VOLTAGE AND REACTIVE POWER-CONTROL USING RECURRENT NEURAL NETWORKS

Many controllers using neural networks have been recently developed. The hybrid and direct types are two major categories of such controllers. While the first type tunes the parameters of the conventional controller by means of neural networks, the latter constructs the controller by learning the inverse dynamics of the control target. Electric power systems require voltage and reactive power (VQ) control to avoid voltage collapse. The conventional VQ control, however, meets this requirement unsatisfactorily because the control is only approximate. In this paper, we will propose a new algorithm for VQ control using recurrent neural networks (RNNs), which have the ability to deal with the system's controlled target by means of RNNs. Second, we will apply this algorithm to VQ control. We will call this controller ''neuro VQC.'' Finally, the usefulness of the neuroVQC will be shown by comparison with the conventional VQ controller.