A distribution network topology identification method, electronic equipment and medium

Abstract

The invention discloses a distribution network topology identification method, electronic equipment and a medium. First, based on the historical distribution network voltage amplitude data set, the voltage amplitude measurement matrix of the voltage amplitude Markov blanket format of the adjacent node pairs of the distribution network is formed, and the voltage amplitude of the distribution network nodes can be compressed and used for power distribution. Network topology recognition Markov blanket vector compression neural network structure, and then iterative training, to obtain the optimal Markov blanket vector compression neural network model; finally according to the real-time voltage amplitude measurement of the distribution network topology Identify and obtain real-time line topology on-off information of the distribution network. The invention improves the traditional neural network model, is applicable to large-scale distribution network topology recognition problems, improves calculation efficiency, enhances recognition accuracy, and is compatible with distribution network stability control and other algorithms.

Description

technical field [0001] The invention belongs to the field of distribution network topology recognition, and in particular relates to a distribution network topology recognition method based on a Markov blanket vector compression neural network, electronic equipment and a medium. Background technique [0002] In recent years, with the increasing integration of renewable energy, electric vehicles, energy storage, etc., the distribution network is developing rapidly. In this case, two-way power flow may flow to the grid to feed back the remaining energy. These changes require enhanced management of grid operation and control, prerequisites of which include timely and reliable estimates of grid topology. In practice, the configuration of the distribution network may change frequently, sometimes even several times per hour. [0003] For the topology recognition algorithm of distribution network, it can be divided into methods not based on graph theory and methods based on graph ...

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Problems solved by technology

[0004] In order to overcome the technical problems of low recognition accuracy, slow model training, low efficiency, and high parameter requirements in the current distribution network topology recognition, the present invention provides a Markov blanket map based vector model with high efficiency, good compatibility and high recognition accuracy. Distribution network topology recognition method, electronic equipment and medium based on compressed neural network

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