Method for identifying and correcting distribution network data based on topological tree

Abstract

The invention relates to a method for identifying and correcting distribution network data based on a topological tree. The method includes the steps of: firstly building a minimum distribution region model of a distribution network, then identifying and correcting current switch telemeasuring data according to the minimum distribution region model, each piece of switch telemeasuring historical data, and each switch rated capacity; secondly performing data identification and correction on each region switch according to the minimum distribution region model and a region balance principle; and finally performing data identification and correction on measurement information and un-supplement measurement information of a distribution transformer at an end node according to the capacity size of the distribution transformer. The method for identifying and correcting the distribution network data based on the topological tree has good measurement supplement and correction effects for the condition that part of measurement is missing in the current cable distribution network, provides a valid data source for further application of the distribution network, and has good practical significance for practical application of the distribution network.

Description

technical field [0001] The invention relates to the field of power system distribution automation, in particular to a method for identifying and correcting power distribution network data based on a topology tree. Background technique [0002] In recent years, with the country's vigorous investment in distribution network infrastructure, a number of distribution network automation pilot projects have successfully passed the acceptance test. The continuous expansion of the scope and scale of distribution network data collection, coupled with the access of quasi-real-time systems such as load management systems (CIS) and geographic information systems (AM\FM\GIS), has made it possible to implement advanced applications in distribution networks. [0003] Distribution network data identification and correction, as the basis of advanced distribution network applications, has the functions of data completion and filtering, and provides mature data sources for modules such as power...

AI Technical Summary

Problems solved by technology

The distribution network state estimation is different from the main network state estimation and has its own characteristics. However, due to the lack of measurement data in the past, the traditional algorithm is mostly completed by the power flow calculation with additional conditions, and a small amount of bad data may lead to Calculation error increases

[0004] In addition, the current distribution network automation construction is transitioning from the traditional type to the intensive type and even the intelligent type. The grid model is mostly derived by GIS, and it is difficult to guarantee the parameters of the feeder section.

Moreover, most of the distribution networks in various places are hybrid distribution networks that combine traditional overhead feeders and cables. The network structure is complex, and most of the overhead feeders are segmented by load switches. estimated to be difficult

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