Global variable-speed variable-pitch coordinated control for VAWTs

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Authors: Fawei He, Fue‐Sang Lien, William Melek
Cited by: 1
References: 34

Abstract

Existing control studies on vertical-axis wind turbines have mainly focused on variable-speed and variable-pitch control in isolation, limiting the ability of existing control approaches to accommodate the shift in operating objectives from energy capture to power regulation under unsteady inflow. This study develops a global variable-speed variable-pitch coordinated control framework for vertical-axis wind turbines. The framework is built upon offline-optimized pitch trajectories and implemented through a hierarchical control architecture. The scheduled pitch command provides the baseline output, while a power-feedback pitch compensation term is superimposed to enhance its effectiveness under unsteady inflow. The results show that below rated wind speed, the proposed framework improves aerodynamic performance by reshaping the bound circulation into a more balanced upwind/downwind distribution. Near rated wind speed, it mitigates mode-switching transients. Above rated wind speed, pitch compensation improves power quality by modulating the blade bound circulation evolution, leading to substantial reductions in power and aerodynamic torque fluctuations, while also lowering overload severity and shortening continuous overload duration. These performance enhancements are achieved without increasing the maximum pitch rate or pitch acceleration. Overall, this study establishes a unified and physically interpretable coordinated control framework for vertical-axis wind turbines across the full operating range. • Proposes a global coordinated variable-speed and variable-pitch control framework. • Introduces a power-feedback pitch compensation approach under unsteady inflow. • Improves rated-power regulation and reduces power and aerodynamic torque fluctuations. • Enhances regulation without increasing maximum pitch rate or pitch acceleration.

Fields of Study & Subjects

Advanced Power Amplifier Design Wind Turbine Control Systems Iterative Learning Control Systems

Publication details

Journal / source
Renewable Energy
Publisher
Elsevier BV
Volume
269
Pages
125847–125847
Publication date
24 April 2026
Language
EN