Wind potential of the Guelmim region-Weibull distribution
Before each implantation of a wind park, an in-depth study is made to identify the potential of the region, forcast the production and the project costs in order to identify if the project is profitable.
I. Presentation of the study area
Located 200 km south of Agadir, 110 km from Tiznit and 30 km from the Atlantic Ocean, 400 km from Laayoune , Guelmim has 200,000 inhabitants in 2018. The Table represents the geographical coordinates of the site.
II. Result of the study
The average monthly wind variations as a function of according to the height. The analysis of these curves describes an increase of the wind speed as a function of height. The months of May, June and July are more interesting, while the months of September, October and November are critical.
II.1. Wind speed distribution
The wind distribution is based on the Weibull distribution used by statisticians.Its parameters K and C are calculated according to the measurements. The Weibull distribution law is expressed by the relation:
In this work, the Weibull parameters are calculated using five methods (Lysen, Justus, Mle, Moment, Energy). Obviously, the important evaluation of the Weibull parameters is controlled by various statistical performance indicators. The results presented in the table indicate that the modified maximum likelihood method provides a better fit than the other methods for the site, Guelmim.
β’ Annual estimation curve
II.2. Power density
It allows to estimate the recoverable power on a site.
As shown in the figures below, the most productive the most productive month is June for the Guelmim site.
III. Choice and wind turbine identification
III.1. Capacity factor
The productivity of the wind turbine is measured by the capacity factor.The πΆπ is expressed when the wind turbine is operating at 100% of its rated power
After choosing the appropriate wind turbines from the capacity coefficient such that Cf is as close to 1.
VI. Technical-economic study
VI.1. Cost per MW of installed wind power
The distribution of costs between the various items may vary from one project to another, depending on the number of the number of wind turbines that will be installed. Indeed, for large wind farms, it is possible to certain economies of scale.
β’ T: assumed lifetime of 20 years
β’ The interest rate (r) and inflation rate (i) are considered 12% and 3% respectively.
β’ The maintenance cost (Comr) is considered as 25% of the annual cost of the turbine
β’ The scrap value (S) is 10% of the turbine cost
β’ The investment (I) includes the cost of the turbine plus its transportation cost to the country (Morocco)
VI.2. Return on investment
The profitability of a wind power project depends on the ratio between the selling price of the wind kWh and its cost price. its cost price.