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Mitigating Intermittency in Offshore Wind Power Using Adaptive Nonlinear MPPT Control Techniques

Author

Listed:
  • Muhammad Waqas Ayub

    (School of Engineering, Lancaster University, Lancaster LA1 4YW, UK)

  • Inam Ullah Khan

    (School of Engineering, Lancaster University, Lancaster LA1 4YW, UK)

  • George Aggidis

    (School of Engineering, Lancaster University, Lancaster LA1 4YW, UK)

  • Xiandong Ma

    (School of Engineering, Lancaster University, Lancaster LA1 4YW, UK)

Abstract

This paper addresses the challenge of maximizing power extraction in offshore wind energy systems through the development of an enhanced maximum power point tracking (MPPT) control strategy. Offshore wind energy is inherently intermittent, leading to discrepancies between power generation and electricity demand. To address this issue, we propose three advanced control algorithms to perform a comparative analysis: sliding mode control (SMC), the Integral Backstepping-Based Real-Twisting Algorithm (IBRTA), and Feed-Back Linearization (FBL). These algorithms are designed to handle the nonlinear dynamics and aerodynamic uncertainties associated with offshore wind turbines. Given the practical limitations in acquiring accurate nonlinear terms and aerodynamic forces, our approach focuses on ensuring the adaptability and robustness of the control algorithms under varying operational conditions. The proposed strategies are rigorously evaluated through MATLAB/Simulink 2024 A simulations across multiple wind speed scenarios. Our comparative analysis demonstrates the superior performance of the proposed methods in optimizing power extraction under diverse conditions, contributing to the advancement of MPPT techniques for offshore wind energy systems.

Suggested Citation

  • Muhammad Waqas Ayub & Inam Ullah Khan & George Aggidis & Xiandong Ma, 2025. "Mitigating Intermittency in Offshore Wind Power Using Adaptive Nonlinear MPPT Control Techniques," Energies, MDPI, vol. 18(15), pages 1-17, July.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:15:p:4041-:d:1712880
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    References listed on IDEAS

    as
    1. Xuan Chau Le & Minh Quan Duong & Kim Hung Le, 2022. "Review of the Modern Maximum Power Tracking Algorithms for Permanent Magnet Synchronous Generator of Wind Power Conversion Systems," Energies, MDPI, vol. 16(1), pages 1-25, December.
    2. Malak Adnan Khan & Qudrat Khan & Laiq Khan & Imran Khan & Ahmad Aziz Alahmadi & Nasim Ullah, 2022. "Robust Differentiator-Based NeuroFuzzy Sliding Mode Control Strategies for PMSG-WECS," Energies, MDPI, vol. 15(19), pages 1-18, September.
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