Abstract In the first part of this study, correlation between MERRA-2 reanalysis wind data and ground data is assessed for 12 selected locations. The correlation coefficient ranges from 0.17 to 0.75 among the sites. Sites with higher average wind speeds show comparatively stronger correlation. Besides, site specific factors are also investigated. In the second part, wind energy potential at same 12 locations is evaluated using high frequency (10-min interval) ground observed data. The diurnal, monthly and annual means for the sites are calculated and wind speed variance is observed utilizing wind data at six altitude levels (10m, 20m, 40m, 50m, 60m and 80m). The data is fitted to the Weibull distribution. Most probable wind speeds, wind speeds carrying maximum energy and wind power densities for all the locations are calculated for 50m and 80m height wind data. Significant variation of wind power density is observed along the height. A low cut-in speed wind turbine is selected, and annual energy production and capacity factors are estimated. Four locations with high wind power densities, namely Sujawal (355.6 W/m2), Sanghar (312.9 W/m2), Tando Ghulam Ali (288.2 W/m2) and Umerkot (252.8 W/m2) showed good potential to add wind share to global energy mix.

中文翻译：

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探索 MERRA-2 再分析数据对巴基斯坦选定地点的风能估算、风特性分析和能源潜力评估的适用性

摘要 在本研究的第一部分中，对 12 个选定位置的 MERRA-2 再分析风数据与地面数据之间的相关性进行了评估。站点之间的相关系数在 0.17 到 0.75 之间。平均风速较高的站点显示出相对较强的相关性。此外，还研究了场地特定因素。在第二部分中，使用高频（10 分钟间隔）地面观测数据评估相同 12 个位置的风能潜力。计算站点的日、月和年平均值，并利用六个海拔高度（10m、20m、40m、50m、60m 和 80m）的风数据观察风速变化。数据拟合为 Weibull 分布。最可能的风速，所有位置承载最大能量的风速和风功率密度是针对 50m 和 80m 高度风数据计算的。沿高度观察到风功率密度的显着变化。选择低切入速度风力涡轮机，并估计年能源生产和容量因子。四个风电密度高的地区，即 Sujawal (355.6 W/m2)、Sanghar (312.9 W/m2)、Tando Ghulam Ali (288.2 W/m2) 和 Umerkot (252.8 W/m2) 显示出增加风能份额的良好潜力全球能源结构。