Researches On Fault Location And Fault Identification Of Power System Based On Spiking Neural P Systems

With the large-scale DGs(Distributed Generation)access to the distribution network,the traditional single centralized power generation mode shifts to the power generation mode which combines the centralized and distributed power generation mode,which changes the power flow structure and operation mode of the passive distribution network,making the fault location process more complicated.At present,the requirement of safe operation and reliability of power supply is increasing in all walks of life.Fault location and fault identification of power system provide guarantee for reliability and continuity of power supply.The method of fault location and fault identification of the power system is to use the large amount of alarm information generated by automation devices installed in power system after fault to locate and identify the fault timely and effectively.Although SCADA/EMS system plays a certain role in the acquisition of power system fault information,a large amount of information in power system fault is far beyond the processing capacity of operators,so a more complete method of power system fault diagnosis is urgently needed to achieve a complete and accurate fault diagnosis of the power system.All the cells in the Spiking Neural P systems are neurons,and the objects in the system are only spikes.Parallel computing is one of the advantages of the P system,because the SNP system is derived from the information exchange mechanism in the biological neuron system,this characteristic is particularly obvious in the SNP system.This feature makes the SNP system suitable for fault location and fault identification in power system.In this paper,the SNP system is applied to the research of fault location and fault identification in power system.The specific work is as follows.In terms of fault location,based on the Spiking Neural P systems(SNP systems),a new Electrical Synaptic Transmission-Based SNP system is proposed by introducing new synapses,bidirectional model,two types of neurons and canceling the delay of axon.Because the SNP system is easy to express the logical relationship between graphics and has strong ability to process information in parallel,this paper effectively combines the bidirectional characteristics of electrical synaptic transmission with the electrical quantity(direction of current)for fault location of distribution network with DGs.In this paper,the fault location model and reasoning algorithm of Electrical Synaptic Transmission-Based SNP system(EESNPS)are studied and applied reasonably in the bidirectional power flow characteristics of distribution network with DGs.The algorithm has the advantages of high accuracy,minor calculation,simple and intuitive model and reasoning algorithm.Finally,the paper verifies the effectiveness,accuracy and reliability of the method through two cases,and each case involves the single fault,multiple fault and misinformation fault.In terms of fault identification,based on the traditional weighted fuzzy reasoning spiking neural P systems(WFRSNP system),a LWFRSNP system(Fault Information Logic-Based Weighted Fuzzy Reasoning Spiking Neural P Systems)is proposed by adding the logic characteristics of fault information.This method makes full use of the protection and circuit breaker information uploaded by SCADA.With the powerful parallel processing ability of WFRSNP,fault identification can be carried out quickly and accurately.Finally,the accuracy,rapidity and fault tolerance of this method are verified through fault cases.