利用大涡流模拟对风电场布局和尾流转向进行数据驱动优化

IF 3.6 Q3 GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY
Nikolaos Bempedelis, Filippo Gori, Andrew Wynn, Sylvain Laizet, Luca Magri
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引用次数: 1

摘要

摘要最大限度地提高大型风电场的发电量是向净零过渡的关键。本文的首要目标是提出一种计算方法,通过两种实用的设计策略实现风电场发电量的最大化。首先,我们提出了一种无梯度方法,利用基于大涡流模拟和贝叶斯框架的高保真代用模型来优化风电场的发电量。其次,我们应用所提出的方法,通过微观选址(布局优化)和尾流转向(偏航角优化)实现风电场发电量的最大化。第三,我们将优化结果与低保真尾流模型的优化结果进行了比较。最后,我们将廉价的尾流模型与高保真框架相结合,提出了一种简单的多保真度策略。所提出的无梯度方法可以有效地最大化风电场的发电量。与尾流模型优化策略相比,该方法的性能有所提高,特别是在流动复杂度增加的情况下,例如在尾流转向问题中,简化流动模型中的一些假设变得不那么准确。高保真方法的优化考虑到了非线性和非稳态流体力学现象,建议的框架利用这些现象来提高风电场的产出。本文为使用高保真方法和无辅助求解器进行风电场优化提供了机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data-driven optimisation of wind farm layout and wake steering with large-eddy simulations
Abstract. Maximising the power production of large wind farms is key to the transition towards net zero. The overarching goal of this paper is to propose a computational method to maximise the power production of wind farms with two practical design strategies. First, we propose a gradient-free method to optimise the wind farm power production with high-fidelity surrogate models based on large-eddy simulations and a Bayesian framework. Second, we apply the proposed method to maximise wind farm power production by both micro-siting (layout optimisation) and wake steering (yaw angle optimisation). Third, we compare the optimisation results with the optimisation achieved with low-fidelity wake models. Finally, we propose a simple multi-fidelity strategy by combining the inexpensive wake models with the high-fidelity framework. The proposed gradient-free method can effectively maximise wind farm power production. Performance improvements relative to wake-model optimisation strategies can be attained, particularly in scenarios of increased flow complexity, such as in the wake steering problem, in which some of the assumptions in the simplified flow models become less accurate. The optimisation with high-fidelity methods takes into account nonlinear and unsteady fluid mechanical phenomena, which are leveraged by the proposed framework to increase the farm output. This paper opens up opportunities for wind farm optimisation with high-fidelity methods and without adjoint solvers.
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来源期刊
Wind Energy Science
Wind Energy Science GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY-
CiteScore
6.90
自引率
27.50%
发文量
115
审稿时长
28 weeks
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