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Operating Costs Sub-Module

t3co.cost_models.operating_costs

OperatingCosts

Source code in src/t3co/cost_models/operating_costs.py 
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class OperatingCosts:
    fuel_cost_dol_per_yr: float = 0.0
    fuel_price_dol_per_gge: float = 0.0
    fuel_used_gal_gge_per_yr: float = 0.0
    fuel_used_gal_gde_per_yr: float = 0.0
    energy_used_kwh_per_yr: float = 0.0
    maintenance_cost_dol_per_yr: float = 0.0
    maintenance_cost_dol_per_mi: float = 0.0
    insurance_cost_dol_per_yr: float = 0.0
    distance_traveled_mi_per_yr: float = 0.0
    purchasing_payment_dol_per_yr: float = 0.0
    purchasing_tax_amount_dol_per_year: float = 0.0
    purchasing_cost_dol_per_yr: float = 0.0
    purchasing_remaining_principal_dol: float = 0.0
    fueling_dwell_labor_cost_dol_per_yr: float = 0.0
    net_oper_cost_dol_per_yr: float = 0.0
    disc_oper_cost_dol_per_yr: float = 0.0

    def __new__(cls, *args, **kwargs):
        """
        Creates a new instance of the OperatingCosts class.
        """
        instance = super(OperatingCosts, cls).__new__(cls)
        return instance

    def __init__(
        self,
        year_number: int,
        cap_costs: CapitalCosts,
        vehicle: Vehicle,
        scenario: Scenario,
        energy: Energy = None,
        oppy_costs: OpportunityCosts = None,
    ):
        """
        Initializes the OperatingCosts instance.

        Args:
            year_number (int): The year number for which the operating costs are calculated.
            cap_costs (CapitalCosts): The capital costs associated with the vehicle.
            vehicle (Vehicle): The vehicle instance.
            scenario (Scenario): The scenario instance containing configuration data.
            energy (Energy, optional): The energy model instance. Defaults to None.
            oppy_costs (OpportunityCosts, optional): The opportunity costs associated with the vehicle. Defaults to None.
        """
        if energy:
            self.mpgge = energy.mpgge
        self.distance_traveled_mi_per_yr = scenario.vmt[year_number - 1]

        if scenario.cost_toggles.fuel_cost:
            self.set_fuel_cost(
                year_number=year_number, vehicle=vehicle, scenario=scenario
            )
        if scenario.cost_toggles.maintenance_oper_cost:
            self.set_maintenance_oper_cost(
                year_number=year_number, vehicle=vehicle, scenario=scenario
            )
        if scenario.cost_toggles.insurance_cost:
            self.set_insurance_cost(
                year_number=year_number,
                cap_cost=cap_costs,
                vehicle=vehicle,
                scenario=scenario,
            )
        if scenario.cost_toggles.fueling_dwell_labor:
            if scenario.activate_tco_fueling_dwell_time_cost and oppy_costs:
                self.set_fueling_dwell_labor_cost(
                    scenario=scenario, oppy_costs=oppy_costs
                )
            else:
                self.fueling_dwell_labor_cost_dol_per_yr = 0.0
        if scenario.cost_toggles.purchasing_cost:
            self.set_purchasing_payment_cost(
                year_number=year_number, scenario=scenario, cap_costs=cap_costs
            )
        self.set_net_oper_cost()
        self.set_disc_oper_cost(year_number=year_number, scenario=scenario)

    def set_fuel_cost(
        self, year_number: int, vehicle: Vehicle, scenario: Scenario
    ) -> None:
        """
        Sets the fuel cost for the given year.

        This method calculates the fuel cost based on the fuel price and the amount of fuel used.
        The calculation uses the following OperatingCosts elements:
        - distance_traveled_mi_per_yr
        - mpgge

        Inputs from scenario:
        - fuel_prices_df
        - fuel_type
        - model_year
        - region

        Estimated class variables:
        - fuel_price_dol_per_gge
        - fuel_used_gal_gge_per_yr
        - fuel_used_gal_gde_per_yr
        - energy_used_kwh_per_yr
        - fuel_cost_dol_per_yr

        Args:
            year_number (int): The year number for which the fuel cost is calculated.
            vehicle (Vehicle): The vehicle instance.
            scenario (Scenario): The scenario instance containing configuration data.
        """
        if scenario.fuel_prices_df is None:
            scenario.fuel_prices_df = pd.read_csv(
                get_path_object(scenario.fuel_prices_file)
            )
            scenario.fuel_prices_df.set_index("Fuel", inplace=True)

        scenario.fuel_prices_df = scenario.fuel_prices_df[
            scenario.fuel_prices_df["Region"] == scenario.region
        ]

