Influence of wind turbine size on Levelized Cost of Energy of the offshore wind farm Energy Island Bornholm
Abstract
This study investigates how wind turbine sizes ranging from 8 MW to 22 MW affect wind farm layouts and the Levelized Cost of Energy (LCOE) for the Energy Island Bornholm project in Denmark. This is accomplished by utilizing and expanding the heuristic optimization algorithm called Smart-Start, which is part of the TOPFARM optimization tool. The analysis evaluates three predefined wind farm sites, Bornholm I North, Bornholm I South, and Bornholm II (referred to as EIB1N, EIB1S and EIB2), by examining key parameters such as wake loss and foundation costs. These parameters provides nuances and insight when determining what turbine is most cost-effective and which site can achieve the lowest LCOE. Furthermore, the analysis investigates the effect of a carbon tax on layout and LCOE. The results show that increasing turbine size generally leads to lower LCOE, primarily due to reduced wake losses and access to better wind resources at higher hub heights. Among the turbine sizes tested, the 22 MW model consistently achieved the lowest LCOE at all sites, although the marginal benefit diminished with each size increase. Compared to the 8 MW turbine, the 22 MW turbine’s LCOE was up to 3.2% lower. Layout patterns were found to prioritize maximizing energy production over minimizing foundation costs, with turbines spaced further apart to reduce wake effects. Generally, this layout tendency remained the same across turbine sizes, except for EIB2, which increasingly favored the shallower waters with larger turbine sizes. EIB2’s lower capacity density (MW/km2) allowed for turbines to be placed in shallow areas without incurring severe wake losses, while EIB1N and EIB1S experienced greater wake losses due to higher capacity density. It was observed that the sites with higher capacity density were also the sites with shallower waters. Despite these differences, all sites showed similar LCOE values, indicating a balance between wake losses (linked to capacity density) and foundation costs (linked to depth). However, EIB1S achieved the lowest overall LCOE, with a value of 59.4 €/MWh. The inclusion of a carbon tax of 16.8 €/tCO2e had a negligible effect on turbine layout while slightly increasing LCOE by 0.3-0.4% corresponding to approximately 0.2 €/MWh. Overall, the findings support the use of larger turbines for minimizing LCOE when moderate carbon tax is considered. However, it was observed that the carbon tax affects larger turbines more due to their mass scaling, why a substantially higher tax would offset the benefits of larger turbines making them less economically favorable. The turning point was found around 300 €/tCO2e where 15-22 MW turbines achieve nearly identical LCOE.
Cite this
Søndergaard, Freja Roed; Bonde, Christian. (2025). Influence of wind turbine size on Levelized Cost of Energy of the offshore wind farm Energy Island Bornholm.
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