scenario_builder.powerplants.get_deflex_pp_by_year() - Code Metrics - reegis/scenario_builder - Measure and Improve Code Quality continuously with Scrutinizer

get_deflex_pp_by_year() B
last analyzed 2021-03-25 19:34 UTC

↳ Parent: scenario_builder.powerplants

Complexity

Conditions

Size

Total Lines	62
Code Lines	31

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
cc	5
eloc	31
nop	5
dl	0
loc	62
rs	8.6693
c	0
b	0
f	0

How to fix Long Method

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

SPDX-FileCopyrightText: 2016-2021 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 config as cfg
from reegis import energy_balance
from reegis import geometries as reegis_geometries
from reegis import powerplants

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=name)

    # 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 plants"].loc[("DE03", "wind"), "capacity"
    ...     ] # doctest: +SKIP
    3052.8
    >>> my_pp["power plants"].loc[("DE03", "lignite"), "capacity"
    ...     ] # doctest: +SKIP
    1135.6
    """
    pp = get_deflex_pp_by_year(regions, year, name, overwrite_capacity=True)
    tables = create_powerplants(pp, table_collection, year, name)
    tables["power plants"]["source region"] = "DE"
    return tables


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 plants": pp.groupby(
            ["model_classes", region_column, "energy_source_level_2"]
        )
        .sum()[["capacity", "count"]]
        .loc["volatile plants"]
    }

    if cfg.get("creator", "group_transformer"):
        power_plants["power plants"] = (
            pp.groupby(
                ["model_classes", region_column, "energy_source_level_2"]
            )
            .sum()[["capacity", "capacity_in", "count"]]
            .loc["power plants"]
        )
        power_plants["power plants"]["fuel"] = power_plants[
            "power plants"
        ].index.get_level_values(1)
    else:
        pp["efficiency"] = pp["efficiency"].round(2)
        power_plants["power plants"] = (
            pp.groupby(
                [
                    "model_classes",
                    region_column,
                    "energy_source_level_2",
                    "efficiency",
                ]
            )
            .sum()[["capacity", "capacity_in", "count"]]
            .loc["power plants"]
        )
        power_plants["power plants"]["fuel"] = power_plants[
            "power plants"
        ].index.get_level_values(1)
        power_plants["power plants"].index = [
            power_plants["power plants"].index.get_level_values(0),
            power_plants["power plants"].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["power plants"]
    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)
            if cfg.has_option("creator", "downtime_bioenergy"):
                add_values.loc["bioenergy", "value"] = cfg.get(
                    "creator", "downtime_bioenergy"
                )
            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["power plants"] = 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["power plants"]
        for limit_trsf in cfg.get_list("creator", "limited_transformer"):
            trsf = table_collection["power plants"]
            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["power plants"] = 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["power plants"].loc[("NW", "hard coal"), "capacity"]
    ...     )  # doctest: +SKIP
    1291
    >>> table=scenario_chp(pp, fs, 2014, "federal_states")  # doctest: +SKIP
    >>> transf=table["power plants"]  # doctest: +SKIP
    >>> chp_hp=table["heat-chp plants"]  # 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": "bioenergy"}, inplace=True)
    heat_b = powerplants.calculate_chp_share_and_efficiency(cb)

    heat_demand = demand.get_heat_profiles_deflex(
        regions, year, weather_year=weather_year
    )
    tables = chp_table(heat_b, heat_demand, table_collection)
    tables["heat-chp plants"]["source region"] = "DE"
    return tables


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["heat-chp plants"] = chp_hp.transpose()

    table_collection = substract_chp_capacity_and_limit_from_pp(
        table_collection, eta_heat_chp, eta_elec_chp
    )

    return {
        "heat-chp plants": table_collection["heat-chp plants"],
        "power plants": table_collection["power plants"],
    }