        if (
            "diesel" in scenario.fuel_type.lower()
            and "bio" not in scenario.fuel_type.lower()
        ):
            diesel_dol_per_gal = scenario.fuel_prices_df.loc[
                "diesel_dol_per_gal", str(scenario.model_year + year_number - 1)
            ]
            self.fuel_price_dol_per_gge = diesel_dol_per_gal * gl.DGE_TO_GGE
        elif "gasoline" in scenario.fuel_type.lower():
            gasoline_dol_per_gal = scenario.fuel_prices_df.loc[
                "gasoline_dol_per_gal", str(scenario.model_year + year_number - 1)
            ]
            self.fuel_price_dol_per_gge = gasoline_dol_per_gal
        elif "electricity" in scenario.fuel_type.lower():
            electricity_dol_per_kwh = scenario.fuel_prices_df.loc[
                "electricity_dol_per_kwh", str(scenario.model_year + year_number - 1)
            ]
            self.fuel_price_dol_per_gge = electricity_dol_per_kwh * gl.KWH_PER_GGE
        elif scenario.fuel_type.lower() == "cng":
            cng_dol_per_gge = scenario.fuel_prices_df.loc[
                "cng_dol_per_gge", str(scenario.model_year + year_number - 1)
            ]
            self.fuel_price_dol_per_gge = cng_dol_per_gge
        elif scenario.fuel_type.lower() == "hydrogen":
            hydrogen_dol_per_gge = scenario.fuel_prices_df.loc[
                "hydrogen_dol_per_gge", str(scenario.model_year + year_number - 1)
            ]
            self.fuel_price_dol_per_gge = hydrogen_dol_per_gge
        else:
            raise Exception(
                f"Operating Costs calculation: Unknown fuel type {scenario.fuel_type}"
            )

        if self.mpgge and self.mpgge > 0:
            self.fuel_used_gal_gge_per_yr = (
                self.distance_traveled_mi_per_yr / self.mpgge
            )
            self.fuel_used_gal_gde_per_yr = (
                self.fuel_used_gal_gge_per_yr / gl.DGE_TO_GGE
            )
            self.energy_used_kwh_per_yr = self.fuel_used_gal_gge_per_yr * gl.KWH_PER_GGE

            self.fuel_cost_dol_per_yr = (
                self.fuel_price_dol_per_gge * self.fuel_used_gal_gge_per_yr
            )
        else:
            self.fuel_used_gal_gge_per_yr = 0
            self.fuel_used_gal_gde_per_yr = 0
            self.energy_used_kwh_per_yr = 0
            self.fuel_cost_dol_per_yr = 0
            # print(f"Warning: mpgge is {self.mpgge}. Fuel cost set to 0.")

    def set_maintenance_oper_cost(
        self, year_number: int, vehicle: Vehicle, scenario: Scenario
    ) -> None:
        """
        Sets the maintenance operating cost for the given year.

        This method calculates the maintenance cost based on the maintenance cost per mile and the distance traveled.

        Inputs from scenario:
        - maint_oper_cost_dol_per_mi
        - vmt

        Estimated class variables:
        - maintenance_cost_dol_per_mi
        - maintenance_cost_dol_per_yr

        Args:
            year_number (int): The year number for which the maintenance cost is calculated.
            vehicle (Vehicle): The vehicle instance.
            scenario (Scenario): The scenario instance containing configuration data.
        """
        self.maintenance_cost_dol_per_mi = scenario.maint_oper_cost_dol_per_mi[
            year_number - 1
        ]

        self.maintenance_cost_dol_per_yr = (
            self.maintenance_cost_dol_per_mi * self.distance_traveled_mi_per_yr
        )

    def set_insurance_cost(
        self,
        year_number: int,
        cap_cost: CapitalCosts,
        vehicle: Vehicle,
        scenario: Scenario,
    ) -> None:
        """
        Sets the insurance cost for the given year.

        This method calculates the insurance cost based on the insurance rate and the total value of the vehicle.

        Inputs from scenario:
        - insurance_rates_pct_per_yr

        Inputs from cap_cost:
        - msrp_total_dol

        Estimated class variables:
        - insurance_cost_dol_per_yr

        Args:
            year_number (int): The year number for which the insurance cost is calculated.
            cap_cost (CapitalCosts): The capital costs associated with the vehicle.
            vehicle (Vehicle): The vehicle instance.
            scenario (Scenario): The scenario instance containing configuration data.
        """
        self.insurance_rates_pct_per_yr = (
            ast.literal_eval(scenario.insurance_rates_pct_per_yr)[year_number - 1]
            if isinstance(scenario.insurance_rates_pct_per_yr, str)
            else scenario.insurance_rates_pct_per_yr[year_number - 1]
        )

        self.insurance_cost_dol_per_yr = (
            cap_cost.msrp_total_dol * self.insurance_rates_pct_per_yr
        )

    def set_purchasing_payment_cost(
        self, year_number: int, scenario: Scenario, cap_costs: CapitalCosts
    ):
        """
        Sets the purchasing payment cost for the given year.

        This method calculates the purchasing payment cost based on the purchasing method specified in the scenario.

