Fault Diagnosis of Power Network Based on GIS Platform and Bayesian Networks
Abstract: In order to determine
the location of the fault components of the power network quickly and give
troubleshooting solutions, this paper obtains a simplify structure of relay
protection and circuit-breaker as key equipment by analyzing the power network
topology of GIS platform and uses the Bayesian networks fault diagnosis
algorithm and finally designs the power network fault diagnosis module based on
GIS platform. Fault diagnosis algorithm based on Bayesian networks is a new
method for power network fault diagnosis which deals with the power network
fault diagnosis with incomplete alarm signals caused by the protection device’s
and the circuit breaker’s malfunction or refusal to move, device failure of
communication and other reasons in the use of Bayesian networks method. This method establishes the transmission line
fault diagnosis model by using Noisy-Or, Noisy-And node model and similar BP
neural network back propagation algorithm, and obtains the fault trust degree
of each component by using the formula, and finally determines the fault
according to the fault trust degree. The practical engineering application
shows that the search speed and accuracy of fault diagnosis are improved by
applying the fault diagnosis module based on GIS platform and Bayesian network.
Author: Yunfang Xie, Yuhong
Zhou, Weina Liu
Journal Code: jptkomputergg160224
