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FLORISvsSOWFA.py
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FLORISvsSOWFA.py
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# This example script compares FLORIS predictions with steady-state SOWFA data as obtained
# throught the simulations described in:
#
import numpy as np
import matplotlib as mpl
from matplotlib import pyplot as plt
from scipy.io import loadmat
import pickle
from Parameters import FLORISParameters
from Circle_assembly import floris_assembly_opt_AEP
# Load steady-state power data from SOWFA
ICOWESdata = loadmat('YawPosResults.mat')
# visualization: define resolution
resolution = 75
# Define turbine characteristics
rotorDiameter = 126.4
rotorArea = np.pi*rotorDiameter*rotorDiameter/4.0
axialInduction = 1.0/3.0 # used only for initialization
generator_efficiency = 0.944
hub_height = 90.0
NREL5MWCPCT = pickle.load(open('NREL5MWCPCT.p'))
datasize = NREL5MWCPCT.CP.size
turbineXinit = np.array([1118.1, 1881.9])
turbineYinit = np.array([1279.5, 1720.5])
myFloris = floris_assembly_opt_AEP(nTurbines=2, nDirections=1, optimize_yaw=False,
optimize_position=False,
datasize=datasize, nSamples = resolution*resolution)
# use default FLORIS parameters
myFloris.parameters = FLORISParameters()
# load turbine properties into FLORIS
myFloris.curve_wind_speed = NREL5MWCPCT.wind_speed
myFloris.curve_CP = NREL5MWCPCT.CP
myFloris.curve_CT = NREL5MWCPCT.CT
myFloris.axialInduction = np.array([axialInduction, axialInduction])
myFloris.rotorDiameter = np.array([rotorDiameter, rotorDiameter])
myFloris.rotorArea = np.array([rotorArea, rotorArea])
myFloris.hubHeight = np.array([hub_height, hub_height])
myFloris.generator_efficiency = np.array([generator_efficiency, generator_efficiency])
myFloris.turbineX = turbineXinit
myFloris.turbineY = turbineYinit
# Define site measurements
windDirection = 30.
myFloris.windrose_directions = np.array([windDirection])
wind_speed = 8.1 # m/s
myFloris.windrose_speeds = wind_speed
myFloris.air_density = 1.1716
myFloris.initVelocitiesTurbines = np.ones_like(myFloris.windrose_directions)*wind_speed
# visualization:
# generate points downstream slice
y_cut = np.linspace(-rotorDiameter,rotorDiameter,resolution)
z_cut = np.linspace(-hub_height,rotorDiameter,resolution)
yy, zz = np.meshgrid(y_cut, z_cut)
xx = np.ones(yy.shape) * 3.5*rotorDiameter
position = np.array([xx.flatten(),yy.flatten(),zz.flatten()])
rotationMatrix = np.array([(np.cos(windDirection*np.pi/180.), -np.sin(windDirection*np.pi/180.), 0.),
(np.sin(windDirection*np.pi/180.), np.cos(windDirection*np.pi/180.),0.),
(0., 0., 1.)])
positionF = np.dot(rotationMatrix, position) + np.dot(np.array([(myFloris.turbineX[0],myFloris.turbineY[0], hub_height)]).transpose(),np.ones((1,np.size(position,1))))
# generate points hub-height
x = np.linspace(750,2400,resolution)
y = np.linspace(750,2400,resolution)
xx, yy = np.meshgrid(x, y)
ws_positionX = xx.flatten()
ws_positionY = yy.flatten()
ws_positionZ = np.ones(ws_positionX.shape)*hub_height
# SWEEP TURBINE YAW
FLORISpower = list()
yawrange = ICOWESdata['yaw'][0]
velocities = list()
velocities_cut = list()
for yaw1 in yawrange:
myFloris.yaw = np.array([yaw1, 0.0])
# Call FLORIS horizontal slice
myFloris.ws_positionX = np.copy(ws_positionX)
myFloris.ws_positionY = np.copy(ws_positionY)
myFloris.ws_positionZ = np.copy(ws_positionZ)
myFloris.run()
FLORISpower.append(myFloris.floris_power_0.wt_power)
velocities.append(np.copy(myFloris.ws_array_0))
# Call FLORIS cut-through slice
myFloris.ws_positionX = np.copy(positionF[0])
myFloris.ws_positionY = np.copy(positionF[1])
myFloris.ws_positionZ = np.copy(positionF[2])
myFloris.run()
velocities_cut.append(np.copy(myFloris.ws_array_0))
# plot slices
velocities = np.array(velocities)
vmin = np.min(velocities)
vmax = np.max(velocities)
velocities_cut = np.array(velocities_cut)
fig, axes = plt.subplots(ncols=int(np.ceil(len(yawrange)/2.)), nrows=4, figsize=(23,12))
fig.suptitle("FLORIS flow-field prediction at hub-height and wake cut-through at 3.5D, for yaw sweep")
axes1 = list(axes[0])+list(axes[2])
axes2 = list(axes[1])+list(axes[3])
for i in range(len(yawrange)):
vel = velocities[i].flatten()
vel = vel.reshape(len(y), len(x))
ax1 = axes1[i]
im = ax1.pcolormesh(x, y, vel, cmap='coolwarm', vmin=vmin, vmax=vmax)
ax1.set_aspect('equal')
ax1.set_xticks(np.arange(800,2800,400))
ax1.set_yticks(np.arange(800,2800,400))
ax1.autoscale(tight=True)
ax1.set_title('front turbine yawed %d deg' % yawrange[i])
vel = velocities_cut[i].flatten()
vel = vel.reshape(len(z_cut), len(y_cut))
ax2 = axes2[i]
im = ax2.pcolormesh(y_cut, z_cut, vel, cmap='coolwarm', vmin=vmin, vmax=vmax)
ax2.set_aspect('equal')
ax2.autoscale(tight=True)
ax2.invert_xaxis()
cbar = plt.colorbar(im, orientation = 'horizontal', ticks=[vmin,(vmin+vmax)/2,vmax])
cbar.set_label('wind speed (m/s)')
axes1[-1].axis('off')
axes2[-1].axis('off')
mpl.rcParams.update({'font.size': 8})
plt.tight_layout()
fig.subplots_adjust(top=0.95)
FLORISpower = np.array(FLORISpower)
SOWFApower = np.array([ICOWESdata['yawPowerT1'][0],ICOWESdata['yawPowerT2'][0]]).transpose()/1000.
