EOS/modules/class_load_container.py

import numpy as np


class Gesamtlast:
    def __init__(self, prediction_hours=24):
        self.lasten = {}  # Contains names and load arrays for different sources
        self.prediction_hours = prediction_hours

    def hinzufuegen(self, name, last_array):
        """
        Adds an array of loads for a specific source.

        :param name: Name of the load source (e.g., "Household", "Heat Pump")
        :param last_array: Array of loads, where each entry corresponds to an hour
        """
        if len(last_array) != self.prediction_hours:
            raise ValueError(
                f"Total load inconsistent lengths in arrays: {name} {len(last_array)}"
            )
        self.lasten[name] = last_array

    def gesamtlast_berechnen(self):
        """
        Calculates the total load for each hour and returns an array of total loads.

        :return: Array of total loads, where each entry corresponds to an hour
        """
        if not self.lasten:
            return []

        # Assumption: All load arrays have the same length
        stunden = len(next(iter(self.lasten.values())))
        gesamtlast_array = [0] * stunden

        for last_array in self.lasten.values():
            gesamtlast_array = [
                gesamtlast + stundenlast
                for gesamtlast, stundenlast in zip(gesamtlast_array, last_array)
            ]

        return np.array(gesamtlast_array)