def test_enduse():
"""testing"""
out = enduse_func.Enduse(submodel='test',
region='test',
scenario_data='test',
assumptions='test',
regional_lp_stock='test',
non_regional_lp_stock='test',
base_yr='test',
curr_yr='test',
enduse='test',
sector='test',
fuel=np.zeros((7, 0)),
tech_stock='test',
heating_factor_y='test',
cooling_factor_y='test',
fuel_fueltype_tech_p_by='test',
sig_param_tech='test',
enduse_overall_change='test',
criterias='test',
strategy_variables='test',
fueltypes_nr='test',
fueltypes='test',
model_yeardays_nrs='test')
assert out.flat_profile_crit == True
def test_enduse():
"""testing"""
out = enduse_func.Enduse(submodel_name='test_name',
region='test',
scenario_data='test',
assumptions='test',
load_profiles='test',
base_yr='test',
curr_yr='test',
enduse='test',
sector='test',
fuel=np.zeros((7, 0)),
tech_stock='test',
heating_factor_y='test',
cooling_factor_y='test',
fuel_tech_p_by='test',
criterias='test',
strategy_vars='test',
fueltypes_nr='test',
fueltypes='test')
assert out.flat_profile_crit == True
def simulate_region(region, data, criterias, assumptions, weather_yr,
weather_by):
"""Run submodels for a single region
Arguments
---------
region : str
Region name
data : dict
Data container
Returns
-------
all_submodels : list
List with submodel objects depending on submodels
"""
submodel_names = assumptions.submodels_names
# ----------------------------
# Create Base year and current weather Regions
# ----------------------------
weather_region_cy = WeatherRegion(
name=region,
assumptions=assumptions,
technologies=assumptions.technologies,
enduses=data['enduses'],
temp_by=data['temp_data'][weather_by][region],
temp_cy=data['temp_data'][weather_yr][region],
tech_lp=data['tech_lp'],
sectors=data['sectors'],
crit_temp_min_max=criterias['crit_temp_min_max'])
# Get region specific disaggregated fuel
region_fuel_disagg = get_disaggregated_fuel_of_reg(submodel_names,
data['fuel_disagg'],
region)
# ----------------------------
# Create Region
# ----------------------------
region_obj = Region(name=region,
longitude=data['reg_coord'][region]['longitude'],
latitude=data['reg_coord'][region]['latitude'],
region_fuel_disagg=region_fuel_disagg)
for submodel_name in submodel_names:
for sector in data['sectors'][submodel_name]:
for enduse in data['enduses'][submodel_name]:
# ------------------------------------------------------
# Configure and select correct Enduse specific inputs
# ------------------------------------------------------
if submodel_name == 'industry' and enduse != "is_space_heating":
flat_profile_crit = True
else:
flat_profile_crit = False
if not data['dw_stocks'][submodel_name]:
dw_stock = False
else:
dw_stock = data['dw_stocks'][submodel_name][
region_obj.name]
# ---------------
# Create submodel for region and enduse
# ---------------
yield endusefunctions.Enduse(
submodel_name=submodel_name,
region=region_obj.name,
scenario_data=data['scenario_data'],
assumptions=assumptions,
load_profiles=weather_region_cy.load_profiles,
base_yr=assumptions.base_yr,
curr_yr=assumptions.curr_yr,
enduse=enduse,
sector=sector,
fuel=region_obj.fuels[submodel_name][enduse][sector],
tech_stock=weather_region_cy.tech_stock[submodel_name],
heating_factor_y=weather_region_cy.f_heat[submodel_name],
cooling_factor_y=weather_region_cy.
