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首页> 外文会议>IEEE International Electrical and Energy Conference >Fine resolution 30-year climatic wind energy dataset over China for renewable energy assessment and operation via Weather Research and Forecasting model hindcast
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Fine resolution 30-year climatic wind energy dataset over China for renewable energy assessment and operation via Weather Research and Forecasting model hindcast

机译：通过天气研究和预报模型后预报法，对中国高分辨率的30年气候风能数据集进行可再生能源评估和运行

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One of the greatest obstacles in the exploitation of wind and solar energy is their intermittency and fluctuation. Long-term dataset of wind energy resource, which is built on basis of atmospheric numerical models, has been proved to be the most effective approach for wind energy resource assessment in wide area, on grid level and in fine resolution, as well as renewable energy electric energy capability forecast, site planning and dispatch/ operation schedule making of power system. To improve the accuracy of wind energy resource dataset by numerical models, the Weather Research and Forecasting model (WRF) and the Climate Four-Dimensional Data Assimilation (CFDDA) are adopted to conduct a sensitivity experiment, in 9 km spatial resolution, to distinguish a reliable model configuration in this study. Based on the statistics between WRF-CFDDA model output in hub-height wind speed and in-situ observations (sited on typical wind farms in Gansu, Xinjiang and Jilin province, 2010-2013), it has been confirmed that the model configuration with MERRA2 background field, Topowind topographic correction method and smoothed VASSO (VAriance of Sub-grid Scale Orography) terrain data is the most reasonable one, with a correlation coefficient 0.79 and RMSE 1.62 for 10-m height wind speed. Following this configuration, with assimilating all 30-year (1987-2016) ground-based meteorological observation from Chinese international exchange sites, the wind energy resource from 1987 to 2016 around China has been hindcasted and assessed in a resolution of 9 km, 15 min. The hindcast is capable to reproduce the characteristics in temporal and spatial distribution. This model system can be a reliable tool for reproducing decades of reanalyzed climatology and finer resolution assessment on hub-height wind energy, moreover, for reconstruction of typical wind power output curve.
机译：利用风能和太阳能的最大障碍之一是它们的间歇性和波动性。在大气数值模型的基础上建立的风能资源长期数据集已被证明是在广域，电网水平和高分辨率以及可再生能源方面最有效的风能资源评估方法。电力系统的电力能力预测，现场规划和调度/运行计划制定。为了通过数值模型提高风能资源数据集的准确性，采用天气研究和预报模型（WRF）和气候四维数据同化（CFDDA）进行了9 km空间分辨率的敏感性实验，以区分本研究中可靠的模型配置。基于轮毂高度风速的WRF-CFDDA模型输出与原位观测值（位于甘肃，新疆和吉林省的典型风电场，2010-2013年）之间的统计数据，已确认使用MERRA2进行模型配置背景场，风向地形校正方法和平滑的VASSO（亚网格尺度地形变异）地形数据是最合理的一种，对于10米高的风速，相关系数为0.79，RMSE为1.62。按照这种配置，吸收了来自中国国际交流站点的所有30年（1987-2016年）的地面气象观测结果，对中国周围1987年至2016年的风能资源进行了后播和分辨率为9 km，15 min的评估。 。后铸物能够再现时间和空间分布中的特征。该模型系统可以是可靠的工具，用于再现数十年的重新分析的气候学以及对轮毂高度风能进行更精细的分辨率评估，还可以重建典型的风能输出曲线。

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