Ladder network parameters identification of an isolated winding by combining the intelligent optimisation algorithm and GNIA. Issue 2 (18th December 2018)

• Record Type: Journal Article
• Authors: Ren, Fuqiang; Xiao, Yao; Zhan, Cao; Liu, Yong; Yang, Fan; Ji, Shengchang; Zhu, Lingyu
• Is Part Of: IET generation, transmission & distribution. Volume 13:Issue 2(2019)
• Page Start: 296
• Page End: 304
• Publication Date: 2018-12-18
• Subjects: least squares approximations -- Jacobian matrices -- Newton method -- transformer windings -- optimisation -- genetic algorithms -- frequency response -- search problems -- parameter estimation -- iterative methods; combined algorithms -- ladder network parameters identification -- intelligent optimisation algorithm -- GNIA -- ladder network parameter identification -- transformer winding -- frequency response function data -- traditional identification method -- intelligent algorithm -- Gauss–Newton iteration algorithm -- optimisation efficiency -- sharply dropped calculation workload -- excellent global search ability -- identification results -- isolated winding show; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2018.6414
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : The ladder network parameter identification for transformer winding is crucial for the interpretation of the frequency response function data. The traditional identification method, mainly based on intelligent optimisation algorithm, is generally very time‐consuming due to a large amount of computation. This study proposes to combine the intelligent algorithm and Gauss–Newton iteration algorithm (GNIA) to improve the optimisation efficiency notably with a sharply dropped calculation workload. These two methods are well‐complementary since the intelligent algorithm holds excellent global search ability while the search of the GNIA is directional and quantitative. This study solves three key problems for the combined algorithms. The first problem is the calculation of the least‐square correction solution to the network parameters in the iteration algorithm. The treatment of the ill‐conditioned Jacobian matrix in the iteration algorithm is the second challenge. Another issue is the determination of the network parameter with zero sensitivity. The identification results on an isolated winding show that the combined algorithms can obtain a more precise solution with far less amount of computation.