def Ainslie(a, Nt, rad):
import wake
from eddy_viscosity import ainslie
from math import sqrt, log, cos, sin
from numpy import deg2rad
from power_curve5MW import power5MW_kW as power # Power curve 5 MW NREL
windrose = open('horns_rev_windrose.dat', 'r')
def determine_front(wind_angle, x_t1, y_t1, x_t2, y_t2):
wind_angle = deg2rad(wind_angle)
b = (x_t2 - x_t1) * cos(wind_angle) + (y_t2 - y_t1) * sin(wind_angle)
if b > 0.0:
return True, b
else:
return False, 0.0
nt = Nt # Number of turbines
D = 2.0 * rad # Diameter
layout_x = [0.0 for x in range(nt)]
layout_y = [0.0 for x in range(nt)]
for x in range(nt):
layout_x[x] = float(a[x][0] / D)
layout_y[x] = float(a[x][1] / D)
windrose_angle = []
windrose_speed = []
windrose_frequency = []
for line in windrose:
columns = line.split()
windrose_angle.append(float(columns[0]))
windrose_speed.append(float(columns[1]))
windrose_frequency.append(float(columns[2]))
windrose.close()
summation = 0.0
## Power curve 2 MW Siemens
# def power(U0):
# if U0 < 4.0:
# return 0.0
# elif U0 >= 4.0:
# return 19.7907842158 * U0 ** 2.0 - 74.9080669331 * U0 + 37.257967033 # From 4 to 11 m/s
# for wind in range(0, len(windrose_speed)):
for wind in range(0, 1):
U1 = windrose_speed[wind] # Free stream wind speed
U0 = U1 * (90.0 / 10.0) ** 0.11 # Power or log law for wind shear profile
# U0 = U1 * log(70.0 / 0.005) / log(10.0 / 0.005)
angle = windrose_angle[wind]
angle3 = angle + 180.0
wake_deficit_matrix = [[0.0 for x in range(nt)] for x in range(nt)]
for turbine in range(0, nt):
parallel_distance = [0.0 for x in range(0, nt)]
perpendicular_distance = [0.0 for x in range(0, nt)]
flag = [False for x in range(nt)]
for i in range(nt):
flag[i], parallel_distance[i] = determine_front(angle3, layout_x[turbine], layout_y[turbine], layout_x[i], layout_y[i])
perpendicular_distance[i] = wake.crosswind_distance(deg2rad(angle3), layout_x[turbine], layout_y[turbine], layout_x[i], layout_y[i])
# Matrix with effect of each turbine <i = turbine> on every other turbine <j> of the farm
for j in range(nt):
if flag[j] is True:
if perpendicular_distance[j] <= 2.5:
wake_deficit_matrix[turbine][j] = ainslie(0.46, U0, parallel_distance[j], perpendicular_distance[j])
else:
wake_deficit_matrix[turbine][j] = 0.0
elif flag[j] is False:
wake_deficit_matrix[turbine][j] = 0.0
total_deficit = [0.0 for x in range(nt)]
total_speed = [0.0 for x in range(nt)]
for j in range(nt):
for i in range(nt):
total_deficit[j] += wake_deficit_matrix[i][j] ** 2.0
total_deficit[j] = sqrt(total_deficit[j])
total_speed[j] = U0 * (1.0 - total_deficit[j])
# Farm efficiency
profit = 0.0
efficiency_proportion = [0.0 for x in range(0, len(windrose_frequency))]
efficiency = 0.0
for l in range(nt):
profit += power(total_speed[l])
efficiency = profit * 100.0 / (nt * power(U0))
efficiency_proportion[wind] = efficiency * windrose_frequency[wind] / 100.0
summation += efficiency_proportion[wind]
return summation
def Ainslie(a, Nt, rad):
import wake
from eddy_viscosity import ainslie
from math import sqrt, log, cos, sin
from numpy import deg2rad
from power_curve5MW import power5MW_kW as power # Power curve 5 MW NREL
windrose = open('horns_rev_windrose.dat', 'r')
def determine_front(wind_angle, x_t1, y_t1, x_t2, y_t2):
