@article{Wu2024, 
author = {Huayi Wu and Zhao Xu and Jiaqi Ruan and Xianzhuo Sun},
title = {PFL-DSSE: A Personalized Federated Learning Approach for Distribution System State Estimation},
year = {2024},
journal = {CSEE Journal of Power and Energy Systems},
volume = {10},
number = {5},
pages = {2265-2270},
keywords = {Distribution system state estimation, personalized federated learning, privacy protection},
url = {https://www.sciopen.com/article/10.17775/CSEEJPES.2023.08830},
doi = {10.17775/CSEEJPES.2023.08830},
abstract = {A centralized framework-based data-driven framework 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 measurement 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.}
}