Using Particle Swarm Optimization Algorithm for Transformer Transient Study

被引:0
作者
Rashtchi, Vahid [1 ,2 ]
Rahimpour, Ebrahim [3 ]
Mirzaei, Jaber [1 ]
机构
[1] Zanjan Univ, Dept Elect Engn, Zanjan, Iran
[2] Zanjan Univ, Fac Engn, Zanjan, Iran
[3] ABB AG, Power Prod Div, Transformers, D-53604 Bad Honnef, Germany
来源
INTERNATIONAL REVIEW OF ELECTRICAL ENGINEERING-IREE | 2011年 / 6卷 / 03期
关键词
Transformer; Transient Model; Parameter Identification; Particle Swarm Optimization (PSO); MODEL; WINDINGS;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The R-C-L-M model of power transformer is able to simulate the high frequency behavior of the magnetic and electric filed inside transformer. This model is used not only in design step for studying transient phenomena but also during operation for detecting mechanical faults. The model is obtained from geometrical structure and the material properties of the transformer. While the precision of the model depends strongly on the precision of its parameters, the accuracy of these parameters calculated by analytical formulas is limited due to different reasons. In this paper a particle swarm optimization (PSO) algorithm is introduced as a method to identify the parameters of the R-C-L-M Model, which are more precise than the parameters achieved by common formulae. Copyright (C) 2011 Praise Worthy Prize S.r.L - All rights reserved.
引用
收藏
页码:1174 / 1180
页数:7
相关论文
共 50 条
  • [41] Prediction of Ground Vibration Velocity Induced by Long Hole Blasting Using a Particle Swarm Optimization Algorithm
    Xie, Lianku
    Yu, Qinglei
    Liu, Jiandong
    Wu, Chunping
    Zhang, Guang
    APPLIED SCIENCES-BASEL, 2024, 14 (09):
  • [42] Improved Particle Swarm Optimization Based on Genetic Algorithm
    Dou, Chunhong
    Lin, Jinshan
    SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING: THEORY AND PRACTICE, VOL 2, 2012, 115 : 149 - 153
  • [43] Optimization of a Heliostat Field Layout on Annual Basis Using a Hybrid Algorithm Combining Particle Swarm Optimization Algorithm and Genetic Algorithm
    Li, Chao
    Zhai, Rongrong
    Yang, Yongping
    ENERGIES, 2017, 10 (11):
  • [44] The Particle Swarm Optimization Algorithm with Adaptive Chaos Perturbation
    Mengxia, L.
    Ruiquan, L.
    Yong, D.
    INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, 2016, 11 (06) : 804 - 818
  • [45] GEPSO: A new generalized particle swarm optimization algorithm
    Sedighizadeh, Davoud
    Masehian, Ellips
    Sedighizadeh, Mostafa
    Akbaripour, Hossein
    MATHEMATICS AND COMPUTERS IN SIMULATION, 2021, 179 : 194 - 212
  • [47] A parallel particle swarm optimization algorithm with communication strategies
    Chang, JF
    Chu, SC
    Roddick, JF
    Pan, JS
    JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, 2005, 21 (04) : 809 - 818
  • [48] Improved VRP based on particle swarm optimization algorithm
    Chen, Zixia
    Xuan, Youshi
    DCABES 2006 PROCEEDINGS, VOLS 1 AND 2, 2006, : 436 - 439
  • [49] Human Cognition Inspired Particle Swarm Optimization Algorithm
    Tanweer, Muhammad Rizwan
    Sundaram, Suresh
    2014 IEEE NINTH INTERNATIONAL CONFERENCE ON INTELLIGENT SENSORS, SENSOR NETWORKS AND INFORMATION PROCESSING (IEEE ISSNIP 2014), 2014,
  • [50] A particle swarm optimization algorithm for balancing assembly lines
    Petropoulos, Dimitris I.
    Nearchou, Andreas C.
    ASSEMBLY AUTOMATION, 2011, 31 (02) : 118 - 129