Data-Driven Uncertainty Modeling-Based Energy Sharing and Operation Algorithm for PV-integrated Battery Charging and Swapping Station

In this study, we propose an optimal energy management algorithm for multiple photovoltaic (PV)-integrated battery charging and swapping stations (BCSSs), considering both energy sharing among BCSSs and their PV generation uncertainties. To minimize the system-wide operating cost, we formulate a cooperative energy-sharing mechanism among BCSSs while strictly satisfying the electric vehicle (EV) charging requirements of each BCSS. In addition, to address the PV uncertainty, we formulate chance constraints based on a data-driven method using historical data. To enhance computational performance while accounting for PV uncertainties, we employ duality theory to reformulate the proposed chance constraints into a deterministic equivalent form. In the numerical investigation, we demonstrate the superior performance of the proposed algorithm in terms of cost reduction, cooperation among BCSSs, and robustness under uncertainty environments characterized by different probability distributions.