        Inputs from scenario:
        - purchasing_method
        - purchasing_interest_apr_pct_per_yr
        - purchasing_payment_frequency_months
        - purchasing_term_yr
        - tax_rate_pct
        - leasing_money_factor

        Inputs from cap_costs:
        - purchasing_initial_principal_dol
        - msrp_total_dol
        - purchase_tax_dol
        - purchasing_downpayment_dol
        - residual_cost_dol

        Estimated OperatingCosts variables:
        - purchasing_payment_dol_per_yr
        - purchasing_cost_dol_per_yr
        - purchasing_remaining_principal_dol
        - purchasing_tax_amount_dol_per_year

        Args:
            year_number (int): The year number for which the purchasing payment cost is calculated.
            scenario (Scenario): The scenario instance containing configuration data, including the purchasing method, interest rate, and term.
            cap_costs (CapitalCosts): The capital costs associated with the vehicle.
        """
        if scenario.purchasing_method == "cash":
            self.purchasing_payment_dol_per_yr = 0
            self.purchasing_cost_dol_per_yr = 0

        elif scenario.purchasing_method == "loan":
            if (
                scenario.purchasing_term_yr <= 0
                or scenario.purchasing_payment_frequency_months <= 0
            ):
                self.purchasing_payment_dol_per_yr = 0
                self.purchasing_cost_dol_per_yr = 0
                self.purchasing_remaining_principal_dol = 0
                return

            interest_rate_pct_per_frequency = (
                scenario.purchasing_interest_apr_pct_per_yr
                / 12
                * scenario.purchasing_payment_frequency_months
            )
            total_number_of_payments = int(
                scenario.purchasing_term_yr
                * 12
                / scenario.purchasing_payment_frequency_months
            )  # TODO check for missing payment
            annual_number_of_payments = int(
                12 / scenario.purchasing_payment_frequency_months
            )

            purchasing_payment_dol_per_freq = (
                cap_costs.purchasing_initial_principal_dol
                * interest_rate_pct_per_frequency
                * (1 + interest_rate_pct_per_frequency) ** total_number_of_payments
            ) / ((1 + interest_rate_pct_per_frequency) ** total_number_of_payments - 1)

            self.purchasing_remaining_principal_dol = (
                cap_costs.purchasing_initial_principal_dol
                * (1 + interest_rate_pct_per_frequency)
                ** (year_number * annual_number_of_payments)
            ) - purchasing_payment_dol_per_freq / interest_rate_pct_per_frequency * (
                (1 + interest_rate_pct_per_frequency)
                ** (year_number * annual_number_of_payments)
                - 1
            )

            self.purchasing_cost_dol_per_yr = sum(
                [
                    interest_rate_pct_per_frequency
                    * (
                        cap_costs.purchasing_initial_principal_dol
                        * (1 + interest_rate_pct_per_frequency) ** n
                        - purchasing_payment_dol_per_freq
                        / interest_rate_pct_per_frequency
                        * ((1 + interest_rate_pct_per_frequency) ** n - 1)
                    )
                    for n in range(
                        (year_number - 1) * annual_number_of_payments,
                        (year_number * annual_number_of_payments + 1),
                    )
                ]
            )

            self.purchasing_payment_dol_per_yr = (
                purchasing_payment_dol_per_freq * annual_number_of_payments
            )

        elif scenario.purchasing_method == "lease":
            if scenario.purchasing_term_yr <= 0:
                self.purchasing_payment_dol_per_yr = 0
                self.purchasing_cost_dol_per_yr = 0
                self.purchasing_tax_amount_dol_per_year = 0
                return

            adjusted_cap_cost_dol = (
                cap_costs.msrp_total_dol
                + cap_costs.purchase_tax_dol
                - cap_costs.purchasing_downpayment_dol
            )
            depreciation_cost_dol_per_month = (
                adjusted_cap_cost_dol + cap_costs.residual_cost_dol
            ) / (scenario.purchasing_term_yr * 12)
            finance_fee_dol_per_month = (
                adjusted_cap_cost_dol - cap_costs.residual_cost_dol
            ) * scenario.leasing_money_factor
            self.purchasing_tax_amount_dol_per_year = (
                (depreciation_cost_dol_per_month + finance_fee_dol_per_month)
                * scenario.tax_rate_pct
                * 12
            )
            self.purchasing_payment_dol_per_yr = (
                depreciation_cost_dol_per_month
                + finance_fee_dol_per_month
                + self.purchasing_tax_amount_dol_per_year / 12
            ) * 12
            self.purchasing_cost_dol_per_yr = finance_fee_dol_per_month * 12

    def set_fueling_dwell_labor_cost(
        self, scenario: Scenario, oppy_costs: OpportunityCosts
    ) -> None:
        """
        Sets the fueling dwell labor cost for the given year.

        This method calculates the fueling dwell labor cost based on the fueling dwell time and the labor rate.

