def main(npoints, nprocesses):
# Define and create signal
start = timeit.default_timer()
mu = 100
freq = [int(npoints * f) for f in [0.005, 0.02, 0.05, 0.2]]
ampl = [1, 2, 4, 8]
time = 3600
seed = npoints * 10
signal = oe.DataFactory.rand(npoints, mu, freq, ampl, time, seed)
# Read some Signal infor
pmin = signal.amv
pmax = max(signal.vals)
peakcut = (pmax - pmin) * 0.4 + pmin
storagepower = pmax - peakcut
end = timeit.default_timer() - start
print('Preprocessing... {} seconds'.format(end))
# Define, create objective and storage
objective = oe.Objective('power', peakcut)
storage = oe.Storage(storagepower, 0.95, 1e6)
name = 'single{}'.format(npoints)
# Start calculation
start = timeit.default_timer()
dia = oe.HybridDia(signal,
storage,
objective,
name=name,
nprocesses=nprocesses)
end = timeit.default_timer() - start
print('Single Calculation ... {} seconds'.format(end))
# Save
start = timeit.default_timer()
dia.save()
end = timeit.default_timer() - start
print('Saving... {} seconds'.format(end))
def main(npoints, nprocesses):
mu = 100
freq = [int(npoints * f) for f in [0.005, 0.02, 0.05, 0.2]]
ampl = [1, 2, 4, 8]
time = 3600
seed = npoints
signal = oe.DataFactory.rand(npoints, mu, freq, ampl, time, seed)
pmin = signal.amv
pmax = max(signal.vals)
peakcut = (pmax - pmin) * 0.3 + pmin
storagepower = pmax - peakcut
objective = oe.Objective('power', peakcut)
storage = oe.Storage(storagepower, 0.95, 1e5)
name = 'all{}'.format(npoints)
start = timeit.default_timer()
dia = oe.HybridDia(signal,
storage,
objective,
name=name,
nprocesses=nprocesses)
end = timeit.default_timer() - start
print('Single Calc went for {} seconds'.format(end))
start = timeit.default_timer()
dia.calculate_curves()
end = timeit.default_timer() - start
print('Curve Calculation went for {} seconds'.format(end))
start = timeit.default_timer()
dia.calculate_area((11, 11))
end = timeit.default_timer() - start
print('Area Calculation went for {} seconds'.format(end))
print('Calculated points: {}'.format(len(dia.area.keys())))
dia.save()
import optess as oe
sig = oe.DataFactory.rand(npoints=128, seed=123)
obj = oe.Objective('power', 12)
stor = oe.Storage(max(sig.vals) - 12, 0.95, 1e6)
hyb = oe.HybridDia(sig, stor, obj)
hyb.compute_serial(cuts=[0.4, 0.6], curves=2)
hyb.pplot()
dummybreakpoint = True
data = np.genfromtxt('stahlwerkmod.csv', delimiter=';')
power = data[:, 4]
time = (np.arange(len(power)) * 6 + 6) / 3600
resampled_power, resampled_time = resample(power,
t=time,
num=int(
np.floor(len(time) / 10 / 15)))
signal = oe.Signal(time, power)
resampled_signal = oe.Signal(resampled_time, resampled_power)
peakcut = 1050
storpower = max(resampled_signal.vals) - peakcut
objective = oe.Objective('power', peakcut)
storage = oe.Storage(storpower, 0.95, 1e-3)
# ax = plt.figure().add_subplot(1, 1, 1)
# signal.pplot(ax=ax)
# resampled_signal.pplot(ax=ax)
print('Initializing HybridDia Object...')
start = timeit.default_timer()
hybdia = oe.HybridDia(resampled_signal,
storage,
objective,
name='Stahlwerk Unna')
end = timeit.default_timer() - start
print('Initialized... Time: {} seconds'.format(end))
#!/usr/bin/env python3
import optess as oe
sig = oe.DataFactory.distorted_sin(npoints=100, mu=0, seed=30349)
obj = oe.Objective('exact', 0)
stor = oe.Storage(max(abs(sig.vals)), 0.95, 500)
hyb = oe.HybridDia(sig, stor, obj)
hyb.compute_parallel(cuts=[0.25, 0.5, 0.75], curves=2, workers=4)
hyb.pplot()
dummybreakpoint = True
#!/usr/bin/env python3
"""
Loads a predefined factory setup, feeds optimization class and prints some
outputs.
"""
import optess as oe
signal = oe.DataFactory.rand(200,
mu=1,
freq=(6, 10),
amp=(1, 3),
time=100,
seed=200)
signal.pplot()
objective = oe.Objective('energy', 190)
power = 1.2
storage = oe.Storage(power, 0.95, 300)
opt = oe.OptimizeSingleESS(signal, storage, objective)
opt.solve_pyomo_model()
energy = opt.results.energycapacity
print('Single: power = {}, energy = {}'.format(power, energy))
base = oe.Storage(0.5 * power, 0.95, 1e50)
peak = oe.Storage(0.5 * power, 0.95, 1e50)
opthyb = oe.OptimizeHybridESS(signal, base, peak, objective)
opthyb.solve_pyomo_model()
baseenergy = opthyb.results.baseenergycapacity
peakenergy = opthyb.results.peakenergycapacity
print('Hybrid: baseenergy = {}, peakenergy = {}'.format(
baseenergy, peakenergy))
#!/usr/bin/env python3
import os
import optess as oe
# sig = oe.DataFactory.freq(128, time=5, seed=1234)
sig = oe.DataFactory.freq(256, mu=0.5, time=20, seed=314159)
# sdia = oe.SingleDia(sig, rel_obj_fronts=[0.8], resolution=4)
# sdia.compute_parallel()
objval = 11.578
obj = oe.Objective('energy', objval)
storval = 2.25
stor = oe.Storage(storval, 0.95, 50)
if os.path.isfile('medenergy.hyb'):
hyb = oe.HybridDia(sig, stor, obj, name='medenergy')
hyb.compute_parallel(cuts=[0.2, 0.5, 0.8], curves=1)
hyb.save('medenergy.hyb')
else:
hyb = oe.HybridDia.load('medenergy.hyb')
overmixed = oe.OverdimDia(sig, stor, hyb.inter[0.5], obj, name='medenergy')
overmixed.build_mesh_arrays()
overmixed.compute_parallel()
overdim = oe.overdimdia.OverdimDiaDim(sig,
stor,
hyb.inter[0.5],
obj,
