scenario_builder.powerplants.chp_table() - Code Metrics - Inspection of "Add deflex scenario builder" - reegis/scenario_builder - Measure and Improve Code Quality continuously with Scrutinizer

Passed

Pull Request — master (#2)

by Uwe

created 2021-02-02 08:37 UTC

scenario_builder.powerplants.chp_table() C

↳ Parent: scenario_builder.powerplants

Complexity

Conditions

Size

Total Lines	114
Code Lines	63

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
cc	7
eloc	63
nop	4
dl	0
loc	114
rs	6.8109
c	0
b	0
f	0

How to fix Long Method

"""Create a basic scenario from the internal data structure.

SPDX-FileCopyrightText: 2016-2019 Uwe Krien <[email protected]>

SPDX-License-Identifier: MIT
"""

import logging
import os
from warnings import warn

import pandas as pd
from reegis import bmwi
from reegis import energy_balance
from reegis import geometries as reegis_geometries
from reegis import powerplants

from scenario_builder import config as cfg
from scenario_builder import data
from scenario_builder import demand

# Todo: Revise and test.


def pp_reegis2deflex(regions, name, filename_in=None, filename_out=None):
    """
    Add federal states and deflex regions to powerplant table from reegis. As
    the process takes a while the result is stored for further usage.

    Returns
    -------
    str : The full path where the result file is stored.

    """
    if filename_out is None:
        filename_out = os.path.join(
            cfg.get("paths", "powerplants"),
            cfg.get("powerplants", "deflex_pp"),
        ).format(map=cfg.get("init", "map"))

    # Add deflex regions to powerplants
    pp = powerplants.add_regions_to_powerplants(
        regions, name, dump=False, filename=filename_in
    )

    # Add federal states to powerplants
    federal_states = reegis_geometries.get_federal_states_polygon()
    pp = powerplants.add_regions_to_powerplants(
        federal_states, "federal_states", pp=pp, dump=False
    )

    # store the results for further usage of deflex
    pp.to_hdf(filename_out, "pp")
    return filename_out


# def remove_onshore_technology_from_offshore_regions(df):
#     """ This filter should be improved. It is slow and has to be adapted
#     manually. Anyhow it seems to work this way."""
#
#     logging.info("Removing onshore technology from offshore regions.")
#     logging.info("The code is not efficient. So it may take a while.")
#
#     offshore_regions=(
#         cfg.get_dict_list('offshore_regions_set')[cfg.get('init', 'map')])
#
#     coast_regions={'de02': {'MV': 'DE01',
#                               'SH': 'DE01',
#                               'NI': 'DE01 '},
#                      'de17': {'MV': 'DE13',
#                               'SH': 'DE01',
#                               'NI': 'DE03'},
#                      'de21': {'MV': 'DE01',
#                               'SH': 'DE13',
#                               'NI': 'DE14'},
#                      'de22': {'MV': 'DE01',
#                               'SH': 'DE13',
#                               'NI': 'DE14'}}
#     try:
#         dc=coast_regions[cfg.get('init', 'map')]
#     except KeyError:
#         raise ValueError('Coast regions not defined for {0} model.'.format(
#             cfg.get('init', 'map')))
#
#     region_column='{0}_region'.format(cfg.get('init', 'map'))
#
#     for ttype in ['Solar', 'Bioenergy', 'Wind']:
#         for region in offshore_regions:
#             logging.debug("Clean {1} from {0}.".format(region, ttype))
#
#             c1=df['energy_source_level_2'] == ttype
#             c2=df[region_column] == region
#
#             condition=c1 & c2
#
#             if ttype == 'Wind':
#                 condition=c1 & c2 & (df['technology'] == 'Onshore')
#
#             for i, v in df.loc[condition].iterrows():
#                 df.loc[i, region_column]=(
#                     dc[df.loc[i, 'federal_states']])
#     return df


def process_pp_table(pp):
    # # Remove powerplants outside Germany
    # for state in cfg.get_list('powerplants', 'remove_states'):
    #     pp=pp.loc[pp.state != state]
    #
    # if clean_offshore:
    #     pp=remove_onshore_technology_from_offshore_regions(pp)
    # Remove PHES (storages)
    if cfg.get("powerplants", "remove_phes"):
        pp = pp.loc[pp.technology != "Pumped storage"]
    return pp


def get_deflex_pp_by_year(
    regions, year, name, overwrite_capacity=False, filename=None
):
    """

    Parameters
    ----------
    regions : GeoDataFrame
    year : int
    name : str
    filename : str
    overwrite_capacity : bool
        By default (False) a new column "capacity_<year>" is created. If set to
        True the old capacity column will be overwritten.

