def ainsliefull_windrose(layout_file, windrose_file):
layout_x, layout_y = read_layout(layout_file)
wind_direction, wind_speed, wind_frequency = read_windrose(windrose_file)
efficiency = []
profit = []
summation = 0.0
nt = len(layout_y)
P = []
U = []
efficiency_proportion = []
for wind in range(len(wind_direction)):
U0 = wind_speed[wind] # Free stream wind speed
angle = wind_direction[wind]
# angle2 = - 270.0 - angle # To read windroses where N is 0 and E is 90
U.append(ainsliefull_1angle(layout_x, layout_y, U0, angle, rotor_radius=40.0, TI=0.08))
P.append([power(u) for u in U[-1]])
# Farm efficiency
profit.append(sum(P[-1]))
efficiency.append(profit[-1] * 100.0 / (float(nt) * max(P[-1]))) # same as using U0
efficiency_proportion.append(efficiency[-1] * wind_frequency[wind] / 100.0)
summation += efficiency_proportion[wind]
# print profit
# print efficiency
# print efficiency_proportion
# print U
# print P
return profit
def ainsliefull_windrose(layout_file, windrose_file):
layout_x, layout_y = read_layout(layout_file)
wind_direction, wind_speed, wind_frequency = read_windrose(windrose_file)
nt = len(layout_y)
U = Parallel(n_jobs=-1)(delayed(ainsliefull_1angle)(layout_x,
layout_y,
wind_speed[i],
wind_direction[i],
rotor_radius=40.0,
TI=0.08)
for i in range(len(wind_direction)))
P = [[power(u) for u in U[i]] for i in range(len(wind_direction))]
profit = [sum(powers) for powers in P]
efficiency = [
profit[ii] * 100.0 / (float(nt) * max(P[ii]))
for ii in range(len(wind_direction))
] # same as using U0
efficiency_proportion = [
efficiency[i] * wind_frequency[i] / 100.0
for i in range(len(wind_direction))
]
summation = sum(efficiency_proportion)
# print profit
# print efficiency
# print efficiency_proportion
# print U
# print P
return profit
def ainsliefull_windrose(layout_file, windrose_file):
layout_x, layout_y = read_layout(layout_file)
wind_direction, wind_speed, wind_frequency = read_windrose(windrose_file)
efficiency = []
profit = []
summation = 0.0
nt = len(layout_y)
P = []
U = []
efficiency_proportion = []
for wind in range(len(wind_direction)):
U0 = wind_speed[wind] # Free stream wind speed
angle = wind_direction[wind]
# angle2 = - 270.0 - angle # To read windroses where N is 0 and E is 90
U.append(ainsliefull_1angle(layout_x, layout_y, U0, angle, rotor_radius=40.0, TI=0.08))
P.append([power(u) for u in U[-1]])
# Farm efficiency
profit.append(sum(P[-1]))
efficiency.append(profit[-1] * 100.0 / (float(nt) * max(P[-1]))) # same as using U0
efficiency_proportion.append(efficiency[-1] * wind_frequency[wind] / 100.0)
summation += efficiency_proportion[wind]
# print profit
# print efficiency
# print efficiency_proportion
# print U
# print P
return profit
def solve_nonlinear(self, params, unknowns, resids):
layout_x = params['layout_x']
layout_y = params['layout_y']
wind_direction = params['windrose_direction']
wind_speed = params['windrose_speed']
wind_frequency = params['windrose_probability']
efficiency = []
profit = []
summation = 0.0
nt = len(layout_y)
P = []
U = []
efficiency_proportion = []
for wind in range(len(wind_direction)):
U0 = wind_speed[wind] # Free stream wind speed
angle = wind_direction[wind]
# angle2 = - 270.0 - angle # To read windroses where N is 0 and E is 90
U.append(
jensen_1angle(layout_x,
layout_y,
U0,
angle,
rotor_radius=40.0,
k=0.04))
P.append([power(u) for u in U[-1]])
# Farm efficiency
profit.append(sum(P[-1]))
efficiency.append(profit[-1] * 100.0 /
(float(nt) * max(P[-1]))) # same as using U0
efficiency_proportion.append(efficiency[-1] *
wind_frequency[wind] / 100.0)
summation += efficiency_proportion[wind]
# print profit
# print efficiency
# print efficiency_proportion
# print U
# print P
unknowns['array_efficiency'] = summation
def ainsliefull_windrose(layout_file, windrose_file):
layout_x, layout_y = read_layout(layout_file)
wind_direction, wind_speed, wind_frequency = read_windrose(windrose_file)
nt = len(layout_y)
U = Parallel(n_jobs=-1)(delayed(ainsliefull_1angle)(layout_x, layout_y, wind_speed[i], wind_direction[i], rotor_radius=40.0, TI=0.08) for i in range(len(wind_direction)))
P = [[power(u) for u in U[i]] for i in range(len(wind_direction))]
profit = [sum(powers) for powers in P]
efficiency = [profit[ii] * 100.0 / (float(nt) * max(P[ii])) for ii in range(len(wind_direction))] # same as using U0
efficiency_proportion = [efficiency[i] * wind_frequency[i] / 100.0 for i in range(len(wind_direction))]
summation = sum(efficiency_proportion)
# print profit
# print efficiency
# print efficiency_proportion
# print U
# print P
return profit
def solve_nonlinear(self, params, unknowns, resids):
layout_x = params['layout_x']
layout_y = params['layout_y']
wind_direction = params['windrose_direction']
wind_speed = params['windrose_speed']
wind_frequency = params['windrose_probability']
efficiency = []
profit = []
summation = 0.0
nt = len(layout_y)
P = []
U = []
efficiency_proportion = []
for wind in range(len(wind_direction)):
U0 = wind_speed[wind] # Free stream wind speed
angle = wind_direction[wind]
# angle2 = - 270.0 - angle # To read windroses where N is 0 and E is 90
U.append(jensen_1angle(layout_x, layout_y, U0, angle, rotor_radius=40.0, k=0.04))
P.append([power(u) for u in U[-1]])
# Farm efficiency
profit.append(sum(P[-1]))
efficiency.append(profit[-1] * 100.0 / (float(nt) * max(P[-1]))) # same as using U0
efficiency_proportion.append(efficiency[-1] * wind_frequency[wind] / 100.0)
summation += efficiency_proportion[wind]
# print profit
# print efficiency
# print efficiency_proportion
# print U
# print P
unknowns['array_efficiency'] = summation