Possibility Forecasting of Voltage Deviations based on Fuzzy-Neuro Autoregressive Model

T. Utsumi, J. Sugimoto, R. Yokoyarna, and T. Niimura (Japan)


possibility forecasting, voltage deviation, fuzzy, autoregressive model, neural network, optimal power flow


This paper presents possibility of voltage deviations based on Fuzzy-neuro Autoregressive model. Under the situation that deregulation and the liberalization advance to, it becomes difficult to predict an electricity demand precisely. Furthermore, it is concerned about voltage deviation due to increase of electricity demand deviation. Therefore, in this paper, the power demand of next day is predicted using neural network from data observed constant periods in the past. In the next, the uncertainly of predicted power demand is showed using fuzzy model. Therefore, it enables to predict not only one power demand but also both upper and lower appearance probability by this proposal method. Then, the optimal power flow calculation is solved to predict the voltage deviation possibility. Moreover, in this paper voltage setting is done by arranging the voltage control equipment based on the requested voltage possibility forecast value.

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