    Returns
    -------

    """
    if filename is None:
        filename = os.path.join(
            cfg.get("paths", "powerplants"),
            cfg.get("powerplants", "deflex_pp"),
        ).format(map=name)
    logging.info("Get deflex power plants for {0}.".format(year))
    if not os.path.isfile(filename):
        msg = "File '{0}' does not exist. Will create it from reegis file."
        logging.debug(msg.format(filename))
        filename = pp_reegis2deflex(regions, name, filename_out=filename)
    pp = pd.DataFrame(pd.read_hdf(filename, "pp"))

    # Remove unwanted data sets
    pp = process_pp_table(pp)

    filter_columns = ["capacity_{0}", "capacity_in_{0}"]

    # Get all powerplants for the given year.
    # If com_month exist the power plants will be considered month-wise.
    # Otherwise the commission/decommission within the given year is not
    # considered.

    for fcol in filter_columns:
        filter_column = fcol.format(year)
        orig_column = fcol[:-4]
        c1 = (pp["com_year"] < year) & (pp["decom_year"] > year)
        pp.loc[c1, filter_column] = pp.loc[c1, orig_column]

        c2 = pp["com_year"] == year
        pp.loc[c2, filter_column] = (
            pp.loc[c2, orig_column] * (12 - pp.loc[c2, "com_month"]) / 12
        )
        c3 = pp["decom_year"] == year
        pp.loc[c3, filter_column] = (
            pp.loc[c3, orig_column] * pp.loc[c3, "com_month"] / 12
        )

        if overwrite_capacity:
            pp[orig_column] = 0
            pp[orig_column] = pp[filter_column]
            del pp[filter_column]

    return pp


def scenario_powerplants(table_collection, regions, year, name):
    """Get power plants for the scenario year

    Examples
    --------
    >>> from reegis import geometries
    >>> fs=geometries.get_federal_states_polygon()
    >>> my_pp=scenario_powerplants(
    ...     dict(), fs, 2014, "federal_states")  # doctest: +SKIP
    >>> my_pp["volatile_source"].loc[("DE03", "wind"), "capacity"
    ...     ] # doctest: +SKIP
    3052.8
    >>> my_pp["transformer"].loc[("DE03", "lignite"), "capacity"
    ...     ] # doctest: +SKIP
    1135.6
    """
    pp = get_deflex_pp_by_year(
        regions, year, name, overwrite_capacity=True
    )
    return create_powerplants(pp, table_collection, year, name)


def create_powerplants(
    pp, table_collection, year, region_column="deflex_region"
):
    """This function works for all power plant tables with an equivalent
    structure e.g. power plants by state or other regions."""
    logging.info("Adding power plants to your scenario.")

    replace_names = cfg.get_dict("source_names")

    # TODO Waste is not "other"
    replace_names.update(cfg.get_dict("source_groups"))
    pp["count"] = 1
    pp["energy_source_level_2"].replace(replace_names, inplace=True)

    pp["model_classes"] = pp["energy_source_level_2"].replace(
        cfg.get_dict("model_classes")
    )

    power_plants = {
        "volatile_source": pp.groupby(
            ["model_classes", region_column, "energy_source_level_2"]
        )
        .sum()[["capacity", "count"]]
        .loc["volatile_source"]
    }

    if cfg.get("creator", "group_transformer"):
        power_plants["transformer"] = (
            pp.groupby(
                ["model_classes", region_column, "energy_source_level_2"]
            )
            .sum()[["capacity", "capacity_in", "count"]]
            .loc["transformer"]
        )
        power_plants["transformer"]["fuel"] = power_plants[
            "transformer"
        ].index.get_level_values(1)
    else:
        pp["efficiency"] = pp["efficiency"].round(2)
        power_plants["transformer"] = (
            pp.groupby(
                [
                    "model_classes",
                    region_column,
                    "energy_source_level_2",
                    "efficiency",
                ]
            )
            .sum()[["capacity", "capacity_in", "count"]]
            .loc["transformer"]
        )
        power_plants["transformer"]["fuel"] = power_plants[
            "transformer"
        ].index.get_level_values(1)
        power_plants["transformer"].index = [
            power_plants["transformer"].index.get_level_values(0),
            power_plants["transformer"].index.map("{0[1]} - {0[2]}".format),
        ]

    for class_name, pp_class in power_plants.items():
        if "capacity_in" in pp_class:
            pp_class["efficiency"] = (
                pp_class["capacity"] / pp_class["capacity_in"] * 100
            )
            del pp_class["capacity_in"]
        if cfg.get("creator", "round") is not None:
            pp_class = pp_class.round(cfg.get("creator", "round"))
        if "efficiency" in pp_class:
            pp_class["efficiency"] = pp_class["efficiency"].div(100)
        pp_class = pp_class.transpose()
        pp_class.index.name = "parameter"
        table_collection[class_name] = pp_class.transpose()
    table_collection = add_pp_limit(table_collection, year)
    table_collection = add_additional_values(table_collection)
    return table_collection


def add_additional_values(table_collection):
    """

    Parameters
    ----------
    table_collection

    Returns
    -------

    """
    transf = table_collection["transformer"]
    for values in ["variable_costs", "downtime_factor"]:
        if cfg.get("creator", "use_{0}".format(values)) is True:
            add_values = getattr(data.get_ewi_data(), values)
            transf = transf.merge(
                add_values, right_index=True, how="left", left_on="fuel",
            )
            transf.drop(["unit", "source"], axis=1, inplace=True)
            transf.rename({"value": values}, axis=1, inplace=True)
        else:
            transf[values] = 0
    table_collection["transformer"] = transf
    return table_collection


def add_pp_limit(table_collection, year):
    """

