Complex power distribution network fault positioning method based on improved manta ray foraging optimization algorithm

Abstract

The invention discloses a complex power distribution network fault positioning method based on an improved manta ray foraging optimization algorithm, and the method comprises the steps: introducing a Sine chaos theory in the initial stage of the algorithm to generate an initial population, enriching the population diversity, and laying a foundation for the global search of the algorithm; secondly, in order to avoid search stagnation of the whole group due to the fact that the optimal manta ray individual falls into local optimum, a Cauchy reverse learning technology is adopted to generate a reverse solution of the manta ray individual, the convergence rate of the algorithm is increased, and the purposes of expanding the search area range and enhancing the global exploration capacity of the algorithm are achieved. According to the method, fault positioning can be quickly carried out when a single-point fault and a multi-point fault occur in the power distribution network containing the DG and the fault information uploaded by the FTU is distorted or lost, and relatively high fault tolerance and extremely high accuracy are achieved.

Description

technical field [0001] The invention relates to a distribution network fault location technology, in particular to a complex distribution network fault location method based on an improved manta ray foraging optimization algorithm. Background technique [0002] At present, there is a distribution network fault section location technology based on intelligent algorithm, which has attracted the attention of many scholars because of its strong fault tolerance and practical engineering significance. With the increase of distributed power supply in the distribution network, the traditional single power supply network structure will be broken. In the complex network structure composed of multiple power supplies, the flow of fault current is no longer unique. The traditional optimization intelligent algorithm has the problems of low accuracy and poor fault tolerance in the distribution network fault section location technology based on the intelligent algorithm. The most significan...

AI Technical Summary

Problems solved by technology

With the increase of distributed power supply in the distribution network, the traditional single power supply network structure will be broken. In the complex network structure composed of multiple power supplies, the flow of fault current is no longer unique.

The traditional optimization intelligent algorithm has the problems of low accuracy and poor fault tolerance in the distribution network fault section location technology based on the intelligent algorithm. The most significant disadvantage is that the traditional intelligent algorithm has poor global search ability and is easy to fall into local optimum. The convergence speed also affects the timeliness of the actual monitoring system for the line operation status of the distribution network

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