Browsing by Author "RAJENDRAN, S."

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A review of estimation of effective wind speed based control of wind turbines
(Elsevier Ltd, 2015) Jena, D.; RAJENDRAN, S.
This paper provides a comprehensive literature review on the estimation of effective wind Speed (EEWS), and EEWS based control techniques applied to wind turbine (WT). Several numbers of good publications have reported the EEWS based control of wind turbine. Wind speed is a driving force for the wind turbine system. In general wind speed measurement is carried out by anemometer which is located at the top of the nacelle. The optimal shaft speed is derived from the exact measurement of wind speed to extract the optimal power output at below rated wind speed. The wind speed provided by the anemometer is measured at a single point of the rotor plane which is not the accurate effective wind speed. At the same time anemometer increases the overall cost, maintenance and reduce the reliability of the overall system. So an accurate EEWS based control technique is required for WT systems to get the optimal power output. In this paper, a detailed description and classification of EEWS and some EEWS based control techniques have been discussed which is based on control strategy and complexity level of WT system. All most all previous work estimates the wind speed using EEWS techniques such as Kalman filter (KF), extended Kalman filter (EKF), neural network (NN) etc., and then different control techniques are applied. In the last section of this paper integral sliding mode control (ISMC) of a WT at below rated speed region is considered. Operating points are determined by proper estimation of effective wind speed, and modified Newton Raphson (MNR) is employed to estimate this. Finally simulation results are presented with a comparison between proposed ISMC, sliding mode control (SMC) and classical controllers such as aerodynamic torque feed forward (ATF) and indirect speed control (ISC). © 2014 Elsevier Ltd. All rights reserved.
Adaptive Fuzzy Sliding mode control of variable speed wind turbine for maximum power extraction
(World Scientific and Engineering Academy and Society wseas.headquarters@gmail.com Ag. Ioannou Theologou 17-23, Zographou Athens 15773, 2014) RAJENDRAN, S.; Jena, D.
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.
Backstepping Sliding Mode Control for variable speed wind turbine
(Institute of Electrical and Electronics Engineers Inc., 2015) RAJENDRAN, S.; Jena, D.
This paper presents the nonlinear control for variable speed wind turbine (VSWT). The dynamics of the wind turbine (WT) are derived from the single mass model. The control objective is to maximize the energy capture from the wind with reduced oscillation on the drive train. The generator torque is considered as the control input and it depends on the optimal rotor speed which is derived from the effective wind speed. The effective wind speed is estimated from the aerodynamic torque and rotor speed by using the modified Newton Rapshon (MNR). Initially the conventional sliding mode controller (SMC) is considered. The control performance of SMC was compared with Backstepping Sliding Mode Control (BSMC) for different level of disturbance. The conventional SMC and proposed BSMC are tested with mathematical model and validated through the different mean wind speed. The result shows the better performance of BSMC and robustness to disturbances. Â© 2014 IEEE.
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).
Comparative analysis of different machine learning techniques for condition monitoring of capacitors in a SEPIC converter
(Institute of Electrical and Electronics Engineers Inc., 2022) RAJENDRAN, S.; Jena, D.; Diaz-D, M.; Devi, V.S.K.
An efficient condition monitoring technique is essential for power converters to avoid unscheduled maintenance. In this work, the condition monitoring of capacitors in a single-ended primary inductance converter (SEPIC) is proposed based on the following machine learning classifiers: K nearest neighbor, support vector machine, back propagation neural network, Naive Bayes, and deep neural network. The feature of the machine learning algorithms is extracted by three node voltages such as voltage across $C$ 1,C2, and load. These features are utilized for training the algorithms. Moreover, the effectiveness of the different classifies are evaluated by considering the accuracy and area under the curve. Further, each algorithm is trained with a different percentage of a dataset. Finally, a comparative study has been made between the algorithms, and the results exhibit that the deep neural network performs better classification than other algorithms. Â© 2022 IEEE.
Comparative analysis of PID, I-PD and fractional order PI-PD for a DC-DC converter
(Institute of Electrical and Electronics Engineers Inc., 2022) Shanthini, C.; Devi, V.S.K.; RAJENDRAN, S.; Jena, D.
