Faculty Publications
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Item Comparison of Sliding Mode Controllers on a DFIG-Wind Turbine Generator for Improving LVRT(Institute of Electrical and Electronics Engineers Inc., 2022) Hiremath, R.; Moger, T.There is a significant risk of grid failure for the grid-connected Doubly Fed Induction Generators (DFIG). There must be some thought put into the controller design for the DFIG's sensitivity to grid disruptions. We compare the Low Voltage Ride Through (LVRT) improvement using a Second Order Sliding Mode (SOSM) and First Order Sliding Mode (FOSM) controller under voltage sag conditions in this study. Sliding surface control convergence is aided by SOSM higher-order switching function augmentations. As a result of the SOSM's reduced chattering impact and enhanced system parameter settlement time, it has many benefits. By using MATLAB/SIMULINK, we are able to evaluate the SOSM's performance to that of other FOSM controllers that have been published. An analysis of DFIG-Wind Turbine (WT) system simulations found that SOSM controllers improved the system's LVRT capacity. © 2022 IEEE.Item Improved LVRT Performance of Doubly-Fed Wind Generator System in Comparison with Neuro and Sliding Mode Control(Institute of Electrical and Electronics Engineers Inc., 2022) Hiremath, R.; Moger, T.The Doubly Fed Induction Generator (DFIG) in wind system is linked to the power-grid, which is vulnerable to significant grid failures. Because of the DFIG's sensitivity to disturbances in the grid, designing of the controller is considered. In this article, the Feed-Forward Neuro-Second Order Sliding Mode (FFN-SOSM) controller and the Second Order Sliding Mode (SOSM) controller are compared for the Low Voltage Ride Through (LVRT) enhancement under voltage sag situation. Convergence in the sliding surface control is assisted by the use of higher-order switching functions in the FFN-SOSM. Importantly, controller benefits are such that reduction in chattering effect and minimized settling time for the system's parameters as a result in the implementation of the FFN-SOSM method. With the assistance of MATLAB/SIMULINK, a comparison is made between the performances of the FFN-SOSM controller and those of SOSM controller, which is described in the existed research. The results of the simulation indicate that the "FFN-SOSM controller improved the LVRT capability of the DFIG-Wind Turbine (WT) system"when it is functioning under dynamic conditions. © 2022 IEEE.Item Enhancement of maximum power output through reconfiguration techniques under non-uniform irradiance conditions(Elsevier Ltd, 2019) Sai Krishna, G.; Moger, T.Partial shading is one of the major drawback which diminishes the power output of the PV array. One of the effective methodologies is reconfiguration strategies, namely shifting the location of PV modules from one place to different places so as to distribute shading effects over the array to increase maximum power output under PSCs. This paper proposed two novel puzzle arrangements followed by Ken-Ken (KK) and Skyscraper (SS) for 4×4 total-cross-tied (TCT) PV array and increase maximum power under PSCs. In this approach, the PV modules in the TCT array is arranged according to Ken-Ken and Skyscraper arrangements without changing the electrical connections. Further, the performance of the proposed arrangements are investigated with different existing PV array configurations by comparing the global maximum power point (GMPP), the voltage at global maximum power point (VGMPP), mismatch losses (ML), fill-factor (FF), efficiency (?) and possible local peaks (PLP) under different shading patterns using Matlab-Simulink. An extensive simulation study is carried out on these configurations under different shading patterns as well as temperatures. Also, a comprehensive comparison has done for various reconfiguration schemes presented in literature. The result shows that the proposed arrangements are enhancing the global maximum power as compared to the other existing configurations. © 2019 Elsevier LtdItem A novel adaptive dynamic photovoltaic reconfiguration system to mitigate mismatch effects(Elsevier Ltd, 2021) Sai Krishna, G.; Moger, T.Unequal solar irradiance of the Photovoltaic (PV) modules diminishes the PV array's maximum power output; this effect is due to Partial Shading Conditions (PSCs). There are a few technical options to fix this issue. One of these is the dynamic reconfiguration technique, which means that the electrical connections between the PV modules in the array are dynamically modified to spread shading effects and increase the power output. This paper proposed a novel adaptive reconfiguration method for 3×3 Total-Cross-Tied (TCT) PV array to enhance the maximum power under partial shading conditions. In this work, the PV module's electrical connections are altered dynamically with the proposed logic algorithm's help to maintain the identical row currents in the array. This technique is implemented on 3×3 size of an array using