Source code for src.tutorials.scenario_generation.scenario_generation_simple_pdfs

# The datafev framework

# Copyright (C) 2022,
# Institute for Automation of Complex Power Systems (ACS),
# E.ON Energy Research Center (E.ON ERC),
# RWTH Aachen University

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# Software.

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import os
import datetime as dt
from datafev.routines.scenario_generation import sceneration
from datafev.routines.scenario_generation import utils


def main():
    """
    Example script for the usage of simple pdfs scenario generator.

    In this tutorial, these operations are carried out in this order:
        - The data from Excel input file 'tutorials/scenario_generation/input_generator_simple_pdfs.xlsx' is read.
        - The data provided by Excel is converted to dictionary datatype with 'utils.excel_to_sceneration_input_simple_pdfs' function.
        - Electric Vehicle Dataframe, which is an electric vehicle fleet scenario, is generated via 'sceneration.generate_fleet_from_simple_pdfs' function with converted dictionary inputs
        - The statistical distribution of generated arrival and departure times and SoCs are visualized via 'utils.visualize_statistical_generation' function under '/results'.
        - Generated statistical output dataframe is converted into an input dataframe for simulators, which are explained under 'tutorials/simulations'.

    The statistical data for both arrival and departure times are based on a research Takahashi, Tamura, et al.,
    'Day-Ahead Planning for EV Aggregators Based on Statistical Analysis of Road Traffic Data in Japan'
    in 2020 International Conference on Smart Grids and Energy Systems (SGES), 2020, DOI 10.1109/SGES51519.2020.00028.
    The rest of the data is not based on any research, the purpose of this tutorial is just to provide the user an
    example use-case.

    """
    (
        arr_times_dict,
        dep_times_dict,
        arr_soc_dict,
        dep_soc_dict,
        ev_dict,
    ) = utils.excel_to_sceneration_input_simple_pdfs(
        file_path="input_generator_simple_pdfs.xlsx"
    )

    # Getting the path of the input excel file
    abs_path_input = os.path.abspath("input_generator_simple_pdfs.xlsx")
    print("Generator inputs are taken from the xlsx file:", abs_path_input)
    print()

    print("Generation started...")
    print()

    ev_df = sceneration.generate_fleet_from_simple_pdfs(
        arr_times_dict=arr_times_dict,
        dep_times_dict=dep_times_dict,
        arr_soc_dict=arr_soc_dict,
        dep_soc_dict=dep_soc_dict,
        ev_dict=ev_dict,
        number_of_evs_per_day=5,
        startdate=dt.date(2021, 6, 1),
        enddate=dt.date(2021, 6, 2),
        timedelta_in_min=15,
        diff_arr_dep_in_min=0,
    )

    print("Generation finished...")
    print()

    utils.visualize_statistical_generation("results/", ev_df, timedelta_in_min=15)

    abs_path_visualization = os.path.abspath("results/")
    print(
        "Generation results are visualized and they are saved under:",
        abs_path_visualization,
    )
    print()

    # Unlocalize datetimes, as Excel does not support datetimes with timezones
    ev_df["ArrivalTime"] = ev_df["ArrivalTime"].dt.tz_localize(None)
    ev_df["DepartureTime"] = ev_df["DepartureTime"].dt.tz_localize(None)
    ev_df.to_excel("results/output_generator_simple_pdfs.xlsx")

    abs_path_output_generator = os.path.abspath(
        "results/output_generator_simple_pdfs.xlsx"
    )
    print("Generation results are saved to the xlsx file:", abs_path_output_generator)
    print()

    utils.output_to_sim_input(ev_df, "results/input_simulator_simple_pdfs.xlsx")

    abs_path_input_simulator = os.path.abspath(
        "results/input_simulator_simple_pdfs.xlsx"
    )
    print(
        "Possible simulator input generated by this tool are saved to the xlsx file:",
        abs_path_input_simulator,
    )
    print()


if __name__ == "__main__":
    main()