GlobeLand30地表覆盖产品应用于精细化风能资源评估

发布时间：2018-07-27 18:56

【摘要】：高山风电场具有多方面复杂特性,因此有必要开展精细化风能资源评估。本文创新性地引入了中国自主制作的全球首套30m分辨率地表覆盖产品Globe Land30,制作高精度地表粗糙度资料,并应用于精细化风能资源评估。该方法在云南大团山风电场案例进行了尝试实施,使用计算流体力学(CFD)模式Meteodyn WT获得了30m分辨率的平均风速和平均风功率密度图谱。采用风电场内测风塔的实测数据对模拟结果进行了检验,观测期6个月平均风速的模拟误差在1%以内,平均风功率密度的模拟误差在4%以内。模拟与实测的风速频率分布和风向玫瑰均保持了较好的一致性。采用模拟数据计算了两种典型风电机组的发电量,观测期的总发电量误差低于1%。利用欧洲空间局地表覆盖产品开展了对照实验,其模拟结果的误差水平显著高于上述结果。本文研究成果基本满足风电场预测长期发电量水平的业务需求,具备应用与推广价值。
[Abstract]:Alpine wind farm has many complex characteristics, so it is necessary to carry out fine wind energy resource evaluation. In this paper, the Globe Land30, the world's first 30m resolution land cover product, is introduced to produce high precision surface roughness data, and it is applied to the evaluation of fine wind energy resources. The method has been applied to the Daguanshan wind farm in Yunnan Province. The average wind speed and mean wind power density atlas with 30m resolution have been obtained by using the computational fluid dynamics (CFD) model Meteodyn WT. The simulation results are verified by the measured data of the wind tower in the wind farm. The simulation error of the average wind speed is less than 1% and the simulation error of the average wind power density is less than 4% during the 6-month observation period. The simulated and measured wind speed frequency distribution and wind direction of rose are in good agreement. The simulation data are used to calculate the power generation of two typical wind turbines, and the total power generation error in the observation period is less than 1. A controlled experiment was carried out using the surface mulching products of the European Space Agency (ESA), and the error level of the simulation results was significantly higher than that of the above results. The research results of this paper basically meet the business demand of forecasting long term power generation level of wind farm, and have the value of application and popularization.
【作者单位】：中国科学院大气物理研究所大气边界层物理与大气化学国家重点实验室;中国科学院大学;中国三峡新能源有限公司;
【基金】：国家自然科学基金(11472272)
【分类号】：TM614

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