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

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.