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Robust Variable-Step Perturb-and-Observe Sliding Mode Controller for Grid-Connected Wind-Energy-Conversion Systems.

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  • 1Department of Electronics and Telecommunications, Faculty of New Technologies of Computing and Communication, University of Ouargla, Ouargla 30000, Algeria.

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Summary
This summary is machine-generated.

A new robust variable-step perturb-and-observe (RVS-P&O) algorithm enhances wind turbine efficiency. This maximum power point tracking (MPPT) method improves power generation and response times for permanent-magnet synchronous generators.

Keywords:
normalizationrobust variable-step perturb and observesecond-order sliding mode controllersuper-twisting algorithmsystematic step size

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Area of Science:

  • Electrical Engineering
  • Renewable Energy Systems
  • Control Systems

Background:

  • Efficient power generation in wind turbines (WT) necessitates accurate maximum power point tracking (MPPT).
  • Existing perturb-and-observe (P&O) MPPT methods have limitations in handling dynamic wind conditions and achieving optimal performance.
  • Permanent-magnet synchronous generators (PMSG) are widely used in WTs, requiring sophisticated control for optimal energy extraction.

Purpose of the Study:

  • To develop a novel robust variable-step perturb-and-observe (RVS-P&O) algorithm for the machine-side converter (MSC) of a WT.
  • To enhance the efficiency and dynamic response of WT systems under varying wind speeds.
  • To improve the grid-side converter (GSC) control for high-quality power injection and grid stability.

Main Methods:

  • Implementation of a systematic step-size selection for the RVS-P&O algorithm based on normalized power and speed measurements.
  • Introduction of a power variation correction mechanism within the RVS-P&O for improved robustness against significant wind speed fluctuations.
  • Application of a second-order sliding mode controller (SOSMC) with an adaptive-gain super-twisting algorithm (STA) for the GSC.

Main Results:

  • The RVS-P&O algorithm achieved a WT efficiency of 99.35%, an improvement of 3.82% over the variable-step P&O algorithm.
  • Settling time was significantly reduced to 0.00794 s, outperforming other P&O variants (LS-P&O, SS-P&O, VS-P&O).
  • The SOSMC for the GSC ensured high-quality grid power injection, power factor correction, and harmonic performance, while eliminating chatter.

Conclusions:

  • The RVS-P&O algorithm demonstrates superior performance compared to existing P&O MPPT techniques for PMSG-based WTs.
  • The proposed control strategy significantly enhances energy efficiency and improves transient and steady-state response under diverse operating conditions.
  • The RVS-P&O algorithm is a highly accurate and robust candidate for online maximum power point tracking in wind energy systems.