Power system fault automatic diagnosis method based on fuzzy reasoning spiking neural P system

Abstract

The invention discloses a power system fault automatic diagnosis method based on a fuzzy reasoning spiking neural P system. Firstly, topological data representing the whole topological structure of apower network, and protection data of protection configuration of a power grid network, are constructed. Secondly, after a SCADA system provides action information of protection and switching, a powernetwork topology analysis algorithm program is called to determine related suspicious fault elements based on on-off states of a breaker, a fuzzy reasoning spiking neural P system diagnosis model corresponding to each suspicious fault element is generated, and then, a reasoning algorithm of the fuzzy reasoning spiking neural P system is called to determine the fault elements. In the method provided by the invention, fault diagnosis of the fuzzy reasoning spiking neural P system in a power transmission network is realized through a programmed mode. The whole fault diagnosis process is realizedautomatically, even under a situation of complex faults of a large-scale power network and a situation where the SCADA system provides complete fault information or information, such as information of maloperation or failure to operate of a protection breaker, is not complete, correct diagnosis results can be obtained efficiently and automatically.

Description

technical field [0001] The invention relates to the technical field of power grid dispatching and fault analysis, in particular to an automatic fault diagnosis method of a power system based on a fuzzy reasoning pulse neural membrane system (FRSN P system). Background technique [0002] With the continuous improvement of productivity in modern society, power users have higher and higher requirements for power supply reliability, especially continuity. High-quality, reliable and stable power supply has become a common demand of power users. At the same time, the scale of interconnection and the complexity of operation of modern power systems are also increasing, making the losses caused by grid failures more than ever before. Therefore, ensuring continuous and reliable power supply has become an extremely important goal of the power system. However, due to the influence of many factors such as nature and man-made, the occurrence of faults is inevitable. On the other hand, w...

AI Technical Summary

Problems solved by technology

At the same time, for different faulty components, it is necessary to establish a diagnostic model based on the fuzzy reasoning impulse neural membrane system. The workload of this process is huge and cumbersome. Quickly realize fault location

In addition, in practical applications, the interconnection scale of modern power systems is also increasing, and the complexity of the entire fault diagnosis process is also increasing. Therefore, the traditional way of manually calculating and deriving results is obviously unable to meet the rapid development of power grids. requirements

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