Energy storage configuration considering user-shared costs in peak shaving auxiliary services with improved multi-objective particle swarm optimization - Yiyou Xing; Jin Shen; Xinru Li (AIP Advances)
To enhance peak-shaving and valley-filling performance in residential microgrids while reducing the costs associated with energy storage systems, this paper selects retired power batteries as the storage solution, breaking through existing optimization models. This research incorporates the simultaneous participation of multiple stakeholders, including consumers and energy storage providers, into the peak shaving process. It introduces an optimized configuration method for microgrid energy storage using retired power batteries, which also accounts for the equitable distribution of peak shaving auxiliary service costs among users. Moreover, an improved particle swarm optimization algorithm, specifically adapted for this model, is developed. The methodology begins with the introduction of mathematical models for power generation output, load calculations, and energy storage charging and discharging dynamics. The objective functions are designed to minimize both the cost of implementing the retired power battery storage system and the distribution of peak shaving auxiliary service costs among users. These functions are addressed using the improved multi-objective particle swarm optimization algorithm. This paper concludes with a case study of a residential microgrid, comparing and analyzing the economic and operational effectiveness of the proposed method. The simulation results corroborate the validity and efficacy of incorporating user cost-sharing for auxiliary peak shaving into the optimization of microgrid retired power battery storage configurations.