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2026, Vol: 15, Issue: 1
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Technical Note
Online Published: 05 Jul 2025
 


A Comprehensive Review of Artificial Intelligence for Shaping Renewable Energy Power Systems

Ahmed Ezzat, Alaa Mahmoud, Ahmed Abd El Hafez.


Abstract
Renewable Energy Sources (RESs) are widely penetrating power systems, due to their environmental compatibility and shortage reserve of the fossil fuels. This mandates the application of intelligent, innovative and smart techniques for forecasting, controlling and managing of RESs. However, RESs suffer from uncertainty, weather and operating condition dependence, which considers as a major challenge of the conventional controlling strategy. Artificial Intelligence (AI) enjoys the advantage of adapting the control and operating routines according to the system status, which is attributed to the numerous training scenarios. AI in the areas of RESs could improve their reliability, security and sustainability. Moreover, AI could boost the operation of different energy storage systems, which are considered integral part for different RESs system. This article comprehensively analyzes several literatures regarding AI for RESs. Moreover, comprehensive comparisons between conventional controlling and driving systems of AI in fields of RESs are given in the article. The article moreover addresses the storage system for RESs and the impact of application of AI in improving the energy management of such systems. The article acts as simple and reliable tools for researchers and engineers in the area of AI for RES.

Key words: Renewable Energy Sources, Artificial Intelligence, Optimization, Energy, Power System, Sustainability.


 
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How to Cite this Article
Pubmed Style

Ezzat A, Mahmoud A, Hafez AAE. [A Comprehensive Review of Artificial Intelligence for Shaping Renewable Energy Power Systems]. Sol. Energy Sustain. Dev.. 2025; 14(1): 504-521. .

doi:10.51646/jsesd.v14i1.369

Web Style

Ezzat A, Mahmoud A, Hafez AAE. [A Comprehensive Review of Artificial Intelligence for Shaping Renewable Energy Power Systems]. https://www.jsesd.org/?mno=302658357 [Access: November 12, 2026]. .

doi:10.51646/jsesd.v14i1.369

AMA (American Medical Association) Style

Ezzat A, Mahmoud A, Hafez AAE. [A Comprehensive Review of Artificial Intelligence for Shaping Renewable Energy Power Systems]. Sol. Energy Sustain. Dev.. 2025; 14(1): 504-521. .


doi:10.51646/jsesd.v14i1.369

Vancouver/ICMJE Style

Ezzat A, Mahmoud A, Hafez AAE. [A Comprehensive Review of Artificial Intelligence for Shaping Renewable Energy Power Systems]. Sol. Energy Sustain. Dev.. (2025), [cited November 12, 2026]; 14(1): 504-521. .


doi:10.51646/jsesd.v14i1.369

Harvard Style

Ezzat, A., Mahmoud, . A. & Hafez, . A. A. E. (2025) [A Comprehensive Review of Artificial Intelligence for Shaping Renewable Energy Power Systems]. Sol. Energy Sustain. Dev., 14 (1), 504-521. .


doi:10.51646/jsesd.v14i1.369

Turabian Style

Ezzat, Ahmed, Alaa Mahmoud, and Ahmed Abd El Hafez. 2025. [A Comprehensive Review of Artificial Intelligence for Shaping Renewable Energy Power Systems]. Solar Energy and Sustainable Development, 14 (1), 504-521. .


doi:10.51646/jsesd.v14i1.369

Chicago Style

Ezzat, Ahmed, Alaa Mahmoud, and Ahmed Abd El Hafez. "[A Comprehensive Review of Artificial Intelligence for Shaping Renewable Energy Power Systems]." Solar Energy and Sustainable Development 14 (2025), 504-521. .


doi:10.51646/jsesd.v14i1.369

MLA (The Modern Language Association) Style

Ezzat, Ahmed, Alaa Mahmoud, and Ahmed Abd El Hafez. "[A Comprehensive Review of Artificial Intelligence for Shaping Renewable Energy Power Systems]." Solar Energy and Sustainable Development 14.1 (2025), 504-521. Print..


doi:10.51646/jsesd.v14i1.369

APA (American Psychological Association) Style

Ezzat, A., Mahmoud, . A. & Hafez, . A. A. E. (2025) [A Comprehensive Review of Artificial Intelligence for Shaping Renewable Energy Power Systems]. Solar Energy and Sustainable Development, 14 (1), 504-521. .


doi:10.51646/jsesd.v14i1.369

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