This article presents the design of fractional order PI-PD (FOPI-PD) controller for maintaining the output voltage of a buck converter. Initially, some conventional controllers were adapted, and these controllers introduced the overshoot and large settling time. Therefore, a FOPI-PD has been adapted to overcome the above limitations. The advantage of the FOPI-PD controller is that the error passes through the proportional and integral rather than all the controller gains, which reduces the overall control action. Further, the efficacy of the controllers is investigated in different simulation studies. The results show that the fractional order PI-PD controller significantly enhances the settling time in the presence of different load levels and controller disturbances. Â© 2022 IEEE.
Complementary Terminal Sliding Mode Control for Variable Speed Wind Turbine
(Institute of Electrical and Electronics Engineers Inc., 2023) RAJENDRAN, S.; Jena, D.; Diaz-D, M.
The reduction in transient loads on the drive train influences the life span of the wind turbine when designing the controller for power extraction. In wind turbines, compromises between the efficiency of power extraction and the load level on the drive train have become key issues. Conventional control techniques enhanced energy extraction at the cost of a higher transient load on the drive train. Therefore, this work proposes the complementary terminal sliding mode controller for energy extraction whilst reducing the drive train load. A 600 kW FAST simulator is utilised to validate the performance of the proposed and conventional controllers. Finally, a detailed investigation has been conducted based on energy extraction and mitigation of transient loads under various turbulence models and mean wind speeds. Â© 2023 IEEE.
Condition monitoring of degradation parameters using dynamic mode decomposition
(Institute of Electrical and Electronics Engineers Inc., 2023) Jena, D.; RAJENDRAN, S.
The parameter estimation of the nonlinear system demands complex estimation algorithms. Recently data-driven modeling such as Dynamic Mode Decomposition (DMD) and Dynamic Mode Decomposition with Control (DMDc), has gained popularity in the field of parameter estimation and system identification of complex non-linear systems. In this paper, we have applied the DMDc technique for system identification and parameter estimation of the DC motor and DC-DC buck converter with and without knowledge of the input matrix. Further, this helps in condition monitoring and predictive maintenance of different passive components in the buck converter, such as capacitors and resistors. The results conclude that the DMD estimates those parameters within a tolerance limit of 2.2% with a minimum number of data required to capture the dynamics of the system. Â© 2023 IEEE.
Condition Monitoring of Submodule Capacitors in Modular Multilevel Converter Using Digital Twin
(Institute of Electrical and Electronics Engineers Inc., 2023) Painuly, M.; RAJENDRAN, S.; Jena, D.
Modular multilevel converter is a fast emerging critical technology in HVDC applications. It comprises of high number of capacitors and reliability of the converter highly depends on the capacitors. Condition monitoring of these capacitors have become necessary to ensure the reliable and efficient operation of the modular multilevel converter system. In this paper, a digital twin concept based condition monitoring method of submodule capacitors of modular multilevel converter is proposed. The proposed method does not require any additional hardware cost and can be simply implemented via software. Furthermore, it monitors the capacitor status of all the submodules at the same time without affecting its operation. The efficacy of the proposed algorithm has been verified with different levels of degradation in the submodule capacitor. Further, the same algorithm is implemented on the three phase modular multilevel converter. The results concluded that the digital twin-based condition monitoring technique could estimate the degradation of the submodule capacitor with high accuracy without additional hardware. Â© 2023 IEEE.
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
Dynamic mode decomposition based fault diagnosis in three-phase electrical machines
(Elsevier B.V., 2025) RAJENDRAN, S.; Sreejesh, R.; Devi, V.S.; Jena, D.; Banjerdpongchai, D.
