考虑度电成本的风力机气动设计
本文根据风力机的工作原理，以度电成本最小化作为优化过程的目标函数，通过遗传算法优化风力机叶片的几何外形，来完成风力机的气动设计。其中，以弦长和扭角作为设计参数，利用MATLAB进行编程，分别建立成本 COST 模型和年发电量 AEP 模型，并利用两个模型的比值,构建出度电成本 COE 模型，以此作为遗传算法的适应度函数来进行寻优探索。成本 COST 模型的构建，针对复合材料风力机叶片形状复杂，本文转化为通过翼型坐标变换求风力机叶片的表面积。表面积降低，意着质量减少，相对应的也就降低了叶片的成本。年发电量 AEP 模型的构建，用 BEM 理论分析风力机叶片的气动性能，由风能利用系数与叶尖速比的曲线得到最大风能利用系数，画出输出功率曲线，并考虑风场分布的概率密度，通过积分得到年发电量 AEP 模型。 本文以 NREL 1.5MW 水平轴风力机为例，应用自己建立的模型，对该型号叶片的弦长和扭角进行了优化，并且将得到的结果与叶片最初的参数进行比较分析，可以发现度电成本有明显的下降，验证了该模型的准确性和可靠性。 25877
毕业论文关键词 气动设计 叶素动量理论 度电成本 遗传算法
Title Wind turbine aerodynamic design considering the cost of energy
Abstract
Along with the rated power of wind turbine is increasing, the size and the cost
of the wind turbine blades are also greatly increased. However, the key component
to turn wind energy into electricity is blades. In order to improve the
competitiveness of wind power online system, it is necessary not only to improve
the operating efficiency of the wind turbine, but also to lower the cost while
optimizing the design. Therefore, taking the cost of energy into consideration
is particularly necessary.
According to the working principle of wind turbines, this article uses the
minimization of COE as the objective function and it also uses Genetic Algorithm
to optimize the shape of the wind turbine blade to complete the wind turbine
aerodynamic design. This article bases on MATLAB programming to establish two
models while setting chord and twist angle as design parameters. One is COST model
and another is AEP model. The ratio between these two models constructs the COE
model and it is used as the fitness function of Genetic Algorithm for optimization.
Since the shape of the composite wind turbine blade is complex, this article turned
it into calculating the surface area through airfoil coordinate transformation.
Reducing surface area means less quality and reducing the cost of the blade. During
the period to build AEP model, We use BEM theory to analyze the aerodynamic
performance of wind turbine blades. We get the maximum power coefficient from the
curve of power coefficient and tip speed ratio and take the probability density
distribution of the wind into consideration. By integrating each section, AEP model
is finally obtained.
In this paper, NREL 1.5MW horizontal axis wind turbine is taken as an example. We apply this model to optimize the chord and twist angle and we compare and analyze
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