    Parameters
    ----------
    table_collection
    year

    Returns
    -------

    """
    if len(cfg.get_list("creator", "limited_transformer")) > 0:
        # Multiply with 1000 to get MWh (bmwi: GWh)
        repp = bmwi.bmwi_re_energy_capacity() * 1000
        trsf = table_collection["transformer"]
        for limit_trsf in cfg.get_list("creator", "limited_transformer"):
            trsf = table_collection["transformer"]
            try:
                limit = repp.loc[year, (limit_trsf, "energy")]
            except KeyError:
                msg = "Cannot calculate limit for {0} in {1}."
                raise ValueError(msg.format(limit_trsf, year))
            cond = trsf["fuel"] == limit_trsf
            cap_sum = trsf.loc[pd.Series(cond)[cond].index, "capacity"].sum()
            trsf.loc[pd.Series(cond)[cond].index, "limit_elec_pp"] = (
                trsf.loc[pd.Series(cond)[cond].index, "capacity"]
                .div(cap_sum)
                .multiply(limit)
                + 0.5
            )
        trsf["limit_elec_pp"] = trsf["limit_elec_pp"].fillna(float("inf"))

        table_collection["transformer"] = trsf
    return table_collection


def scenario_chp(table_collection, regions, year, name, weather_year=None):
    """

    Parameters
    ----------
    table_collection
    regions
    year
    name
    weather_year

    Returns
    -------

    Examples
    --------
    >>> from reegis import geometries
    >>> fs=geometries.get_federal_states_polygon()
    >>> pp=scenario_powerplants(dict(), fs, 2014, "federal_states"
    ...     )  # doctest: +SKIP
    >>> int(pp["transformer"].loc[("NW", "hard coal"), "capacity"]
    ...     )  # doctest: +SKIP
    1291
    >>> table=scenario_chp(pp, fs, 2014, "federal_states")  # doctest: +SKIP
    >>> transf=table["transformer"]  # doctest: +SKIP
    >>> chp_hp=table["chp_hp"]  # doctest: +SKIP
    >>> int(transf.loc[("MV", "hard coal"), "capacity"])  # doctest: +SKIP
    623
    >>> int(chp_hp.loc[("HH", "hard coal"), "capacity_elec_chp"]
    ...     )  # doctest: +SKIP
    667
    """
    # values from heat balance

    cb = energy_balance.get_transformation_balance_by_region(
        regions, year, name
    )
    cb.rename(columns={"re": cfg.get("chp", "renewable_source")}, inplace=True)
    heat_b = powerplants.calculate_chp_share_and_efficiency(cb)

    heat_demand = demand.get_heat_profiles_deflex(
        regions, year, weather_year=weather_year
    )
    return chp_table(heat_b, heat_demand, table_collection)


def chp_table(heat_b, heat_demand, table_collection, regions=None):
    """

    Parameters
    ----------
    heat_b
    heat_demand
    table_collection
    regions

    Returns
    -------

    """

    chp_hp = pd.DataFrame(
        columns=pd.MultiIndex(levels=[[], []], codes=[[], []])
    )

    rows = ["Heizkraftwerke der allgemeinen Versorgung (nur KWK)", "Heizwerke"]
    if regions is None:
        regions = sorted(heat_b.keys())

    eta_heat_chp = None
    eta_elec_chp = None

    for region in regions:
        eta_hp = round(heat_b[region]["sys_heat"] * heat_b[region]["hp"], 2)
        eta_heat_chp = round(
            heat_b[region]["sys_heat"] * heat_b[region]["heat_chp"], 2
        )
        eta_elec_chp = round(heat_b[region]["elec_chp"], 2)

        # Due to the different efficiency between heat from chp-plants and
        # heat from heat-plants the share of the output is different to the
        # share of the input. As heat-plants will produce more heat per fuel
        # factor will be greater than 1 and for chp-plants smaller than 1.
        out_share_factor_chp = heat_b[region]["out_share_factor_chp"]
        out_share_factor_hp = heat_b[region]["out_share_factor_hp"]

        # Remove "district heating" and "electricity" and spread the share
        # to the remaining columns.
        share = pd.DataFrame(columns=heat_b[region]["fuel_share"].columns)
        for row in rows:
            tmp = heat_b[region]["fuel_share"].loc[region, :, row]
            tot = float(tmp["total"])

            d = float(tmp["district heating"] + tmp["electricity"])
            tmp = tmp + tmp / (tot - d) * d
            tmp = tmp.reset_index(drop=True)
            share.loc[row] = tmp.loc[0]
        del share["district heating"]
        del share["electricity"]

