Optimization of blade pitch in H-rotor vertical axis wind turbines through computational fluid dynamics simulations

Chao Li, Yiqing Xiao, You-lin Xu, Yi-xin Peng, Gang Hu and Songye Zhu

Applied Energy, 2018, vol. 212, issue C, 1107-1125

Abstract: Blade pitch control is a well-developed and widely-used approach in modern horizontal axis wind turbines in operation. However, its application in vertical axis wind turbines (VAWTs) is restricted by the ambiguities in its functional mechanism. A generic formulation that uses five governing parameters to represent the solution space of the optimal blade pitch control is developed through an in-depth analysis of the relationship between blade pitch and the output power of VAWTs. Subsequently, a variable blade pitch automatic optimization platform (VBPAOP) composed of genetic algorithm and computational fluid dynamics (CFD) simulation modules is built to search for optimal blade pitches that can maximize turbine power. A 2D unsteady CFD model is used as a performance evaluation tool because of its high computational efficiency, and its accuracy is validated through wind tunnel experiments prior to its application in optimization. Results show that in a wide range of tip speed ratios (TSRs), the optimized blade pitches can increase the average power coefficients by 0.177 and 0.317, respectively, in two simulated VAWT models with different chord lengths. At stages below the rated TSR, stall-induced torque losses are delayed or even avoided by the proposed optimized pitch control. At stages beyond the rated TSR, energy extraction in the downwind zone is improved due to increased upwind wake velocity.

Keywords: Blade pitch; Vertical axis wind turbine; Active control; Computational fluid dynamics (CFD); Genetic algorithm (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (22)

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DOI: 10.1016/j.apenergy.2017.12.035

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