Techno-economic Evaluation of Renewable Energy Microgrids for EV Charging Applications
J. Environ. Nanotechnol., Volume 14, No 2 (June 2025) pp. 363-379
Abstract
This research performs an economic and technological assessment of a renewable energy system optimized by Self adaptive grey wolf optimizer (SA-GWO) which enables sustainable EV charging in microgrids. While reducing the cost of operations and hence carbon emissions from EV charging infrastructure, the combination of solar panels and wind turbines with storage units helps lessen the reliance on the primary power grid. Optimal system architecture consists of renewable energy component sizes together with storage facilities and energy management systems to enable sustainable, dependable and affordable EV charging. Operating inside an optimized framework, the SA-GWO controls optimization parameters to enable suitable exploitation-exploration balances that produce optimal solutions for reducing system energy losses while minimizing operational expenses, thus maximizing system reliability. Technical needs for operational effectiveness and logistical dependability as well as financial concerns (including capital expenses, maintenance costs and financial returns) are handled by this optimizing system. In this study, SA-GWO was used to achieve microgrid design goals with improved energy system efficiency, environmental responsibility, economic sustainability and grid independence. In future transportation systems, SA-GWO will be a useful tool for both environmental sustainability and expansion of EV market. This paper combines the ideas of renewable energy-based microgrid, battery-powered automobile charging and SA-GWO with energy storage systems.
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