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Comparison of Wind Energy Potential for Coastal Locations: Pasni and Gwadar
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A comparative study for the wind power density of the two investigated coastal sites viz. Pasni and Gwadar is presented in this paper. Pasni and Gwadar are located along the coast belt of Balochistan in Arabian Sea. Investigations are performed on daily wind speed data recorded at 12:00 UTC, obtained from Pakistan Meteorological | department (PMD) for a period five years, i.e. from 2003 to 2007. The recorded wind speed data distribution is fitted to the Weibull distribution function described by two fitting parameters i.e. scale (c) and shape (k). The Weibull parameters are numerically calculated using the Method of Moment (MoM). Monthly mean wind speeds for the two stations are predicted and wind power densities are calculated for the two stations. Comparison of the wind power densities of the investigated sites reveals a higher wind energy yield for Pasni as compared to Gwadar. The highest wind power density is predicted for the month of May.
Title: Comparison of Wind Energy Potential for Coastal Locations: Pasni and Gwadar
Description:
A comparative study for the wind power density of the two investigated coastal sites viz.
Pasni and Gwadar is presented in this paper.
Pasni and Gwadar are located along the coast belt of Balochistan in Arabian Sea.
Investigations are performed on daily wind speed data recorded at 12:00 UTC, obtained from Pakistan Meteorological | department (PMD) for a period five years, i.
e.
from 2003 to 2007.
The recorded wind speed data distribution is fitted to the Weibull distribution function described by two fitting parameters i.
e.
scale (c) and shape (k).
The Weibull parameters are numerically calculated using the Method of Moment (MoM).
Monthly mean wind speeds for the two stations are predicted and wind power densities are calculated for the two stations.
Comparison of the wind power densities of the investigated sites reveals a higher wind energy yield for Pasni as compared to Gwadar.
The highest wind power density is predicted for the month of May.
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