        Inputs from scenario:
        - labor_rate_dol_per_hr

        Inputs from oppy_costs:
        - fueling_dwell_time_hr_per_yr

        Estimated OperatingCosts variables:
        - fueling_dwell_labor_cost_dol_per_yr

        Args:
            scenario (Scenario): The scenario instance containing configuration data.
            oppy_costs (OpportunityCosts): The opportunity costs associated with the vehicle.
        """
        self.fueling_dwell_labor_cost_dol_per_yr = (
            oppy_costs.fueling_dwell_time_hr_per_yr * scenario.labor_rate_dol_per_hr
        )

    def set_net_oper_cost(self) -> None:
        """
        Sets the net operating cost for the given year.

        This method calculates the net operating cost by summing the various operating cost components.
        The calculation uses the following OperatingCosts elements:
        - fuel_cost_dol_per_yr
        - fueling_dwell_labor_cost_dol_per_yr
        - maintenance_cost_dol_per_yr
        - insurance_cost_dol_per_yr
        - purchasing_payment_dol_per_yr

        Estimated OperatingCosts variables:
        - net_oper_cost_dol_per_yr
        """
        self.net_oper_cost_dol_per_yr = (
            self.fuel_cost_dol_per_yr
            + self.fueling_dwell_labor_cost_dol_per_yr
            + self.maintenance_cost_dol_per_yr
            + self.insurance_cost_dol_per_yr
            + self.purchasing_payment_dol_per_yr
        )

    def set_disc_oper_cost(self, year_number: int, scenario: Scenario) -> None:
        """
        Sets the discounted operating cost for the given year.

        This method calculates the discounted operating cost based on the net operating cost and the discount rate.
        The calculation uses the following OperatingCosts elements:
        - net_oper_cost_dol_per_yr

        Inputs from scenario:
        - discount_rate_pct_per_yr

        Estimated OperatingCosts variables:
        - disc_oper_cost_dol_per_yr

        Args:
            year_number (int): The year number for which the discounted operating cost is calculated.
            scenario (Scenario): The scenario instance containing configuration data.
        """
        self.disc_oper_cost_dol_per_yr = scenario.get_discounted_value(
            value=self.net_oper_cost_dol_per_yr, year_number=year_number
        )

    def __str__(self) -> str:
        """
        Returns a string representation of the OperatingCosts instance.

        Returns:
            str: String representation of the OperatingCosts instance.
        """
        return obj_to_string(self)

__new__(*args, **kwargs)

Creates a new instance of the OperatingCosts class.

Source code in src/t3co/cost_models/operating_costs.py 
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def __new__(cls, *args, **kwargs):
    """
    Creates a new instance of the OperatingCosts class.
    """
    instance = super(OperatingCosts, cls).__new__(cls)
    return instance

__init__(year_number, cap_costs, vehicle, scenario, energy=None, oppy_costs=None)

Initializes the OperatingCosts instance.

Parameters:

Name Type Description Default
year_number int

The year number for which the operating costs are calculated.

 required
cap_costs CapitalCosts

The capital costs associated with the vehicle.

 required
vehicle Vehicle

The vehicle instance.

 required
scenario Scenario

The scenario instance containing configuration data.

 required
energy Energy

The energy model instance. Defaults to None.

 None
oppy_costs OpportunityCosts

The opportunity costs associated with the vehicle. Defaults to None.

 None
Source code in src/t3co/cost_models/operating_costs.py 
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def __init__(
    self,
    year_number: int,
    cap_costs: CapitalCosts,
    vehicle: Vehicle,
    scenario: Scenario,
    energy: Energy = None,
    oppy_costs: OpportunityCosts = None,
):
    """
    Initializes the OperatingCosts instance.

    Args:
        year_number (int): The year number for which the operating costs are calculated.
        cap_costs (CapitalCosts): The capital costs associated with the vehicle.
        vehicle (Vehicle): The vehicle instance.
        scenario (Scenario): The scenario instance containing configuration data.
        energy (Energy, optional): The energy model instance. Defaults to None.
        oppy_costs (OpportunityCosts, optional): The opportunity costs associated with the vehicle. Defaults to None.
    """
    if energy:
        self.mpgge = energy.mpgge
    self.distance_traveled_mi_per_yr = scenario.vmt[year_number - 1]

    if scenario.cost_toggles.fuel_cost:
        self.set_fuel_cost(
            year_number=year_number, vehicle=vehicle, scenario=scenario
        )
    if scenario.cost_toggles.maintenance_oper_cost:
        self.set_maintenance_oper_cost(
            year_number=year_number, vehicle=vehicle, scenario=scenario
        )
    if scenario.cost_toggles.insurance_cost:
        self.set_insurance_cost(
            year_number=year_number,
            cap_cost=cap_costs,
            vehicle=vehicle,
            scenario=scenario,
        )
    if scenario.cost_toggles.fueling_dwell_labor:
        if scenario.activate_tco_fueling_dwell_time_cost and oppy_costs:
            self.set_fueling_dwell_labor_cost(
                scenario=scenario, oppy_costs=oppy_costs
            )
        else:
            self.fueling_dwell_labor_cost_dol_per_yr = 0.0
    if scenario.cost_toggles.purchasing_cost:
        self.set_purchasing_payment_cost(
            year_number=year_number, scenario=scenario, cap_costs=cap_costs
        )
    self.set_net_oper_cost()
    self.set_disc_oper_cost(year_number=year_number, scenario=scenario)

set_fuel_cost(year_number, vehicle, scenario)

Sets the fuel cost for the given year.

