Title :
An artificial neural network based trouble call analysis
Author :
Lu, C.N. ; Tsay, M.T. ; Hwang, Y.J. ; Lin, Y.C.
Author_Institution :
Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan
fDate :
7/1/1994 12:00:00 AM
Abstract :
The use of trouble call information for handling service interruption events that exist between primary feeders and customers is discussed in this paper. Artificial neural networks are used for fast pattern recognition and classification of trouble calls such that the time and effort required for service restoration can be reduced. A backpropagation network is chosen as the neural network model. This proposed trouble call analysis system is embedded in an integrated automated mapping, facilities management and geographic information system environment
Keywords :
backpropagation; distribution networks; geographic information systems; neural nets; pattern recognition; power engineering computing; power system restoration; artificial neural network; automated mapping; backpropagation network; distribution system; facilities management; fast pattern recognition; geographic information system environment; primary feeders; service interruption events; service restoration; trouble call analysis; trouble call information; trouble calls classification; Artificial neural networks; Circuit faults; Diagnostic expert systems; Dispatching; Fault diagnosis; Fault location; Monitoring; Power system restoration; Power transmission lines; SCADA systems;
Journal_Title :
Power Delivery, IEEE Transactions on
