def __init__(self, id, subsector_id, service_demand_unit, stock_time_unit, cost_of_capital, scenario=None, **kwargs):
self.id = id
self.subsector_id = subsector_id
self.scenario = scenario
StockItem.__init__(self)
self.service_demand_unit = service_demand_unit
self.stock_time_unit = stock_time_unit
for col, att in util.object_att_from_table('DemandTechs', self.id):
setattr(self, col, att)
# if cost_of_capital at the technology level is None, it uses subsector defaults
if self.cost_of_capital is None:
self.cost_of_capital = cost_of_capital
else:
pass
# we can have multiple sales shares because sales share may be specific
# to the transition between two technolog)
self.reference_sales_shares = {}
if self.id in util.sql_read_table('DemandSalesData', 'demand_technology_id', return_unique=True, return_iterable=True):
self.reference_sales_shares[1] = SalesShare(id=self.id, subsector_id=self.subsector_id, reference=True,
sql_id_table='DemandSales', sql_data_table='DemandSalesData',
primary_key='subsector_id', data_id_key='demand_technology_id',
scenario=scenario)
self.book_life()
self.add_class()
self.min_year()
self.shape = shape.shapes.data[self.shape_id] if self.shape_id is not None else None
def __init__(self,
id,
subsector_id,
sql_id_table,
sql_data_table,
primary_key,
data_id_key,
reference=False,
scenario=None):
self.id = id
self.subsector_id = subsector_id
self.sql_id_table = sql_id_table
self.sql_data_table = sql_data_table
self.scenario = scenario
self.mapped = False
if reference:
for col, att in util.object_att_from_table(self.sql_id_table,
self.subsector_id,
primary_key):
if att is not None:
setattr(self, col, att)
DataMapFunctions.__init__(self, data_id_key)
self.read_timeseries_data(subsector_id=self.subsector_id)
self.raw_values = util.remove_df_levels(self.raw_values,
'technology')
else:
self.replaced_demand_tech_id = None
# measure specific sales share does not require technology filtering
Abstract.__init__(self,
self.id,
primary_key=primary_key,
data_id_key=data_id_key)
def __init__(self,
id,
supply_node_id,
sql_id_table,
sql_data_table,
primary_key,
data_id_key,
reference=False,
scenario=None):
self.id = id
self.input_type = 'total'
self.supply_node_id = supply_node_id
self.sql_id_table = sql_id_table
self.sql_data_table = sql_data_table
self.scenario = scenario
self.mapped = False
if reference:
for col, att in util.object_att_from_table(self.sql_id_table,
self.supply_node_id,
primary_key):
setattr(self, col, att)
DataMapFunctions.__init__(self, data_id_key)
self.read_timeseries_data(supply_node_id=self.supply_node_id)
self.raw_values = util.remove_df_levels(self.raw_values,
'supply_technology')
else:
# measure specific sales does not require technology filtering
Abstract.__init__(self,
self.id,
primary_key=primary_key,
data_id_key=data_id_key)
def __init__(self,
id,
supply_node_id,
sql_id_table,
sql_data_table,
reference=False):
self.id = id
self.supply_node_id = supply_node_id
self.sql_id_table = sql_id_table
self.sql_data_table = sql_data_table
self.mapped = False
self.input_type = 'intensity'
if reference:
for col, att in util.object_att_from_table(self.sql_id_table,
self.supply_node_id,
'supply_node_id'):
if att is not None:
setattr(self, col, att)
DataMapFunctions.__init__(self, 'supply_technology')
self.read_timeseries_data()
self.raw_values = util.remove_df_levels(
self.raw_values, ['supply_node', 'supply_technology'])
else:
# measure specific sales share does not require technology filtering
Abstract.__init__(self, self.id)
def __init__(self, id, subsector_id, service_demand_unit, stock_time_unit, cost_of_capital, scenario=None, **kwargs):
self.id = id
self.subsector_id = subsector_id
self.scenario = scenario
StockItem.__init__(self)
self.service_demand_unit = service_demand_unit
self.stock_time_unit = stock_time_unit
for col, att in util.object_att_from_table('DemandTechs', self.id):
setattr(self, col, att)
# if cost_of_capital at the technology level is None, it uses subsector defaults
if self.cost_of_capital is None:
self.cost_of_capital = cost_of_capital
else:
pass
# we can have multiple sales shares because sales share may be specific
# to the transition between two technolog)
self.reference_sales_shares = {}