This method calculates the fuel cost based on the fuel price and the amount of fuel used. The calculation uses the following OperatingCosts elements: - distance_traveled_mi_per_yr - mpgge

Inputs from scenario: - fuel_prices_df - fuel_type - model_year - region

Estimated class variables: - fuel_price_dol_per_gge - fuel_used_gal_gge_per_yr - fuel_used_gal_gde_per_yr - energy_used_kwh_per_yr - fuel_cost_dol_per_yr

Parameters:

Name Type Description Default
year_number int

The year number for which the fuel cost is calculated.

 required
vehicle Vehicle

The vehicle instance.

 required
scenario Scenario

The scenario instance containing configuration data.

 required
Source code in src/t3co/cost_models/operating_costs.py 
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def set_fuel_cost(
    self, year_number: int, vehicle: Vehicle, scenario: Scenario
) -> None:
    """
    Sets the fuel cost for the given year.

    This method calculates the fuel cost based on the fuel price and the amount of fuel used.
    The calculation uses the following OperatingCosts elements:
    - distance_traveled_mi_per_yr
    - mpgge

    Inputs from scenario:
    - fuel_prices_df
    - fuel_type
    - model_year
    - region

    Estimated class variables:
    - fuel_price_dol_per_gge
    - fuel_used_gal_gge_per_yr
    - fuel_used_gal_gde_per_yr
    - energy_used_kwh_per_yr
    - fuel_cost_dol_per_yr

    Args:
        year_number (int): The year number for which the fuel cost is calculated.
        vehicle (Vehicle): The vehicle instance.
        scenario (Scenario): The scenario instance containing configuration data.
    """
    if scenario.fuel_prices_df is None:
        scenario.fuel_prices_df = pd.read_csv(
            get_path_object(scenario.fuel_prices_file)
        )
        scenario.fuel_prices_df.set_index("Fuel", inplace=True)

    scenario.fuel_prices_df = scenario.fuel_prices_df[
        scenario.fuel_prices_df["Region"] == scenario.region
    ]

    if (
        "diesel" in scenario.fuel_type.lower()
        and "bio" not in scenario.fuel_type.lower()
    ):
        diesel_dol_per_gal = scenario.fuel_prices_df.loc[
            "diesel_dol_per_gal", str(scenario.model_year + year_number - 1)
        ]
        self.fuel_price_dol_per_gge = diesel_dol_per_gal * gl.DGE_TO_GGE
    elif "gasoline" in scenario.fuel_type.lower():
        gasoline_dol_per_gal = scenario.fuel_prices_df.loc[
            "gasoline_dol_per_gal", str(scenario.model_year + year_number - 1)
        ]
        self.fuel_price_dol_per_gge = gasoline_dol_per_gal
    elif "electricity" in scenario.fuel_type.lower():
        electricity_dol_per_kwh = scenario.fuel_prices_df.loc[
            "electricity_dol_per_kwh", str(scenario.model_year + year_number - 1)
        ]
        self.fuel_price_dol_per_gge = electricity_dol_per_kwh * gl.KWH_PER_GGE
    elif scenario.fuel_type.lower() == "cng":
        cng_dol_per_gge = scenario.fuel_prices_df.loc[
            "cng_dol_per_gge", str(scenario.model_year + year_number - 1)
        ]
        self.fuel_price_dol_per_gge = cng_dol_per_gge
    elif scenario.fuel_type.lower() == "hydrogen":
        hydrogen_dol_per_gge = scenario.fuel_prices_df.loc[
            "hydrogen_dol_per_gge", str(scenario.model_year + year_number - 1)
        ]
        self.fuel_price_dol_per_gge = hydrogen_dol_per_gge
    else:
        raise Exception(
            f"Operating Costs calculation: Unknown fuel type {scenario.fuel_type}"
        )

    if self.mpgge and self.mpgge > 0:
        self.fuel_used_gal_gge_per_yr = (
            self.distance_traveled_mi_per_yr / self.mpgge
        )
        self.fuel_used_gal_gde_per_yr = (
            self.fuel_used_gal_gge_per_yr / gl.DGE_TO_GGE
        )
        self.energy_used_kwh_per_yr = self.fuel_used_gal_gge_per_yr * gl.KWH_PER_GGE

        self.fuel_cost_dol_per_yr = (
            self.fuel_price_dol_per_gge * self.fuel_used_gal_gge_per_yr
        )
    else:
        self.fuel_used_gal_gge_per_yr = 0
        self.fuel_used_gal_gde_per_yr = 0
        self.energy_used_kwh_per_yr = 0
        self.fuel_cost_dol_per_yr = 0

set_maintenance_oper_cost(year_number, vehicle, scenario)

Sets the maintenance operating cost for the given year.

