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Artificial intelligence techniques for enabling Big Data services in distribution networks: a review

Author
Barja, S.; Aragüés, M.; Munné, I.; Lloret-Gallego, P.; Bullich, E.; R. Villafafila-Robles
Type of activity
Journal article
Journal
Renewable and sustainable energy reviews
Date of publication
2021-10-13
Volume
150
First page
111459:1
Last page
111459:25
DOI
10.1016/j.rser.2021.111459
Project funding
Big Data for OPen innovation Energy Marketplace
URL
https://www.sciencedirect.com/science/article/pii/S1364032121007413 Open in new window
Abstract
Artificial intelligence techniques lead to data-driven energy services in distribution power systems by extracting value from the data generated by the deployed metering and sensing devices. This paper performs a holistic analysis of artificial intelligence applications to distribution networks, ranging from operation, monitoring and maintenance to planning. The potential artificial intelligence techniques for power system applications and needed data sources are identified and classified. The f...
Keywords
Deep learning, Distribution grid, Machine learning, Smart energy service, Smart grid
Group of research
CITCEA - Centre of Technological Innovation in Power Electronics and Drives