Low-voltage transformer district user phase identification method based on voltage curve similarity analysis

Abstract

The invention relates to the field of topological structure identification of a low-voltage power distribution network and particularly relates to a low-voltage transformer district user phase identification method based on smart meter voltage curve similarity analysis. The method comprises a step of extracting a transformer district transformer and the smart meter voltage sequence data of a userfrom power consumption information collection system, a step of calculating a DTW distance between different user voltage sequences and calculating a local outlier factor of each user based on the DTWdistance and judging whether the connection relationship of the transformer district of the user is correct or not, and a step of calculating the DTW distance between each user of a correct transformer district transformer connection relationship and A, B and C phase voltage sequences of the transformer district transformer, wherein the user phase is a phase with a smallest DTW distance in the A,B and C phases. According to the method, the low-voltage transformer district user phase identification can be carried out in an online way, the manual on-site patrol is not needed, and the problemsof low recognition accuracy, low work efficiency and high cost of the low-voltage transformer district user phase identification are effectively solved.

Description

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AI Technical Summary

Benefits of technology

This technology helps gather more accurate usage patterns for users' electrical energy needs by analyzing their power curves over time. It allows us to automatically recognize when there’s an issue or potential hazard related to managing this demand accurately. By doing that we aim to improve our ability to manage household appliances efficiently while also addressing issues like poor indoor air quality caused by excessive lightning strikes during winter months.

Problems solved by technology

This patented describes an improved way to identify users who have heavily loaded or uneven electrical usage by identifying their own phases based only upon measured voltages from the current location. However, existing methods require human labor and materials resource intensive analysis.

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