normalize sector frequency

py_wake/examples/data/hornsrev1.py

@@ -71,7 +71,7 @@ ct_curve = np.array([[3.0, 0.0],
                      [25.0, 0.053]])
 
 
-class HornsrevV80(OneTypeWindTurbines):
+class V80(OneTypeWindTurbines):
     def __init__(self):
         OneTypeWindTurbines.__init__(self, 'V80', diameter=80, hub_height=70,
                                      ct_func=self.ct, power_func=self.power)
@@ -83,6 +83,9 @@ class HornsrevV80(OneTypeWindTurbines):
         return np.interp(u, power_curve[:, 0], power_curve[:, 1])
 
 
+HornsrevV80 = V80
+
+
 class HornsrevSite(UniformWeibullSite):
     def __init__(self):
         f = [3.597152, 3.948682, 5.167395, 7.000154, 8.364547, 6.43485,

py_wake/site/_site.py

@@ -161,6 +161,7 @@ class UniformWeibullSite(UniformSite):
         wdir = np.linspace(0, 360, len(p_wd), endpoint=False)
         indexes = np.argmin((np.arange(360)[:, np.newaxis] - wdir + 360 / len(p_wd) / 2) % 360, 1)
         self.p_wd = np.array(p_wd)[indexes] / (360 / len(p_wd))
+        self.p_wd /= self.p_wd.sum()
         self.a = np.array(a)[indexes]
         self.k = np.array(k)[indexes]
 

py_wake/tests/test_aep.py

@@ -3,7 +3,7 @@ from py_wake.examples.data.iea37 import iea37_path
 from py_wake.examples.data.iea37._iea37 import IEA37_WindTurbines
 from py_wake.examples.data.iea37.iea37_reader import read_iea37_windrose,\
     read_iea37_windfarm
-from py_wake.site._site import UniformSite
+from py_wake.site._site import UniformSite, UniformWeibullSite
 from py_wake.tests import npt
 from py_wake.wake_models.noj import NOJ
 from py_wake.examples.data import hornsrev1
@@ -11,6 +11,13 @@ from py_wake.wake_models.gaussian import IEA37SimpleBastankhahGaussian
 import numpy as np
 
 
+def test_aep_no_wake():
+    site = UniformWeibullSite([1], [10], [2], .75)
+    V80 = hornsrev1.V80()
+    aep = AEP(site, V80, NOJ(V80))
+    npt.assert_almost_equal(aep.calculate_AEP([0], [0]).sum(), 8.260757098, 9)
+
+
 def test_wake_map():
     _, _, freq = read_iea37_windrose(iea37_path + "iea37-windrose.yaml")
     n_wt = 16
@@ -43,8 +50,8 @@ def test_wake_map():
 def test_aep_map():
 
     _, _, freq = read_iea37_windrose(iea37_path + "iea37-windrose.yaml")
-    n_wt = 16
-    x, y, _ = read_iea37_windfarm(iea37_path + 'iea37-ex%d.yaml' % n_wt)
+    # n_wt = 16
+    # x, y, _ = read_iea37_windfarm(iea37_path + 'iea37-ex%d.yaml' % n_wt)
 
     x = [0, 0]
     y = [0, 200]
@@ -52,11 +59,11 @@ def test_aep_map():
     windTurbines = IEA37_WindTurbines(iea37_path + 'iea37-335mw.yaml')
     wake_model = IEA37SimpleBastankhahGaussian(windTurbines)
     aep = AEP(site, windTurbines, wake_model)
-    print(aep.calculate_AEP([0], [0]).sum())
+    # print(aep.calculate_AEP([0], [0]).sum())
     x_j = np.arange(-150, 150, 20)
     y_j = np.arange(-250, 250, 20)
     X, Y, Z = aep.aep_map(x_j, y_j, 0, x, y, wd=[0])
-    print(y_j)
+    # print(y_j)
     if 0:
         import matplotlib.pyplot as plt
         c = plt.contourf(X, Y, Z, 100)  # , np.arange(2, 10, .01))
@@ -68,20 +75,19 @@ def test_aep_map():
         plt.axis('equal')
 
         plt.show()
-    print(np.round(Z[17], 2).tolist())
+    # print(np.round(Z[17], 2).tolist())
     ref = [21.5, 21.4, 21.02, 20.34, 18.95, 16.54, 13.17, 10.17, 10.17, 13.17, 16.54, 18.95, 20.34, 21.02, 21.4]
     npt.assert_array_almost_equal(Z[17], ref, 2)
 
 
-def test_aep_no_wake_loss():
-    _, _, freq = read_iea37_windrose(iea37_path + "iea37-windrose.yaml")
-    n_wt = 16
-    x, y, _ = read_iea37_windfarm(iea37_path + 'iea37-ex%d.yaml' % n_wt)
+def test_aep_no_wake_loss_hornsrev():
+    wt = hornsrev1.V80()
+    x, y = hornsrev1.wt_x, hornsrev1.wt_y
+    site = UniformWeibullSite([1], [10], [2], .75)
 
-    x = [0, 0]
-    y = [0, 200]
-    site = UniformSite(freq, ti=0.75)
-    windTurbines = IEA37_WindTurbines(iea37_path + 'iea37-335mw.yaml')
-    wake_model = IEA37SimpleBastankhahGaussian(windTurbines)
-    aep = AEP(site, windTurbines, wake_model)
-    print(aep.calculate_AEP_no_wake_loss(x, y))
+    aep = AEP(site, wt, NOJ(wt))
+    npt.assert_almost_equal(aep.calculate_AEP_no_wake_loss(x, y).sum() / 80, 8.260757098)
+
+    cap_factor = aep.calculate_AEP(x, y).sum() / aep.calculate_AEP_no_wake_loss(x, y).sum()
+    # print(cap_factor)
+    npt.assert_almost_equal(cap_factor, 0.947175839142014)