A shape optimization of ϕ-shape Darrieus wind turbine under a given range of inlet wind speed

摘要

The ϕ-shape Darrieus wind turbines have great potential in application due to their omni-directionality and structural advantages. However, to achieve a higher aerodynamic performance, the design of such turbine needs attentive optimization to fit the surrounding wind variation. In this paper, a performance optimization of the shape of ϕ-shape Darrieus wind turbine with a given range of inlet wind speed is carried out. By involving a heuristic search algorithm, Covariance Matrix Adaptation Evolutionary Strategy (CMAES), into Double Multiple Streamtube model (DMST), three geometrical variables of the rotor: the equatorial radius (R), the ratio of radius over half-height (β) and the blade number (B) are modified according to the fitness function that was specially built to satisfy the inlet wind range requirements. Moreover, to validate the optimization output, a 3D CFD simulation is conducted as a comparison. The result shows that this program can present an entirely optimized model under the given range of inlet wind speed, with a 12.5% improved Cp at the optimal velocity compared with the baseline. Verification from CFD method shows a satisfactory agreement for the optimized model compared with the DMST output, indicating that this algorithm could provide a reliable reference for the shape selection of ϕ-shape Darrieus turbines under a certain inlet wind condition.

Yaoran Chen

Researcher of Artificial Intelligence

我所研究的专业领域涉及计算流体动力学（Computational Fluid Dynamics）、人工智能（Artificial Intelligence）以及它们的交叉方向。目前，我的研究以海洋为应用背景，包含物理信息神经网络、海洋环境信息、海洋可再生能源等。