An Optimal Approach for Assessing Weibull Parameters and Wind Power Potential for Six Coastal Cities in Pakistan

Assessing and effectively optimizing wind power potential for a wind site demands accurate calculation of Weibull parameters. In this research, we have ameliorated the performance of the recently-introduced novel energy pattern factor method (NEPFM) via a direct search algorithm, i.e., simplex search algorithm (SSA). We designate the resulting algorithm as NEPFM-SSA as it took NEPFM’s Weibull distribution parameters as an initial guess and retuned them with the help of the simplex search algorithm to get updated Weibull distribution parameters, which ensure better fitting characteristics. When applied to wind speed data collected from six coastal cities in Pakistan: Gwadar, Jiwani, Karachi, Ormara, Pasni, and Sonmiani Bay, NEPFM exhibited poor fitting characteristics to the observed wind data. Four statistical indicators, namely root mean square error, mean absolute error, coefficient of determination, and coefficient of efficiency, are taken into consideration to measure the accuracy offered by NEPFM-SSA and NEPFM. An enormous reduction in wind power density-based percentage error (for example, 15.3531% than 51.7205% for Gwadar at 10 m height) was observed in NEPFM-SSA compared to NEPFM. The numerical results reveal that NEPFM-SSA outshined NEPFM for all the cases under consideration, authenticating its workability. This increased accuracy results in improving the reliability of assessments of wind energy and the wider operation of wind energy installations. The MATLAB environment was used to achieve numerical results. The proposed NEPFM-SSA approach may be treated as the first choice to determine Weibull distribution parameters and wind power density for the considered wind sites rather than NEPFM.