This method calculates the maintenance cost based on the maintenance cost per mile and the distance traveled.

Inputs from scenario: - maint_oper_cost_dol_per_mi - vmt

Estimated class variables: - maintenance_cost_dol_per_mi - maintenance_cost_dol_per_yr

Parameters:

Name Type Description Default
year_number int

The year number for which the maintenance cost is calculated.

 required
vehicle Vehicle

The vehicle instance.

 required
scenario Scenario

The scenario instance containing configuration data.

 required
Source code in src/t3co/cost_models/operating_costs.py 
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def set_maintenance_oper_cost(
    self, year_number: int, vehicle: Vehicle, scenario: Scenario
) -> None:
    """
    Sets the maintenance operating cost for the given year.

    This method calculates the maintenance cost based on the maintenance cost per mile and the distance traveled.

    Inputs from scenario:
    - maint_oper_cost_dol_per_mi
    - vmt

    Estimated class variables:
    - maintenance_cost_dol_per_mi
    - maintenance_cost_dol_per_yr

    Args:
        year_number (int): The year number for which the maintenance cost is calculated.
        vehicle (Vehicle): The vehicle instance.
        scenario (Scenario): The scenario instance containing configuration data.
    """
    self.maintenance_cost_dol_per_mi = scenario.maint_oper_cost_dol_per_mi[
        year_number - 1
    ]

    self.maintenance_cost_dol_per_yr = (
        self.maintenance_cost_dol_per_mi * self.distance_traveled_mi_per_yr
    )

set_insurance_cost(year_number, cap_cost, vehicle, scenario)

Sets the insurance cost for the given year.

This method calculates the insurance cost based on the insurance rate and the total value of the vehicle.

Inputs from scenario: - insurance_rates_pct_per_yr

Inputs from cap_cost: - msrp_total_dol

Estimated class variables: - insurance_cost_dol_per_yr

Parameters:

Name Type Description Default
year_number int

The year number for which the insurance cost is calculated.

 required
cap_cost CapitalCosts

The capital costs associated with the vehicle.

 required
vehicle Vehicle

The vehicle instance.

 required
scenario Scenario

The scenario instance containing configuration data.

 required
Source code in src/t3co/cost_models/operating_costs.py 
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def set_insurance_cost(
    self,
    year_number: int,
    cap_cost: CapitalCosts,
    vehicle: Vehicle,
    scenario: Scenario,
) -> None:
    """
    Sets the insurance cost for the given year.

    This method calculates the insurance cost based on the insurance rate and the total value of the vehicle.

    Inputs from scenario:
    - insurance_rates_pct_per_yr

    Inputs from cap_cost:
    - msrp_total_dol

    Estimated class variables:
    - insurance_cost_dol_per_yr

    Args:
        year_number (int): The year number for which the insurance cost is calculated.
        cap_cost (CapitalCosts): The capital costs associated with the vehicle.
        vehicle (Vehicle): The vehicle instance.
        scenario (Scenario): The scenario instance containing configuration data.
    """
    self.insurance_rates_pct_per_yr = (
        ast.literal_eval(scenario.insurance_rates_pct_per_yr)[year_number - 1]
        if isinstance(scenario.insurance_rates_pct_per_yr, str)
        else scenario.insurance_rates_pct_per_yr[year_number - 1]
    )

    self.insurance_cost_dol_per_yr = (
        cap_cost.msrp_total_dol * self.insurance_rates_pct_per_yr
    )

set_purchasing_payment_cost(year_number, scenario, cap_costs)

Sets the purchasing payment cost for the given year.

This method calculates the purchasing payment cost based on the purchasing method specified in the scenario.

Inputs from scenario: - purchasing_method - purchasing_interest_apr_pct_per_yr - purchasing_payment_frequency_months - purchasing_term_yr - tax_rate_pct - leasing_money_factor

Inputs from cap_costs: - purchasing_initial_principal_dol - msrp_total_dol - purchase_tax_dol - purchasing_downpayment_dol - residual_cost_dol

Estimated OperatingCosts variables: - purchasing_payment_dol_per_yr - purchasing_cost_dol_per_yr - purchasing_remaining_principal_dol - purchasing_tax_amount_dol_per_year

Parameters:

Name Type Description Default
year_number int

The year number for which the purchasing payment cost is calculated.

 required
scenario Scenario

The scenario instance containing configuration data, including the purchasing method, interest rate, and term.

 required
cap_costs CapitalCosts

The capital costs associated with the vehicle.

 required
Source code in src/t3co/cost_models/operating_costs.py 
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def set_purchasing_payment_cost(
    self, year_number: int, scenario: Scenario, cap_costs: CapitalCosts
):
    """
    Sets the purchasing payment cost for the given year.

