Employing stochastic models for prediction of arc furnace reactive power to improve compensator performance

The time-varying nature of electric arc furnace (EAF) gives rise to voltage fluctuations, which produce the effect known as flicker. The ability of a static VAr compensator (SVC), a widely used method for flicker reduction, is limited by delays in reactive power measurements and thyristor ignition. To improve the SVC performance in flicker compensation, a technique for the prediction of EAF reactive power for a half cycle ahead is presented. This technique is based on a new procedure for stochastic modelling of EAF reactive power at an SVC bus. This procedure uses huge field data, collected from eight arc furnaces, to determine the most suitable signal among several candidate signals in view of EAF reactive power prediction. In addition, appropriate orders of autoregressive moving average models are found for reactive power time series. For this purpose, various model adequacy checking methods and some other stochastic analysis methods have been applied on data records. The performance of the compensator in the case of employing predicted fundamental reactive power of an EAF is compared with that of the conventional method by using three new indices that have been defined based on concepts of flicker frequencies and the power spectral density.