1 Department of Physics, University of Benin, Nigeria.
2 Scottish Water, UK.
3 Independent Researcher, Plano, TX, U.S.A.
4 San Francisco, USA.
5 NDIC, Nigeria.
6 Independent Researcher, Lagos, Nigeria.
7 Cambridge Engineering Consultants, Amman, Jordan.
Review Article
World Journal of Advanced Research and Reviews, 2024, 21(01), 2487-2499
Article DOI: 10.30574/wjarr.2024.21.1.0347
Received on 18 December 2023; revised on 23 January 2024; accepted on 26 January 2024
The integration of Artificial Intelligence (AI) in the renewable energy sector has emerged as a transformative force, enhancing the efficiency and sustainability of energy systems. This paper provides a comprehensive review of the application of AI in two critical aspects of renewable energy in relation to predictive maintenance and energy optimization. Predictive maintenance, enabled by AI, has revolutionized the renewable energy landscape by predicting and preventing equipment failures before they occur. Utilizing machine learning algorithms, AI analyzes vast amounts of data from sensors and historical performance to identify patterns indicative of potential faults. This proactive approach not only minimizes downtime but also extends the lifespan of renewable energy infrastructure, resulting in substantial cost savings and improved reliability. Furthermore, AI plays a pivotal role in optimizing the energy output of renewable sources. Through advanced data analytics and real-time monitoring, AI algorithms can adapt to changing environmental conditions, predicting energy production patterns and optimizing resource allocation. This ensures maximum energy yield from renewable sources, making them more competitive with traditional energy sources. The paper delves into specific AI techniques such as deep learning, neural networks, and predictive analytics employed for predictive maintenance and energy optimization in various renewable energy systems like solar, wind, and hydropower. Challenges and opportunities associated with implementing AI in renewable energy are discussed, including data security, interoperability, and the need for standardized frameworks. The synthesis of AI technologies with renewable energy not only addresses operational challenges but also contributes to the global transition towards sustainable and clean energy solutions. This review serves as a valuable resource for researchers, practitioners, and policymakers seeking insights into the evolving landscape of AI applications in the renewable energy sector. As technology continues to advance, the synergies between AI and renewable energy are poised to shape the future of the global energy paradigm.
Artificial Intelligence; Renewable Energy; Predictive Maintenance; Energy Optimization; Review
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Shedrack Onwusinkwue, Femi Osasona, Islam Ahmad Ibrahim Ahmad, Anthony Chigozie Anyanwu, Samuel Onimisi Dawodu, Ogugua Chimezie Obi and Ahmad Hamdan. Artificial intelligence (AI) in renewable energy: A review of predictive maintenance and energy optimization. World Journal of Advanced Research and Reviews, 2024, 21(1), 2487-2499. Article DOI: https://doi.org/10.30574/wjarr.2024.21.1.0347