        # Remove the total share
        del share["total"]

        max_val = float(heat_demand[region]["district heating"].max())
        sum_val = float(heat_demand[region]["district heating"].sum())

        share = share.rename({"gas": "natural gas"}, axis=1)

        for fuel in share.columns:
            # CHP
            chp_hp.loc["limit_heat_chp", (region, fuel)] = round(
                sum_val * share.loc[rows[0], fuel] * out_share_factor_chp + 0.5
            )
            cap_heat_chp = round(
                max_val * share.loc[rows[0], fuel] * out_share_factor_chp
                + 0.005,
                2,
            )
            chp_hp.loc["capacity_heat_chp", (region, fuel)] = cap_heat_chp
            cap_elec = cap_heat_chp / eta_heat_chp * eta_elec_chp
            chp_hp.loc["capacity_elec_chp", (region, fuel)] = round(
                cap_elec, 2
            )
            chp_hp[region] = chp_hp[region].fillna(0)

            # HP
            chp_hp.loc["limit_hp", (region, fuel)] = round(
                sum_val * share.loc[rows[1], fuel] * out_share_factor_hp + 0.5
            )
            chp_hp.loc["capacity_hp", (region, fuel)] = round(
                max_val * share.loc[rows[1], fuel] * out_share_factor_hp
                + 0.005,
                2,
            )
            if chp_hp.loc["capacity_hp", (region, fuel)] > 0:
                chp_hp.loc["efficiency_hp", (region, fuel)] = eta_hp
            if cap_heat_chp * cap_elec > 0:
                chp_hp.loc[
                    "efficiency_heat_chp", (region, fuel)
                ] = eta_heat_chp
                chp_hp.loc[
                    "efficiency_elec_chp", (region, fuel)
                ] = eta_elec_chp
            chp_hp.loc["fuel", (region, fuel)] = fuel

    logging.info("Done")

    chp_hp.sort_index(axis=1, inplace=True)

    # for col in trsf.sum().loc[trsf.sum() == 0].index:
    #     del trsf[col]
    # trsf[trsf < 0] = 0

    table_collection["chp_hp"] = chp_hp.transpose()

    table_collection = substract_chp_capacity_and_limit_from_pp(
        table_collection, eta_heat_chp, eta_elec_chp
    )

    return table_collection


def substract_chp_capacity_and_limit_from_pp(tc, eta_heat_chp, eta_elec_chp):
    """

    Parameters
    ----------
    tc
    eta_heat_chp
    eta_elec_chp

    Returns
    -------

    """
    chp_hp = tc["chp_hp"]
    pp = tc["transformer"]
    diff = 0
    for region in chp_hp.index.get_level_values(0).unique():
        for fuel in chp_hp.loc[region].index:
            # If the power plant limit is not "inf" the limited electricity
            # output of the chp plant has to be subtracted from the power plant
            # limit because this is related to the overall electricity output.
            limit_elec_pp = pp.loc[
                (pp.index.get_level_values(0) == region) & (pp.fuel == fuel),
                "limit_elec_pp",
            ].sum()
            if not limit_elec_pp == float("inf"):
                limit_elec_chp = (
                    chp_hp.loc[(region, fuel), "limit_heat_chp"]
                    / eta_heat_chp
                    * eta_elec_chp
                )
                factor = 1 - limit_elec_chp / limit_elec_pp
                pp.loc[
                    (pp.index.get_level_values(0) == region)
                    & (pp.fuel == fuel),
                    "limit_elec_pp",
                ] *= factor

            # Substract the electric capacity of the chp from the capacity
            # of the power plant.
            capacity_elec_pp = pp.loc[
                (pp.index.get_level_values(0) == region) & (pp.fuel == fuel),
                "capacity",
            ].sum()
            capacity_elec_chp = chp_hp.loc[(region, fuel), "capacity_elec_chp"]
            if capacity_elec_chp < capacity_elec_pp:
                factor = 1 - capacity_elec_chp / capacity_elec_pp
            elif capacity_elec_chp == capacity_elec_pp:
                factor = 0
            else:
                factor = 0
                diff += capacity_elec_chp - capacity_elec_pp
                msg = (
                    "Electricity capacity of chp plant it greater than "
                    "existing electricity capacity in one region.\n"
                    "Region: {0}, capacity_elec: {1}, capacity_elec_chp: "
                    "{2}, fuel: {3}"
                )
                warn(
                    msg.format(
                        region, capacity_elec_pp, capacity_elec_chp, fuel
                    ),
                    UserWarning,
                )
            pp.loc[
                (pp.index.get_level_values(0) == region) & (pp.fuel == fuel),
                "capacity",
            ] *= factor
    if diff > 0:
        msg = (
            "Electricity capacity of some chp plants it greater than "
            "existing electricity capacity.\n"
            "Overall difference: {0}"
        )
        warn(msg.format(diff), UserWarning)
    return tc


