Artificial Intelligence and Machine Learning in Energy Conversion and Management

Konstantinos Mira (), Francesca Bugiotti () and Tatiana Morosuk ()
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Konstantinos Mira: Computer Science Department, CentraleSupélec Paris-Saclay University, 3 Rue Joliot Curie, Gif-sur-Yvette, 91190 Paris, France
Francesca Bugiotti: Computer Science Department, CentraleSupélec Paris-Saclay University, 3 Rue Joliot Curie, Gif-sur-Yvette, 91190 Paris, France
Tatiana Morosuk: Institute for Energy Engineering, Technische Universität Berlin, Marchstr. 18, 10587 Berlin, Germany

Energies, 2023, vol. 16, issue 23, 1-36

Abstract: In the modern era, where the global energy sector is transforming to meet the decarbonization goal, cutting-edge information technology integration, artificial intelligence, and machine learning have emerged to boost energy conversion and management innovations. Incorporating artificial intelligence and machine learning into energy conversion, storage, and distribution fields presents exciting prospects for optimizing energy conversion processes and shaping national and global energy markets. This integration rapidly grows and demonstrates promising advancements and successful practical implementations. This paper comprehensively examines the current state of applying artificial intelligence and machine learning algorithms in energy conversion and management evaluation and optimization tasks. It highlights the latest developments and the most promising algorithms and assesses their merits and drawbacks, encompassing specific applications and relevant scenarios. Furthermore, the authors propose recommendations to emphasize the prioritization of acquiring real-world experimental and simulated data and adopting standardized, explicit reporting in research publications. This review paper includes details on data size, accuracy, error rates achieved, and comparisons of algorithm performance against established benchmarks.

Keywords: artificial intelligence; machine learning; energy conversion; energy management; multicriteria evaluation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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