Research on Remote Diagnosis Model of Metering Point Anomaly of 10kV Distribution Line Based on AMI Data

Zhang, Hongda; Yuan, Jingling; Xiong, Lei; Li, Yao; Wang, Jiaying; Hu, Yingjun

doi:10.1109/auteee52864.2021.9668660

Cited by 1 publication

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“…With the proposal of the strategic goal of "carbon peaking and carbon neutrality" in China and the large-scale access of new energy power generation, the traditional power production model has been broken, and the planning, management, and dispatch of power production have become increasingly complex [1]. The data of the power grid presents the characteristics of multisource heterogeneity, scattered data, large scale, rapid change, and many types [2]. The acquisition of distribution data is the basis for the analysis of distribution network operation [3].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Joint Cleaning of Distribution Network Measurement Data Based on Correntropy Criterion with Variable Center Unscented Kalman Filter

Sun

Liu

et al. 2022

Applied Sciences

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Measurement data cleaning is a key step of edge computing in a distribution network; it is beneficial to improve the state perception and regional autonomy level of a distribution network. According to the temporal and spatial correlation of measurement data in the distribution network, a joint cleaning method of measurement data in a distribution network is proposed based on the correntropy criterion with variable center unscented Kalman filter (CC-VC-UKF). Initially, the mean square error (MSE) in the original unscented Kalman filter (UKF) is replaced by the correntropy criterion with variable center (CC-VC) to improve the accuracy of filtering the measurement data in the distribution network with a non-Gaussian non-zero mean measurement deviation. Then, the measured data of different measuring devices located on the same section of the line are filtered based on the CC-VC-UKF algorithm according to their respective reference time series to improve the signal-to-noise ratio of the measured data. Then, the filtered measured data are filtered and cleaned based on the CC-VC-UKF algorithm according to the space–time joint filtering and cleaning technology. Finally, the method is used to test the measurement data of the distribution network obtained by a power supply company in a city in north China to solve the problem of measurement deviation caused by the existence of space distance. Results show that this method can obtain FTU measurement data with higher precision from network topology based on the filtered TTU measurement data through the media of filtered spatial measurement deviation.

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Section: Introductionmentioning

confidence: 99%