rated capacity: 8.0 kW  Heat transfer area: m2 (refrigerant side) m2 (air side)  Gas pipe  Length: 5 m  Liquid pipe  Length: 5 m  Elements  Specification  Refrigerant  R32  COMP  Type: rotary  Stroke volume: 17.2 ml  Condenser  Type: plate fin and tube  Rated capacity: 9.0 kW  Heat transfer area: m2 (refrigerant side) m2 (air side)  Evaporator  Type: plate fin and tube  Rated capacity: 8.0 kW  Heat transfer area: m2 (refrigerant side) m2 (air side)  Gas pipe  Length: 5 m  Liquid pipe  Length: 5 m  According to KUBOTA equations (as shown in Table 1), in order to provide a 37°C SA, which would enable the air jet to reach a vertical length for 2 m, the compressor frequency hence was set as 23 Hz corresponding to the minimum heating capacity during the on-cycling:   Qref=Gr×(Hin−Hout) (1)  Qair=cp×ρ×(TRA−TSA) (2)  Gr=Vst×Fz×ρ×ηv (3)  COP=QW (4)where Qref is the heat exchange capacity in the refrigerant side, Qair is the heat exchange capacity in the air side, Gr is the refrigerant flow rate, TSA is the SA temperature, TRA is the return air temperature, Hin is the inlet enthalpy, Hout is the outlet enthalpy, Vst is the compressor stroke volume, cp is heating capacity, ρ is the density of refrigerant, Fz is the compressor frequency, ηv is the volumetric efficiency, W is the power consumption and COP is the coefficient of performance. Testing points of the device are illustrated in Table 4. The temperatures, compressor frequency, and power were measured throughout the facility. The air side supply and return temperatures, refrigerant side temperatures were measured by T-type thermocouples. The uncertainty in thermocouple measurement was estimated to be 0.5°C. The temperatures were continuously monitored at 1 min intervals at each testing point. Table 4. Testing points. Elements  Testing item  Unit  COMP  Frequency  Hz  Power consumption  W  Suction temp  °C  Discharge temp  °C  Indoor unit  Supply air temp  °C  Return air temp  °C  Indoor HEX  Condensing temp  °C  Intel temp  °C  Outlet temp  °C  Outdoor HEX  Evaporating temp  °C  Intel temp  °C  Outlet temp  °C  Elements  Testing item  Unit  COMP  Frequency  Hz  Power consumption  W  Suction temp  °C  Discharge temp  °C  Indoor unit  Supply air temp  °C  Return air temp  °C  Indoor HEX  Condensing temp  °C  Intel temp  °C  Outlet temp  °C  Outdoor HEX  Evaporating temp  °C  Intel temp  °C  Outlet temp  °C  3.2 Dynamic simulation Figure 6 illustrates the schematic of a refrigeration system, which consists of: evaporator, compressor, condenser, linear expansion valve (LEV) fans and piping. Refrigeration cycle repeated the evaporation, condensation of refrigerant to exchange heat between indoors and outdoors. Generally, the dynamic simulation was based on the following conservation equations [8]. Equations (5–8) describe mass balance, energy balance of each control volume such as evaporator, condenser, LEV, pipes (elements required for our dynamic simulation) and the parameters were measured at each point is shown in Figure 6. Figure 6. View largeDownload slide Refrigeration system. Figure 6. View largeDownload slide Refrigeration system. The dynamic simulation would produce convergence when all elements and points become converge independently. The change of evaporator temperature is a function of the air side and refrigerant side heat transfer rate. Our dynamic simulation was based on the following assumptions. The resistance of the copper and aluminum to internal heat conduction was assumed to be small compared to convective resistance of the air side heat transfer. Gravitational potential energy and kinetic energy of refrigerant were ignored in the simulation, namely, the refrigerant thermal energy was generated by enthalpy difference between the inlet and outlet of heat exchanger. Convective heat transfer coefficient and frictional loss were assumed at steady state condition. The momentum change and the acceleration loss were ignored as being assumed to be small compared to frictional loss. The calculation time step in dynamic simulation was one second. Mass conservation equation:   ΔMΔt=Gin−Gout (5) Momentum conservation:   Δ(Mu)Δt=Ginuin−Goutuout+Ap(Pin−Pout−ΔPf) (6) Energy conservation:   ΔEΔt=GinIin−GoutIout−Q (7)where   Q=Aref⋅αref⋅(T−Tw)=Gair⋅(Iwair−Iairin)⋅{1−exp(−αairi⋅AairGair)}Wetcondition=Gair⋅(Tw−Tairin)⋅{1−exp(−αairt⋅AairGairCpair)}Drycondition (8)where M is the refrigerant mass, G is the refrigerant mass flow rate, u is the velocity, A is the heat exchange area, P is the pressure, Q is the heat exchange rate, E is the energy, Iw represents humidity of saturated enthalpy, Tw represents temperature of heat exchanger, αair is the convective heat transfer coefficient of airflow and αref is the convective heat transfer coefficient of refrigerant flow. 3.3 Model validation using the experimental measurements The validity of the model was checked by comparing it with the experimentally obtained condenser and evaporator temperatures during the on and off-cycle. The