Artificial Intelligence (AI) in Renewable Energy Systems: A Brief Overview for Conserving and Efficiently Utilizing Renewable Resources

Abstract

The global energy demand is anticipated to grow at an average annual rate of 8% from 2000 to 2030. Fossil fuels currently supply a significant portion of this energy, having profound impacts. Renewable energy (RE) sources are gaining popularity as alternatives to fossil fuels for various reasons. However, the transition to RE sources is critical for addressing climate change and reducing dependence on fossil fuels. However, the variability and intermittency of RE present significant challenges for efficient utilization and integration into power grids. Artificial intelligence (AI) and machine learning (ML) are relatively new concepts in the energy sector. The proposed work highlights how AI can optimize the generation and distribution of RE through predictive analytics and ML models. This chapter explores the role of AI in enhancing the efficiency and reliability of RE systems (RES), including solar, wind, hydro, and bioenergy. The work explores the contribution of AI to improving energy storage. The proposed work emphasizes the role of AI in improving energy efficiency and conservation. The synergy between AI and RES offers innovative pathways to conserve resources and promote sustainable energy practices.