figPower, axesPower = plt.subplots(ncols = 2, sharey = True)
axesPower[0].plot(yawrange.transpose(), FLORISpower[:,0], 'r-', yawrange.transpose(), SOWFApower[:,0], 'ro')
axesPower[0].plot(yawrange.transpose(), FLORISpower[:,1], 'b-', yawrange.transpose(), SOWFApower[:,1], 'bo')
axesPower[0].plot(yawrange.transpose(), FLORISpower[:,0]+FLORISpower[:,1], 'k-', yawrange.transpose(), SOWFApower[:,0]+SOWFApower[:,1], 'ko')
axesPower[0].set_xlabel('yaw front turbine 1 (deg)')
axesPower[0].set_ylabel('power (kW)')
axesPower[0].legend(['front turbine FLORIS', 'front turbine SOWFA', 'back turbine FLORIS', 'back turbine SOWFA', 'total FLORIS', 'total SOWFA'])
# SWEEP TURBINE POSITIONS
posrange = ICOWESdata['pos'][0]
myFloris.yaw = np.array([0.0, 0.0])
FLORISpower = list()
velocities = list()
velocities_cut = list()
for pos2 in posrange:
# Define turbine locations and orientation
effUdXY = 0.523599
XY = np.array([turbineXinit, turbineYinit]) + np.dot(np.array([[np.cos(effUdXY),-np.sin(effUdXY)], [np.sin(effUdXY),np.cos(effUdXY)]]), np.array([[0., 0], [0,pos2]]))
myFloris.turbineX = XY[0,:]
myFloris.turbineY = XY[1,:]
# Call FLORIS horizontal slice
myFloris.ws_positionX = np.copy(ws_positionX)
myFloris.ws_positionY = np.copy(ws_positionY)
myFloris.ws_positionZ = np.copy(ws_positionZ)
myFloris.run()
FLORISpower.append(myFloris.floris_power_0.wt_power)
velocities.append(np.copy(myFloris.ws_array_0))
# Call FLORIS cut-through slice
myFloris.ws_positionX = np.copy(positionF[0])
myFloris.ws_positionY = np.copy(positionF[1])
myFloris.ws_positionZ = np.copy(positionF[2])
myFloris.run()
velocities_cut.append(np.copy(myFloris.ws_array_0))
# plot powers
FLORISpower = np.array(FLORISpower)
SOWFApower = np.array([ICOWESdata['posPowerT1'][0],ICOWESdata['posPowerT2'][0]]).transpose()/1000.
axesPower[1].plot(posrange, FLORISpower[:,0], 'r-', posrange, SOWFApower[:,0], 'ro')
axesPower[1].plot(posrange, FLORISpower[:,1], 'b-', posrange, SOWFApower[:,1], 'bo')
axesPower[1].plot(posrange, FLORISpower[:,0]+FLORISpower[:,1], 'k-', posrange, SOWFApower[:,0]+SOWFApower[:,1], 'ko')
axesPower[1].set_xlabel('back turbine displacement (m)')
axesPower[1].set_ylabel('power (kW)')
# plot slices
velocities = np.array(velocities)
vmin = np.min(velocities)
vmax = np.max(velocities)
velocities_cut = np.array(velocities_cut)
fig, axes = plt.subplots(ncols=int(np.ceil(len(posrange)/2.)), nrows=4, figsize=(23,12))
fig.suptitle("FLORIS flow-field prediction at hub-height and wake cut-through at 3.5D, for yaw sweep")
axes1 = list(axes[0])+list(axes[2])
axes2 = list(axes[1])+list(axes[3])
for i in range(len(posrange)):
vel = velocities[i].flatten()
vel = vel.reshape(len(y), len(x))
ax1 = axes1[i]
im = ax1.pcolormesh(x, y, vel, cmap='coolwarm', vmin=vmin, vmax=vmax)
ax1.set_aspect('equal')
ax1.autoscale(tight=True)
ax1.set_xticks(np.arange(800,2800,400))
ax1.set_yticks(np.arange(800,2800,400))
ax1.set_title('back turbine moved %d m' % posrange[i])
vel = velocities_cut[i].flatten()
vel = vel.reshape(len(z_cut), len(y_cut))
ax2 = axes2[i]
im = ax2.pcolormesh(y_cut, z_cut, vel, cmap='coolwarm', vmin=vmin, vmax=vmax)
ax2.set_aspect('equal')
ax2.autoscale(tight=True)
ax2.invert_xaxis()
cbar = plt.colorbar(im, orientation = 'horizontal', ticks=[vmin,(vmin+vmax)/2,vmax])
cbar.set_label('wind speed (m/s)')
axes1[-1].axis('off')
axes2[-1].axis('off')
mpl.rcParams.update({'font.size': 8})
plt.tight_layout()
fig.subplots_adjust(top=0.95)
if __name__ == "__main__":
plt.show()
else:
plt.show(block=False)