The Evolution of AI Applications in the Energy System Transition: A Bibliometric Analysis of Research Development, the Current State and Future Challenges

Daniel Icaza Alvarez (), Fernando González-Ladrón- de-Guevara, Jorge Rojas Espinoza, David Borge-Diez, Santiago Pulla Galindo and Carlos Flores-Vázquez
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Daniel Icaza Alvarez: Laboratorio de Energías Renovables y Simulación en Tiempo Real (ENERSIM), Centro de Investigación, Innovación y Transferencia Tecnológica, Universidad Católica de Cuenca, Cuenca 010203, Ecuador
Fernando González-Ladrón- de-Guevara: Instituto Universitario Mixto de Tecnología de Informática, Universitat Politècnica de València, 46022 Valencia, Spain
Jorge Rojas Espinoza: Universidad Politécnica Salesiana, Cuenca 010105, Ecuador
David Borge-Diez: Department of Electrical, Systems and Automation Engineering, University of Leon, 24071 Leon, Spain
Santiago Pulla Galindo: Laboratorio de Energías Renovables y Simulación en Tiempo Real (ENERSIM), Centro de Investigación, Innovación y Transferencia Tecnológica, Universidad Católica de Cuenca, Cuenca 010203, Ecuador
Carlos Flores-Vázquez: Laboratorio de Robótica (ROBLAB), Unidad de Posgrados, Universidad Católica de Cuenca, Cuenca 010203, Ecuador

Energies, 2025, vol. 18, issue 6, 1-31

Abstract: The transformation of energy markets is at a crossroads in the search for how they must evolve to become ecologically friendly systems and meet the growing energy demand. Currently, methodologies based on bibliographic data analysis are supported by information and communication technologies and have become necessary. More sophisticated processes are being used in energy systems, including new digitalization models, particularly driven by artificial intelligence (AI) technology. In the present bibliographic review, 342 documents indexed in Scopus have been identified that promote synergies between AI and the energy transition (ET), considering a time range from 1990 to 2024. The analysis methodology includes an evaluation of keywords related to the areas of AI and ET. The analyses extend to a review by authorship, co-authorship, and areas of AI’s influence in energy system subareas. The integration of energy resources, including supply and demand, in which renewable energy sources play a leading role at the end-customer level, now conceived as both producer and consumer, is intensively studied. The results identified that AI has experienced notable growth in the last five years and will undoubtedly play a leading role in the future in achieving decarbonization goals. Among the applications that it will enable will be the design of new energy markets up to the execution and start-up of new power plants with energy control and optimization. This study aims to present a baseline that allows researchers, legislators, and government decision-makers to compare their benefits, ambitions, strategies, and novel applications for formulating AI policies in the energy field. The developments and scope of AI in the energy sector were explored in relation to the AI domain in parts of the energy supply chain. While these processes involve complex data analysis, AI techniques provide powerful solutions for designing and managing energy markets with high renewable energy penetration. This integration of AI with energy systems represents a fundamental shift in market design, enabling more efficient and sustainable energy transitions. Future lines of research could focus on energy demand forecasting, dynamic adjustments in energy distribution between different generation sources, energy storage, and usage optimization.

Keywords: artificial intelligence (AI); smart energy systems; energy transition (ET); energy planning; artificial intelligence and energy transition (AI&ET) (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: 2025
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