Topology identification and parameter estimation method for low-voltage distribution network

Abstract

The invention discloses a topology identification and parameter estimation method for a low-voltage distribution network. The method comprises the following steps: fusing the series-parallel relationfeatures of nodes, and building a unified parallel circuit regression model based on a voltage drop equation; screening an optimal matching table pair, and performing minimum error root-mean-square screening according to a regression result of the measurement data; realizing topology identification and parameter estimation between the two points, and recovering an actual power grid model from theunified parallel circuit model according to the regression coefficient; eliminating redundant information, and analyzing and matching upstream and downstream nodes according to the voltage correlation, and generating branch set data. The topology identification and parameter estimation method can accurately identify the affiliation of each measurement node in the low-voltage power distribution network and estimate the transformer area line parameters with high precision; the algorithm is combined with the characteristics of topology identification and parameter estimation problems, and therefore the risks of misjudgment and redundant information generation can be reduced.

Description

technical field [0001] The invention relates to the field of electrical technology, in particular to a low-voltage distribution network topology identification and parameter estimation method. Background technique [0002] The low-voltage distribution network is a key link between power transmission and power consumption. It usually refers to the 400 / 220V power supply network in the Taiwan area, which directly meets the needs of residents, businesses and offices. In terms of power grid observation and identification, the power supply department can monitor the operating conditions of the high-voltage and low-voltage sides of the distribution network transformer, and obtain user load data through the meter. Lack of effective monitoring and management, poor observability of the network; and frequent changes in the topology of the active distribution network with a high proportion of distributed power access, these factors pose new technical challenges to the topology identific...

AI Technical Summary

Problems solved by technology

In view of the fact that the existing topology identification and parameter identification methods based on the circuit regression analysis error screening algorithm may cause misjudgment of the circuit model, and at the same time cannot properly handle the problems of virtual nodes and virtual branches, this invention proposes an improved regression error screening algorithm. Combining the algorithm with the characteristics of topology recognition and parameter estimation problems can reduce the risk of misjudgment and redundant information

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