首页|PFL-DSSE:A Personalized Federated Learning Approach for Distribution System State Estimation
PFL-DSSE:A Personalized Federated Learning Approach for Distribution System State Estimation
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A centralized framework-based data-driven frame-work for active distribution system state estimation(DSSE)has been widely leveraged.However,it is challenged by potential data privacy breaches due to the aggregation of raw measure-ment data in a data center.A personalized federated learning-based DSSE method(PFL-DSSE)is proposed in a decentralized training framework for DSSE.Experimental validation confirms that PFL-DSSE can effectively and efficiently maintain data confidentiality and enhance estimation accuracy.
Distribution system state estimationpersonalized federated learningprivacy protection
Huayi Wu、Zhao Xu、Jiaqi Ruan、Xianzhuo Sun
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Department of Electrical and Electronic Engineering,The Hong Kong Poly-technic University,Hong Kong SAR,China
Department of Electrical and Electronic Engineering,Shenzhen Research Institute,Research Institute of Smart Energy,The Hong Kong Polytechnic University,Hong Kong SAR,China
Department of Electrical and Electronic Engineering,The Hong Kong Polytechnic University,Hong Kong SAR,China
National Natural Science Foundation of ChinaNational Natural Science Foundation of China
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