ebm.saving module

energy_need_net_construction(energy_need: DataFrame, net_construction: DataFrame) → DataFrame[source]
reduced_construction_kwh(energy_need_net_construction: DataFrame) → DataFrame[source]

Compute construction-related energy changes based on reduced energy intensity.

Parameters

energy_need_net_constructionpandas.DataFrame

DataFrame containing at least the following columns: - reduced_kwh_m2 : float

Energy need after reductions (kWh per m²).

  • m2float

    Original total area (m²).

  • net_construction_m2float

    Net area change due to construction (m²). Positive values reduce effective area; negative values increase it.

Returns

pandas.DataFrame

Copy of the input DataFrame with three additional columns: - reduced_construction_kwh : float

Energy after applying net construction area change (reduced_kwh_m2 * (m2 - net_construction_m2)).

  • net_construction_kwhfloat

    Energy need of the constructed area (reduced_kwh_m2 * m2).

Notes

  • No clamping is applied; if net_construction_m2 > m2, the reduced energy may become negative. Validate upstream if needed.

  • Assumes all required columns exist and are numeric.

Examples

>>> import pandas as pd
>>> df = pd.DataFrame({
...     "kwh_m2": [120.0, 95.5],
...     "m2": [1000.0, 2500.0],
...     "net_construction_m2": [200.0, -100.0],
... })
>>> reduced_construction_kwh(df)[[
...     "original_construction_kwh",
...     "reduced_construction_kwh",
...     "net_construction_kwh"
... ]]
   original_construction_kwh  reduced_construction_kwh  net_construction_kwh
0                    120000.0                  96000.0                           24000.0
1                    238750.0                 248525.0                           -9775.0
reduction_policy_kwh(energy_need: DataFrame) → DataFrame[source]

Calculate energy need changed by yearly reduction in KWh.

Parameters

energy_needpd.DataFrame
Must include the columns:

  • original_kwh_m2

  • m2

  • reduction_policy

  • reduction_yearly

  • reduction_condition

Returns

pd.DataFrame

Original DataFrame with two new columns: - reduction_policy_kwh_m2: Difference per m² - reduction_policy_kwh: Difference for total area

reduction_yearly_kwh(energy_need: DataFrame) → DataFrame[source]

Calculate energy need changed by condition in KWh.

Parameters

energy_needpd.DataFrame
Must include the columns:

  • original_kwh_m2

  • m2

  • reduction_yearly

  • reduction_policy

  • reduction_condition

Returns

pd.DataFrame

Original DataFrame with two new columns: - reduction_yearly_kwh_m2: Difference per m² - reduction_yearly_kwh: Difference for total area

reduction_condition_kwh(energy_need: DataFrame) → DataFrame[source]

Calculate energy need changed by condition in KWh.

Parameters

energy_needpd.DataFrame
Must include the columns:

  • calibrated_kwh_m2

  • m2

  • reduction_yearly

  • reduction_policy

  • reduction_condition

Returns

pd.DataFrame

Original DataFrame with two new columns: - reduction_condition_kwh_m2: Difference per m² - reduction_condition_kwh: Difference for total area

household_size(df: DataFrame, household_size: Series) → DataFrame[source]
flat_household_size(dm: DatabaseManager, period: YearRange = YearRange(start=2020, end=2050)) → DataFrame[source]
m2_household_ch(area_flat: DataFrame, area_forecast: DataFrame) → DataFrame[source]
reduced_household_size_kwh(df: DataFrame, area_flat: DataFrame) → DataFrame[source]
reduction_by_year(filtered_df: DataFrame) → DataFrame[source]
sum_savings_by_year(kwh: DataFrame) → DataFrame[source]