Low-carbon collaborative dual-layer optimization for energy station considering joint electricity and heat demand response

Abstract

In the park-level integrated energy system (PIES) trading market involving various heterogeneous energy sources, the traditional vertically integrated market trading structure struggles to reveal the interactions and collaborative relationships between energy stations and users, posing challenges to the economic and low-carbon operation of the system. To address this issue, a dual-layer optimization strategy for energy station-user, taking into account the demand response for electricity and thermal, is proposed in this paper. The upper layer, represented by energy stations, makes decisions on variables such as the electricity and heat prices sold to users, as well as the output plans of energy supply equipment and the operational status of battery energy storage. The lower layer, comprising users, determines their own electricity and heat demand through demand response. Subsequently, a combination of differential evolution and quadratic programming (DE-QP) is employed to solve the interactive strategies between energy stations and users. The simulation results indicate that, compared to the traditional vertically integrated structure, the strategy proposed in this paper increases the revenue of energy stations and the consumer surplus of users by 5.09% and 2.46%, respectively.