Wind turbine power performance measurements often occur at the perimeter of a wind farm, where
the wind flow is subject to blockage effects, which might impact the measured power performance. We perform
Reynolds-averaged Navier–Stokes simulations of a wind farm with five rows of 20 turbines each, operating in
a conventionally neutral boundary layer, to evaluate whether the power performances measured for turbines in
the upstream row would differ from that of a turbine operating in isolation under the same inflow conditions.
We simulate the power performance measurements with both meteorological masts and nacelle-mounted lidars.
Results show that blockage effects have an impact on the measured power performance of the wind farm turbines,
with measured power coefficient varying more than 1 % relative to what is measured for the isolated turbine. In
this work, we propose a method to correct for the effect of blockage on power performance measurements,
yielding a curve that is more consistent with how power curves in energy yield analyses are defined and used,
and thereby allowing for more useful comparisons between these curves. Our numerical results indicate that
the correction method greatly reduces blockage-related variance and bias in the measured power curves. While
flow modeling can be used to calculate the correction factors for actual power performance measurements in the
field, we additionally show how some of the correction factors can be derived from lidar measurements. Finally,
the numerical results suggest that the method could also be used to correct for the effect of wakes on power
performance measurements conducted on turbines located downstream of the leading row.