Abstract

An electric power system requires voltage and reactive power control (VQ control) to avoid voltage collapse. The conventional VQ control, however, does not meet this requirement because of approximated control. The authors propose a new algorithm for VQ control using recurrent neural networks which have the ability to treat system dynamics. Firstly, they propose the learning algorithm for dynamics and inverse dynamics of the controlled target. Secondly, they apply this algorithm to the VQ control. The authors call this controller 'neuro VQC'. Finally, the usefulness of the neuro VQC is shown in comparison with the conventional VQ controller. >

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