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Wake Deficit Analysis with PyWake

How to quantify turbine wake losses using PyWake on a simple offshore layout.

Introduction

Wake losses are one of the largest sources of uncertainty in offshore wind yield assessments. In this post we set up a simple PyWake simulation on a 3×3 grid layout and inspect the per-turbine power deficit.

import numpy as np
import matplotlib.pyplot as plt
from py_wake.examples.data.hornsrev1 import HornsRev1Site, V80
from py_wake import NOJ

Define site and turbine

We use the built-in Horns Rev 1 site and the Vestas V80 power curve.

site = HornsRev1Site()
turbine = V80()

# 3x3 grid, 5D spacing
D = turbine.diameter()
x = np.repeat([0, 5*D, 10*D], 3)
y = np.tile([0, 5*D, 10*D], 3)

Run the NOJ wake model

wf_model = NOJ(site, turbine)
sim = wf_model(x, y, ws=10, wd=270)
print(sim.Power.values / 1e6)  # MW per turbine

Conclusion

Turbines in the second and third rows show clear power deficits. Rows aligned with the prevailing westerly wind lose up to 20% of free-stream power.