The Fault Diagnosis Of Relay Protection Based On Bayesian Network

Uncertain problems are key problems in fault diagnosis fields, which are resulted by many important reasons, including complex diagnosis objects, limit test means and the inexact diagnosis knowledge, etc. Power grid is a large electromechanical equipment, which has complex, correlative relation exiting in its units, and the units are full of uncertain factors and information. So the fault of gird is possible correlative, multi-kinds. In the all, the most important problem of solving power system fault diagnosis is to solve the uncertain problem. There are many common methods for solving uncertain problems. There are many experts researching on those methods, and has obtained that, Bayesian network based on Bayesian theory is the best method for solving uncertain problems now.Bayesian network is one of the most effective theoretical models for uncertainty knowledge expression and reasoning. Bayesian network is a directed acyclic graph with network structure which is intuitionist and easy understanding. It can handle multi-information expression, data fusion and bi-directional parallel reasoning. The ability to colligate the prior information and the current information makes the inference much more accurate and believable. The contents in this paper include the Bayesian network aspects:A power system fault diagnosis model based on Bayesian network has been proposed. Moreover, the temporal order attribute of information is considered in the Bayesian network model; Researched the issue of data pretreatment, the algorithm of identify the coherence of temporal order information and the method of state estimation for incomplete information are proposed; The Bayesian network approach is presented to deal with power system fault diagnosis, and case study proved the effectiveness of this approach; The algorithm of probability learning in fault diagnosis Bayesian network is proposed.