def eval(self, x):
"""
Evaluate the Ackley function at x
:param x: Data point
:type x: numpy.array
:return: Value at x
:rtype: float
"""
# For every circuit, run the time series
for numerical_island in self.numerical_input_islands:
# sample from the CDF give the vector x of values in [0, 1]
# c.sample_at(x)
monte_carlo_input = make_monte_carlo_input(numerical_island)
mc_time_series = monte_carlo_input.get_at(x)
Y, I, S = mc_time_series.get_at(t=0)
# run the sampled values
# res = self.power_flow.run_at(0, mc=True)
res = single_island_pf(circuit,
Vbus,
Sbus,
Ibus,
options=self.options,
logger=self.logger)
self.results.S_points[self.it,
numerical_island.original_bus_idx] = S
self.results.V_points[
self.it, numerical_island.original_bus_idx] = res.voltage[
numerical_island.original_bus_idx]
self.results.Sbr_points[
self.it, numerical_island.original_branch_idx] = res.If[
numerical_island.original_branch_idx]
self.results.loading_points[
self.it, numerical_island.original_branch_idx] = res.loading[
numerical_island.original_branch_idx]
self.it += 1
if self.callback is not None:
prog = self.it / self.max_eval * 100
self.callback(prog)
f = abs(self.results.V_points[self.it - 1, :].sum()) / self.dim
# print(prog, ' % \t', f)
return f
def run_multi_thread(self):
"""
Run the monte carlo simulation
@return:
"""
# print('LHS run')
self.__cancel__ = False
# initialize vars
batch_size = self.sampling_points
n = len(self.circuit.buses)
m = len(self.circuit.branches)
n_cores = multiprocessing.cpu_count()
self.progress_signal.emit(0.0)
self.progress_text.emit(
'Running Latin Hypercube Sampling in parallel using ' +
str(n_cores) + ' cores ...')
lhs_results = MonteCarloResults(n, m, batch_size)
avg_res = PowerFlowResults()
avg_res.initialize(n, m)
# compile
# print('Compiling...', end='')
numerical_circuit = self.circuit.compile()
numerical_islands = numerical_circuit.compute(
branch_tolerance_mode=self.options.branch_impedance_tolerance_mode)
lhs_results.bus_types = numerical_circuit.bus_types
max_iter = batch_size * len(numerical_islands)
Sbase = self.circuit.Sbase
it = 0
# For every circuit, run the time series
for numerical_island in numerical_islands:
# try:
# set the time series as sampled in the circuit
monte_carlo_input = make_monte_carlo_input(numerical_island)
mc_time_series = monte_carlo_input(batch_size,
use_latin_hypercube=True)
Vbus = numerical_island.Vbus
# short cut the indices
b_idx = numerical_island.original_bus_idx
br_idx = numerical_island.original_branch_idx
manager = multiprocessing.Manager()
return_dict = manager.dict()
t = 0
while t < batch_size and not self.__cancel__:
k = 0
jobs = list()
# launch only n_cores jobs at the time
while k < n_cores + 2 and (t + k) < batch_size:
# set the power values
Y, I, S = mc_time_series.get_at(t)
# run power flow at the circuit
p = multiprocessing.Process(
target=power_flow_worker,
args=(t, self.options, numerical_island, Vbus,
S / Sbase, I / Sbase, return_dict))
jobs.append(p)
p.start()
k += 1
t += 1
# wait for all jobs to complete
for proc in jobs:
proc.join()
progress = ((t + 1) / batch_size) * 100
self.progress_signal.emit(progress)
# collect results
self.progress_text.emit('Collecting results...')
for t in return_dict.keys():
# store circuit results at the time index 't'
res = return_dict[t]
lhs_results.S_points[
t, numerical_island.original_bus_idx] = res.Sbus
lhs_results.V_points[
t, numerical_island.original_bus_idx] = res.voltage
lhs_results.I_points[
t, numerical_island.original_branch_idx] = res.Ibranch
lhs_results.loading_points[
t, numerical_island.original_branch_idx] = res.loading
lhs_results.losses_points[
t, numerical_island.original_branch_idx] = res.losses
# except Exception as ex:
# print(c.name, ex)
if self.__cancel__:
break
# compile MC results
self.progress_text.emit('Compiling results...')
lhs_results.compile()
# compute the island branch results
island_avg_res = numerical_island.compute_branch_results(
lhs_results.voltage[b_idx])
# apply the island averaged results
avg_res.apply_from_island(island_avg_res,
b_idx=b_idx,
br_idx=br_idx)
# lhs_results the averaged branch magnitudes
lhs_results.sbranch = avg_res.Sbranch
lhs_results.losses = avg_res.losses
self.results = lhs_results
# send the finnish signal
self.progress_signal.emit(0.0)
self.progress_text.emit('Done!')
