Quantitative method and influencing factors analysis of demand response performance of air conditioning load with rebound effect

Abstract Under the emerging trend of the new power systems, enhancing the energy flexibility of air conditioning loads to promote electricity demand response is crucial for regulating the real-time balance. As a typical temperature-controlled loads, air conditioning loads can generate rebound effect when participating in demand response, resulting in sudden load increases and posing risks to grid security. However, the existing research mainly focuses on the energy flexibility, which leads to an imperfect demand response mechanism and thus affects the optimal scheduling strategy. Therefore, the study proposes a comprehensive quantification method in view of rebound effect for the demand response performance of air conditioning loads, by using probability distribution, Latin hypercube sampling, Monte Carlo simulation, and scenario analysis methods. The demand response event was divided into response phase and recovery phase, and by considering energy flexibility during the response phase and rebound effect during the recovery phase, three dimensionless evaluation indexes for comprehensive demand response performance were constructed. Using this quantification method, the impact patterns of three types of random variables were compared, including meteorological, design variables, and control variables. Additionally, considering the differences in building types (office and hotel buildings) and building capacities (small, medium, and large), the effectiveness of air conditioning load participation in demand response measures in different building application scenarios was explored. The results show that the influence of the design variables on the response performance is less than that of the control variables, but significant, reaching 45% compared to the control variables. Moreover, the influence varies with building type, capacity and climate zone, and building demand response design has more potential in the following scenarios: the cold climate, the hot summer and cold winter climate, the medium building and the hotel building.