Key points are not available for this paper at this time.
In recent years, the intersection of artificial intelligence (AI) and renewable energy has emerged as a pivotal domain with transformative potential. This review delves into a comprehensive review of the impact that AI technologies have had on enhancing efficiency and management in the renewable energy sector. The integration of AI into renewable energy systems has ushered in a new era of optimization, addressing challenges and unlocking opportunities for sustainable energy production. AI's role in renewable energy begins with its ability to analyze vast datasets generated by energy systems, weather patterns, and consumption trends. Machine learning algorithms have been employed to predict energy demand, optimize grid operations, and enhance forecasting accuracy, thereby contributing to the increased efficiency of renewable energy sources. This application is crucial for overcoming the intermittent nature of renewable sources such as solar and wind power. Moreover, AI-driven technologies facilitate the intelligent management of energy storage systems, enabling better utilization of excess energy during peak production periods. Advanced control mechanisms, empowered by AI, have significantly improved the coordination of diverse energy sources, ensuring a seamless integration of renewable energy into existing power grids. Additionally, AI-driven predictive maintenance has proven instrumental in reducing downtime and optimizing the performance of renewable energy infrastructure. The review also explores the potential environmental and economic benefits of AI in renewable energy, emphasizing the role of smart grids, demand response systems, and decentralized energy production. As the world strives towards a sustainable energy future, this review offers valuable insights into the ongoing evolution of AI technologies and their impact on revolutionizing the efficiency and management of renewable energy systems. The findings presented here contribute to the growing body of knowledge aimed at accelerating the global transition to cleaner and more sustainable energy solutions.
Adewumi et al. (Mon,) studied this question.