电气技术2024，Vol.25Issue(9)：14-21,8.
基于多策略融合粒子群算法的油纸绝缘参数辨识
Identification of oil-paper insulation parameters based on multi-strategy fusion particle swarm optimization
徐晨展 1刘庆珍1
作者信息
- 1. 福州大学电气工程与自动化学院,福州 350108
- 折叠
摘要
Abstract
To address the issues of slow convergence speed,susceptibility to local optima,and unstable convergence results in particle swarm optimization (PSO) algorithm,this paper proposes a multi-strategy fusion particle swarm optimization (MSF-PSO) by enhancing the traditional PSO algorithm in three aspects:initial population,boundary handling,and inertia weight. Through the examination of testing functions,the MSF-PSO algorithm is proven to considerably enhance computational speed and efficiency. The MSF-PSO algorithm is applied to the identification of parameters for the Debye equivalent circuit in the dielectric response of oil-paper insulation. The computational results demonstrate that the polarization spectrum of the recovered voltage obtained by this algorithm exhibits better concordance with the polarization spectrum of the recovered voltage acquired from field tests,in comparison to other particle swarm optimization algorithms. This further validates the accuracy of the proposed method and establishes a crucial foundation for diagnosing the aging condition of transformer oil-paper insulation equipment.关键词
油纸绝缘/参数辨识/回复电压/粒子群优化/回复电压极化谱Key words
oil-paper insulation/parameter identification/recovery voltage/particle swarm optimization/recovery voltage polarization spectrum引用本文复制引用
徐晨展,刘庆珍..基于多策略融合粒子群算法的油纸绝缘参数辨识[J].电气技术,2024,25(9):14-21,8.
