Average value model of grid side converter in PMSG for system‐level studies. Issue 13 (19th January 2018)

• Record Type: Journal Article
• Authors: Song, Yankan; Chen, Ying; Huang, Shaowei; Yu, Zhitong; Qiao, Yuan
• Is Part Of: Journal of engineering. Volume 2017:Issue 13(2017)
• Page Start: 1799
• Page End: 1803
• Publication Date: 2018-01-19
• Subjects: invertors -- DC‐DC power convertors -- wind power plants -- synchronous generators -- permanent magnet generators; fast transient fault analysis -- PSCAD -- DC‐AC voltage source inverter -- crowbar protection circuit -- optional DC‐DC boost converter -- electromagnetic transients simulation programme -- AVM -- PMSG wind generator -- wind farms -- permanent magnet synchronous generator -- subsynchronous oscillation phenomena -- system‐level studies -- grid side converter -- average value model; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2017.0641
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : In recent years, the subsynchronous oscillation phenomena have been observed in the permanent magnet synchronous generator (PMSG) based wind farms. Therefore, to design an accurate and efficient model for PMSG wind generator becomes an important issue for related stability studies. In this study, an average value model (AVM) for the grid side converter of PMSG is proposed, which can be easily implemented in traditional electromagnetic transients simulation programme. The proposed AVM model consists of an optional DC–DC boost converter, a crowbar protection circuit, and a DC–AC voltage source inverter. Numerical tests are performed for both the AVM and the detailed PMSG model on PSCAD with different scenarios, including both the slow transients studies and fast transient fault analysis. Simulation results of the proposed average value model show good consistency with those of the detailed PMSG model while providing significant speedups. Such characteristics indicate that the proposed model is accurate and efficient for system‐level dynamic research.