Abstract
This paper presents a hybrid renewable energy system integrated with a smart application-based management solution to enhance the efficiency, sustainability, and scalability of electric vehicle (EV) charging stations. The system utilizes photovoltaic (PV) panels, wind turbines (WTs), and battery storage to reduce reliance on grid power and improve energy resilience. A robust energy management system (EMS) employs an adaptive neuro-fuzzy inference system (ANFIS) to optimize PV production under changing conditions, while machine learning algorithms control the dynamic distribution of energy among the grid, storage, and EVs. A smart application leverages IoT, real-time data analytics, and a scheduling algorithm to optimize charging operations across numerous stations. This app-based management optimizes energy use, reduces grid overload, and offers dynamic charging suggestions. Simulation findings in MATLAB/Simulink demonstrate that the proposed system improves power balance, grid stability, and user convenience, while decreasing grid reliance by more than 30%. Furthermore, a blockchain-based payment solution provides secure transactions, lowering station owners’ operating expenses by up to 25%, while saving users as much as 18%. This study provides a comprehensive foundation for future EV charging infrastructure supporting the transition to sustainable electric mobility.
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CITATION STYLE
Alkahtani, A. A., Al-Shetwi, A. Q., El-Hameed, M. A., Atawi, I. E., Sahli, F. A., & Adaqriri, M. H. (2025). Hybrid Renewable Energy and Smart App-Based Management for Efficient and Sustainable EV Charging Infrastructure. International Journal of Energy Research, 2025(1). https://doi.org/10.1155/er/5872792
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