Journal
IEEE TRANSACTIONS ON POWER DELIVERY
Volume 25, Issue 4, Pages 2859-2867Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRD.2010.2044812
Keywords
Arc furnace; genetic algorithm (GA); nonlinear time-varying arc model; parameter estimation; power quality (PQ)
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Recent studies on the effect of arc furnaces in a power system lack accurate predicting voltage waveform of an arc furnace. This is mainly due to the random nature of the arc length. In this paper, a novel two-step optimization technique is presented to identify the arc furnace parameters considering the stochastic nature of the arc length. The proposed method is based on a genetic algorithm (GA) which adopts the arc current and voltage waveforms to estimate parameters of the nonlinear time-varying model of an electric arc furnace. Simulation results are compared with data obtained from two real arc furnace plants. Analyses show that the proposed method is profitable to identify accurate values of the arc furnace parameters which incorporate the stochastic nature of the arc length.
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