if __name__ == "__main__":
    pass


1			"""Create a basic scenario from the internal data structure.
2
3			SPDX-FileCopyrightText: 2016-2019 Uwe Krien <[email protected]>
4
5			SPDX-License-Identifier: MIT
6			"""
7
8			import logging
9			import os
10			from warnings import warn
11
12			import pandas as pd
13			from reegis import bmwi
14			from reegis import energy_balance
15			from reegis import geometries as reegis_geometries
16			from reegis import powerplants
17
18			from scenario_builder import config as cfg
19			from scenario_builder import data
20			from scenario_builder import demand
21
22			# Todo: Revise and test.
23
24
25			def pp_reegis2deflex(regions, name, filename_in=None, filename_out=None):
26			"""
27			Add federal states and deflex regions to powerplant table from reegis. As
28			the process takes a while the result is stored for further usage.
29
30			Returns
31			-------
32			str : The full path where the result file is stored.
33
34			"""
35			if filename_out is None:
36			filename_out = os.path.join(
37			cfg.get("paths", "powerplants"),
38			cfg.get("powerplants", "deflex_pp"),
39			).format(map=cfg.get("init", "map"))
40
41			# Add deflex regions to powerplants
42			pp = powerplants.add_regions_to_powerplants(
43			regions, name, dump=False, filename=filename_in
44			)
45
46			# Add federal states to powerplants
47			federal_states = reegis_geometries.get_federal_states_polygon()
48			pp = powerplants.add_regions_to_powerplants(
49			federal_states, "federal_states", pp=pp, dump=False
50			)
51
52			# store the results for further usage of deflex
53			pp.to_hdf(filename_out, "pp")
54			return filename_out
55
56
57			# def remove_onshore_technology_from_offshore_regions(df):
58			# """ This filter should be improved. It is slow and has to be adapted
59			# manually. Anyhow it seems to work this way."""
60			#
61			# logging.info("Removing onshore technology from offshore regions.")
62			# logging.info("The code is not efficient. So it may take a while.")
63			#
64			# offshore_regions=(
65			# cfg.get_dict_list('offshore_regions_set')[cfg.get('init', 'map')])
66			#
67			# coast_regions={'de02': {'MV': 'DE01',
68			# 'SH': 'DE01',
69			# 'NI': 'DE01 '},
70			# 'de17': {'MV': 'DE13',
71			# 'SH': 'DE01',
72			# 'NI': 'DE03'},
73			# 'de21': {'MV': 'DE01',
74			# 'SH': 'DE13',
75			# 'NI': 'DE14'},
76			# 'de22': {'MV': 'DE01',
77			# 'SH': 'DE13',
78			# 'NI': 'DE14'}}
79			# try:
80			# dc=coast_regions[cfg.get('init', 'map')]
81			# except KeyError:
82			# raise ValueError('Coast regions not defined for {0} model.'.format(
83			# cfg.get('init', 'map')))
84			#
85			# region_column='{0}_region'.format(cfg.get('init', 'map'))
86			#
87			# for ttype in ['Solar', 'Bioenergy', 'Wind']:
88			# for region in offshore_regions:
89			# logging.debug("Clean {1} from {0}.".format(region, ttype))
90			#
91			# c1=df['energy_source_level_2'] == ttype
92			# c2=df[region_column] == region
93			#
94			# condition=c1 & c2
95			#
96			# if ttype == 'Wind':
97			# condition=c1 & c2 & (df['technology'] == 'Onshore')
98			#
99			# for i, v in df.loc[condition].iterrows():
100			# df.loc[i, region_column]=(
101			# dc[df.loc[i, 'federal_states']])
102			# return df
103
104
105			def process_pp_table(pp):
106			# # Remove powerplants outside Germany
107			# for state in cfg.get_list('powerplants', 'remove_states'):
108			# pp=pp.loc[pp.state != state]
109			#
110			# if clean_offshore:
111			# pp=remove_onshore_technology_from_offshore_regions(pp)
112			# Remove PHES (storages)
113			if cfg.get("powerplants", "remove_phes"):
114			pp = pp.loc[pp.technology != "Pumped storage"]
115			return pp
116
117
118			def get_deflex_pp_by_year(
119			regions, year, name, overwrite_capacity=False, filename=None
120			):
121			"""
122
123			Parameters
124			----------
125			regions : GeoDataFrame
126			year : int
127			name : str
128			filename : str
129			overwrite_capacity : bool
130			By default (False) a new column "capacity_<year>" is created. If set to
131			True the old capacity column will be overwritten.
132
133			Returns
134			-------
135
136			"""
137			if filename is None:
138			filename = os.path.join(
139			cfg.get("paths", "powerplants"),
140			cfg.get("powerplants", "deflex_pp"),
141			).format(map=name)
142			logging.info("Get deflex power plants for {0}.".format(year))
143			if not os.path.isfile(filename):
144			msg = "File '{0}' does not exist. Will create it from reegis file."
145			logging.debug(msg.format(filename))
146			filename = pp_reegis2deflex(regions, name, filename_out=filename)
147			pp = pd.DataFrame(pd.read_hdf(filename, "pp"))