    This method calculates the purchasing payment cost based on the purchasing method specified in the scenario.

    Inputs from scenario:
    - purchasing_method
    - purchasing_interest_apr_pct_per_yr
    - purchasing_payment_frequency_months
    - purchasing_term_yr
    - tax_rate_pct
    - leasing_money_factor

    Inputs from cap_costs:
    - purchasing_initial_principal_dol
    - msrp_total_dol
    - purchase_tax_dol
    - purchasing_downpayment_dol
    - residual_cost_dol

    Estimated OperatingCosts variables:
    - purchasing_payment_dol_per_yr
    - purchasing_cost_dol_per_yr
    - purchasing_remaining_principal_dol
    - purchasing_tax_amount_dol_per_year

    Args:
        year_number (int): The year number for which the purchasing payment cost is calculated.
        scenario (Scenario): The scenario instance containing configuration data, including the purchasing method, interest rate, and term.
        cap_costs (CapitalCosts): The capital costs associated with the vehicle.
    """
    if scenario.purchasing_method == "cash":
        self.purchasing_payment_dol_per_yr = 0
        self.purchasing_cost_dol_per_yr = 0

    elif scenario.purchasing_method == "loan":
        if (
            scenario.purchasing_term_yr <= 0
            or scenario.purchasing_payment_frequency_months <= 0
        ):
            self.purchasing_payment_dol_per_yr = 0
            self.purchasing_cost_dol_per_yr = 0
            self.purchasing_remaining_principal_dol = 0
            return

        interest_rate_pct_per_frequency = (
            scenario.purchasing_interest_apr_pct_per_yr
            / 12
            * scenario.purchasing_payment_frequency_months
        )
        total_number_of_payments = int(
            scenario.purchasing_term_yr
            * 12
            / scenario.purchasing_payment_frequency_months
        )  # TODO check for missing payment
        annual_number_of_payments = int(
            12 / scenario.purchasing_payment_frequency_months
        )

        purchasing_payment_dol_per_freq = (
            cap_costs.purchasing_initial_principal_dol
            * interest_rate_pct_per_frequency
            * (1 + interest_rate_pct_per_frequency) ** total_number_of_payments
        ) / ((1 + interest_rate_pct_per_frequency) ** total_number_of_payments - 1)

        self.purchasing_remaining_principal_dol = (
            cap_costs.purchasing_initial_principal_dol
            * (1 + interest_rate_pct_per_frequency)
            ** (year_number * annual_number_of_payments)
        ) - purchasing_payment_dol_per_freq / interest_rate_pct_per_frequency * (
            (1 + interest_rate_pct_per_frequency)
            ** (year_number * annual_number_of_payments)
            - 1
        )

        self.purchasing_cost_dol_per_yr = sum(
            [
                interest_rate_pct_per_frequency
                * (
                    cap_costs.purchasing_initial_principal_dol
                    * (1 + interest_rate_pct_per_frequency) ** n
                    - purchasing_payment_dol_per_freq
                    / interest_rate_pct_per_frequency
                    * ((1 + interest_rate_pct_per_frequency) ** n - 1)
                )
                for n in range(
                    (year_number - 1) * annual_number_of_payments,
                    (year_number * annual_number_of_payments + 1),
                )
            ]
        )

        self.purchasing_payment_dol_per_yr = (
            purchasing_payment_dol_per_freq * annual_number_of_payments
        )

    elif scenario.purchasing_method == "lease":
        if scenario.purchasing_term_yr <= 0:
            self.purchasing_payment_dol_per_yr = 0
            self.purchasing_cost_dol_per_yr = 0
            self.purchasing_tax_amount_dol_per_year = 0
            return

        adjusted_cap_cost_dol = (
            cap_costs.msrp_total_dol
            + cap_costs.purchase_tax_dol
            - cap_costs.purchasing_downpayment_dol
        )
        depreciation_cost_dol_per_month = (
            adjusted_cap_cost_dol + cap_costs.residual_cost_dol
        ) / (scenario.purchasing_term_yr * 12)
        finance_fee_dol_per_month = (
            adjusted_cap_cost_dol - cap_costs.residual_cost_dol
        ) * scenario.leasing_money_factor
        self.purchasing_tax_amount_dol_per_year = (
            (depreciation_cost_dol_per_month + finance_fee_dol_per_month)
            * scenario.tax_rate_pct
            * 12
        )
        self.purchasing_payment_dol_per_yr = (
            depreciation_cost_dol_per_month
            + finance_fee_dol_per_month
            + self.purchasing_tax_amount_dol_per_year / 12
        ) * 12
        self.purchasing_cost_dol_per_yr = finance_fee_dol_per_month * 12

set_fueling_dwell_labor_cost(scenario, oppy_costs)

Sets the fueling dwell labor cost for the given year.

