Research Projects and Publications



A Feasibility Analysis of a Potential Wind farm In Keldur: Turbine Selection, Production Prediction, and Leading Edge Erosion Review.

Author: Lorenzo Semadeni Muller
Year: 2023
Supervisors: Ármann Gylfason, Ketill Sigurjohnson

Abstract:
To be able to meet the goals for the energy transition, wind power needs to be installed at
an exponential level globally in the next few years. As Icelandic energy demand grows, new
sources of energy are needed. Wind power is an attractive generation technique due to the
climatological conditions of the country. The Norwegian company Zephyr has researched
various different sites, one of them located in Keldur. This study has three aims.
First, to analyze the feasibility of this wind farm by using wind measurements from Veðurstofa
Ísland from the Hella weather station and using the Wind Atlas Analysis and Assessment
Program (WAsP) to generate a localized wind climate in the area of Keldur and predict an
Annual Energy Production (AEP) and a Capacity Factor (CP) by using a theoretical wind
turbine. Second, a hybrid of two Multi-Criteria Decision Making Methodologies (MCDM)
was used to select the best performing turbine of available manufacturers. Third, risk of
leading edge erosion was researched. Existing Leading Edge Erosion mitigation techniques
were reviewed in literature.
According to the WAsP simulation, the wind in the area has a constant direction and low
variability in speed making it an efficient area for wind farm development, reaching a Capacity
Factor of 53%.
The Vestas V136-4.2 ranked best in a Fuzzy Logic Technique for Order of Preference by
Similarity to an Ideal Solution (TOPSIS) methodology which involved five other turbines
evaluated by three different criteria. Finally, Precipitation data was compared to a Erosion
Control mode proposed in literature, which resulted in the precipitation levels expected neat
Keldur not reaching the strictest threshold for enabling of the erosion control operation
scenario indicating corrective measures the most cost effective solution in both time and
energy output.