Faculty Publications
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Item Variable speed wind turbine for maximum power capture using adaptive fuzzy integral sliding mode control(2014) RAJENDRAN, S.; Jena, D.This paper presents a nonlinear control approach to variable speed wind turbine (VSWT) with a wind speed estimator. The dynamics of the wind turbine (WT) is derived from single mass model. In this work, a modified Newton Raphson estimator has been considered for exact estimation of effective wind speed. The main objective of this work is to extract maximum energy from the wind at below rated wind speed while reducing drive train oscillation. In order to achieve the above objectives, VSWT should operate close to the optimal power coefficient. The generator torque is considered as the control input to achieve maximum energy capture. From the literature, it is clear that existing linear and nonlinear control techniques suffer from poor tracking of WT dynamics, increased power loss and complex control law. In addition, they are not robust with respect to input disturbances. In order to overcome the above drawbacks, adaptive fuzzy integral sliding mode control (AFISMC) is proposed for VSWT control. The proposed controller is tested with different types of disturbances and compared with other nonlinear controllers such as sliding mode control and integral sliding mode control. The result shows the better performance of AFISMC and its robustness to input disturbances. In this paper, the discontinuity in integral sliding mode controller is smoothed by using hyperbolic tangent function, and the sliding gain is adapted using a fuzzy technique which makes the controller more robust. © 2014, The Author(s).Item Validation of an integral sliding mode control for optimal control of a three blade variable speed variable pitch wind turbine(Elsevier Ltd, 2015) RAJENDRAN, S.; Jena, D.Reduction in cost of wind energy requires most efficient control technology which can able to extract optimum power from the wind. This paper mainly focuses on the control of variable speed variable pitch wind turbine (VSVPWT) for maximization of extracted power at below rated wind speed (region 2) and regulation of extracted power when operating at above rated wind speed (region 3). To extract maximum power at below rated wind speed torque control is used whereas to regulate rated power at above rated wind speed pitch control is used. In this paper a nonlinear control i.e. integral sliding mode control (ISMC) is proposed for region 2 whereas a conventional proportional-integral (PI) control is adapted for region 3 of a VSVPWT. The proposed controller is combined with modified Newton Raphson (MNR) wind speed estimator to estimate the wind speed. The stability of the proposed ISMC is analyzed using Lyapunov stability criterion and the control law is derived for region 2 which is also adapted for the transition period between region 2 and region 3 (region 2.5). The dynamic simulations are tested with nonlinear FAST (Fatigue, Aerodynamics, Structures, and Turbulence) wind turbine (WT). The simulation results of ISMC are presented and the control performance is compared with conventional SMC and existing controllers such as aerodynamic torque feed forward control (ATF) and Indirect speed control (ISC). It is seen that especially in region 2.5, ISMC gives better performance compared to all other controllers. © 2015 Elsevier Ltd.Item Backstepping sliding mode control of a variable speed wind turbine for power optimization(2015) RAJENDRAN, S.; Jena, D.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. © 2015, The Author(s).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).Item Terminal Integral Synergetic Control for Wind Turbine at Region II Using a Two-Mass Model(Multidisciplinary Digital Publishing Institute (MDPI), 2023) RAJENDRAN, S.; Jena, D.; Diaz-D, M.; Rodríguez, J.Mechanical loads considerably impact wind turbine lifetime, and a reduction in this load is crucial while designing a controller for maximum power extraction at below-rated speed (region II). A trade-off between maximum energy extraction and minimum load on the drive train shaft is a big challenge. Some conventional controllers extract the maximum power with a cost of high fluctuations in the generator torque and transient load. Therefore, to overcome the above issues, this work proposes four different integral synergetic control schemes for a wind turbine at region II using a two-mass model with a wind speed estimator. In addition, the proposed controllers have been developed to enhance the maximum power extraction from the wind whilst reducing the control input and drive train oscillations. Moreover, a terminal manifold has been considered to improve the finite time convergence rate. The effectiveness of the proposed controllers is validated through a 600 kW Fatigue, Aerodynamics, Structures, and Turbulence simulator. Further, the proposed controllers were tested by different wind spectrums, such as Kaimal, Von Karman, Smooth-Terrain, and NWTCUP, with different turbulent intensities (10% and 20%). The overall performance of the proposed and conventional controller was examined with 24 different wind speed profiles. A detailed comparative analysis was carried out based on power extraction and reduction in mechanical loads. © 2023 by the authors.Item Design of modified complementary terminal sliding mode controller for wind turbine at region II using a two-mass model(Elsevier B.V., 2024) RAJENDRAN, S.; Jena, D.; Diaz-D, M.; Rodríguez, J.Mechanical loads impact the life span of a wind turbine; therefore, the reduction of transient loads in the drive train has gained more emphasis during the design of the controller for power extraction. The trade-off between power extraction and load reduction on the drive train has become a critical concern for wind turbines. Existing control approaches improve energy extraction and impose a more significant transient load on the drive train. Therefore, to address the above issue, a modified complementary terminal sliding mode controller is proposed in this study for wind turbines at below-rated wind speeds. The performance of both the proposed and existing controllers has been tested with a 600 kW FAST simulator. Moreover, each controller has been examined using different wind spectral models, such as Kaimal, Von Karman, Smooth-Terrain, and NWTCUP. The turbulent intensities of these models varied from 5% to 25%, and average wind speeds ranged from 7 m/s to 8.5 m/s. A dSPACE 1202 board was used to test the efficacy of the proposed controller in real-time. This analysis indicates that the proposed controller reduces the transient load by 11.98% and the control input by 9.57% compared to the complementary terminal sliding mode controller. Additionally, the proposed controller improves the energy capture by 1.18%. Finally, this analysis shows that the proposed approach can enhance overall performance and capture maximum power at below-rated wind speeds compared to existing control schemes. © 2024 The Authors