Robust sub‐synchronous damping controller to mitigate SSCI in series‐compensated DFIG‐based wind park. Issue 9 (11th March 2020)

• Record Type: Journal Article
• Authors: Li, Penghan; Wang, Jie; Xiong, Linyun; Ma, Meiling; Wang, Ziqiang; Huang, Sunhua
• Is Part Of: IET generation, transmission & distribution. Volume 14:Issue 9(2020)
• Page Start: 1762
• Page End: 1769
• Publication Date: 2020-03-11
• Subjects: eigenvalues and eigenfunctions -- wind turbines -- feedback -- genetic algorithms -- rotors -- asynchronous generators -- damping -- wind power plants -- control system synthesis -- power generation control -- variable structure systems -- robust control -- uncertain systems -- perturbation techniques -- machine control; robust sub‐synchronous damping controller -- series‐compensated DFIG‐based wind park -- FOSMC -- sub‐synchronous control interaction -- series‐compensated transmissions -- control loop -- DFIG rotor‐side converter -- fast SSCI‐damping -- nonaggregated wind system model -- superior damping performance -- online wind turbines -- control parameter perturbation -- fractional‐order sliding mode control method -- IEEE first benchmark model -- three‐phase short circuit -- symmetric fault -- design process -- degree of freedom -- parameter optimisation -- wind speeds -- compensation levels -- genetic algorithm -- eigenvalues approach; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2019.0984
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : This study proposes a robust sub‐synchronous damping controller based on fractional‐order sliding mode control (FOSMC) method to mitigate sub‐synchronous control interaction (SSCI) induced by DFIG‐based wind park connected to series‐compensated transmissions. Firstly, the nonlinearity of DFIG is cancelled through feedback linearisation. Secondly, FOSMC is designed and applied to the control loop of the DFIG rotor‐side converter. During the design process, the extra degree of freedom, provided by the fractional operator, is employed to achieve fast SSCI‐damping. Thirdly, a genetic algorithm is used for parameter optimisation with the aim of making system eigenvalues approach the left plane. The effectiveness of the proposed damping controller is evaluated based on the adapted IEEE first benchmark model, non‐aggregated wind system model with a realistic configuration, and experimental platform. Simulation and experiment results demonstrate the superior damping performance of FOSMC under different wind speeds, compensation levels, and the number of online wind turbines. Moreover, FOSMC also shows the robustness under parameter uncertainty, control parameter perturbation, and symmetric (three‐phase short circuit) fault.