A machine learning approach for real‐time selection of preventive actions improving power network resilience
Author:
Affiliation:
1. School of Electrical and Electronic Engineering The University of Manchester Manchester UK
2. Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus
Funder
Engineering and Physical Sciences Research Council
Newton Fund
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology,Control and Systems Engineering
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1049/gtd2.12287
Reference47 articles.
1. A review of key strategies in realizing power system resilience;Lin Y.;Glob. Energy Interconnect.,2018
2. State-of-the-art review on power grid resilience to extreme weather events: Definitions, frameworks, quantitative assessment methodologies, and enhancement strategies
3. Influence of extreme weather and climate change on the resilience of power systems: Impacts and possible mitigation strategies
4. Electricity system resilience in a world of increased climate change and cybersecurity risk
5. Boosting the Power Grid Resilience to Extreme Weather Events Using Defensive Islanding
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