Review on model validation and parameter estimation approaches of wind power generators. Issue 13 (19th December 2017)

• Record Type: Journal Article
• Authors: Hu, Yi‐Liang; Wu, Yuan‐Kang
• Is Part Of: Journal of engineering. Volume 2017:Issue 13(2017)
• Page Start: 2407
• Page End: 2411
• Publication Date: 2017-12-19
• Subjects: sensitivity analysis -- wind power plants -- parameter estimation -- optimisation -- wind turbines -- power system stability; WT equivalent models -- parameter estimation problems -- wind power generators -- power system planning -- dynamic simulation results -- efficient operation -- reliable operation -- simulated response -- actual response -- parameter calibration -- generating units -- wind farms -- modern power system -- wind power generation -- power system stability -- WT model validation; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2017.0761
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : For the power system planning and operation, the accuracy of the dynamic simulation results plays an important role. To ensure the efficient and reliable operation of the power system, the mismatch between the simulated response and the actual response should be smaller than a threshold value. Therefore, the researches on the model validation and parameter calibration of the generating units have been widely discussed in the past decades. In the recent years, the installation number of the wind turbines (WTs) and wind farms in the modern power system is increasing significantly. Considering the impact of the wind power generation on the power system stability, the WT model should be integrated into the dynamic simulation of the power system. Thus, the research on the WT model validation and parameter estimation is the latest trend. This study gives an overall review of WT equivalent models for the parameter estimation problems in the literature. Because the parameter estimation is regarded as the optimisation problem, this study also summarises the optimisation algorithms utilised in most research. Finally, the approaches of the sensitivity analysis applied to reduce the search domain of the optimisation problem are reviewed in this study.