Using an Idealized Framework to Evaluate Wake Effects on Power Output on a Regional Scale

Wind turbine wakes can significantly reduce total wind farm power output, with losses reaching 10 to 20% for large offshore wind farms. For farms with dense layouts, power losses can be even larger. Along the US East coast, a large number of projects have been proposed and are in varying stages of development, yet little work has been done to explore the interaction of different wind farms on one another throughout the region. Here we investigate how wakes affect power output across lease areas throughout the US East Coast region. Currently, there are only two small pilot offshore wind farm projects along the US East Coast, therefore project viability and optimization in this region is an active area of research.

Specifically, we use downscaled hourly and monthly Weather Research Forecast (WRF) model simulations and a suite of analytical wake deficit models implemented in PyWake to investigate the relative influence of idealized wakes on power output in lease areas across the US East Coast. We simulate ideal wakes using the same mock wind farm design for all lease areas along the US East Coast and perform a leave-one-out analysis to compare inter-farm and intra-farm interactions of wakes and quantify the wake affected areas, which can be multiple times the footprint of the lease area. By comparing the relative effect of wakes on different leasing sites across the region at different temporal scales, we can more accurately (1) estimate the impact of wind farm interactions across a large domain area, and (2) determine the probability of each wind farm lease area being affected by neighboring farms. This analysis offers preliminary insights into which leasing areas across the US East Coast will be most affected by wakes from neighboring lease areas.