Power distribution network fault positioning method based on algebraic relation description and complementary theory

Abstract

The invention discloses a power distribution network fault positioning method based on algebraic relation description and the complementary theory, and the method comprises the following steps: collecting current out-of-limit information of each feed switch of a power distribution network through employing a main station, defining current state characteristic values of the switches, and determining whether each feed line has a permanent fault or not through employing the current state characteristic values of the switches; carrying out the positioning of a feed line fault segment according to the current state characteristic information uploaded by the feed switches; enabling the main station to send a switching-off command to an automatic switch at the feed line fault segment according to the positioning result of the feed line fault segment. The method employs algebraic relation modeling and an approaching relation theory. Compared with a matrix method, the method is easier for the consideration of fault tolerance, gets rid of dependence on a swarm intelligence algorithm based on logic relation modeling optimization fault positioning method, can employ conventional linear optimization to achieve the positioning of the feed line fault region, is good in numerical stability, is higher in fault positioning efficiency, and is suitable for the online fault positioning of a large-scale power distribution network.

Description

technical field [0001] The invention relates to the technical field of power system distribution network automation, more specifically, to a distribution network fault location method based on algebraic relationship description and complementary theory, which determines the fault location of a distribution network feeder section. Background technique [0002] Distribution network fault location is one of the core contents of distribution network automation. The accuracy and effectiveness of its fault identification directly affects the safety and reliability of distribution network power supply and the quality of power supply to users. With the implementation of my country's distribution network transformation project and the construction of intelligent distribution network, in the medium and low voltage distribution network, a large number of automation equipment and monitoring terminals such as FTU, TTU, RTU, etc. , which can dynamically obtain the status and operation info...

AI Technical Summary

Problems solved by technology

Compared with the unified matrix method, the optimization method based on swarm intelligence algorithm has the advantages of being easy to consider complex multiple faults, good fault tolerance and strong versatility, but has the following defects due to the use of logical relationship description: (1) The fault location model construction process Complex; (2) The efficiency of fault identification is low, which is not suitable for large-scale distribution network online applications; (3) It can only be solved by swarm intelligence optimization algorithm, and the fault location process has strong uncertainty and numerical instability, which indirectly increases the fault area The misjudgment or missed judgment rate of the segment leads to the expansion of the scope of fault power outages

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