@inproceedings{d2b2677c4277433593793d16e3d2ac7b,
title = "Modeling voltage-current characteristics of an electric arc furnace based on actual recorded data: A comparison of classic and advanced models",
abstract = "Field measurements of voltage and current is the most effective way for characterizing the electric response of an EAF that describe the nonlinear behavior of AC EAF loads. Sufficient measured information can be adopted to develop an appropriate EAF model. In this paper, two classic methods based on measured data, harmonic current injections and equivalent harmonic voltage sources, for the EAF load modeling are reviewed. For comparison, two advanced methods based on actual recorded data, cubic spline interpolation and radial basis function neural network (RBFNN), are also proposed to model the EAF load. A steel plant power system with EAF loads is used for field measurements and computer simulations. Comparisons between the results of measured data and simulations for the four EAF models are being made according to the voltage/current waveforms and voltage-current characteristics. It is shown that the advanced models yield better performance than classic models of the EAF.",
keywords = "Cubic spline interpolation, Electric arc furnace, Harmonics, Neural network",
author = "Chang, {G. W.} and Liu, {Y. J.} and Chen, {C. I.}",
year = "2008",
doi = "10.1109/PES.2008.4596506",
language = "???core.languages.en_GB???",
isbn = "9781424419067",
series = "IEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES",
booktitle = "IEEE Power and Energy Society 2008 General Meeting",
note = "IEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES ; Conference date: 20-07-2008 Through 24-07-2008",
}