Distribution network maintenance topology identification system based on multi-source data fusion

By using multi-source data fusion technology, the problems of data diversity and inconsistent time scale in distribution network maintenance have been solved, enabling accurate identification of distribution network topology and efficient estimation of parameters, thereby improving maintenance efficiency and power supply reliability.

CN121996730APending Publication Date: 2026-05-08STATE GRID HENAN ELECTRIC POWER CO XIANGCHENG COUNTY POWER SUPPLY CO
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Patent Information

Application Number
CN202511791365.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-01
Publication Date
2026-05-08

AI Technical Summary

Technical Problem

In the current distribution network maintenance, due to the diverse data sources and inconsistent data accuracy, the data time scale is not uniform and the spatiotemporal resolution is insufficient. The existing parameter identification model has poor adaptability under complex sampling conditions, and the identification accuracy and reliability cannot meet the actual needs, affecting the scientific nature and efficiency of maintenance.

Method used

A multi-source data fusion approach is adopted, which integrates and accurately processes multi-source data through a multi-source data acquisition module, a data preprocessing module, a measurement generation module, a topology parameter identification module, an algorithm optimization module, and a graph model database construction module. Combined with deep learning and transfer learning technologies, it establishes a distribution network topology physical feature library, performs dynamic identification of topology structure and accurate estimation of electrical parameters, and constructs a confidence evaluation system for result scoring and self-correction.

Benefits of technology

It significantly improves the spatiotemporal resolution of distribution network status variables, enhances the identification capability in sparse measurement scenarios, improves the accuracy and reliability of parameter identification, ensures the availability and reliability of the system in complex environments, provides accurate topology identification support, and improves maintenance efficiency and power supply reliability.

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Abstract

The invention relates to a distribution network maintenance topology identification system based on multi-source data fusion, and the system achieves the effective integration and precise processing of multi-source power distribution network data through the cooperative work of a multi-source data collection module, a data preprocessing module and a measurement generation module, and remarkably improves the temporal-spatial resolution of the state quantity of a distribution network. According to the method, a confidence evaluation system is constructed, and an algorithm confidence evaluation system is used for carrying out confidence scoring on an output identification structure, so that the uncertainty of an identification result can be quantified, and the availability and reliability of the system in an actual complex environment are greatly improved; through seamless connection and data interaction between a database and a marketing system and a scheduling system, the applicability and effectiveness of the system in an actual maintenance scene are ensured, accurate and reliable topology identification support can be provided for power distribution network maintenance, and the maintenance efficiency and the power supply reliability are improved; the method has the advantages of being high in self-adaption, accurate and reliable.
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