Towards a regional wind farm planning approach: The Wakeness Index

Abstract Offshore wind energy expansion often involves large wind farms built in close proximity, where inter-farm wake interactions can significantly impact energy production. Numerical weather prediction (NWP) models such as the Weather Research and Forecasting (WRF) model can capture these interactions but are computationally expensive for exploring multiple future scenarios. To address this limitation, we introduce the Wakeness Index (WIX), a simplified yet scalable tool for preliminary regional wind farm planning. Two variants of the WIX are presented: WIX G , which captures basic geometric interactions among wind turbines, and WIX C , which incorporates local wind climatology to improve accuracy. Both variants show strong agreement with WRF-based wind speed deficit results, with correlations of up to 0.93, yet require a fraction of the computational resources and time. Although WIX C offers higher fidelity, it runs at a rate roughly twenty-eight times slower than WIX G , underscoring the trade-off between speed and complexity. This study highlights the applicability of the WIX for rapid scenario assessments, enabling stakeholders to identify optimal spatial layouts for offshore wind farms before engaging into more detailed, resource-intensive simulations. The WIX streamlines the planning process for large-scale offshore wind projects, facilitating sustainable development and efficient utilization of marine space.