A New Electric Arc Furnace Model Based on Current Waveform Synthesis From Distributions of DFT Amplitudes and Power System Frequency

The research work presented in this paper proposes a field-data based method for modeling the behavior of the Electric Arc Furnace (EAF) currents for a tap-to-tap period. EAF current DFT distributions and fundamental frequency histograms obtained out of previously collected EAF currents are used to develop the proposed model, which offers a model for each phase of the EAF operation: boring, melting and refining. The model is verified by comparing the THD histograms and the flicker measurements of the original and the modeled EAF current waveforms. The aim of the proposed method is to provide a model, which mimics the EAF load characteristics for all phases of its operation so that the effects of installing one or more similar EAF systems can be observed in the simulation environment. The method utilizes DFT amplitude distribution parameters belonging to the fundamental and the first 13 harmonic components for each operation phase. Moreover, one-cycle sampled data is stored representing the effects of the higher-order harmonics. EAF current waveforms for the whole tap-to-tap period is resynthesized using the collected distribution data. Hence, both the computational complexity and data storage requirements are quite low. The model is novel in the sense that every time the EAF current signal is generated, a unique waveform reflecting the behavior of the corresponding distributions is generated, which is compatible with the random behavior of the EAF operation due to the random nature of each charge.