compressor efficiency and heat exchanger (HEX) conventional heat transfer coefficient were adjusted to match the heating capacity of the real machine. Furthermore, the expansion valve (LEV) pulse and sub cool (SC) and super heat (SH) temperatures were determined by the steady state simulation to match the refrigeration cycle. Then, we modulated the thermal capacity of the heat exchanger and fixed the on and off period (3 min 30 s ON→3 min OFF), according to the on–off cycling testing data. As illustrated in Figure 7, results from our dynamic simulation were in accordance with the field test data, which were taken into full consideration, as the condensing pressure and the evaporate pressure were matched to on-cycling field test data during the operation period. Regarding the variable-capacity compressors, we redefined the baseline of compressors frequency, such as 23 Hz as appropriate in this case. The COMP efficiency was adjusted to as 0.757. To avoid the divergence during the off-cycle, 1 Hz is fixed in the dynamic simulation. The average heating capacity was 1.4 kW per period and energy consumption was 197.6 W per period. Figure 7. View largeDownload slide On–off cycling model validations (field testing vs simulation). Figure 7. View largeDownload slide On–off cycling model validations (field testing vs simulation). 3.4 Evaluating FIO performance As illustrated in Section 2.2, FIO control algorithm would keep the compressor operating at limited low frequency (nearly half of the COMP frequency of conventional thermostatic cycling), consecutively and provide sequential warm air by interrogating the CT which was established as a result of the indoor fan on and off intermittent operation. In order to keep the same assessment premise for comparison with conventional thermostatic model, our dynamic simulation for the FIO control algorithm was modulated with the compressor frequency to realize the same heating capacity (~1.4 kW). The FIO simulation conditions are presented in Table 5. The conditions of elements are as shown in Table 3 Table 5. FIO simulation conditions. Compressor frequency [Hz]  11  Condensing temperature oscillations [°C]  39.0 ⇔ 35.0 (≒37)  Heating capacity [kW]  1.4  Outdoor air temperature [°C]  15.6  Indoor air temperature [°C]  24.3  Outdoor fan airflow rate [m3/min]  21.5  Indoor fan airflow rate [m3/min]  11  Compressor frequency [Hz]  11  Condensing temperature oscillations [°C]  39.0 ⇔ 35.0 (≒37)  Heating capacity [kW]  1.4  Outdoor air temperature [°C]  15.6  Indoor air temperature [°C]  24.3  Outdoor fan airflow rate [m3/min]  21.5  Indoor fan airflow rate [m3/min]  11  As the basic concept of FIO control algorithm, compressor frequency was fixed at 11 Hz then indoor fan was set to on–off operation. Here we assumed the supply temperate was equivalent to the CT. The mean CT per whole cycle was kept the same as the conventional thermostatic control, in which the average on-cycling was ~37°C, at the CT. Figure 8 shows the dynamic simulation results of FIO control algorithm. The average heating capacity was 1406 W per period and energy consumption was 197.2 W per period. Figure 8. View largeDownload slide Dynamic simulation results of FIO control algorithm. Figure 8. View largeDownload slide Dynamic simulation results of FIO control algorithm. 4 RESULTS AND DISCUSSION Figure 9 shows the comparison between conventional on–off cycling and FIO control. A 5% energy saving was yielded from a 2°C difference between the ET generated from the FIO control algorithm and the conventional control algorithm. In case of the conventional control, refrigerant flow rate (Gr) was proportional to COMP frequency (Fz) base on equation (3), and also had positive relationship with heating capacity according to equation (1), hence, the 23 Hz COMP frequency would provide a larger heat exchange capacity in the on-cycling, which resulted in a larger temperature difference between ET and outdoor temperature. Different saturation pressure of the evaporator between the conventional on–off cycling and FIO control was resulted from the different compressor frequency (refrigerant flow rate). Figure 9. View largeDownload slide Comparison between conventional on–off cycling and FIO. Figure 9. View largeDownload slide Comparison between conventional on–off cycling and FIO. The expansion valve (LEV) would ensure even pressure condition during the off-cycle, which mix thermal energy to trigger the entropy increase and had resulted in energy loss in the conventional on–off refrigeration cycling. In addition, the refrigerant was unevenly and inappropriately distributed at each part of the conventional on–off cycling, compared to sequence operation by FIO control algorithm. To re-move stagnate refrigerant and reprocess pressure difference at the start of the on-cycle, an addition work is needed in quantifying cyclic loss in the refrigeration system. Furthermore, the mean CT of the on-cycle is different from the mean CT of