Load power loss probability prediction method and system under wind and rain superposition disasters

Abstract

The invention provides a load power loss probability prediction method and system under wind and rain superposition disasters, and relates to the technical field of power distribution network fault prediction. The method comprises the steps of obtaining typhoon parameters and rainfall parameters under the wind and rain superposition disasters; inputting the typhoon parameters, the rainfall parameters and the to-be-detected distribution line into a power-loss probability prediction model, and outputting the probability of power loss of each load on the to-be-detected distribution line caused by the wind and rain superposition disasters, wherein the power loss probability prediction model is obtained by correcting a constructed load power loss probability result matrix caused by typhoon through a rainfall parameter sample. The method and system provided by the invention are used for solving the defect in the prior art that prediction is carried out aiming at a single disaster-consistent factor when the load power-loss probability is predicted, and accurately predicting the load power-loss probability under the wind and rain superposition disasters, so that the capability of the power distribution network to resist and adapt to the disasters can be more accurately and systematically evaluated.

Description

technical field [0001] The invention relates to the technical field of distribution network fault prediction, in particular to a method and system for predicting load power loss probability under superimposed wind and rain disasters. Background technique [0002] Due to the adverse effects of global warming on the earth's ecology, the frequency of extreme disasters has increased dramatically in recent years. Extreme disasters have the characteristics of high uncertainty and large impact range, and the normal operation of the power system is facing a great threat. As the most vulnerable link in the power system, the urban distribution network is more vulnerable to disaster damage. [0003] Different types of natural disasters are often interrelated, one type of disaster can induce another, and different types of disasters can be coupled with each other or even transformed into each other. For example, the occurrence of typhoons often brings torrential rain, which in turn ca...

AI Technical Summary

Problems solved by technology

[0006] The present invention provides a load power loss probability prediction method and system under wind and rain superimposed disasters, which are used to solve the defect of predicting the single disaster-causing factor in the prior art when predicting the load power loss probability. Accurate prediction of power outage probability enables a more accurate and systematic assessment of the distribution network's resilience and adaptability to disasters

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