A Unified Bi‐Objective Programming Framework for Active Power Optimization and Reactive Power Coordination of Electric Vehicles Integrated With Distribution Feeder Reconfiguration

ABSTRACT This research presents a novel integrated optimization approach to enhance the performance of distribution systems. In this regard, a mathematical model based on mixed‐integer nonlinear programming is introduced, which for the first time simultaneously addresses the problem of active power optimization and reactive power coordination of electric vehicles in the presence of distributed generations alongside distribution system reconfiguration. The proposed framework comprises a bi‐objective programming structure implemented in two steps. In the first stage, the P of EVs is optimized to minimize the total load variations. In the second step, without relying on trigonometric functions or linearization approximations, the Q coordination of EVs alongside DSR is solved by utilizing the node‐branch incidence matrix and the real and imaginary components of voltage and current. This model reduces computational complexity and ensures the attainment of the global optimal solution through the branch and bound algorithm in GAMS software, achieving objectives such as minimizing active power losses, reducing voltage deviation, and improving the voltage profile. Simulations conducted on 33‐bus and 69‐bus distribution systems demonstrate that the proposed method achieves a significant reduction in APL (96.21% and 97.77%) and notable improvement in voltage profile (with VD reduction of 99.55% and 99.60%) in these systems.