self.done_signal.emit()
return lhs_results
def run_single_thread(self):
"""
Run the monte carlo simulation
@return:
"""
# print('LHS run')
self.__cancel__ = False
# initialize the power flow
power_flow = PowerFlowMP(self.circuit, self.options)
# initialize the grid time series results
# we will append the island results with another function
self.circuit.time_series_results = TimeSeriesResults(0, 0, 0, 0, 0)
batch_size = self.sampling_points
n = len(self.circuit.buses)
m = len(self.circuit.branches)
self.progress_signal.emit(0.0)
self.progress_text.emit('Running Latin Hypercube Sampling...')
lhs_results = MonteCarloResults(n, m, batch_size)
avg_res = PowerFlowResults()
avg_res.initialize(n, m)
# compile the numerical circuit
numerical_circuit = self.circuit.compile()
numerical_input_islands = numerical_circuit.compute(
branch_tolerance_mode=self.options.branch_impedance_tolerance_mode)
max_iter = batch_size * len(numerical_input_islands)
Sbase = numerical_circuit.Sbase
it = 0
# For every circuit, run the time series
for numerical_island in numerical_input_islands:
# try:
# set the time series as sampled in the circuit
# build the inputs
monte_carlo_input = make_monte_carlo_input(numerical_island)
mc_time_series = monte_carlo_input(batch_size,
use_latin_hypercube=True)
Vbus = numerical_island.Vbus
# short cut the indices
b_idx = numerical_island.original_bus_idx
br_idx = numerical_island.original_branch_idx
# run the time series
for t in range(batch_size):
# set the power values from a Monte carlo point at 't'
Y, I, S = mc_time_series.get_at(t)
# Run the set monte carlo point at 't'
res = power_flow.run_pf(circuit=numerical_island,
Vbus=Vbus,
Sbus=S / Sbase,
Ibus=I / Sbase)
# Gather the results
lhs_results.S_points[
t, numerical_island.original_bus_idx] = res.Sbus
lhs_results.V_points[
t, numerical_island.original_bus_idx] = res.voltage
lhs_results.I_points[
t, numerical_island.original_branch_idx] = res.Ibranch
lhs_results.loading_points[
t, numerical_island.original_branch_idx] = res.loading
lhs_results.losses_points[
t, numerical_island.original_branch_idx] = res.losses
it += 1
self.progress_signal.emit(it / max_iter * 100)
if self.__cancel__:
break
if self.__cancel__:
break
# compile MC results
self.progress_text.emit('Compiling results...')
lhs_results.compile()
# compute the island branch results
island_avg_res = numerical_island.compute_branch_results(
lhs_results.voltage[b_idx])
# apply the island averaged results
avg_res.apply_from_island(island_avg_res,
b_idx=b_idx,
br_idx=br_idx)
# lhs_results the averaged branch magnitudes
lhs_results.sbranch = avg_res.Sbranch
lhs_results.bus_types = numerical_circuit.bus_types
# Ibranch = avg_res.Ibranch
# loading = avg_res.loading
# lhs_results.losses = avg_res.losses
# flow_direction = avg_res.flow_direction
# Sbus = avg_res.Sbus
self.results = lhs_results
# send the finnish signal
self.progress_signal.emit(0.0)
self.progress_text.emit('Done!')
self.done_signal.emit()
return lhs_results
def run_multi_thread(self):
"""
Run the monte carlo simulation
@return:
"""
# print('LHS run')
self.__cancel__ = False
# initialize vars
batch_size = self.sampling_points
n = len(self.circuit.buses)
m = self.circuit.get_branch_number()
n_cores = multiprocessing.cpu_count()
self.pool = multiprocessing.Pool()
self.progress_signal.emit(0.0)
self.progress_text.emit(
'Running Latin Hypercube Sampling in parallel using ' +
str(n_cores) + ' cores ...')
