market revenue rather than the conventional Annual Energy Production (AEP) objective affects technical and economic performance. Using historical hourly wind and day-ahead price data, wake and power models, and a layout optimization framework, the study compares layouts optimized for AEP with layouts optimized for expected revenue across several locations and three case studies.

Key findings show that revenue-optimized layouts deliver small but consistent improvements in projected revenues while keeping reasonable AEP performance. Site-dependent examples illustrate this trade-off: at one site, the revenue-optimized layout increases revenue by 0.22% while reducing AEP by 0.44%, and at another site, revenue increases by 0.20% with a negligible change in AEP (0.03%). Layouts optimized on an earlier period (2015–2020) retain performance when evaluated on later data (2022–2024), with objective-function losses remaining below 0.12%. Scenario experiments further show that long-term market structure predictions matter: changing the assumed correlation between wind speed and electricity prices in future scenarios can impact revenue substantially.

Overall, the study concludes that incorporating price information into layout optimization yields economic benefits and enhances robustness to realistic market variability. The results recommend that developers consider revenue-based objectives alongside traditional energy metrics when designing offshore wind farms operating in merchant electricity markets.