Artificial Intelligence for Management of Variable Renewable Energy Systems: A Review of Current Status and Future Directions

Latifa A. Yousef (), Hibba Yousef and Lisandra Rocha-Meneses
Additional contact information
Latifa A. Yousef: Renewable and Sustainable Energy Research Center, Technology Innovation Institute, Masdar City, Abu Dhabi P.O. Box 9639, United Arab Emirates
Hibba Yousef: Biotechnology Research Center, Technology Innovation Institute, Masdar City, Abu Dhabi P.O. Box 9639, United Arab Emirates
Lisandra Rocha-Meneses: Renewable and Sustainable Energy Research Center, Technology Innovation Institute, Masdar City, Abu Dhabi P.O. Box 9639, United Arab Emirates

Energies, 2023, vol. 16, issue 24, 1-27

Abstract: This review paper provides a summary of methods in which artificial intelligence (AI) techniques have been applied in the management of variable renewable energy (VRE) systems, and an outlook to future directions of research in the field. The VRE types included are namely solar, wind and marine varieties. AI techniques, and particularly machine learning (ML), have gained traction as a result of data explosion, and offer a method for integration of multimodal data for more accurate forecasting in energy applications. The VRE management aspects in which AI techniques have been applied include optimized power generation forecasting and integration of VRE into power grids, including the aspects of demand forecasting, energy storage, system optimization, performance monitoring, and cost management. Future directions of research in the applications of AI for VRE management are proposed and discussed, including the issue of data availability, types and quality, in addition to explainable artificial intelligence (XAI), quantum artificial intelligence (QAI), coupling AI with the emerging digital twins technology, and natural language processing.

Keywords: digital technologies; forecast; hybrid system; optimization; renewable energy (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/1996-1073/16/24/8057/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/24/8057/ (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:24:p:8057-:d:1299919

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 ().