d8_output.py

import pandas as pd
import mopy as mo
import numpy as np


def curtailment(data_folder_name, start_limit=180, reduction=20, end_limit=0):
    common_files_folder = mo.path.join(mo.output_path, data_folder_name, "common", "files")
    individual_folder = mo.path.join(mo.output_path, data_folder_name, "individual")
    pypsa_out_path = mo.path.join(mo.output_path, data_folder_name, "pypsa_out")

    # input file
    gen_p_max_pu = pd.read_csv(mo.path.join(mo.input_path, data_folder_name, "generators-p_max_pu.csv"),
                               index_col="name", parse_dates=True)
    total_curtailments = pd.DataFrame(index=gen_p_max_pu.columns)

    co2_limit = start_limit
    while co2_limit >= end_limit:
        cur = pd.DataFrame(index=gen_p_max_pu.index)

        # read from folder
        gens = pd.read_csv(mo.path.join(pypsa_out_path, str(co2_limit), "generators.csv"), index_col="name",
                           parse_dates=True)
        electricity = pd.read_csv(mo.path.join(individual_folder, str(co2_limit), "electricity.csv"), index_col="name",
                                  parse_dates=True)

        for i in gen_p_max_pu.columns:
            cur = mo.hor(cur, ((gen_p_max_pu.loc[:, i] * gens.loc[i, "p_nom_opt"]) - electricity.loc[:, i]))

        # save individual curtailment
        cur.to_csv(mo.path.join(individual_folder, str(co2_limit)
                                , "curtailments.csv"))

        # dataframe of total curtailments
        total_curtailments[co2_limit] = cur.sum(axis=0)

        # save total curtailments
        total_curtailments.to_csv(mo.path.join(common_files_folder, "total_curtailments.csv"))
        co2_limit = co2_limit - reduction


def store_cycle(data_folder_name):
    common_files_folder = mo.path.join(mo.output_path, data_folder_name, "common", "files")

    # input file
    electricity = pd.read_csv(mo.path.join(common_files_folder, "electricity_total.csv"), index_col=0)
    heat = pd.read_csv(mo.path.join(common_files_folder, "heat_total.csv"), index_col=0)
    hydrogen = pd.read_csv(mo.path.join(common_files_folder, "hydrogen_total.csv"), index_col=0)
    opt = pd.read_csv(mo.path.join(common_files_folder, "opt.csv"), index_col=0)

    # data frame
    cycle_df = pd.DataFrame(index=opt.columns)

    for i in mo.electricity_list[2]:
        cycle_df = mo.hor(cycle_df, (electricity.loc[i, :] // opt.loc[i, :]))

    for i in mo.heat_list[2]:
        cycle_df = mo.hor(cycle_df, (heat.loc[i, :] // opt.loc[i, :]))

    for i in mo.hydrogen_list[2]:
        cycle_df = mo.hor(cycle_df, (hydrogen.loc[i, :] // opt.loc[i, :]))

    cycle_df.replace([np.inf, -np.inf], np.nan, inplace=True)
    cycle_df = abs(cycle_df.T)

    cycle_df.to_csv(mo.path.join(common_files_folder, "storage_cycles.csv"))


if __name__ == "__main__":
    store_cycle("Result_0.0")