MATLAB and validated experimentally using OPAL-RT software. Further, the proposed technique performance is compared with the existing PV array connections such as Series-Parallel (SP), Total-Cross-Tied (TCT), Bridge-Link (BL), Honey-Comb (HC), and Shade Dispersion Positioning (SDP). Additionally, for different reconfiguration methods, revenue generation from energy savings is estimated. Based on the observations from the results, it is understood that the proposed technique enhanced the maximum power of the TCT array at a higher level as compared to the other PV array connections under PSCs. © 2021 Elsevier LtdItem Grid-Connected DFIG Driven Wind System for Low Voltage Ride Through Enhancement using Neural Predictive Controller(Springer, 2022) Hiremath, R.; Moger, T.Doubly Fed Induction Generators (DFIGs) are exposed to severe grid faults. In such cases, Low Voltage Ride Through (LVRT) enhances the DFIG’s performance under fault conditions. This paper investigates the LVRT enhancement of the DFIG system under grid disturbance. The paper proposes the Neural Predictive (NP) controller for the DFIG based Wind Turbine (WT) generator during grid faults. This controller operates with the Levenberg-Marquardt (LM) algorithm for its fast convergence. The algorithm based Neural Predictive (NP) controller is operated for large signal stability. The proposed controller has the benefit of reducing the peak values and uncertainties, which are raised for the system parameters during grid faults. Further, the proposed controller outcome is compared with existing controllers in the literature such as PI, PID, Feed-Forward Neural Network (FNN), and 2nd order Sliding Mode Controller (SOSMC) with the help of MATLAB/SIMULINK. The Hardware-In-Loop (HIL) is used to validate the simulation results, which have been performed on the OPAL-RT setup. According to the results that are obtained in this study, the proposed controller improved the LVRT performance of the DFIG-Wind Turbine (WT) system while operating under dynamic conditions. © 2022, The Institution of Engineers (India).Item Modified Super Twisting algorithm based sliding mode control for LVRT enhancement of DFIG driven wind system(Elsevier Ltd, 2022) Hiremath, R.; Moger, T.The grid-connected Doubly Fed Induction Generator (DFIG) system is exposed to severe grid faults. The DFIG is sensitive to grid disturbances, which lead to consideration in the controller design. This paper proposed the Modified Super Twisting (MST) algorithm for the Low Voltage Ride Through (LVRT) enhancement under voltage sag condition. This proposed algorithm is implemented using the 2nd Order Sliding Mode (SOSM) to control the DFIG based wind generator. The higher-order switching functions are introduced in the SOSM for sliding surface control. Moreover, the Lyapunov analysis for the MST algorithm brings down the chattering amplitude. The advantages of the proposed algorithm are that it reduces the system uncertainties, chattering effect and improves the settling period of the system parameters. The performance of the proposed algorithm is compared with existing algorithms in the literature with the help of MATLAB/SIMULINK. The Hardware-In-Loop (HIL) is used to validate the simulation results, which have been performed on the OPAL-RT setup. In addition, the proposed algorithm is also tested on an equivalent model of the practical Wind Farm (WF). Based on the studies, it is found that the proposed algorithm enhanced the LVRT performance of the single Wind Turbine (WT)-DFIG system as well as the practical WF under transient conditions. © 2022 The AuthorsItem Improving the DC-Link Voltage of DFIG Driven Wind System Using Modified Sliding Mode Control(River Publishers, 2023) Hiremath, R.; Moger, T.The grid-connected doubly fed induction generator (DFIG) driven wind turbine (WT) system encounters voltage fluctuations due to severe grid faults. The rise in DC-link voltage imbalances the system under voltage sag condition. The system’s protection should ensure that the WT generator meets the grid requirements through a low voltage ride through (LVRT) technique. This paper proposed the modified 2nd order sliding mode (MSOSM) control with gain added super twisting algorithm (GAST) for LVRT enhancement under voltage sag. This controller adds the low positive gains to the switching functions of the super twisting (ST) algorithm. As a result, it maintains the proper variation margins and constant DC-link voltage of the WT-DFIG system under grid fault. The MSOSM controller suppresses the chattering effect, achieves better zero convergence, and eliminates the coordinate transformations. Moreover, the performance of the proposed controller is compared with existing controllers in the literature with the help of MATLAB/SIMULINK. The hardware-in-loop (HIL) validates these simulation results performed on the OPAL-RT setup. Based on the studies, it is found that the proposed controller enhances the performance of the WT-DFIG system under transient conditions. © 2023 River Publishers.