Artificial Intelligence-Based Energy Management System for Renewable Energy Sources
Anilkumar V. Brahmane, Shashikant Raghunathrao Deshmukh
Abstract
Renewable energy sources such as solar and wind are becoming increasingly popular due to their environmental benefits. However, their output can be unpredictable and intermittent, making it difficult to manage energy supply and demand. This research study proposes an artificial intelligence-based energy management system that can optimize the use of renewable energy sources by predicting energy output from solar and wind farms. The system utilizes machine learning algorithms to analyze data from sensors and weather forecasts to predict energy output. The predicted output is then used to optimize energy storage and distribution to ensure reliable energy supply. The proposed system has the potential to improve energy efficiency, reduce energy waste, and lower energy costs, making renewable energy sources more accessible and sustainable.