Faculty Publications
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Item Nonlinear estimation and control of wind turbine(2013) RAJENDRAN, R.; Jena, D.Wind energy is one of the major renewable energy sources which continue to be one of the fastest growing power generation sectors. For variable speed operation of wind energy conversion system, it is required to generate the maximum power at below the rated speed using an authentic and powerful control strategy. Wind speed has the major impact on the dynamics and control of wind turbines. But in practice there is no accurate measurement of effective wind speed available for direct measurement. In this paper a new technique is proposed for optimal power generation of wind turbine below rated speed without estimating the wind speed. An extended Kalman filter (EKF) is used to estimate the rotor speed and a proportional (P) controller is used to track the error between the measured and estimated rotor speed. The output of the P controller is the estimated aerodynamic torque. The estimated aerodynamic torque and the rotor speed act as an input to the aerodynamic torque feed-forward (ATF) controller. The output of the ATF controller is the generated torque. As the aerodynamic torque is highly dependent on the wind speed so it cannot be controlled. So we have to control the generated torque by using ATF for generating optimal power output. Finally the estimated outputs are validated through correlation analysis. © 2013 IEEE.Item Second order ISMC for variable speed wind turbine(2013) RAJENDRAN, R.; Jena, D.In this paper, a nonlinear controller is designed for variable speed wind turbine (WT) where the dynamics of the WT is derived for single mass model. The main aim of the controller is to extract the optimum power capture from the wind and minimize the transient load on low speed shaft. Modified Newton Rapshon (MNR) is used to estimate the effective wind speed and the optimal rotor speed is derived from it. The controller is used to track the optimal rotor speed by adjusting the generator torque which is acting as a control input to the WT. Existing controllers such as Nonlinear static state feedback with estimator (NSSFE) and Nonlinear dynamic state feedback with estimator (NDSFE) are unable to track the WT dynamics and introduces more transient on drive trains. In order to overcome the above drawbacks a nonlinear controller i.e. sliding mode control with integral action (ISMC) is used. In this paper an ISMC with MNR based wind speed estimator is used to control the single mass WT. The result shows the significance improvement in proposed controllers compared with NSSFE and NDSFE. © 2013 IEEE.Item Nonlinear control of a wind turbine based on nonlinear estimation techniques for maximum power extraction(Taylor and Francis Inc. 325 Chestnut St, Suite 800 Philadelphia PA 19106, 2016) RAJENDRAN, R.; Jena, D.This work proposes nonlinear estimators with nonlinear controllers, for variable speed wind turbine (VSWT) considering that either the wind speed measurement is not available or not accurate. The main objective of this work is to maximize the energy capture from the wind and minimizes the transient load on the drive train. Controllers are designed to adjust the generated torque for maximum power output. Estimation of effective wind speed is required to achieve the above objectives. In this work the estimation of effective wind speed is done by using the Modified Newton Rapshon (MNR), Neural Network (NN) trained by different training algorithms and nonlinear time series based estimation. Initially the control strategies applied was the classical ATF (Aerodynamic torque feed forward) and ISC (Indirect speed control), however due their weak performance and unmodeled WT disturbances, nonlinear static and dynamic feedback linearization techniques with the above wind speed estimators are proposed. © 2016 Taylor and Francis Group, LLC.Item Nonlinear control of wind turbine with optimal power capture and load mitigation(Springer Verlag service@springer.de, 2016) RAJENDRAN, R.; Jena, D.The main control objectives associated with the variable speed wind turbine is to extract maximum power at below rated wind speed (region 2) and to regulate the power at above rated wind speed (region 3). This paper proposes a nonlinear framework to achieve the above two control objectives. The paper discusses about the application of an integral sliding mode control (ISMC) in region 2 and a fuzzy based proportional integral (PI) control in region 3. Same ISMC is adopted for the stable switching between operating regions (transition region 2.5) and the control input maintains the continuity at the instant of switching. Lyapunov stability criterion is used to prove the stability of ISMC. The controllers are tested for different wind speed profiles with different turbulence component. Finally the performances of the proposed controllers are tested with nonlinear Fatigue, Aerodynamics, Structures, and Turbulence WT model and the results are compared with the existing baseline + PI controllers. © 2015, Springer-Verlag Berlin Heidelberg.Item Control Strategy to Maximize Power Extraction in Wind Turbine(Taylor and Francis Inc. 325 Chestnut St, Suite 800 Philadelphia PA 19106, 2016) RAJENDRAN, R.; Jena, D.This article deals with nonlinear control of variable speed wind turbine (VSWT), where the dynamics of the wind turbine (WT) is obtained from a 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. To overcome the above drawbacks the nonlinear controllers such Sliding Mode Controller (SMC) and SMC with integral action (ISMC) with the estimation of effective wind speed are 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. Finally both the controllers are validated by using FAST (Fatigue, Aerodynamics, Structures, and Turbulence) WT simulator. © Association of Energy Engineers (AEE).