CERC/costs
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checked units

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Pilar Monsalvete 2023-08-08 15:40:39 -04:00
parent 47ff19a842
commit d8c0644709
1 changed files with 7 additions and 4 deletions
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11
costs/total_operational_costs.py
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@ -20,6 +20,7 @@ class TotalOperationalCosts(CostBase):
""" """
End of life costs class End of life costs class
""" """
def __init__(self, building: Building, configuration: Configuration): def __init__(self, building: Building, configuration: Configuration):
super().__init__(building, configuration) super().__init__(building, configuration)
self._yearly_operational_costs = pd.DataFrame( self._yearly_operational_costs = pd.DataFrame(
@ -48,11 +49,12 @@ class TotalOperationalCosts(CostBase):
variable_gas_cost_year_0 = 0 variable_gas_cost_year_0 = 0
electricity_heating = 0 electricity_heating = 0
domestic_hot_water_electricity = 0 domestic_hot_water_electricity = 0
# todo: each fuel has different units that have to be processed
if self._configuration.fuel_type == 1: if self._configuration.fuel_type == 1:
fixed_gas_cost_year_0 = archetype.operational_cost.fuels[1].fixed_monthly * 12 * factor_residential fixed_gas_cost_year_0 = archetype.operational_cost.fuels[1].fixed_monthly * 12 * factor_residential
variable_gas_cost_year_0 = ( variable_gas_cost_year_0 = (
(building.heating_consumption[cte.YEAR][0] + building.domestic_hot_water_consumption[cte.YEAR][0]) / 1000 * (building.heating_consumption[cte.YEAR][0] + building.domestic_hot_water_consumption[cte.YEAR][0])
archetype.operational_cost.fuels[1].variable[0] / 1000 * cte.WATTS_HOUR_TO_JULES * archetype.operational_cost.fuels[1].variable[0]
) )
if self._configuration.fuel_type == 0: if self._configuration.fuel_type == 0:
electricity_heating = building.heating_consumption[cte.YEAR][0] / 1000 electricity_heating = building.heating_consumption[cte.YEAR][0] / 1000
@ -70,8 +72,9 @@ class TotalOperationalCosts(CostBase):
# todo: change when peak electricity demand is coded. Careful with factor residential # todo: change when peak electricity demand is coded. Careful with factor residential
peak_electricity_load = PeakLoad(building).electricity_peak_load peak_electricity_load = PeakLoad(building).electricity_peak_load
peak_load_value = peak_electricity_load.max(axis=1) peak_load_value = peak_electricity_load.max(axis=1)
peak_electricity_demand = peak_load_value[1]/1000 # self._peak_electricity_demand adapted to kW peak_electricity_demand = peak_load_value[1] / 1000 # self._peak_electricity_demand adapted to kW
variable_electricity_cost_year_0 = total_electricity_consumption * archetype.operational_cost.fuels[0].variable[0] variable_electricity_cost_year_0 = \
total_electricity_consumption * cte.WATTS_HOUR_TO_JULES * archetype.operational_cost.fuels[0].variable[0]
peak_electricity_cost_year_0 = peak_electricity_demand * archetype.operational_cost.fuels[0].fixed_power * 12 peak_electricity_cost_year_0 = peak_electricity_demand * archetype.operational_cost.fuels[0].fixed_power * 12
monthly_electricity_cost_year_0 = archetype.operational_cost.fuels[0].fixed_monthly * 12 * factor_residential monthly_electricity_cost_year_0 = archetype.operational_cost.fuels[0].fixed_monthly * 12 * factor_residential