Simulación de todas las direcciones

server/simulation.py

@@ -11,82 +11,60 @@ import xarray as xr
 
 D = 126      #Diametro del wT
 h = 90       #Altura del WT
-U_ref = 8
+ws = 8
+initial_position = np.array([[1, 1]])
 
-
-initial_position = np.array([[  1  , 1],
-                             [  2. , 2],
-                             [  4  , 4],
-                             [  1  , 4],
-                             [  2  , 4],
-                             [  3  , 4],
-                             [  1  , 5],
-                             [  2  , 5],
-                             [  5  , 5]])
-
-
-def py_wake_Initial_Cong(D,name,h,U_ref,initial_position=initial_position):
-    
-    #Curvas del WT
+def py_wake_Initial_Conf(D, name, h):
     power_curve = np.array([
-			[ 0.1, 1.000],
-            [ 4.5, 267.7],
-			[ 5.0, 387.6],
-			[ 5.5, 534.0],
-			[ 6.0, 707.4],
-			[ 6.5, 910.0],
-			[ 7.0, 1142.7],
-			[ 7.5, 1407.5],
-			[ 8.0, 1707.1],
-			[ 8.5, 2047.3],
-			[ 9.0, 2430.6]]) * [1, 1000]
-
+        [ 0.1, 1.000],
+        [ 4.5, 267.7],
+        [ 5.0, 387.6],
+        [ 5.5, 534.0],
+        [ 6.0, 707.4],
+        [ 6.5, 910.0],
+        [ 7.0, 1142.7],
+        [ 7.5, 1407.5],
+        [ 8.0, 1707.1],
+        [ 8.5, 2047.3],
+        [ 9.0, 2430.6]]) * [1, 1000]
 
     ct_curve = np.array([
-            [ 0.1, 0.100],
-			[ 4.5, 0.928],
-			[ 5.0, 0.892],
-			[ 5.5, 0.861],
-			[ 6.0, 0.835],
-			[ 6.5, 0.812],
-			[ 7.0, 0.792],
-			[ 7.5, 0.776],
-			[ 8.0, 0.7702530978349217],
-			[ 8.5, 0.762],
-			[ 9.0, 0.763]])
-
-    
-    return WindTurbine(name=name,
-                                diameter=D,
-                                hub_height=h,
-                                powerCtFunction=PowerCtTabular(power_curve[:, 0],
-                                                                power_curve[:, 1], 
-                                                                'w',ct_curve[:, 1],
-                                                                method='linear'))
+        [ 0.1, 0.100],
+        [ 4.5, 0.928],
+        [ 5.0, 0.892],
+        [ 5.5, 0.861],
+        [ 6.0, 0.835],
+        [ 6.5, 0.812],
+        [ 7.0, 0.792],
+        [ 7.5, 0.776],
+        [ 8.0, 0.7702530978349217],
+        [ 8.5, 0.762],
+        [ 9.0, 0.763]])
     
+    powerct = PowerCtTabular(power_curve[:, 0], power_curve[:, 1], 'w',ct_curve[:, 1], method='linear')
+
+    return WindTurbine(name=name, diameter=D, hub_height=h, powerCtFunction=powerct)
 
-windTurbines = py_wake_Initial_Cong(D, 'NREL_5MW', h, U_ref)
+windTurbines = py_wake_Initial_Conf(D, 'NREL_5MW', h)
 grid = XYGrid(x=np.arange(0, 10.01, 0.1)*D, y=np.arange(0, 10.01, 0.1)*D)
 
-def run(direction=0, initial_position=initial_position, U_ref=U_ref):
+def run(direction=0, initial_position=initial_position, ws=ws):
     initial_position = np.array(initial_position);
     p_wd = [0] * 360
-    #p_wd[direction * n // 360] = 1
-    p_wd[direction] = 1
-    site = UniformSite(p_wd=p_wd,
-                            ws=U_ref,
-                            initial_position=initial_position*D)
+    p_wd[0] = p_wd[225] = p_wd[270] = p_wd[315] = 1
+    site = UniformSite(p_wd=p_wd, ws=ws, initial_position=initial_position*D)
     #ds = xr.Dataset(
     #    data_vars={'P': ('wd', [1, 1, 1, 1])},
     #    coords={'wd': [0, 90, 180, 270]})
     #ds['TI'] = 0.1
-    #site = XRSite(ds, interp_method='nearest', initial_position=initial_position*D, default_ws=np.atleast_1d(U_ref))
+    #site = XRSite(ds, interp_method='nearest', initial_position=initial_position*D, default_ws=np.atleast_1d(ws))
 
-    wt_x, wt_y = site.initial_position.T/D
+    wt_x, wt_y = site.initial_position.T
     wfm = PropagateDownwind(site, windTurbines, wake_deficitModel=TurboGaussianDeficit())
-    xa = wfm(x=wt_x*D, y=wt_y*D, wd=direction, yaw=0).flow_map(grid)
+    xa = wfm(x=wt_x, y=wt_y, wd=direction, yaw=0).flow_map(grid)
     ws = xa.WS_eff
 
-    aep = wfm(x=wt_x*D, y=wt_y*D).aep()
+    aep = wfm(x=wt_x, y=wt_y).aep()
 
-    return ws[:,:,0,0].values[:,:,0].tolist(), [sum(aep.values[i,:,0]) for i in aep.wt.values]
+    #return ws[:,:,0,0].values[:,:,0].tolist(), list(aep.values[:,direction,0])
+    return ws[:,:,0,0].values[:,:,0].tolist(), {dir: list(aep.values[:,dir,0]) for dir in (0, 225, 270, 315)}