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Open AccessArticle

Improved Blade Design for Tidal Current Turbines

State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
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Energies 2020, 13(10), 2642; https://doi.org/10.3390/en13102642
Received: 28 April 2020 / Revised: 17 May 2020 / Accepted: 18 May 2020 / Published: 22 May 2020
(This article belongs to the Section Wind, Wave and Tidal Energy)
The efficiency and reliability of blades are key indicators for a tidal current turbine (TCT). A traditional blade design is often an empirical design on hydrodynamics and structure, sequentially. A hydrofoil with a low lift–drag ratio is considered when the structural strength cannot satisfy requirements. However, efficiency is then sacrificed. A redundant design is generally adopted to protect from load uncertainty, but this increases blade weight and cost. In this paper, we present an improved blade design method to enhance the blade reliability of TCTs with relatively high efficiency for energy generation. An equivalent S–N curve model describing the relationship between axial load and cycle times and a simplified load spectrum including load caused by shear flow and turbulence are proposed for the first time for convenient lifetime estimation. A multi-objective genetic algorithm is used to optimize the chord length, twist angle, and thickness of the blade for the best match between lifetime and efficiency. This blade design method was conducted on a 4.4 m length blade of a 120 kW TCT. Comparisons between the original design and optimal designs indicate that the comprehensive performance in terms of the hydrodynamics, structure, and lifetime of the blade presented significant improvements with a small, acceptable efficiency loss. The results also provide more alternative blade solutions for developers as a reference. View Full-Text
Keywords: tidal current turbine; fatigue life; power efficiency; equivalent S–N curve model; multi-objective optimization tidal current turbine; fatigue life; power efficiency; equivalent S–N curve model; multi-objective optimization
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Liu, H.-W.; Gu, Y.-J.; Lin, Y.-G.; Li, Y.-J.; Li, W.; Zhou, H.-B. Improved Blade Design for Tidal Current Turbines. Energies 2020, 13, 2642.

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