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Abstract As the world transitions towards sustainable energy sources, offshore wind farms are one of the options under consideration in several countries. Some countries, for instance, the Netherlands, Denmark, Germany, the UK, and China, have already constructed multiple offshore wind farms. Other countries, such as the United States in North America and Brazil in South America, are making movements toward offshore wind. One potential problem is that offshore wind farm wakes can extend for longer distances than onshore, placing challenges on potential wake losses due to farm-to-farm interaction effects. This study proposes a farm-to-farm benchmark to complement ongoing experimental and computational efforts. We consider eight engineering wake models and 31 cases of pairs of existing offshore wind farms, totaling 248 simulations. The results varied according to the engineering wake model applied, alignment (or not) of neighboring wind farms with the prevailing wind direction, and wind turbine capacity. The range of AEP loss significantly varied between 0.075% and around 2.3% in the extreme cases. 

Abstract This study explores the effects of various parameters on wake interactions between offshore wind farms, with a particular focus on the Revolution-Southfork Wind and Vineyard Wind projects. The research examines how factors such as Euclidean distances, turbine-rated power, rotor diameters, and the number of turbines at upstream farms impact the annual energy production (AEP) of downstream installations. The results reveal significant variations in AEP losses, with the Nygaard model demonstrating a marked sensitivity to changes in turbine-rated power, rotor diameter, and the differing Euclidean distances between farms. Our findings indicate that strategic planning regarding turbine characteristics and farm placements is essential for optimizing energy output and reducing wake-induced power losses. These insights lay the groundwork for further analytical research.