EconPapers    
Economics at your fingertips  
 

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

Sabina-Cristiana Necula ()
Additional contact information
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

Energies, 2023, vol. 16, issue 22, 1-24

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.

Keywords: artificial intelligence; clean energy technologies; systematic review; European context; renewable energy; machine learning (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
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/22/7633/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/22/7633/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:22:p:7633-:d:1282657

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:16:y:2023:i:22:p:7633-:d:1282657