Economics Helper Functions¶
calculate_cash_flow_per_year_based_on_detailed_electricity_bill(
grid_tariff: GridTariff,
electricity_price: float,
feed_in_tariff: float,
taxes: float,
grid_power_use_over_investment_horizon: Series,
) -> np.ndarray
Calculates the cash flow for each year based on the electricity bill
calculator. For a description of the parameters, please see the
calculate_electricity_bill() function.
Returns:
| Type | Description |
|---|---|
ndarray
|
Cash flow for each year. |
calculate_cash_flow_per_year_based_on_simplified_electricity_bill(
energy_price: float,
power_price: float,
feed_in_tariff: float,
grid_power_use_over_investment_horizon: Series,
) -> np.ndarray
Simplified version of calculating electricity costs. Usage hours and taxes are ignored.
Returns:
| Type | Description |
|---|---|
ndarray
|
Cash flow for each year. |
stretch_data_over_investment_horizon(
data: Series, investment_horizon_years: int
) -> pd.Series
Stretches a data profile by repeating over a given calculation period. This is necessary for the calculation of
the economics for the hole investment_horizon_years if the simulation was performed for a shorter period of time (
example: We simulated only one year of operation, but want to look into a investment horizon of 10 years).
Note that the beginning is always set to the first date of the year, which is the start of the n-year calculation
period.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
data
|
Series
|
The data profile to stretch. This must have a DateTimeIndex. |
required |
investment_horizon_years
|
int
|
The number of years to stretch the data profile over. |
required |
Returns:
| Type | Description |
|---|---|
Series
|
The stretched data profile as a time series with a DateTimeIndex. |