INTELLIGENT RENEWABLE ENERGY OPTIMIZATION FRAMEWORK FOR ELECTRIC RAILWAYS USING SMART PV CLEANING AND THERMAL MONITORING

This paper presents an Intelligent Renewable Energy Optimization Framework for Electric Railways using Smart PV Cleaning and Thermal Monitoring. The proposed system integrates automated cleaning mechanisms with real-time temperature monitoring to improve the performance and reliability of solar photovoltaic panels. By removing dust accumulation and maintaining optimal temperature conditions, the system enhances solar energy generation efficiency and reduces maintenance requirements. The proposed framework is suitable for large-scale railway renewable energy installations and contributes to the development of sustainable and energy-efficient transportation systems. The study shows that integrating smart technologies into railway solar infrastructure can improve the consistency of power generation and support dependable operation under varying environmental conditions. The proposed approach offers a practical solution for railway sectors seeking to strengthen energy sustainability while reducing operational challenges associated with conventional maintenance practices. In addition, the framework highlights the potential of automation in enhancing the long-term usability of photovoltaic systems installed in railway environments. Therefore, this work serves as a useful step toward the adoption of smarter and cleaner energy solutions in electric railways, supporting future transportation networks that are both environmentally responsible and technologically advanced.

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