A deep learning approach for power system knowledge discovery based on multitask learning
Author:
Affiliation:
1. Department of Electrical EngineeringTsinghua UniversityBeijingPeople's Republic of China
2. Stanford Smart Grid LabStanford UniversityStanfordCAUSA
3. Tsinghua‐Berkeley Shenzhen InstituteShenzhenPeople's Republic of China
Funder
Foundation for Innovative Research Groups of the National Natural Science Foundation of China
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/iet-gtd.2018.5078
Reference34 articles.
1. Review and prospect of integrated demand response in the multi-energy system
2. Power system security assessment
3. Machine‐learning approaches to power‐system security assessment;Wehenkel L.;IEEE Expert,1997
4. Decision tree approach to power systems security assessment
5. Robust Online Dynamic Security Assessment Using Adaptive Ensemble Decision-Tree Learning
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