Optimization of Renewable Energy Resources using an Internet-of-Things and Machine Learning Algorithm

Energy power development and the heavy reliance on traditional sources are creating challenges for sustainable growth. Solar power offers a clean and promising alternative, but it is not without its own set of issues, such as intermittent supply and inefficiency. This paper introduces a smarter way to manage renewable energy: a system designed to combine solar energy generation, storage, and automated management to address these gaps. By using real-time monitoring and advanced technologies, such as Support Vector Machines (SVM) and Maximum PowerPoint Tracking (MPPT), the system helps users make the most of their energy. What makes it even better is its ability to send unused energy back to the grid after meeting household or industrial needs, thereby allowing users to earn subsidies to contribute to a cleaner energy network. This paper outlines a practical, forward-thinking approach to renewable energy that is not only about efficiency but also about creating a sustainable future for all.