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Aiming at the problems of high cost, low real-time performance of manual identification of low-voltage station topological structure, automatic identification methods such as instantaneous power failure method and voltage correlation analysis method, which affect residents’ electricity consumption, and the success rate is limited by application scenarios, this paper proposes a method based on multiple linear regression Line impedance analysis method for automatic identification of the topology of low-voltage stations. Based on the relationship between voltage, current, and impedance, multiple linear regression analysis is used to derive the upstream topology step by step from the bottom up to the top of the topology and then determine the station membership by voltage correlation. The cloud platform based on Docker technology and Hadoop technology is used for data distributed storage calculation, and an identification model in the context of big data is established to effectively improve the efficiency of the algorithm. Finally, the correctness of the algorithm verification is judged based on the results of manual field verification.

Retraction: [Kaiyi Qiu, Xin Liu, Jie Liu, Hongbo Ma, Jingya Li, Zhengchao Zhang, Guangliang Chen, Li Cai, Research on tridimensional monitoring and defence technology of substation, IET Circuits, Devices & Systems 2022 (https://doi.org/10.1049/cds2.12129)]. The above article from IET Circuits, Devices & Systems, published online on 14 September 2022 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor‐in‐Chief, Harry E. Ruda, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.

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