Flicker suppression optimization of DC arc furnace based on improved TS fuzzy algorithm

Abstract

In order to improve the flicker suppression performance of static var compensator (SVC) in response to impact loads such as DC electric arc furnace, a SVC rolling predictive control method based on the improved Takagi-Sugeno (TS) fuzzy algorithm is proposed. Firstly, the electrical model of DC electric arc furnace is established and its reactive power characteristics are simulated and analyzed. Then, an improved method of range adaptive correction is proposed to address the issue of abnormal output set to 0 when the classical TS fuzzy prediction algorithm is applied to fluctuating loads. This method can eliminate the outliers caused by the application mechanism of a class of algorithms, so as to improve the reliability and accuracy of TS fuzzy algorithm for reactive power prediction of fluctuating loads. Finally, based on the model training time constraint, a reactive power half-cycle rolling predictive control model is established to predict the reactive power 10 ms in advance. It is competent to improve the lag characteristics of the traditional SVC control system response. The simulation results show that the average flicker improvement rate of the proposed method increases by 54.17% compared with the traditional SVC control method, and the suppression effect of flicker phenomenon is significantly improved.

Keywords

• takagi-sugeno (ts) fuzzy algorithm
• dc arc furnace
• static var compensator (svc)
• predictive control
• anomaly correction
• flicker suppression