lhs_results = MonteCarloResults(n,
m,
batch_size,
name='Latin Hypercube')
avg_res = PowerFlowResults()
avg_res.initialize(n, m)
# compile the multi-circuit
numerical_circuit = self.circuit.compile_time_series()
# perform the topological computation
calc_inputs_dict = numerical_circuit.compute(
branch_tolerance_mode=self.options.branch_impedance_tolerance_mode,
ignore_single_node_islands=self.options.ignore_single_node_islands)
# for each partition of the profiles...
for t_key, calc_inputs in calc_inputs_dict.items():
# For every island, run the time series
for island_index, numerical_island in enumerate(calc_inputs):
lhs_results.bus_types = numerical_circuit.bus_types
monte_carlo_input = make_monte_carlo_input(numerical_island)
mc_time_series = monte_carlo_input(batch_size,
use_latin_hypercube=True)
Vbus = numerical_island.Vbus
branch_rates = numerical_island.branch_rates
# short cut the indices
b_idx = numerical_island.original_bus_idx
br_idx = numerical_island.original_branch_idx
# Start jobs
self.returned_results = list()
t = 0
while t < batch_size and not self.__cancel__:
Ysh, Ibus, Sbus = mc_time_series.get_at(t)
args = (t, self.options, numerical_island, Vbus, Sbus,
Ibus, branch_rates)
self.pool.apply_async(power_flow_worker_args, (args, ),
callback=self.update_progress_mt)
# wait for all jobs to complete
self.pool.close()
self.pool.join()
# collect results
self.progress_text.emit('Collecting results...')
for t, res in self.returned_results:
# store circuit results at the time index 't'
lhs_results.S_points[
t, numerical_island.original_bus_idx] = res.Sbus
lhs_results.V_points[
t, numerical_island.original_bus_idx] = res.voltage
lhs_results.Sbr_points[
t, numerical_island.original_branch_idx] = res.Sf
lhs_results.loading_points[
t, numerical_island.original_branch_idx] = res.loading
lhs_results.losses_points[
t, numerical_island.original_branch_idx] = res.losses
# compile MC results
self.progress_text.emit('Compiling results...')
lhs_results.compile()
# compute the island branch results
island_avg_res = numerical_island.compute_branch_results(
lhs_results.voltage[b_idx])
# apply the island averaged results
avg_res.apply_from_island(island_avg_res,
b_idx=b_idx,
br_idx=br_idx)
# lhs_results the averaged branch magnitudes
lhs_results.sbranch = avg_res.Sf
lhs_results.losses = avg_res.losses
self.results = lhs_results
# send the finnish signal
self.progress_signal.emit(0.0)
self.progress_text.emit('Done!')
self.done_signal.emit()
return lhs_results
def run_single_thread(self):
"""
Run the monte carlo simulation
@return:
"""
# print('LHS run')
self.__cancel__ = False
# initialize the grid time series results
# we will append the island results with another function
# batch_size = self.sampling_points
self.progress_signal.emit(0.0)
self.progress_text.emit('Running Latin Hypercube Sampling...')
# compile the multi-circuit
numerical_circuit = compile_time_circuit(
circuit=self.circuit,
apply_temperature=False,
branch_tolerance_mode=BranchImpedanceMode.Specified,
opf_results=self.opf_time_series_results)
# do the topological computation
calculation_inputs = numerical_circuit.split_into_islands(
ignore_single_node_islands=self.options.ignore_single_node_islands)
lhs_results = MonteCarloResults(
n=numerical_circuit.nbus,
m=numerical_circuit.nbr,
p=self.sampling_points,
bus_names=numerical_circuit.bus_names,
branch_names=numerical_circuit.branch_names,
bus_types=numerical_circuit.bus_types,
name='Latin Hypercube')
avg_res = PowerFlowResults(
n=numerical_circuit.nbus,
m=numerical_circuit.nbr,
n_tr=numerical_circuit.ntr,
n_hvdc=numerical_circuit.nhvdc,
bus_names=numerical_circuit.bus_names,
branch_names=numerical_circuit.branch_names,
transformer_names=numerical_circuit.tr_names,
hvdc_names=numerical_circuit.hvdc_names,
bus_types=numerical_circuit.bus_types)
it = 0
# For every island, run the time series
for island_index, numerical_island in enumerate(calculation_inputs):
# try:
# set the time series as sampled in the circuit
# build the inputs
monte_carlo_input = make_monte_carlo_input(numerical_island)
mc_time_series = monte_carlo_input(self.sampling_points,
use_latin_hypercube=True)
Vbus = numerical_island.Vbus[:, 0]
# short cut the indices
bus_idx = numerical_island.original_bus_idx
br_idx = numerical_island.original_branch_idx
# run the time series
for t in range(self.sampling_points):
# set the power values from a Monte carlo point at 't'
Y, I, S = mc_time_series.get_at(t)
# Run the set monte carlo point at 't'
res = single_island_pf(
circuit=numerical_island,
Vbus=Vbus,
Sbus=S,
Ibus=I,
branch_rates=numerical_island.branch_rates,
options=self.options,
logger=self.logger)
# Gather the results
lhs_results.S_points[t, bus_idx] = S
lhs_results.V_points[t, bus_idx] = res.voltage
lhs_results.Sbr_points[t, br_idx] = res.Sf
lhs_results.loading_points[t, br_idx] = res.loading
lhs_results.losses_points[t, br_idx] = res.losses
it += 1
self.progress_signal.emit(it / self.sampling_points * 100)
if self.__cancel__:
break
if self.__cancel__:
break
# compile MC results
self.progress_text.emit('Compiling results...')
