Journal
RENEWABLE ENERGY
Volume 154, Issue -, Pages 1240-1251Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2020.03.100
Keywords
MERRA-2 wind data; Wind shear exponent; Wind potential; Weibull distribution; Reanalysis data; Pakistan
Funding
- National University of Sciences and Technology (NUST), Islamabad, Pakistan
- Energy Sector Management Assistance Program (ESMAP)
Ask authors/readers for more resources
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/m(2)), Sanghar (312.9 W/m(2)), Tando Ghulam Ali (288.2 W/m(2)) and Umerkot (252.8 W/m(2)) showed good potential to add wind share to global energy mix. (C) 2020 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available