Feature: provide method to integrate time series values.

[ahobeost]

TRNSYS provides printegrators to integrate values over specific periods.
If specific values are missed, the entire simulation needs to be run again, while printing this value.
If a value is available at a lower level, this integration can be done in post-processing.

The following is some suggested code that would do this:

def integrate_values(df: _pd.DataFrame, column: str, new_index: _pd.DatetimeIndex,
                     to_type: _tp.Literal["hourly", "daily", "weekly", "monthly"],
                     time_step_in_minutes: int | None = None
                     ):
    if to_type == "hourly":
        index = df.index.hour
    elif to_type == "daily":
        index = df.index.date
    elif to_type == "weekly":
        index = df.index.week
    elif to_type == "monthly":
        index = df.index.month

    df_integrated = df.groupby(index)[column].sum()
    df_integrated.index = new_index
    if time_step_in_minutes is not None:
        conversion_factor = 60./time_step_in_minutes
        df_integrated /= conversion_factor

    return df_integrated

sim.step["el_from_grid_trnsys"] = sim.step["ElecPelGrid_kW"].clip(lower=0)
sim.monthly["el_from_grid_trnsys"] = integrate_values(sim.step, "el_from_grid_trnsys",
                                                          new_index=sim.monthly.index, to_type="monthly",
                                                          time_step_in_minutes=2)

sim.step["el_grid_feed_in_trnsys"] = abs(sim.step["ElecPelGrid_kW"].clip(upper=0))
sim.monthly["el_grid_feed_in_trnsys"] = integrate_values(sim.step, "el_grid_feed_in_trnsys",
                                                             new_index=sim.monthly.index, to_type="monthly",
                                                             time_step_in_minutes=2)