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Electric arc furnaces (EAF) used in the steel manufacturing industry are one of the most disturbing loads that cause voltage flicker problems in the electric power network. Means for reduction of voltage flickers by conducting furnace controls, such as electrode controls, or by adding compensation equipment, such as power factor corrector and static var compensator, are widely used in the industry. In order to achieve the best result, an accurate model for flicker analysis and prediction is essential. In this paper, a new technique for EAF voltage flicker analysis is presented. In the proposed method, short-term flicker severity indices, Pst are analyzed by a nonlinear chaotic technique, in which a phase (state) space approach is used. Under the reconstructed phase spaces, Lyapunov exponent patterns in the chaotic trajectory are observed, and three short-term flicker predictions methods are developed and tested. The performance of the proposed method is compared with those of two other time series analysis methods. Test results indicate that with sufficient flicker measurement data, a short-term prediction of the flicker severity is achievable. The information would be useful for remedial controls to reduce displeasing flicker level caused by an EAF. [ABSTRACT FROM PUBLISHER]