State Estimation for Active Distribution Networks Considering Bad Data in Measurements and Topology Parameters

Yizhe Chen, Yifan Gao, Kai Gan, Ming Li, Chengzhi Wei, Xiaoyi Guo, Ruifeng Zhao, Jiangang Lu and Liang Che ()
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Yizhe Chen: Zhaoqing Power Supply Bureau, Guangdong Power Grid Co., Ltd., Zhaoqing 526040, China
Yifan Gao: Zhaoqing Power Supply Bureau, Guangdong Power Grid Co., Ltd., Zhaoqing 526040, China
Kai Gan: Zhaoqing Power Supply Bureau, Guangdong Power Grid Co., Ltd., Zhaoqing 526040, China
Ming Li: Electric Power Research Institute, China Southern Power Grid Co., Ltd., Guangzhou 510663, China
Chengzhi Wei: Electric Power Research Institute, China Southern Power Grid Co., Ltd., Guangzhou 510663, China
Xiaoyi Guo: Electric Power Research Institute, China Southern Power Grid Co., Ltd., Guangzhou 510663, China
Ruifeng Zhao: Power Dispatching and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510600, China
Jiangang Lu: Power Dispatching and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510600, China
Liang Che: College of Electrical and Information Engineering, Hunan University, Changsha 410082, China

Energies, 2025, vol. 18, issue 9, 1-22

Abstract: SE is critical in ADNs integrating renewable DGs. Traditional SE methods face the challenges of increasing SE errors and decreased robustness due to the adverse impact of bad data in measurements and topology parameters. To address these issues, this paper proposes a robust SE method that considers bad data in measurements and topology parameters. First, a bad measurement data processing model is proposed to improve measurement and SE accuracy by generating high-precision pseudo-measurements through adaptive learning from historical data sequences to replace the bad measurement data in measurements. Second, a robust SE model combining network estimation and linear estimation is proposed, which enhances SE accuracy and robustness under bad data generated in measurements and topology parameters in ADNs. In a simulation, the proposed method’s effectiveness is verified on the modified IEEE 33-node system.

Keywords: distribution network; state estimation; bad data (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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