Experimental analysis of flexible characteristics of air conditioning energy use in office buildings based on indoor set temperature regulation
DATE:2025-02-11
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The measured results show that during the demand response period, when the set temperature is adjusted by 1~2 ℃, a better indoor comfort can be maintained; at the same time, during the demand response period, the two buildings are able to provide a flexible load quantity of 10~20 W/m2, and a load transfer of 28.3%~83.1% can be realized. The results of this paper can provide the index support and measurement basis for the flexible quantification of air-conditioning system, which is of reference value for building energy saving under the “double carbon” target.
As society's demand for electricity increases, the proportion of renewable energy power generation to total social power generation increases year by year. However, renewable energy power generation has obvious intermittency and uncertainty, which results in the intensification of the conflict between supply and demand and the continuous increase of the peak-to-valley difference. As a power user with energy flexibility, it has become a necessity to utilize the flexible resources of buildings to participate in demand response (DR) and alleviate the pressure of grid power supply. The essence of demand response is the rational allocation of building energy use, and the basis for realizing this allocation is the quantitative grasp of the building's own flexible resources. Among the many demand-side loads in buildings, the air conditioning system has become the most high-quality flexible resource for building demand response due to its high proportion of electricity consumption, high flexibility, good response effect and other characteristics. As the most direct and simple demand response strategy, indoor set temperature adjustment can utilize air conditioning hysteresis and building envelope thermal inertia to enable the building to participate in demand response under the premise of satisfying indoor comfort. A large number of studies at home and abroad have analyzed the flexible load characteristics of air conditioning under set temperature regulation through simulation, and all of them show that air conditioning systems have a large potential for flexible regulation. Qianqian Ma analyzed the potential of air conditioning as a flexible load to participate in grid peaking under different control strategies through load simulation of buildings by TRNSYS, in which the set temperature regulation is the most direct and has the greatest potential. Lei Yaping established the air conditioning temperature regulation behavior and air conditioning cooling and heating load model through EnergyPlus, and analyzed the reduction of air conditioning energy consumption and system economic cost after the change of air conditioning energy behavior.Yin et al. simulated the air conditioning loads corresponding to different internal and external perturbation parameters by establishing the EnergyPlus model of 16 typical public buildings, and predicted the range of air conditioning flexibility potentials under the control of a 2 ℃ temperature difference through the regression fitting. The range of air-conditioning flexibility potential under 2 °C temperature difference control.Tang et al. used TRNSYS to simulate and model an office building, analyzed the effects of different system design parameters and control parameters on air-conditioning flexibility, and compared the optimal solution under flexibility control with the baseline simulation solution with an inactivated flexibility source, and found that the energy cost for the cooling season could be reduced by up to 21%.Chen et al., Richter et al, Aste et al. and Zhang et al. also analyzed the air conditioning flexibility under different buildings and control strategies by simulation. In addition, some other scholars have used a combination of black-box model and gray-box model to study air conditioning flexibility. Yaoqi Duan proposed a data-driven load forecasting method based on the resistance capacitance (RC) model combined with the enclosure structure, personnel disturbance and control strategy into the model structure for modeling, and the results can provide guidance for flexible load forecasting.Yin et al. used building air conditioning operation data to establish an autoregressive sliding average model, analyzed the instantaneous flexibility, steady-state flexibility, and total energy savings for each air conditioning unit, and quantified the energy savings that can be achieved by various set-value adjustment schemes. Existing studies rely on simulation to study air-conditioning flexibility, but experimental testing of the energy-use characteristics of air-conditioning flexibility is lacking, and the comfort boundaries of flexible regulation are not clear. Since simulation modeling often depends on the accuracy of the model, and model building requires a large number of simplifications and input parameters, this may lead to a certain deviation of the model results from the actual situation. In addition, simulation cannot fully take into account the changes in air conditioning operating conditions, building heat storage and release patterns, and other complex situations in actual operation. In contrast, the actual test can more directly reflect the situation in the actual environment, closer to the real operating state. Therefore, there is an urgent need to carry out experimental tests of flexible regulation and further analyze the flexible characteristics of air-conditioning system energy use. In this study, two office buildings were used as experimental objects to analyze the flexible energy use characteristics of the air conditioning system during the demand response period by adjusting the indoor set temperature. Firstly, the indoor comfort during the conditioning period is analyzed by the predicted mean thermal sensory index (PMV) and other indicators; then the air conditioning flexibility under different conditioning conditions and outdoor temperatures is studied through experiments and the air conditioning flexibility potential range is further analyzed by taking the amount of flexibility and the ratio of flexibility as the evaluation indexes; finally, based on the heat storage attenuation index and the rate of heat release, the flexibility is analyzed by the internal surface temperature of the building thermal energy storage body and the indoor temperature.
