f25b12fc-c5c2-40ff-905a-989b5403900320250804100109063naun:naunmdt@crossref.orgMDT DepositInternational Journal of Circuits, Systems and Signal Processing1998-446410.46300/9106http://www.naun.org/cms.action?id=30298420258420251910.46300/9106.2025.19https://npublications.com/journals/circuitssystemssignal/2025.phpAkram MuhammadEhtshamState Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, PR ChinaShengxueTangState Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, PR ChinaThis research introduces a holistic optimization framework designed to optimize the placement and energy management of electric vehicle (EV) charging stations within microgrids. The primary objective is to boost operational efficiency and cut down on energy expenses. By leveraging sophisticated algorithms and real-time data analytics, the system dynamically modifies charging schedules and energy sourcing strategies. The strategies optimize the utilization of renewable energy sources. Peak load demands are lowered significantly. Extensive field tests and simulations were carried out for the purpose of validating the effectiveness of the framework. This demonstrates significant improvements in operating efficiency. Putting the suggested ideas into practice, increased overall efficiency by 26.3%. This translates to reduced operating expenses and environmental effect. The research provides a useful manual for setting up effective and sustainable EV charging infrastructure.842025842025112https://npublications.com/journals/circuitssystemssignal/2025/a022005-001(2025).pdf10.46300/9106.2025.19.1https://npublications.com/journals/circuitssystemssignal/2025/a022005-001(2025).pdf10.1038/s41598-024-63775-5M. 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