Four optimization methods were employed to minimize the LCoE of
Nawri et al. state that “The wind MG132 potential of Iceland is within the highest class as defined in the European Wind Atlas” . Additionally, development in wind power is supported by 81% of the Icelandic population . Given the quality of the natural resource and public support, it is likely that Landsvirkjun will continue to investigate potential developments in wind power in the near future.
In this paper, the selection of two Enercon E-44 wind turbines at Búrfell was used as a case-study on wind turbine selection methodology. The aim of the case-study was to investigate the method applied by Landsvirkjun, the methods commonly applied in literature, and to develop an alternative method of turbine selection for use by infrastructure developer.
Selection methodologies used in literature were evaluated subjectively. Common shortcomings identified in research to-date, if used for the sake of wind turbine selection, are:•Modelling of fixed speed turbines only  and ;•Overly-simplistic cost estimation methods and models , , ,  and ;•Optimization of parameters interstitial cannot be known by the developer (i.e. blade shape) , , ,  and ;•Sub-optimal objective functions (i.e. capacity factor, rated speed) , ,  and ;•Restriction to a small set of turbines (i.e. a small subset of what is commercially available) ,  and ;•Slow optimization techniques (i.e. brute force calculations or manual iterations) , , ,  and ;•Failure to account for impact of changing hub height on cost and production ,  and ;