Artificial Intelligence for Solar Power Monitoring and Predictive Energy Management

Engineering notes

Engineering notes will be added by the Power for Solar editorial team.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。

Original abstract

<b>AI-Based Solar Power Monitoring System Using Machine Learning</b> presents a data-driven approach to monitoring and analyzing solar power generation using artificial intelligence and machine learning techniques. The work focuses on improving the efficiency and reliability of photovoltaic (PV) systems by applying predictive models to estimate energy generation, detect performance variations, and support informed operational decisions.The research integrates historical and environmental data to develop a scalable framework capable of forecasting solar power output under varying conditions. By combining machine learning with renewable energy applications, the proposed system aims to enhance energy management, reduce operational uncertainty, and contribute to the broader adoption of intelligent, sustainable power systems.This repository contains the research paper and supporting materials intended for academic reference, knowledge sharing, and future research. The study demonstrates the potential of AI-enabled monitoring systems in advancing renewable energy technologies and provides a foundation for further work in solar forecasting, smart energy management, and intelligent power networks.

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