Grey Box Model and Optimization for Inductance Calculation of EHV Reactors
Jin Liang1,2, Zhu Dengfeng1,2, Yang Qingxin1,2, Zhang Junjie3, Gong Dexin1,2
1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin 300400 China; 2. Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province Hebei University of Technology Tianjin 300400 China; 3. Baoding Tianwei BaoBian Electric Co. Ltd Baoding 071056 China
Abstract The error of the existing EHV reactor inductance analysis and empirical calculation formula is greater than 1% of the engineering requirements. When the inductance calculation error is large, the optimization result of the reactor will be poor. Based on the electromagnetic principle, the revised inductance calculation empirical formula is established to reduce the error to about 1%, and the identifiable inductance calculation grey box model based on the prior electromagnetic principle is established. Based on the inductance sample data set obtained by numerical simulation, by introducing the adaptive variation factor and the optimal individual, an improved differential evolution algorithm was established and the parameters of the grey box model were identified, and a high-precision inductance calculation model with an error of 0.1% was obtained. Using the NSGA-II algorithm to optimize the design of the ultra-high voltage reactor, the wire quality and loss of the reactor were reduced by 21.4% and 18.6%, respectively. The experiment proves the correctness of the grey box model of inductance calculation obtained by parameter identification and the effectiveness of the optimization method. The reactor inductance parameter identification method established in this paper provides a new theoretical and practical idea for high-precision inductance calculation.
Jin Liang,Zhu Dengfeng,Yang Qingxin等. Grey Box Model and Optimization for Inductance Calculation of EHV Reactors[J]. Transactions of China Electrotechnical Society, 2022, 37(23): 6093-6103.
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2022, Vol. 37 
