Benzaouia, Mohammed (National School of Applied Sciences, Mohamed First University, O), Benzaouia, Soufyane (LIS UMR CNRS 7020, of Aix Marseille University), Rabhi, Abdelhamid (M.I.S (Modelisation, Information et Systèmes)), Hajji, Bekkay (National School of Applied Sciences, Mohamed First University, O), elgharib, ahmed 1 (Arab Academy for Science, Technology and Maritime Transport)

Direct-Driven PMSG Wind Turbines: Adaptive Super Twisting Algorithm Control Approach

Scheduled for presentation during the Regular Session "Advances in the control of hybrid renewable energy systems" (FriS2T2), Friday, July 12, 2024, 11:30−11:50, Grand Amphitheater

12th IFAC Symposium on Control of Power & Energy Systems, July 10-12, 2024, Rabat, Morocco

This information is tentative and subject to change. Compiled on January 2, 2025

Abstract

This paper deals with the development of a robust nonlinear control strategy for direct-driven Permanent Magnet Synchronous Generator (PMSG) wind turbines. First-Order Sliding Mode Controllers (FOSMC) are commonly used in such systems to regulate generator rotational speed and optimize power extraction; however, they encounter significant drawbacks, notably the undesirable chattering effect and the necessity for measuring additional system states, leading to increased complexity and implementation costs. In addressing these issues, an effective control technique based on an Adaptive Super-Twisting Algorithm (ASTA) has been proposed. This algorithm not only mitigates the chattering effect but also offers a more cost-effective implementation by incorporating online gains adaptation to accommodate the unpredictable nature of wind speeds. The proposed control technique has been evaluated in MATLAB/Simulink through model-in-the-loop simulations; demonstrating superior performance compared to classical FOSMC and STA controllers under various scenarios.