def energy_demand_model(
regions,
data,
criterias,
assumptions,
weather_stations,
weather_yr,
weather_by
):
"""Main function of energy demand model to calculate yearly demand
Arguments
----------
regions : list
Regions
data : dict
Data container
assumptions : dict
Assumptions
weather_yr: int
Year of weather data
Returns
-------
result_dict : dict
A nested dictionary containing all data for energy supply model with
timesteps for every hour in a year.
[fueltype : region : timestep]
modelrun_obj : dict
Object of a yearly model run
Note
----
This function is executed in the wrapper
"""
logging.info("... Number of modelled regions: %s", len(regions))
modelrun = model.EnergyDemandModel(
regions=regions,
data=data,
criterias=criterias,
assumptions=assumptions,
weather_stations=weather_stations,
weather_yr=weather_yr,
weather_by=weather_by)
# Calculate base year demand
fuels_in = testing_functions.test_function_fuel_sum(
data, data['fuel_disagg'], criterias['mode_constrained'], assumptions.enduse_space_heating)
# Log model results
write_data.logg_info(modelrun, fuels_in, data)
return modelrun
def energy_demand_model(data):
"""Main function of energy demand model to calculate yearly demand
Parameters
----------
data : dict
Data container
Returns
-------
result_dict : dict
A nested dictionary containing all data for energy supply model with
timesteps for every hour in a year.
[fuel_type : region : timestep]
model_run_object : dict
Object of a yearly model run
Note
----
This function is executed in the wrapper
"""
fuel_in, fuel_in_elec, _ = testing.test_function_fuel_sum(data)
# Add all region instances as an attribute (region name) into the class `EnergyModel`
model_run_object = energy_model.EnergyModel(
region_names=data['lu_reg'],
data=data,
)
# Total fuel of country
fueltot = model_run_object.sum_uk_fueltypes_enduses_y
print("================================================")
print("Simulation year: " + str(model_run_object.curr_yr))
print("Number of regions " + str(len(data['lu_reg'])))
print("Fuel input: " + str(fuel_in))
print("Fuel output: " + str(fueltot))
print("FUEL DIFFERENCE: " + str(round((fueltot - fuel_in), 4)))
print("elec fuel in: " + str(fuel_in_elec))
print("elec fuel out: " + str(np.sum(model_run_object.all_submodels_sum_uk_specfuelype_enduses_y[2])))
print("ele fueld diff: " + str(round(fuel_in_elec - np.sum(model_run_object.all_submodels_sum_uk_specfuelype_enduses_y[2]), 4))) #ithout transport
print("================================================")
for fff in range(8):
print("FF: " + str(np.sum(model_run_object.all_submodels_sum_uk_specfuelype_enduses_y[fff])))
# # --- Write to csv and YAML Convert data according to region and fueltype
#result_dict = read_data.convert_out_format_es(data, model_run_object, ['rs_submodel', 'ss_submodel', 'is_submodel', 'ts_submodel'])
###write_data.write_final_result(data, result_dict, model_run_object.curr_yr, data['lu_reg'], False)
print("...finished energy demand model simulation")
return _, model_run_object
def energy_demand_model(data, assumptions, fuel_in=0, fuel_in_elec=0):
"""Main function of energy demand model to calculate yearly demand
Arguments
----------
data : dict
Data container
Returns
-------
result_dict : dict
A nested dictionary containing all data for energy supply model with
timesteps for every hour in a year.
