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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/73

Title: Artificial neural net approach for capacitor placement in power system
Authors: Dash, P K
Saha, S
Nanda, P K
Keywords: backpropagation
feedforward neural nets
power capacitors
reactive power
Issue Date: 1991
Publisher: IEEE
Citation: Proceedings of the First International Forum on Applications of Neural Networks to Power Systems, 23-26 July 1991, Seattle, WA, P 247-250
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
Description: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
URI: http://hdl.handle.net/2080/73
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