Multi‐Period Optimal Power Flow of Thermal–Wind Systems With Battery Storage and Static Synchronous Compensator Under High Electric Vehicle Charging Demand and Contingency Conditions

ABSTRACT This paper develops a contingency‐based multi‐period optimal power flow (MP‐OPF) problem for a thermal–wind–battery energy storage system (BESS) under peak plug‐in hybrid electric vehicle (PHEV) charging load. Different case studies are considered to assess the effect of peak PHEV charging, wind uncertainty, energy storage, contingency issues, and FACTS support on the power system. A BESS model is presented that implements state‐of‐charge continuity, charging–discharging dynamics, and time‐coupled operational constraints to ensure reliable energy management across the scheduling horizon. Furthermore, a STATCOM is strategically placed and configured with optimal control parameters to enhance voltage and reactive power support under stressed operating conditions. A quasi‐oppositional birds‐of‐prey–based optimization (QOBPBO) algorithm is used to solve the highly nonconvex and complicated MP‐OPF problem. Quasi‐oppositional learning enhances QOBPBO's exploration, leading to better solution quality and a more robust convergence profile. The proposed methodology is examined on the IEEE 57‐bus benchmark system under normal and contingency operation. The simulation results indicate that the combined operation of wind and BESS substantially reduces peak‐hour system stress due to PHEV charging load, decreases thermal generation dependence, and improves operational security during line outages. Furthermore, incorporating STATCOM lowers generation costs by improving voltage regulation and reducing transmission losses. The simulation results confirm that the suggested algorithm delivers higher‐quality, more robust solutions that are also computationally more efficient than the sophisticated methods employed.