Wind and PV Power Consumption Strategy Based on Demand Response: A Model for Assessing User Response Potential Considering Differentiated Incentives

Wenhui Zhao, Zilin Wu (), Bo Zhou and Jiaoqian Gao
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Wenhui Zhao: College of Economics and Management, Shanghai Electric Power University, Shanghai 201306, China
Zilin Wu: College of Economics and Management, Shanghai Electric Power University, Shanghai 201306, China
Bo Zhou: College of Economics and Management, Shanghai Electric Power University, Shanghai 201306, China
Jiaoqian Gao: Qingpu Power Supply Company, State Grid Shanghai Electric Power Company, Shanghai 201700, China

Sustainability, 2024, vol. 16, issue 8, 1-22

Abstract: In China, the inversion between peak periods of wind and photovoltaic (PV) power (WPVP) generation and peak periods of electricity demand leads to a mismatch between electricity demand and supply, resulting in a significant loss of WPVP. In this context, this article proposes an improved demand response (DR) strategy to enhance the consumption of WPVP. Firstly, we use feature selection methods to screen variables related to response quantity and, based on the results, establish a response potential prediction model using random forest algorithm. Then, we design a subsidy price update formula and the subsidy price constraint conditions that consider user response characteristics and predict the response potential of users under differentiated subsidy price. Subsequently, after multiple iterations of the price update formula, the final subsidy and response potential of the user can be determined. Finally, we establish a user ranking sequence based on response potential. The case analysis shows that differentiated price strategy and response potential prediction model can address the shortcomings of existing DR strategies, enabling users to declare response quantity more reasonably and the grid to formulate subsidy price more fairly. Through an improved DR strategy, the consumption rate of WPVP has increased by 12%.

Keywords: demand response; wind and PV power consumption; differentiated subsidy price; prediction model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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