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["heat-chp plants"]
    pp = tc["power plants"]
    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: 2016-2021 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 config as cfg
15			from reegis import energy_balance
16			from reegis import geometries as reegis_geometries
17			from reegis import powerplants
18
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=name)
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 plants"].loc[("DE03", "wind"), "capacity"
192			... ] # doctest: +SKIP
193			3052.8
194			>>> my_pp["power plants"].loc[("DE03", "lignite"), "capacity"
195			... ] # doctest: +SKIP
196			1135.6
197			"""
198			pp = get_deflex_pp_by_year(regions, year, name, overwrite_capacity=True)
199			tables = create_powerplants(pp, table_collection, year, name)
200			tables["power plants"]["source region"] = "DE"
201			return tables
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 plants": pp.groupby(
224			["model_classes", region_column, "energy_source_level_2"]
225			)
226			.sum()[["capacity", "count"]]
227			.loc["volatile plants"]
228			}
229
230			if cfg.get("creator", "group_transformer"):
231			power_plants["power plants"] = (
232			pp.groupby(
233			["model_classes", region_column, "energy_source_level_2"]
234			)
235			.sum()[["capacity", "capacity_in", "count"]]
236			.loc["power plants"]
237			)
238			power_plants["power plants"]["fuel"] = power_plants[
239			"power plants"
240			].index.get_level_values(1)
241			else:
242			pp["efficiency"] = pp["efficiency"].round(2)
243			power_plants["power plants"] = (
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["power plants"]
254			)
255			power_plants["power plants"]["fuel"] = power_plants[
256			"power plants"
257			].index.get_level_values(1)
258			power_plants["power plants"].index = [
259			power_plants["power plants"].index.get_level_values(0),
260			power_plants["power plants"].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
277			table_collection = add_pp_limit(table_collection, year)
278			table_collection = add_additional_values(table_collection)
279			return table_collection
280
281
282			def add_additional_values(table_collection):
283			"""
284
285			Parameters
286			----------
287			table_collection
288
289			Returns
290			-------
291
292			"""
293			transf = table_collection["power plants"]
294			for values in ["variable_costs", "downtime_factor"]:
295			if cfg.get("creator", "use_{0}".format(values)) is True:
296			add_values = getattr(data.get_ewi_data(), values)
297			if cfg.has_option("creator", "downtime_bioenergy"):
298			add_values.loc["bioenergy", "value"] = cfg.get(
299			"creator", "downtime_bioenergy"
300			)
301			transf = transf.merge(
302			add_values,
303			right_index=True,
304			how="left",
305			left_on="fuel",
306			)
307			transf.drop(["unit", "source"], axis=1, inplace=True)
308			transf.rename({"value": values}, axis=1, inplace=True)
309			else:
310			transf[values] = 0
311			table_collection["power plants"] = transf
312			return table_collection
313
314
315			def add_pp_limit(table_collection, year):
316			"""
317
318			Parameters
319			----------
320			table_collection
321			year
322
323			Returns
324			-------
325
326			"""
327			if len(cfg.get_list("creator", "limited_transformer")) > 0:
328			# Multiply with 1000 to get MWh (bmwi: GWh)
329			repp = bmwi.bmwi_re_energy_capacity() * 1000
330			trsf = table_collection["power plants"]
331			for limit_trsf in cfg.get_list("creator", "limited_transformer"):
332			trsf = table_collection["power plants"]
333			try:
334			limit = repp.loc[year, (limit_trsf, "energy")]
335			except KeyError:
336			msg = "Cannot calculate limit for {0} in {1}."
337			raise ValueError(msg.format(limit_trsf, year))
338			cond = trsf["fuel"] == limit_trsf
339			cap_sum = trsf.loc[pd.Series(cond)[cond].index, "capacity"].sum()
340			trsf.loc[pd.Series(cond)[cond].index, "limit_elec_pp"] = (
341			trsf.loc[pd.Series(cond)[cond].index, "capacity"]
342			.div(cap_sum)
343			.multiply(limit)
