Multi-objective optimal sizing and techno-economic analysis of on- and off-grid hybrid renewable energy systems for EV charging stations

Integrating electric vehicle charging stations (EVCSs) with renewable energy systems requires the consideration of several factors during the planning stage, including environmental impact, economic viability, grid reliability, and self-sufficiency. Therefore, this study conducts a multi-objective optimal sizing of on- and off-grid hybrid renewable energy systems for EVCSs. The sizing problem is solved using the Non-dominated Sorting Genetic Algorithm (NSGA-II). Subsequently, the best suitable solutions from the obtained non-dominated solutions are selected using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, prioritizing the objective functions based on diverse interests of different stakeholders (large and small private investors and governmental entities). Finally, a techno-economic analysis is made considering payback period, profitability index (PI), and internal rate of return (IRR). The results show that on-grid systems show high economic viability with payback periods between 1.98 and 7.72 years, an average PI of 5.07 and an average IRR of 23.97%. Although off-grid systems present lower economic viability with payback periods between 8.77 and 22.42 years, an average PI of 1.68 and an average IRR of 4.91%, in certain cases they reach investable levels with payback periods below 10 years, PI above 2, and IRR above the interest rate.