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Adaptive Fuzzy Sliding Mode Control of Variable Speed Wind Turbine for Maximum Power Extraction

Publication Type : Journal Article

Publisher : WSEAS Transactions on Power Systems

Source : WSEAS Transactions on Power Systems, Volume 9 (2014)

Url : https://pdfs.semanticscholar.org/ddce/0c89dc850c79b86191256ccd02e708abd6a2.pdf

Keywords : ATF and ISC, Fuzzy Sliding mode controller, Modified Newton Raphson, variable speed wind turbine

Campus : Bengaluru

School : School of Engineering

Department : Electrical and Electronics

Year : 2014

Abstract : This paper deals with nonlinear control of variable speed wind turbine (VSWT), where the dynamics of the wind turbine (WT) is obtained from single mass model. The main objective of this work is to maximize the energy capture form the wind with reduced oscillation on the drive train. The generator torque is considered as the control input to the WT. In general the conventional control techniques such as Aerodynamic torque feed forward (ATF) and Indirect speed control (ISC) are unable to track the dynamic aspect of the WT. The nonlinear controllers such as nonlinear dynamic state feedback linearization with estimator (NDSFE) and nonlinear static state feedback linearization with estimator (NSSFE) are not robust with respect to model uncertainty and disturbances. To overcome the above drawbacks a Fuzzy Sliding mode controller (FSMC) with the estimation of effective wind speed is proposed. The Modified Newton Raphson (MNR) is used to estimate the effective wind speed from aero dynamic torque and rotor speed. The proposed controller is tested with different wind profiles with the presence of disturbances and model uncertainty. From the results the proposed controller was found to be suitable in maintaining a trade-off between the maximum energy capture and reduced transient on the drive train.

Cite this Research Publication : D. Jena and R. Saravanakumar, “Adaptive Fuzzy Sliding Mode Control of Variable Speed Wind Turbine for Maximum Power Extraction”, WSEAS Transactions on Power Systems, vol. 9, 2014.

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