Journal
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
Volume 15, Issue 3, Pages 1089-1096Publisher
INST CONTROL ROBOTICS & SYSTEMS, KOREAN INST ELECTRICAL ENGINEERS
DOI: 10.1007/s12555-016-0537-1
Keywords
Extended Kalman filter; Kalman filter; wind speed estimation; wind turbine
Categories
Funding
- National Natural Science Foundation of China [51677194]
- National High-tech R&D Program of China (863 Program) [2015AA050604]
- Project of Innovation-driven Plan in Central South University
- Program for New Century Excellent Talents in University [NCET-13-0599]
- Fundamental Research Funds for the Central Universities of Central South University [2015zzts050]
- Basic Science Research Program through the National Research Foundation of Korea - Ministry of Education [NRF-2016R1A6A1A03013567]
- National Research Foundation of Korea [2016R1A6A1A03013567] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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To improve power production and reduce loads on turbine components, exact wind speed information is required in modern wind turbine controllers. However, the wind speed measured on the nacelle is imprecise because of its drawbacks of single point measurement and non-immunity to disturbances. To solve this problem, the EWS (Effective Wind Speed) estimator has been proposed as an alternative. According to the literatures, there are two kinds of EWS estimator, that is, the KF-based estimator and the EKF-based one. Where, the former is applied to estimate the aerodynamic torque, then the EWS is numerically calculated; and the latter directly estimate the EWS. Since the estimate EWS significantly affect the controller's effectiveness, their performance needs to be clarified. To fully investigate the two estimators, there is a need to evaluate their performance on an even platform. In this paper, we present comparative studies on these two methods. Their advantages and drawbacks are investigated on the commercial turbine design software-bladed and compared through detailed simulation results. Finally, we demonstrate some simulation results and differences between the KF-based estimator and the EKF-based one.
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