Economic and Reliability Assessment of Hybrid EV Charging Systems using Improved Coot Bird Optimisation on IEEE-33 Bus System

Electric Vehicles (EVs) are crucial to the transition to sustainable transportation on a global scale due to their near-zero emissions and their ability to mitigate noise pollution. However, widespread adoption of EVs is hindered by the less accessible and high cost of Electric Vehicle Charging Stations (EVCS) for distant areas. This study addresses this issue through the development of a Hybrid Renewable Energy Sources (HRES)-based EVCS system connected to the IEEE 33 bus radial distribution network. The system incorporates a Renewable Energy System including Photovoltaic (PV) and Wind Turbine (WT), to decrease the cost of EV charging based on the renewable energy availability, and improve energy sustainability. To develop an optimized design and efficient hybrid system, this research introduces an Improved Coot Bird Optimization Algorithm (ICBOA). This improved metaheuristic algorithm quickly produces the best sizing and location for RES based on calculations intended to balance cost and reliability objectives. The reliability of the system is tested using standard reliability indices, which ensure some measure of operational stability and reliability in the energy provided. The simulation outcomes demonstrate that the proposed method has adequately reduced charging costs, improved overall reliability, and aided in achieving sustainability goals.