if self.id in util.sql_read_table('DemandSalesData', 'demand_technology_id', return_unique=True, return_iterable=True):
self.reference_sales_shares[1] = SalesShare(id=self.id, subsector_id=self.subsector_id, reference=True,
sql_id_table='DemandSales', sql_data_table='DemandSalesData',
primary_key='subsector_id', data_id_key='demand_technology_id',
scenario=scenario)
self.book_life()
self.add_class()
self.min_year()
if self.shape_id is not None:
self.shape = shape.shapes.data[self.shape_id]
def __init__(self, dispatch_feeders, dispatch_geography, dispatch_geographies, scenario):
#TODO replace 1 with a config parameter
for col, att in util.object_att_from_table('DispatchConfig', 1):
setattr(self, col, att)
self.node_config_dict = dict()
for supply_node in util.sql_read_table('DispatchNodeConfig','supply_node_id',return_iterable=True):
self.node_config_dict[supply_node] = DispatchNodeConfig(supply_node)
self.set_dispatch_orders()
self.dispatch_window_dict = dict(util.sql_read_table('DispatchWindows'))
self.curtailment_cost = util.unit_convert(0, unit_from_den='megawatt_hour',unit_to_den=cfg.calculation_energy_unit)
self.unserved_capacity_cost = util.unit_convert(10000.0, unit_from_den='megawatt_hour',unit_to_den=cfg.calculation_energy_unit)
self.dist_net_load_penalty = util.unit_convert(15000.0, unit_from_den='megawatt_hour',unit_to_den=cfg.calculation_energy_unit)
# this bulk penalty is mostly for transmission
self.bulk_net_load_penalty = util.unit_convert(5000.0, unit_from_den='megawatt_hour',unit_to_den=cfg.calculation_energy_unit)
self.ld_upward_imbalance_penalty = util.unit_convert(150.0, unit_from_den='megawatt_hour',unit_to_den=cfg.calculation_energy_unit)
self.ld_downward_imbalance_penalty = util.unit_convert(50.0, unit_from_den='megawatt_hour',unit_to_den=cfg.calculation_energy_unit)
self.dispatch_feeders = dispatch_feeders
self.feeders = [0] + dispatch_feeders
self.dispatch_geography = dispatch_geography
self.dispatch_geographies = dispatch_geographies
self.stdout_detail = cfg.cfgfile.get('opt','stdout_detail')
self.transmission = dispatch_transmission.DispatchTransmission(cfg.transmission_constraint_id, scenario)
if self.stdout_detail == 'False':
self.stdout_detail = False
else:
self.stdout_detail = True
self.solve_kwargs = {"keepfiles": False, "tee": False}
def __init__(self, id, primary_key='id', data_id_key=None, **filters):
# Ryan: I've introduced a new parameter called data_id_key, which is the key in the "Data" table
# because we are introducing primary keys into the Data tables, it is sometimes necessary to specify them separately
# before we only has primary_key, which was shared in the "parent" and "data" tables, and this is still the default as we make the change.
if data_id_key is None:
data_id_key = primary_key
try:
col_att = util.object_att_from_table(self.sql_id_table, id,
primary_key)
except:
print self.sql_id_table, id, primary_key
raise
if col_att is None:
self.data = False
else:
for col, att in col_att:
# if att is not None:
setattr(self, col, att)
self.data = True
DataMapFunctions.__init__(self, data_id_key)
self.read_timeseries_data(**filters)
def __init__(self, id=None):
if id is not None:
self.id = id
self.sql_id_table = 'Shapes'
self.sql_data_table = 'ShapesData'
for col, att in util.object_att_from_table(self.sql_id_table, id):
setattr(self, col, att)
# creates the index_levels dictionary
dmf.DataMapFunctions.__init__(self, data_id_key='parent_id')
def __init__(self, id=None):
if id is not None:
self.id = id
self.sql_id_table = 'Shapes'
self.sql_data_table = 'ShapesData'
for col, att in util.object_att_from_table(self.sql_id_table, id):
setattr(self, col, att)
# creates the index_levels dictionary
dmf.DataMapFunctions.__init__(self)
def __init__(self, id):
self.id = id
self.sql_id_table = 'Shapes'
self.sql_data_table = 'ShapesData'
for col, att in util.object_att_from_table(self.sql_id_table, id):
setattr(self, col, att)
dmf.DataMapFunctions.__init__(self, data_id_key='parent_id')
# needed for parallel process
self.workingdir = cfg.workingdir
self.cfgfile_name = cfg.cfgfile_name
self.log_name = cfg.log_name
