Applications of Artificial Intelligence Algorithms in the Energy Sector

Hubert Szczepaniuk () and Edyta Karolina Szczepaniuk
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Hubert Szczepaniuk: Warsaw University of Life Science WULS-SGGW, 02-787 Warsaw, Poland
Edyta Karolina Szczepaniuk: Polish Air Force University, 08-521 Dęblin, Poland

Energies, 2022, vol. 16, issue 1, 1-24

Abstract: The digital transformation of the energy sector toward the Smart Grid paradigm, intelligent energy management, and distributed energy integration poses new requirements for computer science. Issues related to the automation of power grid management, multidimensional analysis of data generated in Smart Grids, and optimization of decision-making processes require urgent solutions. The article aims to analyze the use of selected artificial intelligence (AI) algorithms to support the abovementioned issues. In particular, machine learning methods, metaheuristic algorithms, and intelligent fuzzy inference systems were analyzed. Examples of the analyzed algorithms were tested in crucial domains of the energy sector. The study analyzed cybersecurity, Smart Grid management, energy saving, power loss minimization, fault diagnosis, and renewable energy sources. For each domain of the energy sector, specific engineering problems were defined, for which the use of artificial intelligence algorithms was analyzed. Research results indicate that AI algorithms can improve the processes of energy generation, distribution, storage, consumption, and trading. Based on conducted analyses, we defined open research challenges for the practical application of AI algorithms in critical domains of the energy sector.

Keywords: artificial intelligence; cybersecurity; machine learning; metaheuristic; fuzzy inference systems; genetic algorithms; artificial neural networks; energy sector; Smart Grid (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: 2022
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