Title :
Application of AI techniques for fault diagnosis in power distribution system
Author :
Teo, C.Y. ; Kwok, W.K. ; Lee, C.C.
Author_Institution :
Nanyang Technol. Univ., Singapore
Abstract :
A fault diagnosis system for power distribution system using rule-based approach and machine learning of fault pattern through network state capturing mechanism is described. Special KBS record format is proposed for knowledge representation. By linking to a distribution system simulator, the diagnostic system has been trained and verified. Two model distribution systems have also been tested and the developed system can be integrated to an existing SCADA system. The test networks were: the Changi network is a 22 kV distribution system for an international airport which has 3 incoming 31.25 MVA sources, 21 buses, 8 bus couplers and 17 feeders; and the Western network which is abstracted from part of an urban distribution system consisting of 35 buses, 4 incoming 75 MVA sources, 36 feeders and 4 bus-couplers
Keywords :
distribution networks; failure analysis; fault location; knowledge based systems; learning systems; power engineering computing; 22 kV; 31.25 MVA; 75 MVA; AI techniques; Changi network; Western network; distribution system; distribution system simulator; fault diagnosis system; fault pattern; international airport; knowledge representation; machine learning; network state capturing mechanism; power distribution system; rule-based approach; urban distribution system;
Conference_Titel :
Intelligent Systems Engineering, 1992., First International Conference on (Conf. Publ. No. 360)
Conference_Location :
Edinburgh
Print_ISBN :
0-85296-549-4
