def init_store(power_system, times, data):
'''create the store before the first stage'''
wipe_storage()
storage = get_storage()
generators = power_system.generators()
# store the problem info read from the spreadsheets
for key, df in data.iteritems():
if key != 'scenario_values':
for k, v in (df.dtypes == object).iterkv():
if v:
df[k] = df[k].fillna('')
key = 'data_' + key
storage[key] = df
stages = len(times) # stage_times
est_Nt = len(data['timeseries'])
t = [times[0].initialTime]
# store first stage initial state
storage.append('power',
gen_time_dataframe(generators, t,
values=[[gen.initial_power for gen in generators]]),
expectedrows=est_Nt)
storage.append('status',
gen_time_dataframe(generators, t,
values=[[gen.initial_status for gen in generators]]),
expectedrows=est_Nt)
storage['hrsinstatus'] = gen_time_dataframe(generators, t,
values=[[gen.initial_status_hours for gen in generators]])
# setup empty containers for variables
storage['load_shed'] = Series()
storage['gen_shed'] = Series()
storage['expected_cost'] = DataFrame()
storage['observed_cost'] = DataFrame()
storage['expected_status'] = DataFrame()
storage['expected_power'] = DataFrame()
storage['expected_fuelcost'] = DataFrame()
storage['observed_fuelcost'] = DataFrame()
# setup one-per-stage results
storage['solve_time'] = Series(index=range(stages))
storage['mipgap'] = Series(index=range(stages))
# store configuration
storage['configuration'] = Series(user_config)
storage['version'] = Series({
'minpower': pkg_resources.get_distribution('minpower').version,
# try storing version number of the current working directory
'problem': _get_problem_version(),
})
return storage
def init_store(power_system, times, data):
'''create the store before the first stage'''
wipe_storage()
storage = get_storage()
generators = power_system.generators()
# store the problem info read from the spreadsheets
for key, df in data.iteritems():
if key != 'scenario_values':
for k, v in (df.dtypes == object).iterkv():
if v: df[k] = df[k].fillna('')
key = 'data_' + key
storage[key] = df
stages = len(times) # stage_times
est_Nt = len(data['timeseries'])
t = [times[0].initialTime]
# store first stage initial state
storage.append('power',
gen_time_dataframe(generators, t,
values=[[gen.initial_power for gen in generators]]),
expectedrows=est_Nt)
storage.append('status',
gen_time_dataframe(generators, t,
values=[[gen.initial_status for gen in generators]]),
expectedrows=est_Nt)
storage['hrsinstatus'] = gen_time_dataframe(generators, t,
values=[[gen.initial_status_hours for gen in generators]])
# setup empty containers for variables
storage['load_shed'] = Series()
storage['gen_shed'] = Series()
storage['expected_cost'] = DataFrame()
storage['observed_cost'] = DataFrame()
storage['expected_status'] = DataFrame()
storage['expected_power'] = DataFrame()
storage['expected_fuelcost'] = DataFrame()
storage['observed_fuelcost'] = DataFrame()
# setup one-per-stage results
storage['solve_time'] = Series(index=range(stages))
storage['mipgap'] = Series(index=range(stages))
# store configuration
storage['configuration'] = Series(user_config)
storage['version'] = Series({
'minpower': pkg_resources.get_distribution('minpower').version,
# try storing version number of the current working directory
'problem': _get_problem_version(),
})
return storage
def gen_time_df(self, method, non_overlap=True, evaluate=False,
generators=None):
times = self.times_non_overlap if non_overlap else self.times
if generators is None:
generators = self.generators
return gen_time_dataframe(generators, times,
[self.get_values(generators, method, t, evaluate) for t in times])
def store_state(power_system, times, sln=None):
storage = get_storage()
generators = power_system.generators()
stg = sln.stage_number
table_append(storage, 'power', sln.generators_power)
table_append(storage, 'status', sln.generators_status)
table_append(storage, 'load_shed', sln.load_shed_timeseries)
table_append(storage, 'gen_shed', sln.gen_shed_timeseries)
