Economic Optimization Operation Strategy of Microgrid Based on Behavioral Economics Theory - TAO Changhe, LU Ling, ZHANG Yu, WANG Can, LIU Yuzheng, HE Jintao, YANG Daiqiang, WANG Mingchao, CHENG Bentao (Dianli jianshe, 2025)
[Objective] With the continuous increase in the proportion of renewable energy in the overall energy mix， the inherent uncertainty and variability in power generation pose challenges to the stable operation and economic efficiency of microgrid systems. Demand response strategies have emerged as crucial measures for enhancing the integration capacity of renewable energy in microgrids.[Methods] First， to optimize the fitting ability of the demand response model to the user behavior， this study constructs a demand response model based on the endowment effect by analyzing the psychological factors of users participating in demand response. Then， based on this demand response model， an economic optimization operation strategy for microgrids is proposed. Considering the comprehensive satisfaction of users and the operation cost， a microgrid economic operation model is established. Pareto optimization technology combining the constraint and relaxation factor is adopted to solve the operation model， and the economic optimization of the microgrid is achieved under the constraints of the equipment operation power and grid interaction.[Results] The simulation analysis verified the effectiveness of the demand response model proposed in this study in improving the economic benefits of microgrids and its superiority over traditional demand response models， while also enhancing user satisfaction.[Conclusions] The demand response model based on behavioral economics theory proposed in this study can more accurately describe the user demand response behavior. The introduction of the endowment effect theory provides a new perspective for understanding and predicting consumer responses to energy price changes， enabling microgrid operators to more accurately adjust power supply strategies to cope with demand fluctuations and market changes. The demand response model proposed in this study can effectively promote user participation in peak shaving and valley filling and reduce the operation cost of the system.