344			+ 0.5
345			)
346			trsf["limit_elec_pp"] = trsf["limit_elec_pp"].fillna(float("inf"))
347
348			table_collection["power plants"] = trsf
349			return table_collection
350
351
352			def scenario_chp(table_collection, regions, year, name, weather_year=None):
353			"""
354
355			Parameters
356			----------
357			table_collection
358			regions
359			year
360			name
361			weather_year
362
363			Returns
364			-------
365
366			Examples
367			--------
368			>>> from reegis import geometries
369			>>> fs=geometries.get_federal_states_polygon()
370			>>> pp=scenario_powerplants(dict(), fs, 2014, "federal_states"
371			... ) # doctest: +SKIP
372			>>> int(pp["power plants"].loc[("NW", "hard coal"), "capacity"]
373			... ) # doctest: +SKIP
374			1291
375			>>> table=scenario_chp(pp, fs, 2014, "federal_states") # doctest: +SKIP
376			>>> transf=table["power plants"] # doctest: +SKIP
377			>>> chp_hp=table["heat-chp plants"] # doctest: +SKIP
378			>>> int(transf.loc[("MV", "hard coal"), "capacity"]) # doctest: +SKIP
379			623
380			>>> int(chp_hp.loc[("HH", "hard coal"), "capacity_elec_chp"]
381			... ) # doctest: +SKIP
382			667
383			"""
384			# values from heat balance
385
386			cb = energy_balance.get_transformation_balance_by_region(
387			regions, year, name
388			)
389			cb.rename(columns={"re": "bioenergy"}, inplace=True)
390			heat_b = powerplants.calculate_chp_share_and_efficiency(cb)
391
392			heat_demand = demand.get_heat_profiles_deflex(
393			regions, year, weather_year=weather_year
394			)
395			tables = chp_table(heat_b, heat_demand, table_collection)
396			tables["heat-chp plants"]["source region"] = "DE"
397			return tables
398
399
400			def chp_table(heat_b, heat_demand, table_collection, regions=None):
401			"""
402
403			Parameters
404			----------
405			heat_b
406			heat_demand
407			table_collection
408			regions
409
410			Returns
411			-------
412
413			"""
414
415			chp_hp = pd.DataFrame(
416			columns=pd.MultiIndex(levels=[[], []], codes=[[], []])
417			)
418
419			rows = ["Heizkraftwerke der allgemeinen Versorgung (nur KWK)", "Heizwerke"]
420			if regions is None:
421			regions = sorted(heat_b.keys())
422
423			eta_heat_chp = None
424			eta_elec_chp = None
425
426			for region in regions:
427			eta_hp = round(heat_b[region]["sys_heat"] * heat_b[region]["hp"], 2)
428			eta_heat_chp = round(
429			heat_b[region]["sys_heat"] * heat_b[region]["heat_chp"], 2
430			)
431			eta_elec_chp = round(heat_b[region]["elec_chp"], 2)
432
433			# Due to the different efficiency between heat from chp-plants and
434			# heat from heat-plants the share of the output is different to the
435			# share of the input. As heat-plants will produce more heat per fuel
436			# factor will be greater than 1 and for chp-plants smaller than 1.
437			out_share_factor_chp = heat_b[region]["out_share_factor_chp"]
438			out_share_factor_hp = heat_b[region]["out_share_factor_hp"]
439
440			# Remove "district heating" and "electricity" and spread the share
441			# to the remaining columns.
442			share = pd.DataFrame(columns=heat_b[region]["fuel_share"].columns)
443			for row in rows:
444			tmp = heat_b[region]["fuel_share"].loc[region, :, row]
445			tot = float(tmp["total"])
446
447			d = float(tmp["district heating"] + tmp["electricity"])
448			tmp = tmp + tmp / (tot - d) * d
449			tmp = tmp.reset_index(drop=True)
450			share.loc[row] = tmp.loc[0]
451			del share["district heating"]
452			del share["electricity"]
453
454			# Remove the total share
455			del share["total"]
456
457			max_val = float(heat_demand[region]["district heating"].max())
458			sum_val = float(heat_demand[region]["district heating"].sum())
459
460			share = share.rename({"gas": "natural gas"}, axis=1)
461
462			for fuel in share.columns:
463			# CHP
464			chp_hp.loc["limit_heat_chp", (region, fuel)] = round(
465			sum_val * share.loc[rows[0], fuel] * out_share_factor_chp + 0.5
466			)
467			cap_heat_chp = round(
468			max_val * share.loc[rows[0], fuel] * out_share_factor_chp
469			+ 0.005,
470			2,
471			)
