Open AccessPrecise equivalent model of small hydro generator cluster and its parameter identification using improved Grey Wolf optimiser
Author(s) -
Zhou Jianzhong,
Zhu Wenlong,
Zheng Yang,
Li Chaoshun
Publication year - 2016
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2015.1141
Subject(s) - control theory (sociology) , generator (circuit theory) , mathematics , equivalent circuit , stability (learning theory) , permanent magnet synchronous generator , chaotic , voltage , system identification , identification (biology) , power (physics) , computer science , data modeling , engineering , control (management) , artificial intelligence , physics , botany , quantum mechanics , machine learning , database , electrical engineering , biology
With the total installed capacity of small hydro generator cluster (SHGC) continues to grow rapidly, the effect of SHGC will have affected to the security and stability of the main network in China, especially to power oscillations of passageway of ultra‐high‐voltage AC and DC. Thus, a precise equivalent model of SHGC is proposed in this study. In the proposed model, the fifth‐order model of generator is adopted as the equivalent generator model, the excitation system is simplified into proportional feedback control model and exponential load model is used as equivalent load model. In addition, Grey Wolf optimiser with chaotic local search is designed to identify the parameters of the equivalent model. Finally, the proposed equivalent technique is applied in one simulation experiment and one practical experiment. The experimental results demonstrate that the validity and accuracy of the proposed equivalent model and identification method in solving dynamic equivalent of SHGC in engineering practice.