148
149			# Remove unwanted data sets
150			pp = process_pp_table(pp)
151
152			filter_columns = ["capacity_{0}", "capacity_in_{0}"]
153
154			# Get all powerplants for the given year.
155			# If com_month exist the power plants will be considered month-wise.
156			# Otherwise the commission/decommission within the given year is not
157			# considered.
158
159			for fcol in filter_columns:
160			filter_column = fcol.format(year)
161			orig_column = fcol[:-4]
162			c1 = (pp["com_year"] < year) & (pp["decom_year"] > year)
163			pp.loc[c1, filter_column] = pp.loc[c1, orig_column]
164
165			c2 = pp["com_year"] == year
166			pp.loc[c2, filter_column] = (
167			pp.loc[c2, orig_column] * (12 - pp.loc[c2, "com_month"]) / 12
168			)
169			c3 = pp["decom_year"] == year
170			pp.loc[c3, filter_column] = (
171			pp.loc[c3, orig_column] * pp.loc[c3, "com_month"] / 12
172			)
173
174			if overwrite_capacity:
175			pp[orig_column] = 0
176			pp[orig_column] = pp[filter_column]
177			del pp[filter_column]
178
179			return pp
180
181
182			def scenario_powerplants(table_collection, regions, year, name):
183			"""Get power plants for the scenario year
184
185			Examples
186			--------
187			>>> from reegis import geometries
188			>>> fs=geometries.get_federal_states_polygon()
189			>>> my_pp=scenario_powerplants(
190			... dict(), fs, 2014, "federal_states") # doctest: +SKIP
191			>>> my_pp["volatile_source"].loc[("DE03", "wind"), "capacity"
192			... ] # doctest: +SKIP
193			3052.8
194			>>> my_pp["transformer"].loc[("DE03", "lignite"), "capacity"
195			... ] # doctest: +SKIP
196			1135.6
197			"""
198			pp = get_deflex_pp_by_year(
199			regions, year, name, overwrite_capacity=True
200			)
201			return create_powerplants(pp, table_collection, year, name)
202
203
204			def create_powerplants(
205			pp, table_collection, year, region_column="deflex_region"
206			):
207			"""This function works for all power plant tables with an equivalent
208			structure e.g. power plants by state or other regions."""
209			logging.info("Adding power plants to your scenario.")
210
211			replace_names = cfg.get_dict("source_names")
212
213			# TODO Waste is not "other"
214			replace_names.update(cfg.get_dict("source_groups"))
215			pp["count"] = 1
216			pp["energy_source_level_2"].replace(replace_names, inplace=True)
217
218			pp["model_classes"] = pp["energy_source_level_2"].replace(
219			cfg.get_dict("model_classes")
220			)
221
222			power_plants = {
223			"volatile_source": pp.groupby(
224			["model_classes", region_column, "energy_source_level_2"]
225			)
226			.sum()[["capacity", "count"]]
227			.loc["volatile_source"]
228			}
229
230			if cfg.get("creator", "group_transformer"):
231			power_plants["transformer"] = (
232			pp.groupby(
233			["model_classes", region_column, "energy_source_level_2"]
234			)
235			.sum()[["capacity", "capacity_in", "count"]]
236			.loc["transformer"]
237			)
238			power_plants["transformer"]["fuel"] = power_plants[
239			"transformer"
240			].index.get_level_values(1)
241			else:
242			pp["efficiency"] = pp["efficiency"].round(2)
243			power_plants["transformer"] = (
244			pp.groupby(
245			[
246			"model_classes",
247			region_column,
248			"energy_source_level_2",
249			"efficiency",
250			]
251			)
252			.sum()[["capacity", "capacity_in", "count"]]
253			.loc["transformer"]
254			)
255			power_plants["transformer"]["fuel"] = power_plants[
256			"transformer"
257			].index.get_level_values(1)
258			power_plants["transformer"].index = [
259			power_plants["transformer"].index.get_level_values(0),
260			power_plants["transformer"].index.map("{0[1]} - {0[2]}".format),
261			]
262
263			for class_name, pp_class in power_plants.items():
264			if "capacity_in" in pp_class:
265			pp_class["efficiency"] = (
266			pp_class["capacity"] / pp_class["capacity_in"] * 100
267			)
268			del pp_class["capacity_in"]
269			if cfg.get("creator", "round") is not None:
270			pp_class = pp_class.round(cfg.get("creator", "round"))
271			if "efficiency" in pp_class:
272			pp_class["efficiency"] = pp_class["efficiency"].div(100)
273			pp_class = pp_class.transpose()
274			pp_class.index.name = "parameter"
275			table_collection[class_name] = pp_class.transpose()
276			table_collection = add_pp_limit(table_collection, year)
277			table_collection = add_additional_values(table_collection)
278			return table_collection
279
280
281			def add_additional_values(table_collection):
282			"""
283
284			Parameters
285			----------
286			table_collection
287
288			Returns
289			-------
290
291			"""
292			transf = table_collection["transformer"]
293			for values in ["variable_costs", "downtime_factor"]:
