Performance Assessment of a PV-Powered EV Charging Station Using Conventional and Enhanced MPPT Algorithms with Economic Feasibility Analysis

As the world moves toward cleaner transportation solutions, photovoltaic (PV)-powered electric vehicle (EV) charging stations present a promising solution to reducing greenhouse gas emissions and relieving pressure on conventional power grids. However, the intermittent nature of solar energy poses significant challenges to maintaining a consistent and efficient power supply. To address this, Maximum Power Point Tracking (MPPT) controllers are crucial for continuously extracting the maximum available power from PV systems under dynamic environmental conditions. This study presents a comprehensive evaluation of six well-known MPPT algorithms: Perturb and Observe (P&O), Incremental Conductance (IC), Variable Step-Size P&O (VSS-P&O), Variable Step-Size IC (VSS-IC), and their modified variants, aimed at enhancing the performance of PV-powered EV charging stations. The feasibility and effectiveness of these methods are validated through MATLAB/SIMULINK simulations. Results carried out under both stable and rapidly changing irradiance conditions demonstrate that the modified variable step-size algorithms provide better tracking accuracy, faster convergence, and enhanced power stability, making them well-suited for dynamic scenarios. These improvements contribute to more reliable and energy-efficient solar EV charging infrastructure. Additionally, the study also evaluates the economic viability of an on-grid energy storage system, based on projected energy needs and system design assumptions, including five Dacia Spring EVs and 140 PV panels sized to meet expected consumption. The return on investment analysis reveals a favorable payback period, with the initial investment anticipated to be recovered by the end of the fourth year. Overall, the findings support the development of reliable, economically viable, and environmentally sustainable PV-integrated EV charging solutions.