英文摘要 |
This paper provides the study of large-scale industrial harmonic filterdesign problems using optimization techniques and probability-basedmethods, considering system impedance and harmonic currents uncertainties. The solutions of difficult optimization planning problems are achieved. Itis indicated that the proposed methods not only reduce harmonic pollutionbut also improve power quality. In the passive harmonic filter design ofthe applications, this method can determine optimal filter sizes. Thepurposes are to minimize the total demand distortion of harmonic currents.Filters loss, reactive power compensation, constraints of individual harmonicsare also considered. These are difficult to solve by conventionalmethods since the solution space is extremely broad. Owing to the abilitydealing with optimization problems, the paper presents a combination ofresponse surface methodology (RSM) and particle swarm optimizationwith nonlinear time-varying evolution (PSO_NTVE) to investigate theplanning of large-scale passive harmonic filters. The basic strategy ofRSM guides the search point to local optimum and the PSO_NTVEescapes from the valley of the local optimum in order to arrive at a globaloptimum. Finally, in order to verify the proposed methods, case studiesare taken from a chemical plant where DC arc furnaces are installed. Theresults show that the proposed methods can quickly determine filtercapacitors, reduce harmonic pollution, and avoid amplification. |