lhs_results.compile()
# compute the island branch results
Sfb, Stb, If, It, Vbranch, loading, \
losses, flow_direction, Sbus = power_flow_post_process(numerical_island,
Sbus=lhs_results.S_points.mean(axis=0)[bus_idx],
V=lhs_results.V_points.mean(axis=0)[bus_idx],
branch_rates=numerical_island.branch_rates)
# apply the island averaged results
avg_res.Sbus[bus_idx] = Sbus
avg_res.voltage[bus_idx] = lhs_results.voltage[bus_idx]
avg_res.Sf[br_idx] = Sfb
avg_res.St[br_idx] = Stb
avg_res.If[br_idx] = If
avg_res.It[br_idx] = It
avg_res.Vbranch[br_idx] = Vbranch
avg_res.loading[br_idx] = loading
avg_res.losses[br_idx] = losses
avg_res.flow_direction[br_idx] = flow_direction
self.results = lhs_results
# send the finnish signal
self.progress_signal.emit(0.0)
self.progress_text.emit('Done!')
self.done_signal.emit()
return lhs_results
def run_single_thread(self):
"""
Run the monte carlo simulation
@return:
"""
# print('LHS run')
self.__cancel__ = False
# initialize the grid time series results
# we will append the island results with another function
batch_size = self.sampling_points
n = len(self.circuit.buses)
m = len(self.circuit.branches)
self.progress_signal.emit(0.0)
self.progress_text.emit('Running Latin Hypercube Sampling...')
lhs_results = MonteCarloResults(n,
m,
batch_size,
name='Latin Hypercube')
avg_res = PowerFlowResults()
avg_res.initialize(n, m)
# compile the multi-circuit
numerical_circuit = self.circuit.compile()
# perform the topological computation
calc_inputs_dict = numerical_circuit.compute_ts(
branch_tolerance_mode=self.options.branch_impedance_tolerance_mode,
ignore_single_node_islands=self.options.ignore_single_node_islands)
it = 0
# for each partition of the profiles...
for t_key, calc_inputs in calc_inputs_dict.items():
# For every island, run the time series
for island_index, numerical_island in enumerate(calc_inputs):
# try:
# set the time series as sampled in the circuit
# build the inputs
monte_carlo_input = make_monte_carlo_input(numerical_island)
mc_time_series = monte_carlo_input(batch_size,
use_latin_hypercube=True)
Vbus = numerical_island.Vbus
# short cut the indices
b_idx = numerical_island.original_bus_idx
br_idx = numerical_island.original_branch_idx
# run the time series
for t in range(batch_size):
# set the power values from a Monte carlo point at 't'
Y, I, S = mc_time_series.get_at(t)
# Run the set monte carlo point at 't'
res = single_island_pf(
circuit=numerical_island,
Vbus=Vbus,
Sbus=S,
Ibus=I,
branch_rates=numerical_island.branch_rates,
options=self.options,
logger=self.logger)
# Gather the results
lhs_results.S_points[
t, numerical_island.original_bus_idx] = res.Sbus
lhs_results.V_points[
t, numerical_island.original_bus_idx] = res.voltage
lhs_results.I_points[
t, numerical_island.original_branch_idx] = res.Ibranch
lhs_results.loading_points[
t, numerical_island.original_branch_idx] = res.loading
lhs_results.losses_points[
t, numerical_island.original_branch_idx] = res.losses
it += 1
self.progress_signal.emit(it / batch_size * 100)
if self.__cancel__:
break
if self.__cancel__:
break
# compile MC results
self.progress_text.emit('Compiling results...')
lhs_results.compile()
# compute the island branch results
island_avg_res = numerical_island.compute_branch_results(
lhs_results.voltage[b_idx])
# apply the island averaged results
avg_res.apply_from_island(island_avg_res,
b_idx=b_idx,
br_idx=br_idx)
# lhs_results the averaged branch magnitudes
lhs_results.sbranch = avg_res.Sbranch
lhs_results.bus_types = numerical_circuit.bus_types
self.results = lhs_results
# send the finnish signal
self.progress_signal.emit(0.0)
self.progress_text.emit('Done!')
self.done_signal.emit()
return lhs_results
