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Evaluation of weather research and forecasting model for the assessment of wind resource over Gharo, Pakistan

机译:巴基斯坦Gharo的天气研究评估模型和风资源评估预报模型

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Weather research and forecasting (WRF) model is the state-of-the-art mesoscale model that could be used as a guideline to effectively assess the wind resource of Gharo wind station lying in the coastal belt of Pakistan. The anemometer heights of 10 and 30 m for the year 2005 have been used to study the wind profile of the region for summer (June, July, August, September) and winter (December, January, February, March). The study uses an innovative approach for model comparisons, i.e. an eta-half level is added in the model on 60 m height and is interpolated to 30 m height by using well known power law. This is done by studying the diurnal variation of wind shear for the whole year of 2005 in order to reduce maximum possible interpolation error. For both seasons, the error measures of mean bias error (MBE), mean absolute error (MAE) and root mean square error (RMSE) of 30 m interpolated data were found lower than 10 m height data with increased correlation (r). A bias correction methodology (best easy systematic estimator) was further applied over the model output showing a significant improvement toward MBE, MAE and RMSE reduction, i.e. up to 99%, 73% and 68% on 10 m height and 99%, 51% and 46% on 30 m height. Errors were reduced more for summer than winter. The selected bias correction methodology was thus found to be highly applicable for both model heights. The wind energy assessment of Gharo wind station from the corrected model simulation showed summer having more potential for wind energy than winter with an estimated energy of up to 1000 MWh.
机译:气象研究和预报(WRF)模型是最新的中尺度模型,可以用作有效评估位于巴基斯坦沿海地带的Gharo电站的风资源的指南。 2005年的风速计高度为10 m和30 m,用于研究该地区夏季(六月,七月,八月,九月)和冬季(十二月,一月,二月,三月)的风廓线。这项研究使用了一种创新的方法进行模型比较,即在模型中添加了60m高的eta-半水平,并使用众所周知的幂定律将其内插到30m高。这是通过研究2005年全年风切变的昼夜变化来完成的,以减少最大可能的插值误差。对于两个季节,发现30 m内插数据的平均偏差误差(MBE),平均绝对误差(MAE)和均方根误差(RMSE)的误差量度均低于10 m高度数据,且相关性增加(r)。在模型输出上进一步应用了偏差校正方法(最简单的系统估计器),显示出MBE,MAE和RMSE降低方面的显着改进,即在10 m高度上分别达到99%,73%和68%,在99%,51%上30 m高度上占46%。夏天减少的错误比冬天减少的更多。因此,发现所选择的偏差校正方法学对于两个模型高度都非常适用。根据修正的模型模拟对Gharo风力发电站进行的风能评估显示,夏季比冬季更有风能潜力,估计能量高达1000 MWh。

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