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- Title
Guest editorial: Applications of advanced machine learning and big data techniques in renewable energy‐based power grids.
- Authors
Dabbaghjamanesh, Morteza; Kavousi‐Fard, Abdollah; Dong, Zhao Yang; Jolfaei, Alireza
- Abstract
His current research interests include operation, management and cyber security analysis of smart grids, microgrid, smart city, electric vehicles, artificial intelligence, and machine learning. In recent years, due to the grid modernizations, high penetration of renewable energies, and using smart sensors in the main structure of the power grids, a large amount of data has been generated that can potentially lead to the complexity of the network. His current research interests include power system operation, reliability, resiliency, renewable energy sources, cybersecurity analysis, machine learning, smart grids, and microgrids. TOPIC 1: OPTIMAL OPERATION AND MANAGEMENT OF MULTI-MICROGRIDS USING BLOCKCHAIN TECHNOLOGY Paper 1 by Misagh Dehghani Ghotbabadi et al. investigates the optimal operation of a networked microgrid from the reliability perspective in a correlated atmosphere for the wind generators using an advanced machine learning technique.
- Subjects
ELECTRIC power distribution grids; MACHINE learning; SMART power grids; DEEP learning; PHASOR measurement; BIG data; WATER supply
- Publication
IET Renewable Power Generation (Wiley-Blackwell), 2022, Vol 16, Issue 16, p3445
- ISSN
1752-1416
- Publication type
Article
- DOI
10.1049/rpg2.12622