def __init__(self, id, cost_of_capital, **kwargs):
self.id = id
self.sql_id_table = 'DemandFuelSwitchingMeasures'
self.sql_data_table = 'DemandFuelSwitchingMeasuresData'
for col, att in util.object_att_from_table(self.sql_id_table, self.id):
if att is not None:
setattr(self, col, att)
self.calculate_book_life()
self.cost_of_capital = cost_of_capital
self.impact = FuelSwitchingImpact(self.id)
self.energy_intensity = FuelSwitchingEnergyIntensity(self.id)
self.cost = DemandMeasureCost(id, self.cost_of_capital, self.book_life, 'DemandFuelSwitchingMeasuresCost', 'DemandFuelSwitchingMeasuresCostData')
def __init__(self, id, drivers, sql_id_table, sql_data_table, primary_key, technology_id=None, **kwargs):
self.id = id
self.drivers = drivers
self.technology_id = technology_id
self.sql_id_table = sql_id_table
self.sql_data_table = sql_data_table
self.primary_key = primary_key
for col, att in util.object_att_from_table(self.sql_id_table, self.id, 'subsector_id'):
setattr(self, col, att)
self.in_use_drivers()
DataMapFunctions.__init__(self, self.primary_key)
self.read_timeseries_data()
self.projected = False
def __init__(self, dispatch_feeders, dispatch_geography,
dispatch_geographies, scenario):
#TODO replace 1 with a config parameter
for col, att in util.object_att_from_table('DispatchConfig', 1):
setattr(self, col, att)
self.node_config_dict = dict()
for supply_node in util.sql_read_table('DispatchNodeConfig',
'supply_node_id',
return_iterable=True):
self.node_config_dict[supply_node] = DispatchNodeConfig(
supply_node)
self.set_dispatch_orders()
self.dispatch_window_dict = dict(
util.sql_read_table('DispatchWindows'))
self.curtailment_cost = util.unit_convert(
0,
unit_from_den='megawatt_hour',
unit_to_den=cfg.calculation_energy_unit)
self.unserved_capacity_cost = util.unit_convert(
10000.0,
unit_from_den='megawatt_hour',
unit_to_den=cfg.calculation_energy_unit)
self.dist_net_load_penalty = util.unit_convert(
15000.0,
unit_from_den='megawatt_hour',
unit_to_den=cfg.calculation_energy_unit)
# this bulk penalty is mostly for transmission
self.bulk_net_load_penalty = util.unit_convert(
5000.0,
unit_from_den='megawatt_hour',
unit_to_den=cfg.calculation_energy_unit)
self.ld_upward_imbalance_penalty = util.unit_convert(
150.0,
unit_from_den='megawatt_hour',
unit_to_den=cfg.calculation_energy_unit)
self.ld_downward_imbalance_penalty = util.unit_convert(
50.0,
unit_from_den='megawatt_hour',
unit_to_den=cfg.calculation_energy_unit)
self.dispatch_feeders = dispatch_feeders
self.feeders = [0] + dispatch_feeders
self.dispatch_geography = dispatch_geography
self.dispatch_geographies = dispatch_geographies
self.stdout_detail = cfg.cfgfile.get('opt', 'stdout_detail')
self.transmission = dispatch_transmission.DispatchTransmission(
cfg.transmission_constraint_id, scenario)
if self.stdout_detail == 'False':
self.stdout_detail = False
else:
self.stdout_detail = True
self.solve_kwargs = {"keepfiles": False, "tee": False}
def __init__(self, id, drivers, sql_id_table, sql_data_table, demand_technology_id=None, **kwargs):
self.id = id
self.drivers = drivers
self.demand_technology_id = demand_technology_id
self.sql_id_table = sql_id_table
self.sql_data_table = sql_data_table
self.primary_key = 'subsector_id'
self.data_id_key = 'subsector_id'
for col, att in util.object_att_from_table(self.sql_id_table, self.id, 'subsector_id'):
setattr(self, col, att)
self.in_use_drivers()
DataMapFunctions.__init__(self, self.data_id_key)
self.read_timeseries_data()
self.projected = False
def __init__(self, id, cost_of_capital, **kwargs):
self.id = id
self.sql_id_table = 'DemandFuelSwitchingMeasures'
self.sql_data_table = 'DemandFuelSwitchingMeasuresData'
for col, att in util.object_att_from_table(self.sql_id_table, self.id):
if att is not None:
setattr(self, col, att)
self.calculate_book_life()
self.cost_of_capital = cost_of_capital
self.impact = FuelSwitchingImpact(self.id)
self.energy_intensity = FuelSwitchingEnergyIntensity(self.id)
self.cost = DemandMeasureCost(id, self.cost_of_capital, self.book_life,
'DemandFuelSwitchingMeasuresCost',
'DemandFuelSwitchingMeasuresCostData')
def __init__(self, id, cost_of_capital, **kwargs):
self.id = id