tEnd = times.last_non_overlap()
storage['hrsinstatus'] = gen_time_dataframe(
generators, [tEnd],
values=[[gen.finalstatus['hoursinstatus'] for gen in generators]])
_add_tbl_val(storage, 'solve_time', stg, sln.solve_time)
_add_tbl_val(storage, 'mipgap', stg, sln.mipgap)
if sln._resolved:
table_append(storage, 'observed_cost', sln.observed_totalcost)
table_append(storage, 'observed_fuelcost', sln.observed_fuelcost)
table_append(storage, 'expected_cost', sln.expected_totalcost)
table_append(storage, 'expected_fuelcost', sln.expected_fuelcost)
table_append(storage, 'expected_power', sln.expected_power)
table_append(storage, 'expected_status', sln.expected_status)
else:
table_append(storage, 'expected_cost', sln.totalcost_generation)
table_append(storage, 'expected_fuelcost', sln.fuelcost)
# # DEBUGGING
# from pandas.util.testing import assert_frame_equal
# try:
# gens = storage['data_generators'].copy()
# gens.index = ['g{}'.format(g) for g in gens.index]
# status = storage['status'].ix[1:]
# power = storage['power'][status.columns].ix[status.index]
# cost = storage['observed_cost'][status.columns].ix[status.index]
# fuelcost = storage['observed_fuelcost'][status.columns].ix[status.index]
# stcost = cost - fuelcost
#
# pcheck = (power * status)
# ccheck = (cost * status)
# stcheck = (stcost * status)
# assert_frame_equal(pcheck, power)
# assert_frame_equal(ccheck, cost)
# assert_frame_equal(stcheck, stcost)
# assert(((stcost < gens.startupcost - 1e-5) & (stcost > 1e-5) ).sum().sum() == 0)
#
# except AssertionError:
# raise
return storage
def store_state(power_system, times, sln=None):
storage = get_storage()
generators = power_system.generators()
stg = sln.stage_number
table_append(storage, 'power', sln.generators_power)
table_append(storage, 'status', sln.generators_status)
table_append(storage, 'load_shed', sln.load_shed_timeseries)
table_append(storage, 'gen_shed', sln.gen_shed_timeseries)
tEnd = times.last_non_overlap()
storage['hrsinstatus'] = gen_time_dataframe(generators, [tEnd],
values=[
[gen.finalstatus['hoursinstatus'] for gen in generators]
])
_add_tbl_val(storage, 'solve_time', stg, sln.solve_time)
_add_tbl_val(storage, 'mipgap', stg, sln.mipgap)
if sln._resolved:
table_append(storage, 'observed_cost', sln.observed_totalcost)
table_append(storage, 'observed_fuelcost', sln.observed_fuelcost)
table_append(storage, 'expected_cost', sln.expected_totalcost)
table_append(storage, 'expected_fuelcost', sln.expected_fuelcost)
table_append(storage, 'expected_power', sln.expected_power)
table_append(storage, 'expected_status', sln.expected_status)
else:
table_append(storage, 'expected_cost', sln.totalcost_generation)
table_append(storage, 'expected_fuelcost', sln.fuelcost)
# # DEBUGGING
# from pandas.util.testing import assert_frame_equal
# try:
# gens = storage['data_generators'].copy()
# gens.index = ['g{}'.format(g) for g in gens.index]
# status = storage['status'].ix[1:]
# power = storage['power'][status.columns].ix[status.index]
# cost = storage['observed_cost'][status.columns].ix[status.index]
# fuelcost = storage['observed_fuelcost'][status.columns].ix[status.index]
# stcost = cost - fuelcost
#
# pcheck = (power * status)
# ccheck = (cost * status)
# stcheck = (stcost * status)
# assert_frame_equal(pcheck, power)
# assert_frame_equal(ccheck, cost)
# assert_frame_equal(stcheck, stcost)
# assert(((stcost < gens.startupcost - 1e-5) & (stcost > 1e-5) ).sum().sum() == 0)
#
# except AssertionError:
# raise
return storage
def gen_time_df(self, method, scenario, non_overlap=True, evaluate=False,
generators=None):
if generators is None:
generators = self.generators
if evaluate:
getval = lambda gen, t: value(
getattr(gen, method)(t, scenario, evaluate=True))
else:
getval = lambda gen, t: value(getattr(gen, method)(t, scenario))
times = self.times_non_overlap if non_overlap else self.times
return gen_time_dataframe(generators, times,
[[getval(gen, t) for t in times] for gen in generators])
