Wind energy is one of the most cost-effective forms of renewable energy source with significant increment in yearly installed capacities all around the world. In this study, three commercial wind turbines, namely POLARIS P15-50, POLA-RIS P50-500 and VESTAS V110-2.0, were chosen as large-scale wind energy conversion systems (WECSs) for technical assessment of electric power generation in eight selected locations spreading across the Tigray region of Ethiopia. The economic evaluations of these three WECSs for electric power generation in the selected locations were estimated using present value of cost (PVC) method. These results showed that the highest capacity factor is obtained as 7.873 % using VESTAS V110-2.0 at Mekele, while the lowest as 0.002 % using POLARIS P15-50 at Shire. Average minimum cost per kWh obtained at Mekele was 0.0011$/kWh using VESTAS V110-2.0, while the highest average cost was 7.3148$/kWh using POLARIS P15-50 at Shire. Furthermore, it can be suggested that Atsbi, Chercher, Mekele and Senkata were most profitable for electrical and mechanical applications than hydropower cost in the country.

Paramount two-parameter Weibull function has been extensively used to assess the wind energy potential. The performance contrast of four statistical methods, i.e., energy pattern factor method, least squares regression method, method of moments and mean standard deviation method in estimating extensively used Weibull parameters for wind energy application at four selected locations of northern Ethiopia has been studied. The contrast of statistical methods is compared through relative percentage error, root mean square error, mean percentage error, mean absolute percentage error, Chi-square error and analysis of variance (or) efficiency of the methods used. Test results evidently revealed that, least squares regression method presents better performance than other methods selected in the investigation. The least efficient methods to fit the Weibull distribution curves for the assessment of wind speed data especially for four selected locations are energy pattern factor method, method of moments and mean standard deviation. From the actual data analysis, it is found that if wind speed distribution matches well with the Weibull function, the above three methods are applicable, but if not, least squares regression method can be considered based on the cross checks including energy potential and cumulative distribution function.

No abstract

No abstract

In this study, the relative economic contrast of wind energy conver-sion systems (WECSs) are examined using levelized cost of electricity(LCOE) and present value cost (PVC) as measures of merit of systemlife cycle cost. From the analysis of data and discussion, capacity factorand useful life of the wind turbine have a positive impact on the costof electricity produced by the WECS, while the other input parametersof LCOE and PVC increase the system life cycle cost, as their values in-creases. The trend of capacity factors decreased linearly, and the simul-taneous increase in LCOE and PVC was noticed.