This project introduces an innovative energy management algorithm designed for a 20-kW Electric Vehicle Charging Station (EVCS) powered by a hybrid solar and fuel cell system. The proposed algorithm, implemented using a fuzzy inference system in MATLAB SIMULINK, optimally balances techno-economic considerations and environmental impact. The key parameters managed by the algorithm include power generation, electric vehicle (EV) power demand, charging periods, and the utilization of renewable energy sources. The results demonstrate the effectiveness of the proposed algorithm in significantly reducing energy costs, achieving a remarkable 74.67% reduction compared to existing flat rate tariffs. The algorithm further offers differentiated charging costs for weekdays and weekends, enhancing cost-effectiveness for both EV users and station owners. The integration of hybrid renewable energy sources not only contributes to cost savings but also leads to a substantial decrease in greenhouse gas emissions, promoting environmental sustainability. The economic viability of the project is highlighted by short payback periods for charging station owners, reinforcing the profitability of investing in such hybrid renewable energy-based EV charging stations.
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