A Novel Control Method for DSTATCOM Using Artificial Neural Network

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1 August 2006

conference paper
Published by Institute of Electrical and Electronics Engineers (IEEE)

Vol. 3, 1-4
DOI:10.1109/ipemc.2006.4778294

Abstract

In this paper, a new control method for distribution static compensator (DSTATCOM) using artificial neural networks (ANN) instead of the conventional direct controller is presented. A feedforward three-layer neural network is adopted to control the output compensating currents. This is accomplished by producing the appropriate switching patterns of the IGBTs. A backpropagation algorithm trains this network. A practical case with PSCAD/EMTDC is presented to check the proposed control performance. The simulation results show a better source current waveforms and a near unity power factor operation is achieved. This technique offers an alternative to the multi-pulse techniques that require complex magnetic circuit arrangements as well as to the conventional PI controller that the parameters are hard to determine

Keywords

This publication has 1 reference indexed in Scilit:

A comparison of PSO and backpropagation for training RBF neural networks for identification of a power system with STATCOM
2005