294			if cfg.get("creator", "use_{0}".format(values)) is True:
295			add_values = getattr(data.get_ewi_data(), values)
296			transf = transf.merge(
297			add_values, right_index=True, how="left", left_on="fuel",
298			)
299			transf.drop(["unit", "source"], axis=1, inplace=True)
300			transf.rename({"value": values}, axis=1, inplace=True)
301			else:
302			transf[values] = 0
303			table_collection["transformer"] = transf
304			return table_collection
305
306
307			def add_pp_limit(table_collection, year):
308			"""
309
310			Parameters
311			----------
312			table_collection
313			year
314
315			Returns
316			-------
317
318			"""
319			if len(cfg.get_list("creator", "limited_transformer")) > 0:
320			# Multiply with 1000 to get MWh (bmwi: GWh)
321			repp = bmwi.bmwi_re_energy_capacity() * 1000
322			trsf = table_collection["transformer"]
323			for limit_trsf in cfg.get_list("creator", "limited_transformer"):
324			trsf = table_collection["transformer"]
325			try:
326			limit = repp.loc[year, (limit_trsf, "energy")]
327			except KeyError:
328			msg = "Cannot calculate limit for {0} in {1}."
329			raise ValueError(msg.format(limit_trsf, year))
330			cond = trsf["fuel"] == limit_trsf
331			cap_sum = trsf.loc[pd.Series(cond)[cond].index, "capacity"].sum()
332			trsf.loc[pd.Series(cond)[cond].index, "limit_elec_pp"] = (
333			trsf.loc[pd.Series(cond)[cond].index, "capacity"]
334			.div(cap_sum)
335			.multiply(limit)
336			+ 0.5
337			)
338			trsf["limit_elec_pp"] = trsf["limit_elec_pp"].fillna(float("inf"))
339
340			table_collection["transformer"] = trsf
341			return table_collection
342
343
344			def scenario_chp(table_collection, regions, year, name, weather_year=None):
345			"""
346
347			Parameters
348			----------
349			table_collection
350			regions
351			year
352			name
353			weather_year
354
355			Returns
356			-------
357
358			Examples
359			--------
360			>>> from reegis import geometries
361			>>> fs=geometries.get_federal_states_polygon()
362			>>> pp=scenario_powerplants(dict(), fs, 2014, "federal_states"
363			... ) # doctest: +SKIP
364			>>> int(pp["transformer"].loc[("NW", "hard coal"), "capacity"]
365			... ) # doctest: +SKIP
366			1291
367			>>> table=scenario_chp(pp, fs, 2014, "federal_states") # doctest: +SKIP
368			>>> transf=table["transformer"] # doctest: +SKIP
369			>>> chp_hp=table["chp_hp"] # doctest: +SKIP
370			>>> int(transf.loc[("MV", "hard coal"), "capacity"]) # doctest: +SKIP
371			623
372			>>> int(chp_hp.loc[("HH", "hard coal"), "capacity_elec_chp"]
373			... ) # doctest: +SKIP
374			667
375			"""
376			# values from heat balance
377
378			cb = energy_balance.get_transformation_balance_by_region(
379			regions, year, name
380			)
381			cb.rename(columns={"re": cfg.get("chp", "renewable_source")}, inplace=True)
382			heat_b = powerplants.calculate_chp_share_and_efficiency(cb)
383
384			heat_demand = demand.get_heat_profiles_deflex(
385			regions, year, weather_year=weather_year
386			)
387			return chp_table(heat_b, heat_demand, table_collection)
388
389
390			def chp_table(heat_b, heat_demand, table_collection, regions=None):
391			"""
392
393			Parameters
394			----------
395			heat_b
396			heat_demand
397			table_collection
398			regions
399
400			Returns
401			-------
402
403			"""
404
405			chp_hp = pd.DataFrame(
406			columns=pd.MultiIndex(levels=[[], []], codes=[[], []])
407			)
408
409			rows = ["Heizkraftwerke der allgemeinen Versorgung (nur KWK)", "Heizwerke"]
410			if regions is None:
411			regions = sorted(heat_b.keys())
412
413			eta_heat_chp = None
414			eta_elec_chp = None
415
416			for region in regions:
417			eta_hp = round(heat_b[region]["sys_heat"] * heat_b[region]["hp"], 2)
418			eta_heat_chp = round(
419			heat_b[region]["sys_heat"] * heat_b[region]["heat_chp"], 2
420			)
421			eta_elec_chp = round(heat_b[region]["elec_chp"], 2)
422
423			# Due to the different efficiency between heat from chp-plants and
424			# heat from heat-plants the share of the output is different to the
425			# share of the input. As heat-plants will produce more heat per fuel
426			# factor will be greater than 1 and for chp-plants smaller than 1.
427			out_share_factor_chp = heat_b[region]["out_share_factor_chp"]
428			out_share_factor_hp = heat_b[region]["out_share_factor_hp"]
429
430			# Remove "district heating" and "electricity" and spread the share
431			# to the remaining columns.
432			share = pd.DataFrame(columns=heat_b[region]["fuel_share"].columns)
433			for row in rows:
434			tmp = heat_b[region]["fuel_share"].loc[region, :, row]
435			tot = float(tmp["total"])
436
437			d = float(tmp["district heating"] + tmp["electricity"])
