Modified Super Twisting algorithm based sliding mode control for LVRT enhancement of DFIG driven wind system

Hiremath, Ravikiran; Moger, Tukaram

doi:10.1016/j.egyr.2022.02.235

Cited by 41 publications

(11 citation statements)

References 25 publications

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“…R. Hiremath and T. Moger introduced a modified super-twisting technique that utilizes second order sliding mode control in Ref. 37 . The utilisation of sophisticated phase-locked loop methodologies, although highly efficient, frequently necessitates significant computational capabilities, resulting in processing delays.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis and mitigation of PQ disturbances in grid connected system using fuzzy logic based IUPQC

Ravi,

Kumar,

Dhanamjayulu

et al. 2023

Sci Rep

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Renewable energy integration introduces grid instability due to variable and intermittent sources like solar and wind, impacting reliability. This paper provides a thorough discussion of recent advancements and emerging trends in grid-integrated wind energy systems (GIWES) and grid-integrated solar energy systems (GISES). More than 70 research articles have been rigorously assessed and listed the technological and economic challenges. The increase in installations of grid-Integrating systems gives rise to challenges like as grid strain, peak shaving impacts, unpredictability of renewable energy sources (RES), and power quality disturbances. A variety of custom power devices, such as dynamic voltage restorers (DVR), static synchronous compensators (STATCOM), active power filters (APF), and unified power quality conditioners (UPQC), have gained popularity in response to these challenges. Among the various challenges, power quality disturbances, including voltage sag, swell, current and harmonics pose significant issues. To address these disturbances this work present a novel approach utilizing fuzzy logic (FL) to develop multi-feeder interline unified power-quality conditioners (MF-IUPQCs). The MF-IUPQC has three legs and three levels, each of which has four diode-clamped inverters. Switching is carried out through the use of space vector pulse width/duration modulation (SVPWM). Total harmonic distortion (THD) induced by nonlinear loads is reduced by the FLC-based MF-IUPQC, which also improves dynamic performance and offers a smooth DC-link voltage. The proposed control mechanism is implemented using MATLAB/Simulink. The fuzzy-based controller is compared to the industry-standard proportional-integral (PI) controller to determine its efficacy. Among them, the MF-IUPQC based on FLC delivers the smoothest voltage profile and the lowest THD.

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Section: Literature Reviewmentioning

confidence: 99%

Analysis and mitigation of PQ disturbances in grid connected system using fuzzy logic based IUPQC

Ravi,

Kumar,

Dhanamjayulu

et al. 2023

Sci Rep

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“…Renewable energy integration with a high proportion has dramatically changed the operation characteristics and behavior of the power system 8,9 . As a result, the regional power system is more susceptible to failure than the traditional power system.…”

Section: Introductionmentioning

confidence: 99%

Enhanced dynamic state estimation of regional new energy power system under different abnormal scenarios

Li,

Jiang,

Cui

et al. 2024

Int J Numerical Modelling

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The high proportion of renewable energy sources in the power grid increases the failure probability of the system, which becomes a new challenge for the safe and stable operation of the regional power grid. To ensure stable control of the power network with substantial renewable energy integration, this article proposes a new method that combines the long short‐term memory (LSTM) neural networks and adaptive cubature Kalman filter (ACKF) to improve the prediction accuracy of mutation data inherited from the renewable generation. Four abnormal scenarios, including low voltage ride‐through (LVRT), high voltage ride‐through (HVRT), continuous fault ride‐through and bad data injection of the regional power grid are investigated through extensive case studies. The proposed method is implemented on the IEEE 30‐node system for performance verification. The simulation results demonstrate that the proposed method has considerably higher robustness than the traditional Kalman filter algorithm and can effectively improve the overall state estimation accuracy of the renewable energy power system under different scenarios.

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“…The optimal solutions from the available searching space and the creation of training dataset are identified offline by the modified elephant herding algorithm which takes into consideration multiple parameters which related to LVRT like, current, voltage, and active and reactive powers. In reference 37 , R. Hiremath and T. Moger introduced a modified super-twisting algorithm for the LVRT improvement under voltage dip condition. The proposed method employs the second-order sliding mode for controlling the DFIG based WECS.…”

Section: Introductionmentioning

confidence: 99%

Optimal low voltage ride through of wind turbine doubly fed induction generator based on bonobo optimization algorithm

Mostafa

El-Hay

Elkholy

2023

Sci Rep

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The large-scale wind energy conversion system (WECS) based on a doubly fed induction generator (DFIG) has gained popularity in recent years because of its various economic and technical merits. The fast integration of WECS with existing power grids has caused negative influence on the stability and reliability of power systems. Grid voltage sags produce a high overcurrent in the DFIG rotor circuit. Such these challenges emphasise the necessity of the low voltage ride through (LVRT) capability of a DFIG for ensuring power grid stability during voltage dips. To deal with these issues simultaneously, this paper aims to obtain the optimal values of injected rotor phase voltage for DFIG and wind turbine pitch angles for all operating wind speeds in order to achieve LVRT capability. Bonobo optimizer (BO) is a new optimization algorithm that is applied to crop the optimum values of injected rotor phase voltage for DFIG and wind turbine pitch angles. These optimal values provide the maximum possible DFIG mechanical power to guarantee rotor and stator currents do not exceed the rated values and also deliver the maximum reactive power for supporting grid voltage during faults. The ideal power curve of a 2.4 MW wind turbine has been estimated to get the allowable maximum wind power for all wind speeds. To validate the results accuracy, the BO results are compared to two other optimization algorithms: particle swarm optimizer and driving training optimizer. Adaptive neuro fuzzy inference system is employed as an adaptive controller for the prediction of the values of rotor voltage and wind turbine pitch angle for any stator voltage dip and any wind speed.

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Modified Super Twisting algorithm based sliding mode control for LVRT enhancement of DFIG driven wind system

Cited by 41 publications

References 25 publications

Analysis and mitigation of PQ disturbances in grid connected system using fuzzy logic based IUPQC

Analysis and mitigation of PQ disturbances in grid connected system using fuzzy logic based IUPQC

Enhanced dynamic state estimation of regional new energy power system under different abnormal scenarios

Optimal low voltage ride through of wind turbine doubly fed induction generator based on bonobo optimization algorithm

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