Finally, based on the heat storage decay index and heat release rate, the ability of the building heat storage to transfer the air conditioning load during the adjustment period is analyzed by the surface temperature and indoor temperature of the building heat storage. The measured data provide a statistical guarantee for the flexible characteristics of air conditioning energy use during the indoor temperature regulation period, and the results of the study can provide an index support and measurement basis for the quantification of air conditioning system flexibility, which is of reference value for building energy saving under the goal of “double carbon”.
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As society's demand for electricity increases, the proportion of renewable energy power generation to total social power generation increases year by year. However, renewable energy power generation has obvious intermittency and uncertainty, which results in the intensification of the conflict between supply and demand and the continuous increase of the peak-to-valley difference. As a power user with energy flexibility, it has become a necessity to utilize the flexible resources of buildings to participate in demand response (DR) and alleviate the pressure of grid power supply. The essence of demand response is the rational allocation of building energy use, and the basis for realizing this allocation is the quantitative grasp of the building's own flexible resources. Among the many demand-side loads in buildings, the air conditioning system has become the most high-quality flexible resource for building demand response due to its high proportion of electricity consumption, high flexibility, good response effect and other characteristics. As the most direct and simple demand response strategy, indoor set temperature adjustment can utilize air conditioning hysteresis and building envelope thermal inertia to enable the building to participate in demand response under the premise of satisfying indoor comfort. A large number of studies at home and abroad have analyzed the flexible load characteristics of air conditioning under set temperature regulation through simulation, and all of them show that air conditioning systems have a large potential for flexible regulation. Qianqian Ma analyzed the potential of air conditioning as a flexible load to participate in grid peaking under different control strategies through load simulation of buildings by TRNSYS, in which the set temperature regulation is the most direct and has the greatest potential. Lei Yaping established the air conditioning temperature regulation behavior and air conditioning cooling and heating load model through EnergyPlus, and analyzed the reduction of air conditioning energy consumption and system economic cost after the change of air conditioning energy behavior.Yin et al. simulated the air conditioning loads corresponding to different internal and external perturbation parameters by establishing the EnergyPlus model of 16 typical public buildings, and predicted the range of air conditioning flexibility potentials under the control of a 2 ℃ temperature difference through the regression fitting. The range of air-conditioning flexibility potential under 2 °C temperature difference control.Tang et al. used TRNSYS to simulate and model an office building, analyzed the effects of different system design parameters and control parameters on air-conditioning flexibility, and compared the optimal solution under flexibility control with the baseline simulation solution with an inactivated flexibility source, and found that the energy cost for the cooling season could be reduced by up to 21%.Chen et al., Richter et al, Aste et al. and Zhang et al. also analyzed the air conditioning flexibility under different buildings and control strategies by simulation. In addition, some other scholars have used a combination of black-box model and gray-box model to study air conditioning flexibility. Yaoqi Duan proposed a data-driven load forecasting method based on the resistance capacitance (RC) model combined with the enclosure structure, personnel disturbance and control strategy into the model structure for modeling, and the results can provide guidance for flexible load forecasting.Yin et al. used building air conditioning operation data to establish an autoregressive sliding average model, analyzed the instantaneous flexibility, steady-state flexibility, and total energy savings for each air conditioning unit, and quantified the energy savings that can be achieved by various set-value adjustment schemes. Existing studies rely on simulation to study air-conditioning flexibility, but experimental testing of the energy-use characteristics of air-conditioning flexibility is lacking, and the comfort boundaries of flexible regulation are not clear. Since simulation modeling often depends on the accuracy of the model, and model building requires a large number of simplifications and input parameters, this may lead to a certain deviation of the model results from the actual situation. In addition, simulation cannot fully take into account the changes in air conditioning operating conditions, building heat storage and release patterns, and other complex situations in actual operation. In contrast, the actual test can more directly reflect the situation in the actual environment, closer to the real operating state. Therefore, there is an urgent need to carry out experimental tests of flexible regulation and further analyze the flexible characteristics of air-conditioning system energy use. In this study, two office buildings were used as experimental objects to analyze the flexible energy use characteristics of the air conditioning system during the demand response period by adjusting the indoor set temperature. Firstly, the indoor comfort during the conditioning period is analyzed by the predicted mean thermal sensory index (PMV) and other indicators; then the air conditioning flexibility under different conditioning conditions and outdoor temperatures is studied through experiments and the air conditioning flexibility potential range is further analyzed by taking the amount of flexibility and the ratio of flexibility as the evaluation indexes; finally, based on the heat storage attenuation index and the rate of heat release, the flexibility is analyzed by the internal surface temperature of the building thermal energy storage body and the indoor temperature.
Finally, based on the heat storage decay index and heat release rate, the ability of the building heat storage to transfer the air conditioning load during the adjustment period is analyzed by the surface temperature and indoor temperature of the building heat storage. The measured data provide a statistical guarantee for the flexible characteristics of air conditioning energy use during the indoor temperature regulation period, and the results of the study can provide an index support and measurement basis for the quantification of air conditioning system flexibility, which is of reference value for building energy saving under the goal of “double carbon”.