472			chp_hp.loc["capacity_heat_chp", (region, fuel)] = cap_heat_chp
473			cap_elec = cap_heat_chp / eta_heat_chp * eta_elec_chp
474			chp_hp.loc["capacity_elec_chp", (region, fuel)] = round(
475			cap_elec, 2
476			)
477			chp_hp[region] = chp_hp[region].fillna(0)
478
479			# HP
480			chp_hp.loc["limit_hp", (region, fuel)] = round(
481			sum_val * share.loc[rows[1], fuel] * out_share_factor_hp + 0.5
482			)
483			chp_hp.loc["capacity_hp", (region, fuel)] = round(
484			max_val * share.loc[rows[1], fuel] * out_share_factor_hp
485			+ 0.005,
486			2,
487			)
488			if chp_hp.loc["capacity_hp", (region, fuel)] > 0:
489			chp_hp.loc["efficiency_hp", (region, fuel)] = eta_hp
490			if cap_heat_chp * cap_elec > 0:
491			chp_hp.loc[
492			"efficiency_heat_chp", (region, fuel)
493			] = eta_heat_chp
494			chp_hp.loc[
495			"efficiency_elec_chp", (region, fuel)
496			] = eta_elec_chp
497			chp_hp.loc["fuel", (region, fuel)] = fuel
498
499			logging.info("Done")
500
501			chp_hp.sort_index(axis=1, inplace=True)
502
503			# for col in trsf.sum().loc[trsf.sum() == 0].index:
504			# del trsf[col]
505			# trsf[trsf < 0] = 0
506
507			table_collection["heat-chp plants"] = chp_hp.transpose()
508
509			table_collection = substract_chp_capacity_and_limit_from_pp(
510			table_collection, eta_heat_chp, eta_elec_chp
511			)
512
513			return {
514			"heat-chp plants": table_collection["heat-chp plants"],
515			"power plants": table_collection["power plants"],
516			}
517
518
519			def substract_chp_capacity_and_limit_from_pp(tc, eta_heat_chp, eta_elec_chp):
520			"""
521
522			Parameters
523			----------
524			tc
525			eta_heat_chp
526			eta_elec_chp
527
528			Returns
529			-------
530
531			"""
532			chp_hp = tc["heat-chp plants"]
533			pp = tc["power plants"]
534			diff = 0
535			for region in chp_hp.index.get_level_values(0).unique():
536			for fuel in chp_hp.loc[region].index:
537			# If the power plant limit is not "inf" the limited electricity
538			# output of the chp plant has to be subtracted from the power plant
539			# limit because this is related to the overall electricity output.
540			limit_elec_pp = pp.loc[
541			(pp.index.get_level_values(0) == region) & (pp.fuel == fuel),
542			"limit_elec_pp",
543			].sum()
544			if not limit_elec_pp == float("inf"):
545			limit_elec_chp = (
546			chp_hp.loc[(region, fuel), "limit_heat_chp"]
547			/ eta_heat_chp
548			* eta_elec_chp
549			)
550			factor = 1 - limit_elec_chp / limit_elec_pp
551			pp.loc[
552			(pp.index.get_level_values(0) == region)
553			& (pp.fuel == fuel),
554			"limit_elec_pp",
555			] *= factor
556
557			# Substract the electric capacity of the chp from the capacity
558			# of the power plant.
559			capacity_elec_pp = pp.loc[
560			(pp.index.get_level_values(0) == region) & (pp.fuel == fuel),
561			"capacity",
562			].sum()
563			capacity_elec_chp = chp_hp.loc[(region, fuel), "capacity_elec_chp"]
564			if capacity_elec_chp < capacity_elec_pp:
565			factor = 1 - capacity_elec_chp / capacity_elec_pp
566			elif capacity_elec_chp == capacity_elec_pp:
567			factor = 0
568			else:
569			factor = 0
570			diff += capacity_elec_chp - capacity_elec_pp
571			msg = (
572			"Electricity capacity of chp plant it greater than "
573			"existing electricity capacity in one region.\n"
574			"Region: {0}, capacity_elec: {1}, capacity_elec_chp: "
575			"{2}, fuel: {3}"
576			)
577			warn(
578			msg.format(
579			region, capacity_elec_pp, capacity_elec_chp, fuel
580			),
581			UserWarning,
582			)
583			pp.loc[
584			(pp.index.get_level_values(0) == region) & (pp.fuel == fuel),
585			"capacity",
586			] *= factor
587			if diff > 0:
588			msg = (
589			"Electricity capacity of some chp plants it greater than "
590			"existing electricity capacity.\n"
591			"Overall difference: {0}"
592			)
593			warn(msg.format(diff), UserWarning)
594			return tc
595
596
597			if __name__ == "__main__":
598			pass
599

reegis / scenario_builder

get_deflex_pp_by_year() B last analyzed 2021-03-25 19:34 UTC

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last analyzed 2021-03-25 19:34 UTC