region_selection = read_data.get_region_selection(
os.path.join(
data['local_paths']['local_path_datafolder'],
"region_definitions",
config['CRITERIA']['reg_selection_csv_name']))
#region_selection = ['E02003237', 'E02003238']
setattr(data['assumptions'], 'reg_nrs', len(region_selection))
else:
region_selection = data['regions']
# -------------------------------------------
# Create .ini file with simulation information
# -------------------------------------------
write_data.write_simulation_inifile(
path_new_scenario,
data,
region_selection)
# Write population data to file
for sim_yr in data['assumptions'].sim_yrs:
write_data.write_scenaric_population_data(
sim_yr,
os.path.join(path_new_scenario, 'model_run_pop'),
list(data['scenario_data']['population'][sim_yr].values()))
# -----------------------
# Main model run function
# -----------------------
for sim_yr in data['assumptions'].sim_yrs:
print("Local simulation for year: " + str(sim_yr))
def load_data_before_simulation(data, sim_yrs, config, curr_yr):
# ---------
# Configuration
# -----------
base_yr = config['CONFIG']['base_yr']
weather_yr_scenario = config['CONFIG']['weather_yr_scenario']
path_new_scenario = config['PATHS']['path_new_scenario']
data['data_path'] = os.path.normpath(config['PATHS']['path_local_data'])
data['processed_path'] = os.path.normpath(
config['PATHS']['path_processed_data'])
data['result_path'] = os.path.normpath(config['PATHS']['path_result_data'])
data['paths'] = config['CONFIG_DATA']
# Downloaded (FTP) data
data['local_paths'] = config['DATA_PATHS']
# ------------------------------------------------
# Load Inputs
# ------------------------------------------------
data['enduses'], data['sectors'], data['fuels'], lookup_enduses, \
lookup_sector_enduses = data_loader.load_fuels(config['CONFIG_DATA'])
# ------------------------------------------------
# Load Assumptions
# ------------------------------------------------
data['assumptions'] = general_assumptions.Assumptions(
lookup_enduses=lookup_enduses,
lookup_sector_enduses=lookup_sector_enduses,
base_yr=base_yr,
weather_by=config['CONFIG']['user_defined_weather_by'],
simulation_end_yr=config['CONFIG']['user_defined_simulation_end_yr'],
curr_yr=curr_yr,
sim_yrs=sim_yrs,
paths=config['CONFIG_DATA'],
enduses=data['enduses'],
sectors=data['sectors'],
reg_nrs=len(data['regions']))
# ------------------------------------------
# Make selection of regions to model
# ------------------------------------------
if config['CRITERIA']['reg_selection']:
region_selection = read_data.get_region_selection(
os.path.join(config['DATA_PATHS']['local_path_datafolder'],
"region_definitions",
config['CRITERIA']['reg_selection_csv_name']))
#region_selection = ['E02003237', 'E02003238']
setattr(data['assumptions'], 'reg_nrs', len(region_selection))
else:
region_selection = data['regions']
# Create .ini file with simulation parameter
write_data.write_simulation_inifile(path_new_scenario, data,
region_selection)
# -------------------------------------------
# Weather year specific initialisations
# -------------------------------------------
path_folder_weather_yr = os.path.join(
os.path.join(path_new_scenario,
str(weather_yr_scenario) + "__" + "all_stations"))
data['weather_result_paths'] = basic_functions.get_result_paths(
path_folder_weather_yr)
folders_to_create = [
path_folder_weather_yr, data['weather_result_paths']['data_results'],
data['weather_result_paths']['data_results_PDF'],
data['weather_result_paths']['data_results_validation'],
data['weather_result_paths']['data_results_model_run_results_txt']
]
for folder in folders_to_create:
basic_functions.create_folder(folder)
# ------------------------------------------------
# Load load profiles of technologies
# ------------------------------------------------
data['tech_lp'] = data_loader.load_data_profiles(
config['CONFIG_DATA'], config['DATA_PATHS'],
data['assumptions'].model_yeardays,
data['assumptions'].model_yeardays_daytype)
# Obtain population data for disaggregation
if config['CRITERIA']['msoa_crit']:
name_population_dataset = config['DATA_PATHS'][
'path_population_data_for_disaggregation_msoa']
else:
name_population_dataset = config['DATA_PATHS'][
'path_population_data_for_disaggregation_lad']
data['pop_for_disag'] = data_loader.read_scenario_data(
name_population_dataset, region_name='region', value_name='value')
# ------------------------------------------------
# Load building related data
# ------------------------------------------------
if config['CRITERIA']['virtual_building_stock_criteria']:
data['scenario_data']['floor_area']['rs_floorarea'], data[
'scenario_data']['floor_area']['ss_floorarea'], data[
'service_building_count'], rs_regions_without_floorarea, ss_regions_without_floorarea = data_loader.floor_area_virtual_dw(
data['regions'],
data['sectors'],
config['DATA_PATHS'],
data['scenario_data']['population'][
data['assumptions'].base_yr],
base_yr=data['assumptions'].base_yr)
# Add all areas with no floor area data
data['assumptions'].update("rs_regions_without_floorarea",
rs_regions_without_floorarea)
data['assumptions'].update("ss_regions_without_floorarea",
ss_regions_without_floorarea)
else:
# ------------------------------------------------
# Load floor area directly from scenario
# ------------------------------------------------
data['scenario_data']['floor_area']['rs_floorarea'] = {}
data['scenario_data']['floor_area']['rs_floorarea'] = data[
'scenario_data']['rs_floorarea']
data['scenario_data']['floor_area']['ss_floorarea'] = data[
'scenario_data']['ss_floorarea']
data['scenario_data']['service_building_count'][
data['assumptions'].base_yr] = {}
return data
print("... Load data from script calculations")
data = read_data.load_script_data(data) #SCENARIO INITIALISATION
#-------------------
# Folder cleaning
#--------------------
print("... delete previous model run results")
basic_functions.del_previous_setup(data['result_paths']['data_results'])
basic_functions.create_folder(data['result_paths']['data_results'])
basic_functions.create_folder(data['result_paths']['data_results_PDF'])
basic_functions.create_folder(
data['result_paths']['data_results_model_run_pop'])
# Create .ini file with simulation information
write_data.write_simulation_inifile(data['result_paths']['data_results'],
data['enduses'], data['assumptions'],
data['reg_nrs'], data['regions'])
for sim_yr in data['assumptions'].simulated_yrs:
setattr(data['assumptions'], 'curr_yr', sim_yr)
print("Simulation for year --------------: " + str(sim_yr))
fuel_in, fuel_in_biomass, fuel_in_elec, fuel_in_gas, fuel_in_heat, fuel_in_hydro, fuel_in_solid_fuel, fuel_in_oil, tot_heating = testing.test_function_fuel_sum(
data, data['criterias']['mode_constrained'],
data['assumptions'].enduse_space_heating)
a = datetime.datetime.now()
# Main model run function
modelrun_obj = energy_demand_model(data, data['assumptions'], fuel_in,
fuel_in_elec)