Medium-voltage power distribution network topology identification method based on multiple measurement sections

Abstract

The invention discloses a medium-voltage power distribution network topology identification method based on multiple measurement sections. The method comprises the following steps: acquiring real-timevoltage amplitude measurement data of a mu PMU; establishing a topology change detection index and judging whether topology changes or not; acquiring measurement data of a plurality of time sectionsof the changed DSCADA and [mu]PMU measurement device; constructing a mixed integer quadratic programming topology identification model of multiple measurement sections by taking the minimum residual error as a target; linearizing nonlinear terms in the mixed integer quadratic programming topology identification model by adopting a large M method; and inputting the measurement data of the pluralityof time sections into the linearized mixed integer quadratic programming topology identification model to obtain a topology structure of the power distribution network. Power distribution network pseudo-quantity measurement and limited quantity measurement are well utilized for topology identification. The problem that in the prior art, redundant real-time measurement data are lacked, and consequently topology identification of a power distribution network cannot be accurately conducted is solved, and the method is simple, convenient to implement and high in accuracy.

Description

technical field [0001] The invention relates to the technical field of power system power distribution, in particular to a method for identifying the topology of a medium-voltage distribution network based on multiple measurement sections. Background technique [0002] Distribution network topology identification technology is an important application of distribution network state estimation. Correct topology is an important basis for distribution network security analysis and control decision-making. The large number of distribution network lines and frequent transformation of the power grid lead to frequent errors in the topology of the distribution network, which seriously affects the operation and management of the distribution system. [0003] The existing transmission network topology identification methods mainly include transfer flow method, innovation graph method, set theory method, artificial neural network algorithm, etc. The measurement data is much less than t...

AI Technical Summary

Problems solved by technology

The large number of distribution network lines and frequent transformation of the power grid lead to frequent errors in the topology of the distribution network, seriously affecting the operation and management of the distribution system

[0003] The existing transmission network topology identification methods mainly include transfer flow method, innovation graph method, set theory method, artificial neural network algorithm, etc. The measured data is much less than that of the transmission network, and the above method cannot be directly applied to the topology identification of the distribution network

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