Voltage and Reactive Power Control using Recurrent Neural Networks

Abstract

Recently, many controllers using neural networks are proposed. The hybrid and direct type controllers are two major categories. While the former one tunes up parameters of the conventional controller using neural networks, the latter constructs the controller by learning inverse dynamics of control target.
Meanwhile, the electric power system requires voltage and reactive power control (VQ control) to avoid voltage collapse. The conventional VQ control, however, meets this requirement unsatisfactory because of approximated control.
In this paper, we will propose a new algorithm for VQ control using recurrent neural networks which have the ability to treat system dynamics. Firstly, we will propose the learning algorithm for inverse dynamics of controlled target using recurrent neural networks. Secondly, we will apply this algorithm to the VQ control. We will call this controller ‘neuro VQC’. Finally, usefulness of the neuro VQC will be shown in comparison with conventional VQ controller.