Comprehensive modeling and parameter identification of wind farms based on wide-area measurement systems

doi:10.1007/s40565-016-0208-5

Home > Archive>Volume 4, Issue 3, 2016 >383-393. DOI:10.1007/s40565-016-0208-5

PDF HTML Export

Comprehensive modeling and parameter identification of wind farms based on wide-area measurement systems

DOI:

10.1007/s40565-016-0208-5

Author:

Yinfeng WANG
Yinfeng WANG
State Key Laboratory of Power System, Department of Electrical Engineering, Tsinghua University, Beijing, 100084, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
Chao LU
Chao LU
State Key Laboratory of Power System, Department of Electrical Engineering, Tsinghua University, Beijing, 100084, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
Lipeng ZHU
Lipeng ZHU
State Key Laboratory of Power System, Department of Electrical Engineering, Tsinghua University, Beijing, 100084, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
Guoli ZHANG
Guoli ZHANG
Power Research Institute, Eastern Inner Mongolia Power Grid of China, Saihan District, Hohhot, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
Xiu LI
Xiu LI
Power Research Institute, Eastern Inner Mongolia Power Grid of China, Saihan District, Hohhot, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site
Ying CHEN
Ying CHEN
Power Research Institute, Eastern Inner Mongolia Power Grid of China, Saihan District, Hohhot, China
Find this author on All Journals
Find this author on BaiDu
Search for this author on this site

Affiliation:

1. State Key Laboratory of Power System, Department of Electrical Engineering, Tsinghua University, Beijing, 100084, China 2. Power Research Institute, Eastern Inner Mongolia Power Grid of China, Saihan District, Hohhot, China

Fund Project:

National Basic Research Program of China (No. 2012CB215206) ; National Natural Science Foundation of China (No. 51107061)

Article

Figures

Metrics

Reference

Cited by

Materials

Abstract:

With intermittence and stochastics of wind power largely introduced into power systems, power system stability analysis and control is in urgent need of reliable wind farm models. Considering the superiority of wide-area measurement systems, this paper develops a novel methodology for practical synchrophasor measurement-based modeling and parameter identification of wind farms. For the sake of preserving basic structural characteristics and control patterns simultaneously, a comprehensive wind farm model is constructed elaborately. To improve the efficiency of the identification procedure, dominant parameters are classified and selected by trajectory sensitivity analysis. Furthermore, an improved genetic algorithm is proposed to strengthen the capability of global optimization. The test results on the WECC benchmark system and the CEPRI 36-bus system demonstrate the effectiveness and reliability of the proposed modeling and identification methodology.

Key words:Wind farm Trajectory sensitivity Dominant parameter Improved genetic algorithm (IGA)Parameter identification

Get Citation

Copy

Article Metrics

Abstract:
PDF:
HTML:
Cited by:

History

Received:
Revised:
Adopted:
Online: July 27,2016
Published:

Home

Introduction

Editorial Board

For Author

Call For Papers

APC

Sponsor & Publisher

Get Citation

Share

Article Metrics

History