Title :
Application of artificial neural networks for series compensated line protection
Author :
Bachmann, Bemhard ; Novosel, Damir ; Hart, David ; Hu, Yi ; Saha, Murari Mohan
Author_Institution :
ABB/TTI, USA
Abstract :
This paper investigates the feedforward neural network (with a quasi-Newton method for minimization of the error function) for on-line calculation of the voltage across a nonlinear capacitor installation. This technique is incorporated into a new scheme which is independent of the series capacitor installation, operation of the capacitor protection, and the surrounding power system elements. The proposed scheme is simple and accurate and requires only local voltage and current at the bus to improve the reach measurement of distance relays and fault locators. Detailed testing using EMTP has been done to show the benefits, robustness and generalization capabilities of the ANN technique
Keywords :
fault location; feedforward neural nets; generalisation (artificial intelligence); power capacitors; power system analysis computing; power system protection; relay protection; EMTP; artificial neural networks; distance relays; error function minimisation; fault locators; feedforward neural network; generalization capabilities; nonlinear capacitor installation; on-line voltage calculation; power system elements; quasi-Newton method; reach measurement; robustness; series compensated line protection; Artificial neural networks; Capacitors; Feedforward neural networks; Minimization methods; Neural networks; Power system faults; Power system measurements; Power system protection; Power system relaying; Voltage;
Conference_Titel :
Intelligent Systems Applications to Power Systems, 1996. Proceedings, ISAP '96., International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-3115-X
DOI :
10.1109/ISAP.1996.501046