The data analysis presented here indicates that the mean annual wind speed at the Airport is about 9.5 m/s while the mean annual wind speed at the Seaport is about 7.0 m/s. We attribute this difference to the different levels of wind exposure at the two stations. The Airport is located outside the city and has excellent wind exposure, whereas the Seaport station is located in a developed area within the town.
 

Before realizing that there were two stations at Aseb - a fact not indicated in the DATSAV2 data set - the annual average wind speed at Aseb appeared to be about 8 meters per second. This value compares favorably to the results obtained by Mulugetta and Drake (1996), who reported an observed mean annual wind speed of 8.1 meters per second and a predicted mean annual wind speed of 7.9 meters per second at Aseb.

After dividing the data set into Airport and Seaport station data, several other problems were encountered in finding an accurate estimation of mean annual wind speeds. In solving these problems, many different methods were utilized. Table 11 provides a summary of the Weibull parameters, mean annual wind speeds and wind power densities obtained using four different methods of data analysis.

It is interesting to note the significant difference in these results. As discussed in Chapter 5, inconsistent sampling methods favored the high wind speeds found during the daytime, resulting in the artificially high values listed after "Unadjusted." The standard Weibull fits to the adjusted wind speed distributions also produced higher values because they failed to recognize the high percentage of calms recorded at Aseb. The linear correlation and three-parameter Weibull fit methods used in this analysis resulted in more conservative, and presumably more accurate, mean annual wind speed values.

The disparity between values shown in Table 11 highlights the skepticism one must have when dealing with data records, particularly when the accuracy of the data cannot easily be confirmed. Based on these findings, it is recommended that any data set to be used for wind assessment be examined carefully before proceeding with analyses.

The other source of disparity is derived from the standard method of using the Weibull distribution to describe the wind speed frequency distribution at a given site. Based on the findings presented here, it seems that the Weibull distribution is not always a good representation of a wind regime. In particular, the Weibull distribution does not allow for a wind speed of zero, and may therefore overestimate wind speeds in certain regions. More research needs to be conducted on this subject to determine whether the high frequency of calms indicated by the DATSAV2 data for Aseb is a real phenomenon or an idiosyncrasy.

Because of the uncertainties in wind speeds, financing and other factors, cost estimates at this stage are highly unreliable. However, the cost of wind generated electricity at Aseb will almost certainly be lower than the current cost of electricity, which is generated from imported diesel fuel.

As noted previously, the California Energy Commission (1997) estimates that the cost of wind power at "good" sites is about 4.6 cents per kilowatt-hour. All else being equal, the cost of wind power at 4.6 cents is already less than the cost of diesel fuel at Aseb, which is about 6.5 cents per kilowatt-hour. Based on the unusually high mean annual wind speeds and capacity factors at Aseb, it is safe to assume that the cost of wind power would be even lower than 4.6 cents per kilowatt-hour.