Analysis of Factors Affecting Sub-Synchronous Oscillation in Doubly-Fed Wind Power Grid-Connected System Based on Impedance Sensitivity and Research on Suppression Strategy

Abstract

Aiming at the matter of sub-synchronous oscillation (SSO) of the doubly-fed induction generator (DFIG) series compensation capacitors grid connection, a SSO suppression strategy based on adding damping controllers in rotor-side converter (RSC) is put forwarded. Considering the control parameters of power and current control loops of RSC, the equivalent impedance model of DFIG series compensation grid connection (SCGC) is established, and then combined with the equivalent RLC resonant circuit of the system, the mechanism and factors of SSO are analyzed by impedance method. Calculating the impedance sensitivity of the system impedance to parameters by sensitivity analysis method, so as to identify the leading factor affecting the SSO characteristics of wind power system. Combined with the stability criterion of system impedance characteristics, the parameters are adjusted to meliorate system stability. Based on the leading factor affecting the SSO and the mechanism of the SSO, the damping controllers are added in the RSC to supply positive damping for the system to eliminate the negative damping brought by the RSC and rotor resistance, thus suppressing the SSO of the system. The validity of the put forwarded suppression strategy is proved through PSCAD/EMTDC simulation.

Keywords:

• sub-synchronous oscillation
• DFIG
• damping controllers
• impedance sensitivity
• suppression strategy

AUTHOR CONTRIBUTIONS

This paper was completed by the authors in cooperation. Guoxian Guo carried out theoretical research, data analysis, simulation analysis and paper writing. Yingming Liu and Xiaodong Wang provided constructive suggestions. Hanbo Wang, Liming Wang and Ruikang Li revised the paper.

DISCLOSURE STATEMENT

The authors declare no conflict of interest.

Additional information

Funding

This work was supported by development and industrialization of intelligent wind farm holographic state accurate perception and optimization decision system project (2021JH1/10400009).

Notes on contributors

Guoxian Guo

Guoxian Guo was born in Henan, China, in 1993. He received the B.S. degree in electrical engineering and automation from Anyang Normal University, Anyang, China, in 2017. He received the M.S. degree in electrical engineering from Liaoning Shihua University, Fushun, China, in 2020. He is currently working toward the D.S. degree in electrical engineering with Shenyang University of Technology, Shenyang, China. His research interests include new energy power generation technology, power system modeling, and grid-connected stability analysis of new energy power generation.

Yingming Liu

Yingming Liu was born in Liaoning, China, in 1973.He received the B.S. degree in applied electronic technology, the M.S. degree in electrical engineering, and the Ph.D. degree in electrical theory and new technology from the Shenyang University of Technology, Shenyang, Liaoning, in 1995, 2005, and 2011, respectively. He is currently a Professor with the Shenyang University of Technology. His research interests include control theory of large offshore wind turbine, design of wind turbine control system, and wind farm energy storage technology.

Xiaodong Wang

Xiaodong Wang was born in Henan, China, in 1978. He received the B.S. and M.S. degrees in computer science, and the Ph.D. degree in electrical theory and new technology from the Shenyang University of Technology, Shenyang, Liaoning, in 2001, 2004, and 2011, respectively. He is currently a Professor with the Shenyang University of Technology and the Director of Liaoning Renewable Energy Society. His research interests include offshore wind energy, turbine fault diagnosis, wind power big data processing, and intelligent power prediction.

Hanbo Wang

Hanbo Wang was born in Liaoning, China, in 1991. He received bachelor's degree from Jilin Engineering Normal University and Shenyang University of technology in 2015, 2019, respectively. He is currently a Doctoral candidate in the Department of electrical engineering of Shenyang University of technology. His research interests include control strategy of Virtual Synchronous Generator, low frequency oscillation of wind power generation system.

Liming Wang

Liming Wang male, born in 1988. In 2013, he received the master's degree in Dalian Maritime University, Dalian, China. In 2020, he is currently studying for the D.S. degree in electrical engineering with Shenyang University of Technology, Shenyang, China. He is an Engineer with the Shenyang Institute of Engineering. His research include Internet of things application technology, new energy power generation technology, power system modeling, and grid-connected stability analysis of new energy power generation.

Ruikang Li

Ruikang Li was born in Shandong, China, in 1994. He received the B.S. degree in electrical engineering and automation from the Qingdao Agricultural University, Qingdao, Shandong, in 2018. He is currently pursuing the M.S. degree in electrical engineering with the Shenyang University of Technology, Shenyang, Liaoning. His research interests include wind farm control, wind turbine fault diagnosis, machine learning techniques, and frequency regulation.