wind_angle = deg2rad(wind_angle)
b = (x_t2 - x_t1) * cos(wind_angle) + (y_t2 - y_t1) * sin(wind_angle)
if b > 0.0:
return True, b
else:
return False, 0.0
nt = Nt # Number of turbines
D = 2.0 * rad # Diameter
layout_x = [0.0 for x in range(nt)]
layout_y = [0.0 for x in range(nt)]
for x in range(nt):
layout_x[x] = float(a[x][0] / D)
layout_y[x] = float(a[x][1] / D)
windrose_angle = []
windrose_speed = []
windrose_frequency = []
for line in windrose:
columns = line.split()
windrose_angle.append(float(columns[0]))
windrose_speed.append(float(columns[1]))
windrose_frequency.append(float(columns[2]))
windrose.close()
summation = 0.0
## Power curve 2 MW Siemens
# def power(U0):
# if U0 < 4.0:
# return 0.0
# elif U0 >= 4.0:
# return 19.7907842158 * U0 ** 2.0 - 74.9080669331 * U0 + 37.257967033 # From 4 to 11 m/s
# for wind in range(0, len(windrose_speed)):
for wind in range(0, 1):
U1 = windrose_speed[wind] # Free stream wind speed
U0 = U1 * (90.0 /
10.0)**0.11 # Power or log law for wind shear profile
# U0 = U1 * log(70.0 / 0.005) / log(10.0 / 0.005)
angle = windrose_angle[wind]
angle3 = angle + 180.0
wake_deficit_matrix = [[0.0 for x in range(nt)] for x in range(nt)]
for turbine in range(0, nt):
parallel_distance = [0.0 for x in range(0, nt)]
perpendicular_distance = [0.0 for x in range(0, nt)]
flag = [False for x in range(nt)]
for i in range(nt):
flag[i], parallel_distance[i] = determine_front(
angle3, layout_x[turbine], layout_y[turbine], layout_x[i],
layout_y[i])
perpendicular_distance[i] = wake.crosswind_distance(
deg2rad(angle3), layout_x[turbine], layout_y[turbine],
layout_x[i], layout_y[i])
# Matrix with effect of each turbine <i = turbine> on every other turbine <j> of the farm
for j in range(nt):
if flag[j] is True:
if perpendicular_distance[j] <= 2.5:
wake_deficit_matrix[turbine][j] = ainslie(
0.46, U0, parallel_distance[j],
perpendicular_distance[j])
else:
wake_deficit_matrix[turbine][j] = 0.0
elif flag[j] is False:
wake_deficit_matrix[turbine][j] = 0.0
total_deficit = [0.0 for x in range(nt)]
total_speed = [0.0 for x in range(nt)]
for j in range(nt):
for i in range(nt):
total_deficit[j] += wake_deficit_matrix[i][j]**2.0
total_deficit[j] = sqrt(total_deficit[j])
total_speed[j] = U0 * (1.0 - total_deficit[j])
# Farm efficiency
profit = 0.0
efficiency_proportion = [
0.0 for x in range(0, len(windrose_frequency))
]
efficiency = 0.0
for l in range(nt):
profit += power(total_speed[l])
efficiency = profit * 100.0 / (nt * power(U0))
efficiency_proportion[
wind] = efficiency * windrose_frequency[wind] / 100.0
summation += efficiency_proportion[wind]
return summation
def Jensen(a, Nt, rad):
from math import sqrt, log
import wake
from power_curve5MW import power5MW_kW as power # Power curve 5 MW NREL
windrose = open('horns_rev_windrose.dat', 'r')
nt = Nt
layout_x = [0.0 for x in range(nt)]
layout_y = [0.0 for x in range(nt)]
for x in range(nt):
layout_x[x] = float(a[x][0])
layout_y[x] = float(a[x][1])
windrose_angle = []
windrose_speed = []
windrose_frequency = []
for line in windrose:
columns = line.split()
windrose_angle.append(float(columns[0]))
windrose_speed.append(float(columns[1]))
windrose_frequency.append(float(columns[2]))
windrose.close()
