Output Power Control and Load Mitigation of a Horizontal Axis Wind Turbine with a Fully Coupled Aeroelastic Model: Novel Sliding Mode Perspective

Hongfu Zhang, Jiahao Wen, Farshad Golnary and Lei Zhou
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Hongfu Zhang: School of Civil Engineering, Northeast Forestry University, Harbin 150040, China
Jiahao Wen: School of Civil Engineering, Northeast Forestry University, Harbin 150040, China
Farshad Golnary: Department of Civil Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
Lei Zhou: Department of Civil Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong

Mathematics, 2022, vol. 10, issue 15, 1-40

Abstract: The power control of horizontal axis wind turbines can affect significantly the vibration loads and fatigue life of the tower and the blades. In this paper, we both consider the power control and vibration load mitigation of the tower fore-aft vibration. For this purpose, at first, we developed a fully coupled model of the NREL 5MW turbine. This model considers the full aeroelastic behaviour of the blades and tower and is validated by experiment results, comparing the time history data with the FAST (Fatigue, Aerodynamics, Structures, and Turbulence) code which is developed by NREL (National Renewable Energy Lab in the United States). In the next, novel sensorless control algorithms are developed based on the supper twisting sliding mode control theory and sliding mode observer for disturbance rejection. In region II (the wind speed is between the cut-in and rated wind velocity), the novel sensorless control algorithm increased the power coefficient in comparison to the conventional indirect speed control (ISC) method (the conventional method in the industry). In region III (the wind speed is between the rated and cut-out speed), an adaptive neural fuzzy inference system (ANFIS) is developed to estimate pitch sensitivity. The rotor speed, pitch angle, and effective wind velocity are inputs, and pitch sensitivity is the output. The designed novel pitch control performance is compared with the gain scheduled PI (GPI) method (the conventional approach in this region). The simulation results demonstrate that the flapwise blade displacement is reduced significantly. Finally, to reduce the fore-aft vibration of the tower, a tuned mass damper (TMD) was designed by using the genetic algorithm and the fully coupled model. In comparison to the literature body, we demonstrate that the fully coupled model provides much better accuracy in comparison to the uncoupled model to estimate the vibration loads.

Keywords: aeroelastic model; disturbance rejection; vibration control; tuned mass dampers; sliding mode observer (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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