Transformer area topology identification method and system based on user branches

Abstract

The invention belongs to the field of power topology big data analysis, and particularly relates to a transformer area topology identification method and system based on user branches. The method comprises the following steps of: S1, performing data access and processing: classifying users according to user acquisition features, address features and power consumption features; S2, realizing user branch identification by taking power supply and distribution design specification analysis as a main analysis method and collecting topology analysis and voltage correlation analysis as auxiliary analysis methods; S3, after user branch identification, diagnosing the transformer area where the user branches belong to; and S4, according to a voltage correlation analysis result and / or a power supply and distribution design specification, realizing automatic identification and output of the transformer area topology through branch adjacent identification and branch collinear identification. According to the method, a virtual power supply network based on the user branches under the limiting conditions of the existing archive data and the collected operation data is constructed, and the operation data is limited by an actual power supply network, so that the accuracy of the data analysis result is very high, and the practical level can be completely reached.

Description

technical field [0001] The invention belongs to the field of power topology big data analysis, and in particular relates to a method and a system for identifying station area topology based on user branches. Background technique [0002] With the comprehensive coverage of the electricity consumption information collection system, the operation data of the electric energy meter of the electric power user under the low-voltage station area can be collected in quasi-real time, because the change of the operation data of the electric energy meter at each time depends on the change of the user load and from the transformer end to the The electrical parameters of the power supply lines at the user end are different, so through the statistics and analysis of the change rules of the operating data within a certain period, it is possible to realize the intelligent diagnosis of the topology of the low-voltage station area. [0003] The buildings of power users in the low-voltage stati...

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Problems solved by technology

[0007] At present, when performing big data analysis on the topology of the station area, due to the complexity and frequent changes of the topology analysis of the station area, the results of the data analysis are not good. The accuracy rate of 80% of the abnormal identification of household changes is considered a good result, and the identifiable topology is also good. It is relatively simple and cannot be consistent with the actual power supply topology

[0008] There are a large number of users in the station area, and the number of residential users accounts for the vast majority. Most users have low power consumption and various power supply methods. Only through the analysis of power consumption line loss correlation and voltage correlation cannot be accurately extracted. Accurate identification of household substations and topologies based on features, resulting in low identification accuracy and detection rate of substation status, and the identifiable topology level is simple, which cannot be consistent with the actual power supply topology, resulting in insufficient support for the actual power supply business. Unable to reach practical level

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