Title :
Artificial neural net approach for capacitor placement in power system
Author :
Dash, P.K. ; Saha, S. ; Nanda, P.K.
Author_Institution :
Dept. of Electr. Eng., R.E. College, Rourkela, India
Abstract :
The authors propose a new methodology for controlling multitap capacitors in a power system using a three layer feedforward neural network. The neural network, in the proposed scheme is separately trained with two algorithms namely backpropagation and a combined backpropagation-Cauchy´s learning algorithm. Studies on 30 bus IEEE test system are carried out and quite satisfactory results are obtained. The inputs to the net are the real power, reactive power and voltage magnitude at a few selected buses and the network´s outputs are the values of capacitive Var injection. Performance comparison is made between two algorithms and the combined backpropagation-Cauchy´s algorithm is found to be better than the other
Keywords :
backpropagation; feedforward neural nets; power capacitors; power engineering computing; power systems; reactive power; Cauchy´s algorithm; algorithms; backpropagation; buses; capacitive Var injection; capacitor placement; learning algorithm; multitap capacitors; power capacitors; power engineering computing; power system; reactive power; real power; three layer feedforward neural network; voltage magnitude; Artificial neural networks; Backpropagation algorithms; Control systems; Feedforward neural networks; Neural networks; Power capacitors; Power systems; Reactive power; System testing; Voltage;
Conference_Titel :
Neural Networks to Power Systems, 1991., Proceedings of the First International Forum on Applications of
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0065-3
DOI :
10.1109/ANN.1991.213469