Simultaneous Optimal Allocation of Renewable Distributed Generations and Electric Vehicle Charging Points using Dynamic Hunting Leadership Algorithm

Abstract The transportation sector emits a large amount of carbon emissions into the atmosphere. Electrically powered vehicles (EPVs) thus have emerged as an achievable strategy to lessen reliance on finite fuel supplies and carbon emissions. Globally, EPVs have become increasingly popular, but their broad popularity depends on the establishment of infrastructure enabling charging vehicles. This study suggests employing a dynamic hunting leadership (DHL) algorithm to strategically place electric vehicle charging point (EVCP) within distribution system (DS) featuring renewable distributed generation (RDG). The best location for the EVCP is determined for two case situations with the target objectives of minimizing power losses, voltage variation, and voltage stability index. A single-objective task framework is adopted for the optimization problem. The competence of the DHL approach is substantiated through simulations conducted in MATLAB. Notably, the integration of RDG and EVCP ensures that bus voltages remain within acceptable limits. The IEEE 33 and 69 buses test system are used in DS to evaluate the two cases presented 1) without RDG and EVCP 2) with RDG and EVCP respectively