def TEST_crowfail():
from simulation_batch import SimulationBatch
text = """# NetworkProbability data file
# bus bus_id fail_rate repair_rate
bus 101 0.0 10.0
bus 102 0.0 10.0
bus 103 0.0 10.0
# line name fbus tbus fail_rate repair_rate trans_fail
line a1 101 102 100000000000.0 10.0 0.0
line a2 102 103 0.0 10.0 0.0
# crow line1 line2 probability
crow a1 a2 0.5
"""
count = 100000
prob = NetworkProbability()
prob.read(StringIO(text))
batch = SimulationBatch()
for x in range(count):
batch.add(prob.outages(str(x)))
assert count == len(batch)
batch.write_stats(sys.stdout)
def make_outages(prob, count):
"""func make_outages :: NetworkProbability, Int -> SimulationBatch
----
Monte Carlo sample the network for it's expected condition.
e.g. existing outages, weather & load forcast, etc.
"""
batch = SimulationBatch()
for x in range(count):
batch.add(prob.outages(str(x)))
EnsureEqual(count, batch.size())
return batch
def make_failures(prob, count):
"""func make_failures :: NetworkProbability, Int -> SimulationBatch
----
Monte Carlo sample the network for unexpected changes.
e.g. new outages (failures), actual weather, actual load level, etc.
"""
batch = SimulationBatch()
for x in range(count):
batch.add(prob.failures(str(x)))
EnsureEqual(count, batch.size())
return batch
def make_failures(prob, count):
"""func make_failures :: NetworkProbability, Int -> SimulationBatch
----
Monte Carlo sample the network for unexpected changes.
e.g. new outages (failures), actual weather, actual load level, etc.
"""
batch = SimulationBatch()
for x in range(count):
batch.add(prob.failures(str(x)))
EnsureEqual(count, batch.size())
return batch
def make_outages(prob, count):
"""func make_outages :: NetworkProbability, Int -> SimulationBatch
----
Monte Carlo sample the network for it's expected condition.
e.g. existing outages, weather & load forcast, etc.
"""
batch = SimulationBatch()
for x in range(count):
batch.add(prob.outages(str(x)))
EnsureEqual(count, batch.size())
return batch
def text_to_scenario(text):
"""func text_to_scenario :: Str -> Scenario
----
make `text` into a Scenario by reading as if a
single element batch file
"""
with closing(StringIO(text)) as batch_stream:
batch = SimulationBatch()
batch.read(batch_stream)
EnsureEqual(len(batch), 1)
return list(batch)[0]
def text_to_scenario(text):
"""func text_to_scenario :: Str -> Scenario
----
make `text` into a Scenario by reading as if a
single element batch file
"""
with closing(StringIO(text)) as batch_stream:
batch = SimulationBatch()
batch.read(batch_stream)
EnsureEqual(len(batch), 1)
return list(batch)[0]
def example5():
clean_files()
clean = False
data = """
[base] opf
[dead_slack] opf
remove generator g12
[two_dead_slack] opf
remove generator g12
remove generator g13
[three_dead_slack] opf
remove generator g12
remove generator g15
[four_dead_slack] opf
remove generator g13
remove generator g12
[five_dead_slack] opf
remove generator g15
remove generator g12
[all_dead_slack] opf
remove generator g12
remove generator g13
remove generator g15
[rem_bus_1] opf
remove bus 1
[rem_li_a1] opf
remove line a1
[rem_gen_g1] opf
remove generator g1
[set_double] opf
set all demand 2.0
[set_half] opf
set all demand 0.5
"""
#data = """
# [fail_001] pf
# remove generator g32
# remove generator g13
#"""
batch = SimulationBatch()
batch.read(StringIO(data))
psat = read_psat("rts.m")
for scenario in batch:
report = simulate_scenario(psat, scenario, clean)
print "result = '" + str(report_in_limits(report)) + "'"
def make_outage_cases(prob, count):
"""func make_outage_cases :: NetworkProbability, Int -> SimulationBatch
----
like `make_outages` but makes `count` *after* reducing.
Monte Carlo sample the network for it's expected condition.
e.g. existing outages, weather & load forcast, etc.
"""
batch = SimulationBatch()
current = 0
while len(batch) < count:
batch.add(prob.outages(str(current)))
current += 1
EnsureEqual(count, len(batch))
return batch
def make_outage_cases(prob, count):
"""func make_outage_cases :: NetworkProbability, Int -> SimulationBatch
----
like `make_outages` but makes `count` *after* reducing.
Monte Carlo sample the network for it's expected condition.
e.g. existing outages, weather & load forcast, etc.
"""
batch = SimulationBatch()
current = 0
while len(batch) < count:
batch.add(prob.outages(str(current)))
current += 1
EnsureEqual(count, len(batch))
return batch
def make_failure_cases(prob, count):
"""func make_failure_cases :: NetworkProbability, Int -> SimulationBatch
----
like `make_failures` but makes `count` *after* reducing.
Monte Carlo sample the network for unexpected changes.
e.g. new outages (failures), actual weather, actual load level, etc.
"""
batch = SimulationBatch()
current = 0
while len(batch) < count:
batch.add(prob.failures(str(current)))
current += 1
EnsureEqual(count, len(batch))
return batch
def make_failure_cases(prob, count):
"""func make_failure_cases :: NetworkProbability, Int -> SimulationBatch
----
like `make_failures` but makes `count` *after* reducing.
Monte Carlo sample the network for unexpected changes.
e.g. new outages (failures), actual weather, actual load level, etc.
"""
batch = SimulationBatch()
current = 0
while len(batch) < count:
batch.add(prob.failures(str(current)))
current += 1
EnsureEqual(count, len(batch))
return batch
def test007():
"""batch and single should gave same results"""
clean_files()
psat = read_psat("rts2.m")
# prob = read_probabilities("rts.net")
# batch = make_outages(prob, 2)
data = """
[batch0] opf
remove generator g1
remove generator g4
remove generator g31
set all demand 0.3987456
result pass
[batch1] opf
remove generator g22
remove generator g24
set all demand 0.6670332
result fail
"""
batch = SimulationBatch()
batch.read(StringIO(data))
batch_simulate(batch, psat, 10, False)
with open("rts.bch", "w") as result_file:
batch.write(result_file)
for n, scenario in enumerate(batch):
scenario.title = "single" + str(n)
report = simulate_scenario(psat, scenario, False)
scenario.result = report_in_limits(report)
with open("rts2.bch", "w") as result_file:
batch.write(result_file)
