Intelligent power grid fault diagnosis method based on event origin

Abstract

The invention discloses an intelligent power grid fault diagnosis method based on an event origin. According to the method, on the basis of improvement of a bus and line stratification weight fuzzy Petri network model, the fault occurrence time is taken as the event origin, a protection and breaker motion information sequential constraint inspection method based on the event origin is proposed. The time point and time distance constraints can be acquired according to the protection and breaker alarm information, forward sequential reasoning and reverse sequential reasoning are carried out to acquire the event origin and the time point constraints of the warning information, an initial confidence vector of a place is corrected, influence of sequential inconsistency and the error alarm information on a diagnosis result can be effectively eliminated, and diagnosis accuracy is improved. The method is advantaged in that not only can the fault occurrence time of equipment be acquired, through comparing and analyzing the acquisition time point of the alarm information and the time point constraints, protection and breaker error motion / rejection motion and alarm information missing report conditions are evaluated, and a fault development process is explained according to an evaluation result.

Description

technical field [0001] The invention belongs to the field of grid fault diagnosis research, and more specifically relates to an intelligent grid fault diagnosis method based on an event starting point. Background technique [0002] When the power grid fails, fast and accurate fault diagnosis is very important to speed up the process of accident handling and system recovery, and ensure the safe and reliable operation of the power system. However, with the continuous development and interconnection of the power grid, a large number of alarm information such as protection and circuit breaker action will flood to the dispatch center within a short period of time after the fault occurs, and may be accompanied by uncertainties such as information loss and distortion, which seriously increases the operational efficiency. The personnel can quickly and accurately judge the pressure of the faulty component, and the role of the fault diagnosis system is particularly important at this t...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the above defects of the prior art, the present invention provides a fault diagnosis method for an intelligent power grid based on an event starting point, by constructing a hierarchical weighted fuzzy temporal Petri net (TWFPN, Temporal Weighted Fuzzy Petrinet) fault diagnosis model to perform reasoning to identify real The fault component is designed to solve the technical problem that the fault tolerance performance of the existing fault diagnosis method is not strong due to the failure to make full use of the timing characteristics of the alarm information in the existing fault diagnosis method

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