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Abstract. With the transition towards green energies gaining momentum, the expansion of wind farm areas and associated technologies is growing fast. The North Seas Energy Cooperation group has set an ambitious target to increase the offshore wind-generated power capacity from 26 GW in 2022 to 300 GW by 2050 in the geographical areas of the North Seas. With this goal, an extensive offshore infrastructure is planned to be deployed in the region. Studies have been carried out to assess the power production of such future development. However, the associated uncertainties are often only partially addressed due to the complexity and diversity of contributing factors, ranging from technical aspects such as turbine geometry and layout to atmospheric processes across multiple scales, from small-scale turbulence to mesoscale dynamics. Wake effects have been identified as the primary source of power losses. They are often studied in individual wind farms or small clusters, but the dynamics of large wind farm clusters at a regional scale are only beginning to be explored. In this study, we address uncertainties of power output derived from projected wind farm areas in the North Sea in scenarios that encompass different turbine setups and boundary conditions. To achieve this, we used COSMO6.0-CLM, the newest version of the regional climate model COSMO-CLM, and further improved the existing wind farm module to extend the model's capability to design more flexible and realistic scenarios. This allows us to quantify impacts from different factors that contribute to power output uncertainties. Our analysis indicates that the combined uncertainty due to driving conditions and the difference of turbine types amounts to approx. 15 GW, corresponding to 10 % of the total installed capacity (150 GW). Of this, the contribution from driving conditions accounts for 2.5 %, whereas the difference of turbine types has a larger influence, contributing roughly 7.5 %. After applying a correction factor (0.25) to the turbulence production term from the Fitch wind farm parameterization, we found that this modification translates to a reduction in power output of roughly 2 GW (about 1 % of the installed capacity). Given that economic evaluations, environmental assessments, and energy policy decisions make use of modelled wind power outputs in their analyses, accounting for these uncertainties would help to ensure more reliable results.