Three-phase electrical machines are widely used in various industrial applications, and the mechanical fault in those machines leads to an oscillation in the load torque, which introduces an amplitude and/or phase modulation in the stator current. This work proposes a methodology to detect mechanical faults in rotating machines using dynamic mode decomposition (DMD). The DMD technique utilises singular value decomposition (SVD) to extract the dominant modulation frequencies and indexes by constructing a shifted-stack matrix of the three-phase current signal. Further, to validate the proposed methodology, an unbalance in the three-phase signal is examined, which includes both amplitude and phase unbalance with additive white Gaussian noise. The results demonstrated that the proposed DMD extracts the modulation frequencies and indexes with a maximum error of 2%. Additionally, different fault severities are considered to establish a real-time scenario, and the results show that the proposed DMD effectively identifies the faults with a maximum error of 1.3%. © 2024 The Author(s)
ISMC based variable speed wind turbine for maximum power capture
(Institute of Electrical and Electronics Engineers Inc., 2014) RAJENDRAN, S.; Jena, D.
This paper presents the nonlinear control for variable speed wind turbine (WT) where the dynamics of WT is derived from single mass model. The main objective is to maximize the energy capture from the wind and reduce the drive train oscillations. In order to control the WT the generator torque is considered as the control input. This torque depends on the optimal rotor speed derived from the effective wind speed. The effective wind speed is estimated from aerodynamic torque and rotor speed by using modified Newton Rapshon (MNR). The conventional techniques such as aero dynamic torque feed forward (ATF) & Indirect speed control (ISC) which does not depend on the effective wind speed, are unable to track the dynamic aspect of the WT. The other disadvantages of the above conventional methods are more power loss and not robust with respect to disturbances and uncertainties. To overcome these weaknesses nonlinear controllers are found to be more suitable than the conventional controller. In this paper a sliding mode control with integral action i.e. integral sliding mode controller (ISMC) is applied to the WT and a modified Newton Rapshon is used to estimate the effective wind speed. The result shows the significance improvement in proposed controllers compared with existing controllers. Â© 2014 IEEE.
Machine learning based condition monitoring of a DC-link capacitor in a Back-to-Back converter
(Institute of Electrical and Electronics Engineers Inc., 2022) RAJENDRAN, S.; Jena, D.; Diaz-D, M.; Devi, V.S.K.
The utilization of power electronic converters has increased, and the significance of continuous operation is essential in various applications. Therefore, proper condition monitoring (CM) is vital for power converters to eradicate unpredictable maintenance. However, the existing CM techniques may require additional sensors or injection of controlled voltage to the converters. The following machine learning algorithms, such as a K-nearest neighbors (KNN), Support Vector Machine (SVM), and Naive Bayes (NB), have been proposed to monitor the condition of the dc-link capacitor in a Back-to-Back (BTB) converter. The dc-link voltage is measured, and a wavelet decomposition is employed for the feature extraction. Moreover, the performance index evaluates the efficacy of the different classifiers. Further, different datasets have been considered for the evaluation of the classifiers. From this analysis, it is found that the SVM classifier performs better than others. Â© 2022 IEEE.
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.
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.
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).
Wind Turbine Emulators—A Review
(Multidisciplinary Digital Publishing Institute (MDPI), 2023) RAJENDRAN, S.; Diaz-D, M.; Devi, V.S.K.; Jena, D.; Travieso-Torres, J.C.; Rodríguez, J.
Renewable energy sources have become a significant alternative energy source due to the continuing depletion of conventional energy sources and fluctuation in fuel costs. Currently, wind energy is the foremost among all other renewable energy sources. However, modeling and analyzing industrial wind turbines is complex as the wind turbine power ratio and size have steadily increased. Undoubtedly, industrial wind turbines are huge and challenging to keep in research labs; simultaneously, exploring the controller/power converter performance is practically impossible. Therefore, to overcome the above drawbacks, wind turbine emulators have been developed to achieve the static and dynamic characteristics of wind energy conversion systems. This paper aims to present a comprehensive review of the different wind turbine emulators available in the literature. In addition, the implementation of real-time emulators is classified according to the structure and approaches. Furthermore, an extensive analysis of the emulators was presented based on the significant parameters utilized for the real-time wind turbine emulators. Finally, this review analyzes the different emulator topologies according to cost, accuracy, complexity, and hardware implementation. © 2023 by the authors.