PURPOSE: To eliminate the need for the extrapolation of active power since the direct relation between past data and a future predicted value is obtained by a highly precise predicting and a weight learning function by the nonlinear mapping of a neural network.
CONSTITUTION: The voltage reactive power prediction part 11 of this voltage reactive power controller consists of a prediction part 111, a data storage part 112, and a weight coefficient learning part 113. The prediction part 111 is composed of a neural network device which outputs a voltage predicted value and a reactive current predicted value according to past supplied time series data of the system of active power P, a voltage v, and reactive power Q. The data storage part 112 is composed of a storage device which stores the past time series data. The weight coefficient learning part 113 corrects the weight coefficient of the neural network of the prediction part 111 according to the past time series data. The obtained predicted values of the voltage and reactive power are supplied as a current system voltage and reactive power to a voltage reactive power control part 12.
ICHIKAWA YOSHINORI
HAYASHI SHINJI
TOYOZUMI TAKAHIRO
TOSHIBA CORP