[fueltype : region : timestep]
modelrun_obj : dict
Object of a yearly model run
Note
----
This function is executed in the wrapper
"""
modelrun_obj = model.EnergyDemandModel(regions=data['regions'],
data=data,
assumptions=assumptions)
# Calculate base year demand
fuel_in, fuel_in_biomass, fuel_in_elec, fuel_in_gas, fuel_in_heat, fuel_in_hydrogen, fuel_in_solid_fuel, fuel_in_oil, tot_heating = testing.test_function_fuel_sum(
data, data['criterias']['mode_constrained'],
assumptions.enduse_space_heating)
print("================================================")
print("Simulation year: " + str(modelrun_obj.curr_yr))
print("Number of regions " + str(data['reg_nrs']))
print(" TOTAL KTOE: " + str(conversions.gwh_to_ktoe(fuel_in)))
print("-----------------")
print("[GWh] Total fuel input: " + str(fuel_in))
print("[GWh] Total output: " +
str(np.sum(modelrun_obj.ed_fueltype_national_yh)))
print("[GWh] Total difference: " + str(
round((np.sum(modelrun_obj.ed_fueltype_national_yh) - fuel_in), 4)))
print("-----------")
print("[GWh] oil fuel in: " + str(fuel_in_oil))
print("[GWh] oil fuel out: " + str(
np.sum(modelrun_obj.ed_fueltype_national_yh[data['lookups']
['fueltypes']['oil']])))
print("[GWh] oil diff: " + str(
round(
np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['oil']]) - fuel_in_oil, 4)))
print("-----------")
print("[GWh] biomass fuel in: " + str(fuel_in_biomass))
print("[GWh] biomass fuel out: " + str(
np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['biomass']])))
print("[GWh] biomass diff: " + str(
round(
np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['biomass']]) -
fuel_in_biomass, 4)))
print("-----------")
print("[GWh] solid_fuel fuel in: " + str(fuel_in_solid_fuel))
print("[GWh] solid_fuel fuel out: " + str(
np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['solid_fuel']])))
print("[GWh] solid_fuel diff: " + str(
round(
np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['solid_fuel']]) -
fuel_in_solid_fuel, 4)))
print("-----------")
print("[GWh] elec fuel in: " + str(fuel_in_elec))
print("[GWh] elec fuel out: " + str(
np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['electricity']])))
print("[GWh] ele fuel diff: " + str(
round(
np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['electricity']]) -
fuel_in_elec, 4)))
print("-----------")
print("[GWh] gas fuel in: " + str(fuel_in_gas))
print("[GWh] gas fuel out: " + str(
np.sum(modelrun_obj.ed_fueltype_national_yh[data['lookups']
['fueltypes']['gas']])))
print("[GWh] gas diff: " + str(
round(
np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['gas']]) - fuel_in_gas, 4)))
print("-----------")
print("[GWh] hydro fuel in: " + str(fuel_in_hydrogen))
print("[GWh] hydro fuel out: " + str(
np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['hydrogen']])))
print("[GWh] hydro diff: " + str(
round(
np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['hydrogen']]) -
fuel_in_hydrogen, 4)))
print("-----------")
print("TOTAL HEATING " + str(tot_heating))
print("[GWh] heat fuel in: " + str(fuel_in_heat))
print("[GWh] heat fuel out: " + str(
np.sum(modelrun_obj.ed_fueltype_national_yh[data['lookups']
['fueltypes']['heat']])))
print("[GWh] heat diff: " + str(
round(
np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['heat']]) - fuel_in_heat, 4)))
print("-----------")
print("Diff elec %: " + str(
round((np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['electricity']]) / fuel_in_elec), 4)))
print("Diff gas %: " + str(
round((np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['gas']]) / fuel_in_gas), 4)))
print("Diff oil %: " + str(
round((np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['oil']]) / fuel_in_oil), 4)))
print("Diff solid_fuel %: " + str(
round((np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['solid_fuel']]) /
fuel_in_solid_fuel), 4)))
print("Diff hydrogen %: " + str(
round((np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['hydrogen']]) /
fuel_in_hydrogen), 4)))
print("Diff biomass %: " + str(
round((np.sum(modelrun_obj.ed_fueltype_national_yh[
data['lookups']['fueltypes']['biomass']]) / fuel_in_biomass), 4)))
print("================================================")
logging.info("...finished running energy demand model simulation")
return modelrun_obj
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)
# --------------------
# Result unconstrained
#
# Sum according to first element in array (sectors)
# which aggregtes over the sectors
# ---
supply_results_unconstrained = sum(