Vollständiger Abstract
Worum geht es in dieser Arbeit?
Artificial intelligence (AI) has emerged as a key enabler in optimizing renewable energy systems, significantly contributing to global efforts toward environmental sustainability. This review explores the application of AI technologies in enhancing the efficiency, reliability, and integration of renewable energy sources such as solar, wind, and hydropower. It focuses on how machine learning (ML), deep learning (DL), and other AI-driven algorithms improve energy forecasting, grid management, and storage optimization. Survey data and case studies demonstrate the potential of AI to minimize energy waste, reduce costs, and lower greenhouse gas emissions, reinforcing its role in transitioning to a sustainable energy future. The review concludes with a discussion of challenges and future research directions.
Bibliografischer Nachweis
Publikationsdaten
- Autor:innen
- Chisom Assumpta Nnajiofor, Daniel Edet Eyo, Adedolapo Olujuwon Adegbite, Isyaku Abdullahi Odoguje, Elizabeth W. Salako, Femi Emmanuel Folorunsho, Abdulafees Adeolu Adeyeye
- Quelle
- World Journal of Advanced Research and Reviews
- Publikation
- 2024-01-01
- Band / Ausgabe
- Nicht angegeben
- Seiten
- Nicht angegeben
- ISSN / ISBN
- 2581-9615
- Zitationen
- 1 laut Crossref
- Referenzen
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Zitierfähiger Nachweis
Chisom Assumpta Nnajiofor, Daniel Edet Eyo, Adedolapo Olujuwon Adegbite, Isyaku Abdullahi Odoguje, Elizabeth W. Salako, Femi Emmanuel Folorunsho, Abdulafees Adeolu Adeyeye (2024). OI url: https://doi.org/10.30574/wjarr.2024.23.3.2934. World Journal of Advanced Research and Reviews. https://doi.org/10.30574/wjarr.2026.31.2.2139