{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,23]],"date-time":"2026-05-23T05:05:04Z","timestamp":1779512704056,"version":"3.53.1"},"reference-count":123,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T00:00:00Z","timestamp":1779062400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Machine learning (ML) has become a key enabling technology for optimizing renewable energy systems and supporting global sustainability objectives. This paper presents a comprehensive review of recent advances in ML-based optimization techniques applied to clean and renewable energy systems, with particular emphasis on wind energy, hybrid energy systems, energy storage, and intelligent energy management. A systematic literature review covering peer-reviewed publications from 2021 to 2025 was conducted, resulting in the analysis of 138 high-quality journal and conference studies. The reviewed studies were categorized according to evolutionary algorithm-based hybrid models, classical neural networks, and deep learning architectures, including Convolutional Neural Network (CNN), LSTMs, GRUs, and attention-based models. The analysis demonstrates that hybrid ML\u2013metaheuristic frameworks significantly enhance forecasting accuracy, system reliability, fault diagnosis, and multi-objective optimization compared to traditional methods. These intelligent approaches directly contribute to Sustainable Development Goals SDG-7 (Affordable and Clean Energy), SDG-9 (Industry, Innovation, and Infrastructure), and SDG-13 (Climate Action). Key challenges and future research directions are discussed, highlighting the need for scalable, explainable, and real-time ML solutions to enable resilient, low-carbon, and sustainable energy systems.<\/jats:p>","DOI":"10.3390\/a19050405","type":"journal-article","created":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T12:36:40Z","timestamp":1779107800000},"page":"405","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Machine Learning-Based Optimization for Renewable Energy Systems: A Comprehensive Review"],"prefix":"10.3390","volume":"19","author":[{"given":"Mohammad","family":"Shehab","sequence":"first","affiliation":[{"name":"College of Information Technology, Amman Arab University, Amman 11953, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Afaf","family":"Edinat","sequence":"additional","affiliation":[{"name":"College of Information Technology, Amman Arab University, Amman 11953, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-7470-3469","authenticated-orcid":false,"given":"Mariam Al","family":"Ghamri","sequence":"additional","affiliation":[{"name":"College of Information Technology, Amman Arab University, Amman 11953, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mamdouh","family":"Gomaa","sequence":"additional","affiliation":[{"name":"College of Information Technology, Amman Arab University, Amman 11953, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1600-7990","authenticated-orcid":false,"given":"Fatima","family":"Alhaj","sequence":"additional","affiliation":[{"name":"Department of Data Science and Artificial Intelligence, Faculty of Information Technology, Applied Science Private University, Amman 11937, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Israa Wahbi","family":"Kamal","sequence":"additional","affiliation":[{"name":"College of Information Technology, Amman Arab University, Amman 11953, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmed E.","family":"Fakhry","sequence":"additional","affiliation":[{"name":"College of Information Technology, Amman Arab University, Amman 11953, Jordan"},{"name":"Department of Computer Science, Faculty of Information System and Computer Science, October Six University, Giza 12585, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,5,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1002\/cpt.1796","article-title":"An introduction to machine learning","volume":"107","author":"Badillo","year":"2020","journal-title":"Clin. 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