Low-voltage transformer area topology identification method and identification device

Abstract

The invention relates to the technical field of big data analysis, and provides a low-voltage transformer area topology identification method and a low-voltage transformer area topology identificationdevice. A low-voltage transformer area comprises a plurality of line branches. The low-voltage transformer area topology identification method comprises the steps of: collecting power utilization information data of each line branch at a preset time interval in a preset time period, and forming an original data matrix; preprocessing the original data matrix to obtain a standardized data matrix; mapping the standardized data matrix into a low-dimensional space of a preset dimensionality to obtain a low-dimensional data matrix; and drawing a topological structure of the low-voltage transformerarea according to the low-dimensional data matrix. According to the low-voltage transformer area topology identification method and the low-voltage transformer area topology identification device provided by the invention, the topological structure of the low-voltage transformer area can be accurately, efficiently and automatically identified, so that the management level of the low-voltage transformer area is greatly improved.

Description

technical field [0001] The invention relates to the technical field of big data analysis, in particular to a low-voltage station area topology identification method and a low-voltage station area topology identification device. Background technique [0002] In the new generation of power systems, intelligent terminals such as power distribution automation and power consumption information collection are increasing, and the connection relationship and connectivity between terminals are becoming increasingly complex. Accurate acquisition of network topology information is beneficial to more and more Lean management of complex distribution networks. [0003] The topological structure of the low-voltage station area provides connections such as feeders, distribution transformers, marketers and users. This connection relationship is of great significance for line loss analysis, power outage research and judgment, and effective management during power outages of the distribution n...

AI Technical Summary

Problems solved by technology

However, the existing topology identification methods cannot capture this instantaneous change in time, which leads to problems such as low efficiency and long cycle for troubleshooting the abnormal point of line loss in the distribution network, thus failing to meet the real-time and accuracy requirements of topology identification.

Moreover, the existing topology recognition methods still require more manual participation, which is cumbersome and time-consuming, and cannot meet the needs of intelligent topology recognition.

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