Comparison of DC Electric Arc Furnace Chaotic Models for Power Quality Indices Assessment

Due to their particular feature, DC Electric Arc Furnace (EAF) installations are peculiar loads that cause moderate to severe Power Quality (PQ) disturbances. Among them, voltage fluctuations and waveform distortions are the most impactful ones, and they should be adequately addressed in order to mitigate the detrimental effects on power systems. Several types of models have been developed in order to evaluate the effects of EAFs on networks, and chaotic models have been specifically recognized as suitable tools to evaluate the impact of EAFs in terms of PQ disturbances. This paper compares the performance of three chaotic models (Chua, Lorenz and Rossler) aiming at estimating PQ indices values of DC EAFs. An optimization procedure is proposed to find the parameters of the three chaotic models. The procedure exploits a block diagramming tool of the DC EAF installation and minimizes the deviation of estimated PQ indices from the actual ones. Actual data collected at an Italian DC EAF installation are used to conduct a numerical comparative analysis and to validate the effectiveness of the models in estimating the PQ disturbances.