Wind energy integration: Dynamic modeling and control of DFIG based on super twisting fractional order terminal sliding mode controller

Soomro, Mansoor Ahmad; Memon, Zubair Ahmad; Kumar, Mahesh; Baloch, Mazhar Hussain

doi:10.1016/j.egyr.2021.09.022

Cited by 30 publications

(18 citation statements)

References 24 publications

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“…However, the work does not focus on the higher order SMC to ensure chattering-free results through continuous control inputs. Fractional order SMC with super-twisting feature is used to control the operation of a DFIG through rotor speed and current tracking, 38 again the controller performance is not investigated in the events of wind power disturbances and load variations.…”

Section: Literature Surveymentioning

confidence: 99%

Higher order sliding mode reactive power control of a hybrid power system with wind power and parameter uncertainty

Thoker

Lone

2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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Reactive power management and voltage control are the critical problems to be dealt with in hybrid power systems, considering the frequent changes in load and wind power along with parameter uncertainties. Therefore, in this work, the load-side converter with a doubly-fed induction generator is controlled and operated as a static synchronous compensator to provide reactive power support to the system. A higher order sliding mode controller with a super-twisting feature is proposed as a robust controller for the load-side converter operation to regulate the reactive power balance and improve the voltage response of the system. The asymptotic stability of the applied control scheme is guaranteed using the Lyapunov stability analysis. MATLAB-based computer simulation studies are conducted to show the efficacy of the proposed control structure while considering the disturbances in load, wind power, and parameter uncertainties.

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Section: Literature Surveymentioning

confidence: 99%

Higher order sliding mode reactive power control of a hybrid power system with wind power and parameter uncertainty

Thoker

Lone

2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…In recent years, renewable energy sources have attracted considerable interest on a global scale, becoming a viable option due to technological development, cost reduction, and increasing demand, especially in developing countries [1,2]. Wind energy conversion is one of the most promising renewable energy technologies that has developed rapidly in recent years and provides a substantial share of electricity in an increasing number of countries.…”

Section: Introductionmentioning

confidence: 99%

Condition Assessment and Analysis of Bearing of Doubly Fed Wind Turbines Using Machine Learning Technique

et al. 2023

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Condition monitoring of wind turbines is progressively increasing to maintain the continuity of clean energy supply to power grids. This issue is of great importance since it prevents wind turbines from failing and overheating, as most wind turbines with doubly fed induction generators (DFIG) are overheated due to faults in generator bearings. Bearing fault detection has become a main topic targeting the optimum operation, unscheduled downtime, and maintenance cost of turbine generators. Wind turbines are equipped with condition monitoring devices. However, effective and reliable fault detection still faces significant difficulties. As the majority of health monitoring techniques are primarily focused on a single operating condition, they are unable to effectively determine the health condition of turbines, which results in unwanted downtimes. New and reliable strategies for data analysis were incorporated into this research, given the large amount and variety of data. The development of a new model of the temperature of the DFIG bearing versus wind speed to identify false alarms is the key innovation of this work. This research aims to analyze the parameters for condition monitoring of DFIG bearings using SCADA data for k-means clustering training. The variables of k are obtained by the elbow method that revealed three classes of k (k = 0, 1, and 2). Box plot visualization is used to quantify data points. The average rotation speed and average temperature measurement of the DFIG bearings are found to be primary indicators to characterize normal or irregular operating conditions. In order to evaluate the performance of the clustering model, an analysis of the assessment indices is also executed. The ultimate goal of the study is to be able to use SCADA-recorded data to provide advance warning of failures or performance issues.

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“…In the last three decades, the renewable-energy sources have garnered a lot of interest worldwide. Undoubtedly, one of the renewable energy sources with the highest global growth is wind energy, that's because it has qualities like being widely available, pure, and completely renewable [1,2]. The doubly-fed induction generator (DFIG), because of its unique properties of low power electronic converter size (about 25% to 30% of nominal power), good efficiency, and broad range of speed control, becomes one of the most electric approaches employed with wind turbine (WT) [3] so it is reliable for variablespeed WT (VSWT) system technique.…”

Section: Introductionmentioning

confidence: 99%

“…The study in [9] presents a reliable control method for the optimal torque determination for the WT based on the super-twisting technology (STW) that tracks maximum power, which is preferred over the conventional sliding mode algorithm, the results are compared with PI controller to deduce the efficacy of the proposed control on improving the dynamic system performance. In [1], STW sliding mode controller with fractional order calculation is proposed to regulate speed to generate reference torque and the results of this robust, non-linear control are compared with PI control. The authors, in [10], provide a neural network controller for speed adjustment with straightforward connection weight modification taking system parameter resilience into account.…”

Section: Introductionmentioning

confidence: 99%

Influence of interval type-2 fuzzy control approach for a grid-interconnected doubly-fed induction generator driven by wind energy turbines in variable-speed system

2022

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This paper suggests a developed control technique using an interval type-2 fuzzy logic control (FLC) tuned PI for optimum torque adjustment for wind turbines operated by doubly fed induction generator (DFIG). The suggested control regulates the error of the mechanical rotor speed to enhance the performance of the torque and the output power results in the study system's overall performance improving. The suggested control combines the advantages of the two techniques: fast response of conventional PI control and adaptively properties of interval type-2 FLC. The studied system is a wind farm of 9 MW composed of 6 wind turbines of 1.5 MW each. Wind speed functions of several types are studied such as step change, extreme change, and constant high speed. The results indicate how the power and optimal torque have fast response with interval type-2 FLC tuned PI compared to the type-1 fuzzy tuned PI and conventional PI control. The simulated results deduce that the suggested interval type-2 FLC can enhance the wind energy system's stability and reliability in a better manner compared to the type-1 FLC and conventional PI.

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Wind energy integration: Dynamic modeling and control of DFIG based on super twisting fractional order terminal sliding mode controller

Cited by 30 publications

References 24 publications

Higher order sliding mode reactive power control of a hybrid power system with wind power and parameter uncertainty

Higher order sliding mode reactive power control of a hybrid power system with wind power and parameter uncertainty

Condition Assessment and Analysis of Bearing of Doubly Fed Wind Turbines Using Machine Learning Technique

Influence of interval type-2 fuzzy control approach for a grid-interconnected doubly-fed induction generator driven by wind energy turbines in variable-speed system

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