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Hydrokinetic turbine design through performance prediction and hybrid metaheuristic multi-objective optimization

机译：通过性能预测和杂交地横向多目标优化设计水动力涡轮机设计

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摘要

Small wind turbines (SWT) and hydrokinetic turbines (HT) are affordable ways to distribute power generation from renewable resources. In order to better harness such available sources and to design future equipment as efficient as possible, this paper aims to develop a layout optimization. Firstly, the Blade Element Momentum (BEM) method is applied to validate the aerodynamic models from literature with experimental data. It intends to replicate turbine operation and its performance. The power and thrust curves could be well-predicted according to tip-speed ratio (TSR) variation. Secondly, meta-heuristic algorithms based on natural behaviour are used to find the best hydrokinetic turbine design in a hypothetical environment subjected to a single person's electricity demand. Later, an analysis of a higher power supply will also be made. The optimization was carried out concerning power and blade inertia, and the layout parameters used as input were the rotor diameter, the number of blades, and the rotational speed. Cavitation effect was taking into account and tried to be avoided at chord calculation. The most efficient algorithm could find a turbine with a power coefficient 18% lower than the Betz Limit.
机译：小型风力涡轮机（SWT）和水动力学涡轮机（HT）是可以从可再生资源分配发电的经济型方式。为了更好地利用这种可用的来源并尽可能高效地设计未来的设备，本文旨在开发布局优化。首先，应用刀片元件动量（BEM）方法以通过实验数据验证文献的空气动力学模型。它打算复制涡轮机操作及其性能。根据尖端速度比（TSR）变化，可以良好地预测功率和推力曲线。其次，基于自然行为的元 - 启发式算法用于在假设环境中寻找最佳的水动力涡轮机设计，这些环境受到单一人的电力需求。后来，还将进行对更高电源的分析。关于电力和刀片惯性的优化，用作输入的布局参数是转子直径，叶片的数量和转速。考虑到空化效果并试图在和弦计算中避免。最有效的算法可以找到比BETZ限制低18％的电力系数的涡轮机。

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