Eco-Efficient Mobility: Comparative Optimization of PV-Wind EV Charging Solutions

This research work aims to conduct a comprehensive analysis of the optimization of Electric Vehicle Charging Stations (EVCS) by integrating photovoltaic (PV) and wind energy sources. The study applies the Multi-Objective Particle Swarm Optimization (MOPSO) method to evaluate the trade-off between the Total Net Present Cost (TNPC) and the Loss of Power Supply Probability (LPSP) in the proposed hybrid energy system. The optimization results are compared with those obtained by the HOMER software, which is a widely used tool for energy system design and analysis. The comparison reveals significant differences between the MOPSO and HOMER solutions. The HOMER software achieves a lower LPSP of 0.00%, indicating a higher reliability of the system. However, the MOPSO method achieves a lower TNPC, implying a higher economic efficiency of the system. These findings highlight the complex interplay between system reliability, economic efficiency, and renewable energy utilization in the context of PV-wind integrated EVCS. The comparative analysis enhances our knowledge of optimization techniques and their implications for developing sustainable transportation infrastructures.