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Assessing the Potential of Artificial Intelligence in Advancing Clean Energy Technologies in Europe: A Systematic Review

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  • Sabina-Cristiana Necula

    (Department of Accounting, Business Information Systems and Statistics, Faculty of Economics and Business Administration, Alexandru Ioan Cuza University of Iasi, 700505 Iasi, Romania)

Abstract

This systematic review investigates the role of artificial intelligence (AI) in advancing clean energy technologies within Europe, based on a literature survey from 2006 to 2023. The assessment reveals that AI, particularly through deep learning and neural networks, enhances the efficiency, optimization, and management of clean energy systems. Noteworthy is AI’s capacity to improve short-term energy forecasts, essential for smart cities and IoT applications. Our findings indicate that AI drives innovation in renewable energy, contributing to the development of smart grids and enabling collaborative energy-sharing models. While the research underscores AI’s substantial influence in Europe’s energy sector, it also identifies gaps, such as varied AI algorithm applications in different renewable energy sectors. The study emphasizes the need for integrating AI with emerging clean energy innovations, advocating for interdisciplinary research to navigate the socio-economic, environmental, and policy dimensions. This approach is crucial for guiding a sustainable and balanced advancement in the clean energy landscape, signifying AI’s pivotal role in Europe’s energy transition.

Suggested Citation

  • Sabina-Cristiana Necula, 2023. "Assessing the Potential of Artificial Intelligence in Advancing Clean Energy Technologies in Europe: A Systematic Review," Energies, MDPI, vol. 16(22), pages 1-24, November.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:22:p:7633-:d:1282657
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    References listed on IDEAS

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    1. Izabela Rojek & Dariusz Mikołajewski & Krzysztof Galas & Adrianna Piszcz, 2025. "Advanced Deep Learning Algorithms for Energy Optimization of Smart Cities," Energies, MDPI, vol. 18(2), pages 1-19, January.

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