Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Journal Article
Publisher : Journal of Modern Power Systems and Clean Energy
Source : Journal of Modern Power Systems and Clean Energy, Volume 3, Issue 3, p.402–410 (2015)
Url : https://link.springer.com/article/10.1007/s40565-015-0106-2
Campus : Bengaluru
School : School of Engineering
Department : Electrical and Electronics
Year : 2015
Abstract : To optimize the energy capture from the wind, wind turbine (WT) should operate at variable speed. Based on the wind speed, the operating regions of the WT are divided into two parts: below and above the rated wind speed. The main aim at below rated wind speed is to maximize the energy capture from the wind with reduced oscillation on the drive train. At above rated wind speed, the aim is to maintain the rated power by using pitch control. This paper presents the control of WT at below rated wind speed by using backstepping sliding mode control (BSMC). In BSMC, generator torque is considered as the control input that depends on the optimal rotor speed. Usually, this optimal rotor speed is derived from effective wind speed. In this paper, effective wind speed is estimated from aerodynamic torque and rotor speed by using the modified Newton Rapshon (MNR) algorithm. Initially, a conventional sliding mode controller (SMC) is applied to the WT, but the performance of the controller was found to be less robust with respect to disturbances. Generally, WT external disturbance is not predictable. To overcome the above drawback, BSMC is proposed and both the controllers are tested with mathematical model and finally validated with the fatigue, aerodynamics, structures, and turbulence (FAST) WT simulator in the presence of disturbances. From the results, it is concluded that the proposed BSMC is more robust than conventional SMC in the presence of disturbances.
Cite this Research Publication : R. Saravanakumar and Debashisha, J., “Backstepping sliding mode control of a variable speed wind turbine for power optimization”, Journal of Modern Power Systems and Clean Energy, vol. 3, no. 3, pp. 402–410, 2015.