f_colling[submodel_name],
fuel_tech_p_by=assumptions.fuel_tech_p_by[enduse][sector],
criterias=criterias,
strategy_vars=assumptions.regional_vars[region_obj.name],
fueltypes_nr=assumptions.fueltypes_nr,
fueltypes=assumptions.fueltypes,
dw_stock=dw_stock,
reg_scen_drivers=assumptions.scenario_drivers,
flat_profile_crit=flat_profile_crit)
def simulate_region(region, data, criterias, assumptions, weather_stations,
weather_yr, weather_by):
"""Run submodels for a single region
Arguments
---------
region : str
Region name
data : dict
Data container
Returns
-------
all_submodels : list
List with submodel objects depending on submodels
"""
submodel_objs = []
submodel_names = assumptions.submodels_names
# Get closest weather region object
weather_region_id = weather_station_location.get_closest_station(
latitude_reg=data['reg_coord'][region]['latitude'],
longitude_reg=data['reg_coord'][region]['longitude'],
weather_stations=weather_stations)
# ----------------------------
# Create Base year and current weather Regions
# ----------------------------
weather_regions_weather_cy = WeatherRegion(
name=weather_region_id,
latitude=weather_stations[weather_region_id]['latitude'],
longitude=weather_stations[weather_region_id]['longitude'],
assumptions=assumptions,
technologies=assumptions.technologies,
enduses=data['enduses'],
temp_by=data['temp_data'][weather_by][weather_region_id],
temp_cy=data['temp_data'][weather_yr][weather_region_id],
tech_lp=data['tech_lp'],
sectors=data['sectors'],
crit_temp_min_max=criterias['crit_temp_min_max'])
weather_regions_weather_by = WeatherRegion(
name=weather_region_id,
latitude=weather_stations[weather_region_id]['latitude'],
longitude=weather_stations[weather_region_id]['longitude'],
assumptions=assumptions,
technologies=assumptions.technologies,
enduses=data['enduses'],
temp_by=data['temp_data'][weather_by][weather_region_id],
temp_cy=data['temp_data'][weather_yr][weather_region_id],
tech_lp=data['tech_lp'],
sectors=data['sectors'],
crit_temp_min_max=criterias['crit_temp_min_max'])
# Get region specific disaggregated fuel
region_fuel_disagg = get_disaggregated_fuel_of_reg(submodel_names,
data['fuel_disagg'],
region)
# ----------------------------
# Create Region
# ----------------------------
region_obj = Region(name=region,
longitude=data['reg_coord'][region]['longitude'],
latitude=data['reg_coord'][region]['latitude'],
region_fuel_disagg=region_fuel_disagg,
weather_reg_cy=weather_regions_weather_cy,
weather_reg_by=weather_regions_weather_by)
for submodel_name in submodel_names:
for sector in data['sectors'][submodel_name]:
for enduse in data['enduses'][submodel_name]:
# ------------------------------------------------------
# Configure and select correct Enduse specific inputs
# ------------------------------------------------------
if submodel_name == 'industry' and enduse != "is_space_heating":
flat_profile_crit = True
else:
flat_profile_crit = False
if not data['dw_stocks'][submodel_name]:
dw_stock = False
else:
dw_stock = data['dw_stocks'][submodel_name][
region_obj.name]
# ---------------
# Create submodel for region and enduse
# ---------------
submodel_obj = endusefunctions.Enduse(
submodel_name=submodel_name,
region=region_obj.name,
scenario_data=data['scenario_data'],
assumptions=assumptions,
load_profiles=weather_regions_weather_cy.load_profiles,
f_weather_correction=region_obj.
f_weather_correction[submodel_name],
base_yr=assumptions.base_yr,
curr_yr=assumptions.curr_yr,
enduse=enduse,
sector=sector,
fuel=region_obj.fuels[submodel_name][enduse][sector],
tech_stock=weather_regions_weather_cy.
tech_stock[submodel_name],
heating_factor_y=weather_regions_weather_cy.
f_heat[submodel_name],
cooling_factor_y=weather_regions_weather_cy.
f_colling[submodel_name],
fuel_tech_p_by=assumptions.fuel_tech_p_by[enduse][sector],
criterias=criterias,
strategy_vars=assumptions.regional_vars[region_obj.name],
fueltypes_nr=assumptions.fueltypes_nr,
fueltypes=assumptions.fueltypes,
dw_stock=dw_stock,
reg_scen_drivers=assumptions.scenario_drivers,
flat_profile_crit=flat_profile_crit)
submodel_objs.append(submodel_obj)
