Integrating Renewable Energy Sources with Micro Grid Using IOT and Machine Learning

Abstract

The integration of renewable energy sources with microgrids using IoT and energy management technologies has become a promising solution for achieving sustainable and efficient energy systems. In this paper, propose a methodology for integrating renewable energy sources with microgrids using IoT and energy management technologies, and apply an Artificial Neural Network (ANN) algorithm for energy demand prediction. The proposed methodology aims to optimize the energy consumption of the micro grid by utilizing renewable energy sources and energy storage devices. Validate the proposed methodology using a real-world dataset, and compare the performance with traditional forecasting methods. The results show that the proposed methodology outperforms traditional methods in terms of accuracy and efficiency. The proposed methodology can be utilized in various micro grid applications for load forecasting and energy consumption optimization.