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Pakistan has been facing an energy crisis for many years. Techno-economic analysis of wind power generation is carried out to meet energy demand. Wind data from 2016 to 2018 has been selected for a coastal site of Sindh, Pakistan. For this purpose, four distribution functions, namely Weibull, Gamma, Rayleigh, and Lognormal are used. These distribution functions are compared using the coefficient of determination (R 2 ) and root mean square error tests. Wind potential on a daily, monthly, yearly and seasonal basis is evaluated. In this regard, various turbine models are selected to estimate their power generation capacity. The assessment results for a hub height of 100 m shows the average wind speed for three years is 7.9 m/s with direction dominated between the West and Southwest. The most probable wind speed is 9.5 m/s having a maximum energy density of 455 kWh/m 2 in May. The maximum mean wind speed of 8.55 m/s is in the spring. The Weibull distribution function (k = 2.92 & C = 8.86 m/s) performs the best. The maximum capacity factor for Fuhrlander LLC WTU 3.0-120 is 55.49% and for Siemens SWT-3.15-142 is 55.22%. Likewise, the estimated lowest LCOE ($/1kWh) for Fuhrlander LLC WTU 3.0-120 and Siemens SWT-3.15-142 is $0.04016 and $0.04035 respectively. Thus, this site contains suitable technical and economic characteristics of the wind power plant. KeywordsAnnual energy generation • Capacity factor • Cost of energy generation • Cumulative and probability distribution functions • Wind power and energy densities * Kalsoom Bhagat