# Collect all submodels with respect to submodel names and store in list
# e.g. [[all_residential-submodels], [all_service_submodels]...]
all_submodels = []
submodels = lookup_tables.basic_lookups()['submodels_names']
for submodel in submodels:
submodels = get_all_submodels(submodel_objs, submodel)
all_submodels.append(submodels)
return all_submodels
def industry_submodel(region, weather_region, scenario_data,
non_regional_lp_stock, assumptions, lookups, criterias,
enduses, sectors):
"""Industry subsector model
A flat load profile is assumed except for is_space_heating
Arguments
----------
region : int
Region
data : dict
Data containter
enduses : list
Enduses of industry submodel
sectors : list
Sectors of industry submodel
Return
------
submodules : list
Submodule objects
"""
logging.debug("... industry submodel start")
submodels = []
for sector in sectors:
for enduse in enduses:
# ------------------------------------------------------
# Configure and select correct Enduse() specific inputs
# ------------------------------------------------------
if enduse == "is_space_heating":
flat_profile_crit = False
else:
flat_profile_crit = True
if criterias['spatial_exliclit_diffusion']:
sig_param_tech = assumptions.is_sig_param_tech[enduse][sector][
region.name]
strategy_variables = assumptions.regional_strategy_variables[
region.name]
else:
sig_param_tech = assumptions.is_sig_param_tech[enduse][sector]
strategy_variables = assumptions.strategy_variables
# ------------------------------------------------------
# Create submodel
# ------------------------------------------------------
submodel = endusefunctions.Enduse(
submodel='is_submodel',
region=region.name,
scenario_data=scenario_data,
assumptions=assumptions,
regional_lp_stock=weather_region.is_load_profiles,
non_regional_lp_stock=non_regional_lp_stock,
base_yr=assumptions.base_yr,
curr_yr=assumptions.curr_yr,
enduse=enduse,
sector=sector,
fuel=region.is_enduses_sectors_fuels[enduse][sector],
tech_stock=weather_region.is_tech_stock,
heating_factor_y=weather_region.f_heat_is_y,
cooling_factor_y=weather_region.f_cooling_is_y,
fuel_fueltype_tech_p_by=assumptions.is_fuel_tech_p_by[enduse]
[sector],
sig_param_tech=sig_param_tech,
enduse_overall_change=assumptions.enduse_overall_change,
criterias=criterias,
strategy_variables=strategy_variables,
fueltypes_nr=lookups['fueltypes_nr'],
fueltypes=lookups['fueltypes'],
model_yeardays_nrs=assumptions.model_yeardays_nrs,
reg_scen_drivers=assumptions.scenario_drivers['is_submodule'],
flat_profile_crit=flat_profile_crit)
submodels.append(submodel)
return submodels
def service_submodel(region, weather_region, scenario_data, ss_dw_stock,
non_regional_lp_stock, assumptions, lookups, criterias,
enduses, sectors):
"""Create the service submodules per enduse, sector and region and add to list
Arguments
----------
data : dict
Data container
enduses : list
All residential enduses
sectors : list
Service sectors
Returns
-------
submodels : list
List with submodels
"""
logging.debug("... service submodel start")
submodels = []
for sector in sectors:
for enduse in enduses:
# ------------------------------------------------------
# Configure and select correct Enduse() specific inputs
# ------------------------------------------------------
if criterias['spatial_exliclit_diffusion']:
sig_param_tech = assumptions.ss_sig_param_tech[enduse][sector][
region.name]
strategy_variables = assumptions.regional_strategy_variables[
region.name]
else:
sig_param_tech = assumptions.ss_sig_param_tech[enduse][sector]
strategy_variables = assumptions.strategy_variables
# ------------------------------------------------------
# Create submodel
# ------------------------------------------------------
submodel = endusefunctions.Enduse(
submodel='ss_submodel',
region=region.name,
scenario_data=scenario_data,
assumptions=assumptions,
regional_lp_stock=weather_region.ss_load_profiles,
non_regional_lp_stock=non_regional_lp_stock,
base_yr=assumptions.base_yr,
curr_yr=assumptions.curr_yr,
enduse=enduse,
sector=sector,
fuel=region.ss_enduses_sectors_fuels[enduse][sector],
tech_stock=weather_region.ss_tech_stock,
heating_factor_y=weather_region.f_heat_ss_y,
cooling_factor_y=weather_region.f_cooling_ss_y,
fuel_fueltype_tech_p_by=assumptions.ss_fuel_tech_p_by[enduse]
[sector],
sig_param_tech=sig_param_tech,
criterias=criterias,
strategy_variables=strategy_variables,
fueltypes_nr=lookups['fueltypes_nr'],
fueltypes=lookups['fueltypes'],
model_yeardays_nrs=assumptions.model_yeardays_nrs,
enduse_overall_change=assumptions.enduse_overall_change,
dw_stock=ss_dw_stock)
# Add to list
submodels.append(submodel)
return submodels