文献类型：期刊文献

英文题名：Coordinated Optimization of PV-ES Charging Stations and Integrated Energy Communities with Energy Sharing and Revenue Allocation

作者：Wei, Jijiao[1]; Li, Zhichen[1]; Yan, Huaicheng[1]; Xu, Jing[1]; Song, Bing[1]; Zhao, Zhongqi[2]

机构：[1] East China University of Science and Technology, School of Information Science and Engineering, Shanghai, China; [2] State Grid Qinghai Electric Power Company, Haibei Power Supply Company, Haibei, China

年份：2026

起止页码：121

外文期刊名：2026 14th International Conference on Intelligent Control and Information Processing, ICICIP 2026

收录：EI(收录号：20261620536022)

语种：英文

外文关键词：Charge storage - Charging (batteries) - Electric vehicles - Natural resources - Optimization - Power markets - Renewable energy

摘要：The increasing adoption of new energy vehicle and growing penetration of renewable energy sources have raised the demand for enhanced construction and scheduling optimization in integrated energy systems (IES). In this paper, an energy sharing optimization architecture is put forward for two key entities in IES: energy producers and sellers (Prosumers) and electric vehicle charging service providers (EVCS). Firstly, the photovoltaic-energy storage charging station (PV-ES CS) is proposed as charging service model for EVCSs in multi-IES energy sharing framework. Compared to traditional charging stations, PV-ES CS achieves notable cost savings and lower carbon emissions for Prosumers. Secondly, to safeguard the privacy of stakeholders such as Prosumers and EVCSs during energy trading, a parallel GPP-ADMM algorithm is proposed. This method significantly reduces solution time compared to the conventional ADMM algorithm. Thirdly, considering energy trading process and each participant's characteristics, an improved benefit distribution approach is developed to equitably allocate marginal benefits generated by cooperative alliance. Finally, the effectiveness and advantages for the proposed distributed optimization algorithm and trading strategy is verified via case study. ? 2026 IEEE.