In this paper, the effect of the computational grids on the wind turbine positioning optimization is studied. The linear wake flow model is used to calculate the turbine wake flow. The power law is used to model the power curve of wind turbine. Greedy algorithm with repeated adjustments is introduced to solve the wind turbine positioning problem, with the target of maximizing the total power output of wind farm. Square grid and triangle grid with various orientations are used to discretize the area of wind farm. Three numerical cases are introduced to study the effect of the computational grids on the optimized results. The results show that the optimized power output can be improved through choosing appropriate grid orientation. The suggested grid orientations for single direction wind case and multi-direction wind case are given.
煤炭、石油和天然气等化石能源面临着枯竭,各国争相开发利用可再生能源,风能是目前最具开发利用潜力的可再生能源。风能受地理条件和周围环境的影响大,所以风电场的风资源评估在选址、运营和预测方面都至关重要。本文开发了一套风电场风资源评估系统,它充分考虑了地形、当地风速风向、风电场使用的风力机类型和风力机间的尾流影响,采用基于风力机特性的粒子尾流模型,通过CFD计算,得到风电场的功率输出和风资源分布,此系统既可应用于风电场建造前的选址和评估,也可应用于运营中的检验和预测,有很强的工程应用价值。本文通过澳大利亚Wattle Point Wind Farm(WPWF)实测数据对评估系统的可靠性和精确度进行了验证。
In this article,the random walking method is used to solve the steady linear convection-diffusion equation(CDE)with disc boundary condition.The integral solution corresponding to the random walking method is deduced and the relationship between the diffusion coefficient of CDE and the intensity of the random diffusion motion is obtained.The random number generator for arbitrary axisymmetric disc boundary is deduced through the polynomial fitting and inverse transform sampling method.The proposed method is tested through two numerical cases.The results show that the random walking method can solve the steady linear CDE effectively.The influence of the parameters on the results is also studied.It is found that the error of the solution can be decreased by increasing the particle releasing rate and the total walking time.