438			tmp = tmp + tmp / (tot - d) * d
439			tmp = tmp.reset_index(drop=True)
440			share.loc[row] = tmp.loc[0]
441			del share["district heating"]
442			del share["electricity"]
443
444			# Remove the total share
445			del share["total"]
446
447			max_val = float(heat_demand[region]["district heating"].max())
448			sum_val = float(heat_demand[region]["district heating"].sum())
449
450			share = share.rename({"gas": "natural gas"}, axis=1)
451
452			for fuel in share.columns:
453			# CHP
454			chp_hp.loc["limit_heat_chp", (region, fuel)] = round(
455			sum_val * share.loc[rows[0], fuel] * out_share_factor_chp + 0.5
456			)
457			cap_heat_chp = round(
458			max_val * share.loc[rows[0], fuel] * out_share_factor_chp
459			+ 0.005,
460			2,
461			)
462			chp_hp.loc["capacity_heat_chp", (region, fuel)] = cap_heat_chp
463			cap_elec = cap_heat_chp / eta_heat_chp * eta_elec_chp
464			chp_hp.loc["capacity_elec_chp", (region, fuel)] = round(
465			cap_elec, 2
466			)
467			chp_hp[region] = chp_hp[region].fillna(0)
468
469			# HP
470			chp_hp.loc["limit_hp", (region, fuel)] = round(
471			sum_val * share.loc[rows[1], fuel] * out_share_factor_hp + 0.5
472			)
473			chp_hp.loc["capacity_hp", (region, fuel)] = round(
474			max_val * share.loc[rows[1], fuel] * out_share_factor_hp
475			+ 0.005,
476			2,
477			)
478			if chp_hp.loc["capacity_hp", (region, fuel)] > 0:
479			chp_hp.loc["efficiency_hp", (region, fuel)] = eta_hp
480			if cap_heat_chp * cap_elec > 0:
481			chp_hp.loc[
482			"efficiency_heat_chp", (region, fuel)
483			] = eta_heat_chp
484			chp_hp.loc[
485			"efficiency_elec_chp", (region, fuel)
486			] = eta_elec_chp
487			chp_hp.loc["fuel", (region, fuel)] = fuel
488
489			logging.info("Done")
490
491			chp_hp.sort_index(axis=1, inplace=True)
492
493			# for col in trsf.sum().loc[trsf.sum() == 0].index:
494			# del trsf[col]
495			# trsf[trsf < 0] = 0
496
497			table_collection["chp_hp"] = chp_hp.transpose()
498
499			table_collection = substract_chp_capacity_and_limit_from_pp(
500			table_collection, eta_heat_chp, eta_elec_chp
501			)
502
503			return table_collection
504
505
506			def substract_chp_capacity_and_limit_from_pp(tc, eta_heat_chp, eta_elec_chp):
507			"""
508
509			Parameters
510			----------
511			tc
512			eta_heat_chp
513			eta_elec_chp
514
515			Returns
516			-------
517
518			"""
519			chp_hp = tc["chp_hp"]
520			pp = tc["transformer"]
521			diff = 0
522			for region in chp_hp.index.get_level_values(0).unique():
523			for fuel in chp_hp.loc[region].index:
524			# If the power plant limit is not "inf" the limited electricity
525			# output of the chp plant has to be subtracted from the power plant
526			# limit because this is related to the overall electricity output.
527			limit_elec_pp = pp.loc[
528			(pp.index.get_level_values(0) == region) & (pp.fuel == fuel),
529			"limit_elec_pp",
530			].sum()
531			if not limit_elec_pp == float("inf"):
532			limit_elec_chp = (
533			chp_hp.loc[(region, fuel), "limit_heat_chp"]
534			/ eta_heat_chp
535			* eta_elec_chp
536			)
537			factor = 1 - limit_elec_chp / limit_elec_pp
538			pp.loc[
539			(pp.index.get_level_values(0) == region)
540			& (pp.fuel == fuel),
541			"limit_elec_pp",
542			] *= factor
543
544			# Substract the electric capacity of the chp from the capacity
545			# of the power plant.
546			capacity_elec_pp = pp.loc[
547			(pp.index.get_level_values(0) == region) & (pp.fuel == fuel),
548			"capacity",
549			].sum()
550			capacity_elec_chp = chp_hp.loc[(region, fuel), "capacity_elec_chp"]
551			if capacity_elec_chp < capacity_elec_pp:
552			factor = 1 - capacity_elec_chp / capacity_elec_pp
553			elif capacity_elec_chp == capacity_elec_pp:
554			factor = 0
555			else:
556			factor = 0
557			diff += capacity_elec_chp - capacity_elec_pp
558			msg = (
559			"Electricity capacity of chp plant it greater than "
560			"existing electricity capacity in one region.\n"
561			"Region: {0}, capacity_elec: {1}, capacity_elec_chp: "
562			"{2}, fuel: {3}"
563			)
564			warn(
565			msg.format(
566			region, capacity_elec_pp, capacity_elec_chp, fuel
567			),
568			UserWarning,
569			)
570			pp.loc[
571			(pp.index.get_level_values(0) == region) & (pp.fuel == fuel),
572			"capacity",
573			] *= factor
574			if diff > 0:
575			msg = (
576			"Electricity capacity of some chp plants it greater than "
577			"existing electricity capacity.\n"
578			"Overall difference: {0}"
579			)
580			warn(msg.format(diff), UserWarning)
581			return tc
582
583
584			if __name__ == "__main__":
585			pass
586

reegis / scenario_builder

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