1. Guest Editorial: Artificial intelligence‐empowered reliable forecasting for energy sectors.
- Author
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Mahmoud, Karar, Guerrero, Josep M., Abdel‐Nasser, Mohamed, and Yorino, Naoto
- Subjects
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ENERGY industries , *ARTIFICIAL neural networks , *MACHINE learning , *FORECASTING , *QUANTILE regression , *CONVOLUTIONAL neural networks , *DEMAND forecasting - Abstract
This document is a guest editorial from the journal IET Generation, Transmission & Distribution. It discusses the use of artificial intelligence (AI) in reliable forecasting for energy sectors. The editorial highlights the challenges of integrating renewable energy sources and fluctuating electricity demand, and emphasizes the importance of accurate forecasting for system operators. The document also provides summaries of several papers included in a special issue on AI-empowered forecasting in energy sectors, covering topics such as load forecasting, wind power prediction, and control parameter optimization. The editorial concludes by recommending further research and practical implementations of AI approaches in the energy sectors. [Extracted from the article]
- Published
- 2024
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