for col, att in util.object_att_from_table('SupplyTechs', id):
setattr(self, col, att)
if self.cost_of_capital is None:
self.cost_of_capital = cost_of_capital
self.add_costs()
self.efficiency = SupplyTechEfficiency(id)
self.capacity_factor = SupplyTechCapacityFactor(id)
self.reference_sales_shares = {}
if self.id in util.sql_read_table('SupplySalesShareData', 'supply_technology', return_unique=True, return_iterable=True):
self.reference_sales_shares[1] = SupplySalesShare(id=self.id, supply_node_id=self.supply_node_id, reference=True,sql_id_table='SupplySalesShare', sql_data_table='SupplySalesShareData')
self.reference_sales = {}
if self.id in util.sql_read_table('SupplySalesData','supply_technology', return_unique=True, return_iterable=True):
self.reference_sales[1] = SupplySales(id=self.id, supply_node_id=self.supply_node_id, reference=True,sql_id_table='SupplySales', sql_data_table='SupplySalesData')
StockItem.__init__(self)
def __init__(self, id, drivers, sql_id_table, sql_data_table, scenario=None, demand_technology_id=None):
self.id = id
self.drivers = drivers
self.demand_technology_id = demand_technology_id
self.sql_id_table = sql_id_table
self.sql_data_table = sql_data_table
if scenario:
self.scenario = scenario
self.primary_key = 'subsector_id'
self.data_id_key = 'subsector_id'
for col, att in util.object_att_from_table(self.sql_id_table, self.id, 'subsector_id'):
setattr(self, col, att)
self.in_use_drivers()
DataMapFunctions.__init__(self, self.data_id_key)
self.read_timeseries_data()
self.projected = False
def __init__(self, id, supply_node_id, sql_id_table, sql_data_table, primary_key, data_id_key, reference=False):
self.id = id
self.input_type = 'total'
self.supply_node_id = supply_node_id
self.sql_id_table = sql_id_table
self.sql_data_table = sql_data_table
self.mapped = False
if reference:
for col, att in util.object_att_from_table(self.sql_id_table, self.supply_node_id, primary_key):
setattr(self, col, att)
DataMapFunctions.__init__(self, data_id_key)
self.read_timeseries_data(supply_node_id=self.supply_node_id)
self.raw_values = util.remove_df_levels(self.raw_values, 'supply_technology')
else:
# measure specific sales does not require technology filtering
Abstract.__init__(self, self.id, primary_key=primary_key, data_id_key=data_id_key)
def __init__(self, id, supply_node_id, sql_id_table, sql_data_table, reference=False):
self.id = id
self.supply_node_id = supply_node_id
self.sql_id_table = sql_id_table
self.sql_data_table = sql_data_table
self.mapped = False
self.input_type = 'intensity'
if reference:
for col, att in util.object_att_from_table(self.sql_id_table, self.supply_node_id, 'supply_node_id'):
if att is not None:
setattr(self, col, att)
DataMapFunctions.__init__(self, 'supply_technology')
self.read_timeseries_data()
self.raw_values = util.remove_df_levels(self.raw_values, ['supply_node','supply_technology'])
else:
# measure specific sales share does not require technology filtering
Abstract.__init__(self, self.id)
def __init__(self, id, subsector_id, sql_id_table, sql_data_table, primary_key, data_id_key, reference=False):
self.id = id
self.subsector_id = subsector_id
self.sql_id_table = sql_id_table
self.sql_data_table = sql_data_table
self.mapped = False
if reference:
for col, att in util.object_att_from_table(self.sql_id_table, self.subsector_id, primary_key):
if att is not None:
setattr(self, col, att)
DataMapFunctions.__init__(self, data_id_key)
self.read_timeseries_data(subsector_id=self.subsector_id)
self.raw_values = util.remove_df_levels(self.raw_values, 'technology')
else:
self.replaced_demand_tech_id = None
# measure specific sales share does not require technology filtering
Abstract.__init__(self, self.id, primary_key=primary_key, data_id_key=data_id_key)
def __init__(self, id, primary_key='id', **filters):
try:
for col, att in util.object_att_from_table(self.sql_id_table, id, primary_key):
# if att is not None:
setattr(self, col, att)
DataMapFunctions.__init__(self, primary_key)
self.data = True
except:
self.data = False
try:
if len(filters):
self.read_timeseries_data(**filters)
else:
self.read_timeseries_data()
self.empty = False
except:
self.empty = True
