Research on complex faults diagnosis of multi-area power network based on Bayesian networks
Shu Zhou · Power System Protection and Control · 2011
According to the fault conditions of complicated topology and large-scale power networks,an efficient method is proposed to partition the large-scale power networks.A hierarchical recursive fault diagnosis model is proposed based on rough set and Bayesian network.Using the ability of knowledge reduction and processing indeterminate information of rough set theory,the hierarchical mining of substation's fault diagnosis knowledge is carried out and optimal seeking of attributes is performed.Then Bayesian network is applied to identify fault areas and fault components.For complicated fault,this paper adopts multi-area parallel diagnosis.Results of calculation examples show that the proposed method is correct and effective,and can improve the fault tolerance capability and speed of the fault diagnosis system while the kernel attribute is lost,so this method is available.