summation = 0.0
## Power curve 2 MW Siemens.
# def power(U0):
# if U0 < 4.0:
# return 0.0
# elif U0 >= 4.0:
# return 19.7907842158 * U0 ** 2.0 - 74.9080669331 * U0 + 37.257967033 # From 4 to 11 m/s
# for wind in range(0, len(windrose_speed)):
for wind in range(0, 1):
U1 = windrose_speed[wind] # Free stream wind speed
U0 = U1 * (90.0 / 10.0) ** 0.11 # Power or log law for wind shear profile
# U0 = U1 * log(70.0 / 0.005) / log(10.0 / 0.005)
k = 0.04 # Decay constant
r0 = rad # Turbine rotor radius
angle = windrose_angle[wind]
angle3 = angle + 180.0
wake_deficit_matrix = [[0.0 for x in range(nt)] for x in range(nt)]
for turbine in range(nt):
flag = [False for x in range(nt)]
proportion = [0.0 for x in range(nt)]
for i in range(nt):
try:
proportion[i], flag[i] = wake.determine_if_in_wake(layout_x[turbine], layout_y[turbine], layout_x[i], layout_y[i], k, r0, angle3)
except TypeError:
print layout_x[turbine], layout_y[turbine], layout_x[i], layout_y[i], k, r0, angle3
# Matrix with effect of each turbine <i = turbine> on every other turbine <j> of the farm
for j in range(nt):
if turbine != j and flag[j] is True:
wake_deficit_matrix[turbine][j] = proportion[j] * wake.wake_deficit(0.46, k, wake.distance(layout_x[turbine], layout_y[turbine], layout_x[j], layout_y[j]), r0)
elif turbine == j:
wake_deficit_matrix[turbine][j] = 0.0
total_deficit = [0.0 for x in range(nt)]
total_speed = [0.0 for x in range(nt)]
for j in range(nt):
for i in range(nt):
total_deficit[j] += wake_deficit_matrix[i][j] ** 2.0
total_deficit[j] = sqrt(total_deficit[j])
total_speed[j] = U0 * (1.0 - total_deficit[j])
# Farm efficiency
profit = 0.0
efficiency_proportion = [0.0 for x in range(0, len(windrose_frequency))]
efficiency = 0.0
for l in range(nt):
profit += power(total_speed[l])
efficiency = profit * 100.0 / (float(nt) * power(U0))
efficiency_proportion[wind] = efficiency * windrose_frequency[wind] / 100.0
summation += efficiency_proportion[wind]
return summation # Farm efficiency
# if __name__ == '__main__':
# start_time = time.time()
# Jensen()
# print("--- %s seconds ---" % (time.time() - start_time))
def Jensen(a, Nt, rad):
from math import sqrt, log
import wake
from power_curve5MW import power5MW_kW as power # Power curve 5 MW NREL
windrose = open('horns_rev_windrose.dat', 'r')
nt = Nt
layout_x = [0.0 for x in range(nt)]
layout_y = [0.0 for x in range(nt)]
for x in range(nt):
layout_x[x] = float(a[x][0])
layout_y[x] = float(a[x][1])
windrose_angle = []
windrose_speed = []
windrose_frequency = []
for line in windrose:
columns = line.split()
windrose_angle.append(float(columns[0]))
windrose_speed.append(float(columns[1]))
windrose_frequency.append(float(columns[2]))
windrose.close()
summation = 0.0
## Power curve 2 MW Siemens.
# def power(U0):
# if U0 < 4.0:
# return 0.0
# elif U0 >= 4.0:
# return 19.7907842158 * U0 ** 2.0 - 74.9080669331 * U0 + 37.257967033 # From 4 to 11 m/s
# for wind in range(0, len(windrose_speed)):
for wind in range(0, 1):
U1 = windrose_speed[wind] # Free stream wind speed
U0 = U1 * (90.0 /
10.0)**0.11 # Power or log law for wind shear profile
# U0 = U1 * log(70.0 / 0.005) / log(10.0 / 0.005)
k = 0.04 # Decay constant
r0 = rad # Turbine rotor radius
angle = windrose_angle[wind]
angle3 = angle + 180.0
wake_deficit_matrix = [[0.0 for x in range(nt)] for x in range(nt)]
for turbine in range(nt):
flag = [False for x in range(nt)]
proportion = [0.0 for x in range(nt)]
for i in range(nt):
try:
proportion[i], flag[i] = wake.determine_if_in_wake(
layout_x[turbine], layout_y[turbine], layout_x[i],
layout_y[i], k, r0, angle3)
except TypeError:
print layout_x[turbine], layout_y[turbine], layout_x[
i], layout_y[i], k, r0, angle3
# Matrix with effect of each turbine <i = turbine> on every other turbine <j> of the farm
for j in range(nt):
if turbine != j and flag[j] is True:
wake_deficit_matrix[turbine][
j] = proportion[j] * wake.wake_deficit(
0.46, k,
wake.distance(layout_x[turbine], layout_y[turbine],
layout_x[j], layout_y[j]), r0)
elif turbine == j:
wake_deficit_matrix[turbine][j] = 0.0
total_deficit = [0.0 for x in range(nt)]
total_speed = [0.0 for x in range(nt)]
for j in range(nt):
for i in range(nt):
total_deficit[j] += wake_deficit_matrix[i][j]**2.0
total_deficit[j] = sqrt(total_deficit[j])
total_speed[j] = U0 * (1.0 - total_deficit[j])
# Farm efficiency
profit = 0.0
efficiency_proportion = [
0.0 for x in range(0, len(windrose_frequency))
]
efficiency = 0.0
for l in range(nt):
profit += power(total_speed[l])
efficiency = profit * 100.0 / (float(nt) * power(U0))
efficiency_proportion[
wind] = efficiency * windrose_frequency[wind] / 100.0
summation += efficiency_proportion[wind]
return summation # Farm efficiency
# if __name__ == '__main__':
# start_time = time.time()
# Jensen()
# print("--- %s seconds ---" % (time.time() - start_time))