def __init__(self, id, cost_of_capital, scenario, **kwargs):
self.id = id
for col, att in util.object_att_from_table('SupplyTechs', id):
setattr(self, col, att)
if self.cost_of_capital is None:
self.cost_of_capital = cost_of_capital
self.scenario = scenario
self.add_costs()
self.efficiency = SupplyTechEfficiency(id, self.scenario)
self.capacity_factor = SupplyTechCapacityFactor(id, self.scenario)
self.co2_capture = SupplyTechCO2Capture(id, self.scenario)
self.reference_sales_shares = {}
if self.id in util.sql_read_table('SupplySalesShareData',
'supply_technology_id',
return_unique=True,
return_iterable=True):
self.reference_sales_shares[1] = SupplySalesShare(
id=self.id,
supply_node_id=self.supply_node_id,
reference=True,
sql_id_table='SupplySalesShare',
sql_data_table='SupplySalesShareData',
primary_key='supply_node_id',
data_id_key='supply_technology_id',
scenario=self.scenario)
self.reference_sales = {}
if self.id in util.sql_read_table('SupplySalesData',
'supply_technology_id',
return_unique=True,
return_iterable=True):
self.reference_sales[1] = SupplySales(
id=self.id,
supply_node_id=self.supply_node_id,
reference=True,
sql_id_table='SupplySales',
sql_data_table='SupplySalesData',
primary_key='supply_node_id',
data_id_key='supply_technology_id',
scenario=self.scenario)
StockItem.__init__(self)
if self.shape_id is not None:
self.shape = shape.shapes.data[self.shape_id]
def __init__(self, id, cost_of_capital, scenario, **kwargs):
self.id = id
for col, att in util.object_att_from_table('SupplyTechs', id):
setattr(self, col, att)
if self.cost_of_capital is None:
self.cost_of_capital = cost_of_capital
self.scenario = scenario
self.add_costs()
self.efficiency = SupplyTechEfficiency(id, self.scenario)
self.capacity_factor = SupplyTechCapacityFactor(id, self.scenario)
self.co2_capture = SupplyTechCO2Capture(id, self.scenario)
self.reference_sales_shares = {}
if self.id in util.sql_read_table('SupplySalesShareData', 'supply_technology_id', return_unique=True, return_iterable=True):
self.reference_sales_shares[1] = SupplySalesShare(id=self.id, supply_node_id=self.supply_node_id, reference=True,sql_id_table='SupplySalesShare', sql_data_table='SupplySalesShareData', primary_key='supply_node_id', data_id_key='supply_technology_id', scenario=self.scenario)
self.reference_sales = {}
if self.id in util.sql_read_table('SupplySalesData','supply_technology_id', return_unique=True, return_iterable=True):
self.reference_sales[1] = SupplySales(id=self.id, supply_node_id=self.supply_node_id, reference=True,sql_id_table='SupplySales', sql_data_table='SupplySalesData', primary_key='supply_node_id', data_id_key='supply_technology_id', scenario=self.scenario)
StockItem.__init__(self)
if self.shape_id is not None:
self.shape = shape.shapes.data[self.shape_id]
def __init__(self, id, primary_key='id', data_id_key=None, **filters):
# Ryan: I've introduced a new parameter called data_id_key, which is the key in the "Data" table
# because we are introducing primary keys into the Data tables, it is sometimes necessary to specify them separately
# before we only has primary_key, which was shared in the "parent" and "data" tables, and this is still the default as we make the change.
if data_id_key is None:
data_id_key = primary_key
try:
col_att = util.object_att_from_table(self.sql_id_table, id, primary_key)
except:
print self.sql_id_table, id, primary_key
raise
if col_att is None:
self.data = False
else:
for col, att in col_att:
# if att is not None:
setattr(self, col, att)
self.data = True
DataMapFunctions.__init__(self, data_id_key)
self.read_timeseries_data(**filters)
def __init__(self, id, **kwargs):
self.id = id
self.sql_id_table = 'DispatchNodeConfig'
for col, att in util.object_att_from_table(self.sql_id_table, id, primary_key='supply_node_id'):
setattr(self, col, att)
def __init__(self, id):
self.id = id
for col, att in util.object_att_from_table('DemandServiceLink', self.id):
setattr(self, col, att)
def __init__(self, id, **kwargs):
self.id = id
self.sql_id_table = 'DispatchNodeConfig'
for col, att in util.object_att_from_table(
self.sql_id_table, id, primary_key='supply_node_id'):
setattr(self, col, att)
