Optimal Scheduling of EV Charging Station With Renewable Generation Considering Line Outages and Network Losses

The uncertain renewable energy sources (RESs) and grid integration of EV charging stations create several operational challenges in the power system. This research provides a comprehensive mathematical optimization model for EV charging scheduling that integrates stochastic network-constrained unit commitment (NCUC) with N-1 criteria and network losses. A generalized generation distribution factor (GGDF) for the pre-and post-contingency selection technique is applied based on the DC power flow model to address the uncertain parameters. A line outage distribution factors (LODF) method is proposed for the post-contingency constraints to reduce the computational burden due to many scenarios and N-k line outages. In addition, the bender decomposition approach is employed to simplify the problem complexity. Hence, this work evaluates the impact of transportation networks for EV charging stations and N-k outages in a proposed model for economic and technical benefits. The validity of the NCUC model is substantiated through verification using IEEE 24-bus systems. The economic benefits shared by EV charging stations and RES with post-contingency LODF were reduced by about 5.91% in scheduling costs as compared to the conventional preventive GGDF-based approach.