Application of an artificial neural network to decentralized voltage control in power systems
Hiroyuki Mori · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
This paper proposes an artificial neural-net based method for voltage control in power networks. Power system voltages are necessary to minimize a cost function of the voltage deviation from the target in order to keep sound power system conditions. Centralized control for the voltages is difficult to handle as the power system size becomes larger. Although on- line voltage control is required in power system control, the conventional nonlinear programming based approaches are quite time-consuming. In this paper, a decentralized scheme for voltage control is proposed to minimize the voltage deviations with an artificial neural network. It is expected that the voltage control problem is easier to handle in a decentralized way because of the problem characteristics. A three-layer perceptrons is utilized as an artificial neural network to estimate the optimal control variables. The proposed method allows us to alleviate the curse of dimensionality in power systems and make the computation much more efficient.