Recent Developments in AI-Based Control for Wind and PV Systems: A Short Review
Youness HAKAM, Mohamed TABAA
Abstract: Artificial intelligence (AI) is playing an expanded role in the regulation of wind and photovoltaic (PV) systems, enabling operators to tame the variability of renewable resources with more accurate forecasting, adaptive control and leaner maintenance. Methods such as fuzzy logic, neural network and Q-learning have their own merits while none of them is the best choice for all problems. The recent advancements indicate the possibilities of hybrid AI and light-weight edge-based solutions, which may enable faster local action decision-making and improved resilience in dynamic settings. In this brief, we provide a short note on the recent advances of AI-based control of wind and PV going systems and forecasts some remaining challenges, including cost, computational complexity and adoption into practical implementations in the modern smart grid.
Keywords
Artificial Intelligence, Wind Energy, Photovoltaic Systems, Maximum Power Point Tracking (MPPT), Fuzzy Logic Control, Neural Networks, Reinforcement Learning, Smart Grid, Energy Management
Published online 4/25/2026, 9 pages
Copyright © 2026 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Youness HAKAM, Mohamed TABAA, Recent Developments in AI-Based Control for Wind and PV Systems: A Short Review, Materials Research Proceedings, Vol. 64, pp 75-83, 2026
DOI: https://doi.org/10.21741/9781644904091-10
The article was published as article 10 of the book Energy Futures
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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