This method calculates the fueling dwell labor cost based on the fueling dwell time and the labor rate.

Inputs from scenario: - labor_rate_dol_per_hr

Inputs from oppy_costs: - fueling_dwell_time_hr_per_yr

Estimated OperatingCosts variables: - fueling_dwell_labor_cost_dol_per_yr

Parameters:

Name Type Description Default
scenario Scenario

The scenario instance containing configuration data.

 required
oppy_costs OpportunityCosts

The opportunity costs associated with the vehicle.

 required
Source code in src/t3co/cost_models/operating_costs.py 
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def set_fueling_dwell_labor_cost(
    self, scenario: Scenario, oppy_costs: OpportunityCosts
) -> None:
    """
    Sets the fueling dwell labor cost for the given year.

    This method calculates the fueling dwell labor cost based on the fueling dwell time and the labor rate.

    Inputs from scenario:
    - labor_rate_dol_per_hr

    Inputs from oppy_costs:
    - fueling_dwell_time_hr_per_yr

    Estimated OperatingCosts variables:
    - fueling_dwell_labor_cost_dol_per_yr

    Args:
        scenario (Scenario): The scenario instance containing configuration data.
        oppy_costs (OpportunityCosts): The opportunity costs associated with the vehicle.
    """
    self.fueling_dwell_labor_cost_dol_per_yr = (
        oppy_costs.fueling_dwell_time_hr_per_yr * scenario.labor_rate_dol_per_hr
    )

set_net_oper_cost()

Sets the net operating cost for the given year.

This method calculates the net operating cost by summing the various operating cost components. The calculation uses the following OperatingCosts elements: - fuel_cost_dol_per_yr - fueling_dwell_labor_cost_dol_per_yr - maintenance_cost_dol_per_yr - insurance_cost_dol_per_yr - purchasing_payment_dol_per_yr

Estimated OperatingCosts variables: - net_oper_cost_dol_per_yr

Source code in src/t3co/cost_models/operating_costs.py 
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def set_net_oper_cost(self) -> None:
    """
    Sets the net operating cost for the given year.

    This method calculates the net operating cost by summing the various operating cost components.
    The calculation uses the following OperatingCosts elements:
    - fuel_cost_dol_per_yr
    - fueling_dwell_labor_cost_dol_per_yr
    - maintenance_cost_dol_per_yr
    - insurance_cost_dol_per_yr
    - purchasing_payment_dol_per_yr

    Estimated OperatingCosts variables:
    - net_oper_cost_dol_per_yr
    """
    self.net_oper_cost_dol_per_yr = (
        self.fuel_cost_dol_per_yr
        + self.fueling_dwell_labor_cost_dol_per_yr
        + self.maintenance_cost_dol_per_yr
        + self.insurance_cost_dol_per_yr
        + self.purchasing_payment_dol_per_yr
    )

set_disc_oper_cost(year_number, scenario)

Sets the discounted operating cost for the given year.

This method calculates the discounted operating cost based on the net operating cost and the discount rate. The calculation uses the following OperatingCosts elements: - net_oper_cost_dol_per_yr

Inputs from scenario: - discount_rate_pct_per_yr

Estimated OperatingCosts variables: - disc_oper_cost_dol_per_yr

Parameters:

Name Type Description Default
year_number int

The year number for which the discounted operating cost is calculated.

 required
scenario Scenario

The scenario instance containing configuration data.

 required
Source code in src/t3co/cost_models/operating_costs.py 
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def set_disc_oper_cost(self, year_number: int, scenario: Scenario) -> None:
    """
    Sets the discounted operating cost for the given year.

    This method calculates the discounted operating cost based on the net operating cost and the discount rate.
    The calculation uses the following OperatingCosts elements:
    - net_oper_cost_dol_per_yr

    Inputs from scenario:
    - discount_rate_pct_per_yr

    Estimated OperatingCosts variables:
    - disc_oper_cost_dol_per_yr

    Args:
        year_number (int): The year number for which the discounted operating cost is calculated.
        scenario (Scenario): The scenario instance containing configuration data.
    """
    self.disc_oper_cost_dol_per_yr = scenario.get_discounted_value(
        value=self.net_oper_cost_dol_per_yr, year_number=year_number
    )

__str__()

Returns a string representation of the OperatingCosts instance.

Returns:

Name Type Description
str str

String representation of the OperatingCosts instance.
Source code in src/t3co/cost_models/operating_costs.py 
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def __str__(self) -> str:
    """
    Returns a string representation of the OperatingCosts instance.

    Returns:
        str: String representation of the OperatingCosts instance.
    """
    return obj_to_string(self)