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

Abstract

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.

Stakeholders’ satisfaction as a key determinant of critical success factors in renewable energy projects

“…Pakistan has huge potential to produce renewable energy through the successful use of biomass, solar and geothermal energy, wind power, and small hydropower plants. According to some reliable resources, Pakistan has a potential to provide renewable energy of 1600 GW through solar energy projects [8], up to 44,000 MW through wind power projects [9,10], 13,900 GWh through biomass projects [11], 100,000 MW through geothermal resources [12], and 100 GW through small hydropower projects [13].…”

Optimizing the Weather Research and Forecasting (WRF) Model for Mapping the Near-Surface Wind Resources over the Southernmost Caribbean Islands of Trinidad and Tobago

“…Therefore, a set of NWP model configurations has to be determined for mapping the spatial wind resources. In this study, we configure the WRF NWP for mapping the wind resources of the island state of Trinidad and Tobago, the southernmost islands in the Caribbean, as this model has been tested for mapping the wind resources in several countries [17,25,[47][48][49]. The objectives of this study were to determine the spin-up period for developing mesoscale features as well as assess which one of two input atmospheric data sets and seven PBL parameterizations available to the WRF model would optimize the accuracy of simulating the wind resources for the area of interest.…”

A Parametric Approach to Compare the Wind Potential of Sanghar and Gwadar Wind Sites

“…Calculation of the wind shear of the selected sites can be done using Equations ( 7) and ( 8) respectively. In this process, Alpha (∝) is very important to estimate wind velocities at higher altitude by processing the wind velocities measured at lower or previous altitudes [46], [47].…”