the whole cycle; which depends on the thermal capacitance of the heat exchangers. Since the SA temperature follows the oscillations of the refrigerant saturation temperatures (CT), thus, the FIO control algorithm can provide relatively higher and successive SA to maintain a better well-being of occupants and a more comfortable environment for the task zone as compared to the conventional thermal on–off control algorithm. Table 6 summarizes the comparison between conventional thermostatic control and FIO control algorithm. The energy consumption of FIO control algorithm was 197.2 W per period base on fixed compressor frequency (11 Hz), and the energy consumption of conventional control algorithm was 197.6 W per period (on–off cycling 23 Hz ⇔ 1 Hz), and a total of 5% energy saving rate for the whole unit can be yielded. Table 6. Comparison between conventional thermostatic control and FIO control algorithm. Item  Normal symbols  Unit  Conventional control algorithm  FIO control algorithm  COMP frequency  Hz  Hz  23.0 ⇔ 1.0  11.0  Indoor fan airflow rate  V  m3/min  11.0  11.0 → 0.1  Condensing temperature  CT  °C  38.6 → 22.9 (≒37 on-cycling)  39.0 ⇔ 35.0 (≒37)  COMP ON–OFF period  COMP—ON/OFF    3 min 30 s ON → 3minOFF  –  Indoor fan ON–OFF period  FAN—ON/OFF    –  50 s ON→ 45 s OFF  Cycle period   Heating capacity  Q  W  1400  1406   Power consumption of COMP  Pcomp  W  198  197   Power consumption of indoor fan  Pfan_in  W  14  7   Power consumption of outdoor fan  Pfan_out  W  15  15   Total power consumption  P  W  227  218   Energy saving rate  –  %  –  5%  Item  Normal symbols  Unit  Conventional control algorithm  FIO control algorithm  COMP frequency  Hz  Hz  23.0 ⇔ 1.0  11.0  Indoor fan airflow rate  V  m3/min  11.0  11.0 → 0.1  Condensing temperature  CT  °C  38.6 → 22.9 (≒37 on-cycling)  39.0 ⇔ 35.0 (≒37)  COMP ON–OFF period  COMP—ON/OFF    3 min 30 s ON → 3minOFF  –  Indoor fan ON–OFF period  FAN—ON/OFF    –  50 s ON→ 45 s OFF  Cycle period   Heating capacity  Q  W  1400  1406   Power consumption of COMP  Pcomp  W  198  197   Power consumption of indoor fan  Pfan_in  W  14  7   Power consumption of outdoor fan  Pfan_out  W  15  15   Total power consumption  P  W  227  218   Energy saving rate  –  %  –  5%  5 CONCLUSION This article presents a novel control algorithm FIO for the indoor unit of the room air conditioner, to remove the compressor on–off cycling under low load condition. The results show that FIO control algorithm can provide a better well-being of occupants and a more comfortable environment for the task zone compared to conventional thermal on–off control algorithm. A 5% energy saving would be yielded in the heating mode from an ~2°C difference in the evaporating temperature due to the smaller refrigerant flow by FIO control algorithm. In addition, cycling loss would basically occur during COMP cut-in and cut-out running, and refrigerant would become unevenly and inappropriately distributed at each part of the conventional on–off cycling, compared to sequence operation by FIO control algorithm. In the dynamic simulation, the cycling loss such as the overshot of the starting current was not taken into account. The total power consumption could effectively be increased in the real operation. Finally, FIO control algorithm can provide relatively higher and successive SA to maintain a better well-being of occupants and a more comfortable environment for the task zone compared to conventional thermal on–off control algorithm. REFERENCES 1 Strategy for energy conservation of Japan 2016. Ministry of Economy, Trade and Industry. Renewable Energy Department (in Japanese). 2 International Panel on Climate Change (IPCC) 2013. 3 Coulter WH, Bullard CW. An experimental analysis of cycling losses in domestic refrigerator-freezers. ASHRAE Trans  1997; 103: 587– 96. 4 Llic SM, Bullard CW. Effect of Shorter Compressor On/Off Cycle Times on A/C System Performance. Air Conditioning and Refrigeration Center CR-43, 2001. http://hdl.handle.net/2142/13401. 5 Koestel A. Computing temperatures and velocities in vertical jet of hot and coal air. Trans Am Soc Heat Ventilat Eng  1954; 1512: 385– 410. 6 Papanicolaou NP, List E. Investigations of round vertical turbulent buoyant jets. J Fluid Mech  1988; 195: 341– 91. Google Scholar CrossRef Search ADS   7 Kubota H. Analysis of inclined buoyant jets. Int J Trans Soc Heat Air-Condition Sanitary Eng  1987; 2: 85– 95. (in Japanese). 8 Unezaki F, Matsuoka F. A dynamic model of a vapor compression refrigeration cycle using zeotropic refrigerant mixtures—1st report: a versatile model for zeotropic refrigerant mixtures. Int J Trans Jpn Soc Refrig Air-Condition Eng  2001; 18: 321– 30. (in Japanese). © The Author(s) 2018. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

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International Journal of Low-Carbon TechnologiesOxford University Press

Published: Mar 1, 2018

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