| Total Complexity | 60 |
| Total Lines | 1283 |
| Duplicated Lines | 5.77 % |
| Changes | 0 | ||
Duplicate code is one of the most pungent code smells. A rule that is often used is to re-structure code once it is duplicated in three or more places.
Common duplication problems, and corresponding solutions are:
Complex classes like data.datasets.electrical_neighbours often do a lot of different things. To break such a class down, we need to identify a cohesive component within that class. A common approach to find such a component is to look for fields/methods that share the same prefixes, or suffixes.
Once you have determined the fields that belong together, you can apply the Extract Class refactoring. If the component makes sense as a sub-class, Extract Subclass is also a candidate, and is often faster.
| 1 | """The central module containing all code dealing with electrical neighbours |
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| 2 | """ |
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| 3 | |||
| 4 | import zipfile |
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| 5 | |||
| 6 | from shapely.geometry import LineString |
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| 7 | from sqlalchemy.orm import sessionmaker |
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| 8 | import geopandas as gpd |
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| 9 | import pandas as pd |
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| 10 | |||
| 11 | from egon.data import config, db |
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| 12 | from egon.data.datasets import Dataset |
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| 13 | from egon.data.datasets.fill_etrago_gen import add_marginal_costs |
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| 14 | from egon.data.datasets.scenario_parameters import get_sector_parameters |
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| 15 | import egon.data.datasets.etrago_setup as etrago |
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| 16 | import egon.data.datasets.scenario_parameters.parameters as scenario_parameters |
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| 17 | |||
| 18 | |||
| 19 | class ElectricalNeighbours(Dataset): |
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| 20 | def __init__(self, dependencies): |
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| 21 | super().__init__( |
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| 22 | name="ElectricalNeighbours", |
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| 23 | version="0.0.7", |
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| 24 | dependencies=dependencies, |
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| 25 | tasks=(grid, {tyndp_generation, tyndp_demand}), |
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| 26 | ) |
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| 27 | |||
| 28 | |||
| 29 | def get_cross_border_buses(scenario, sources): |
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| 30 | """Returns buses from osmTGmod which are outside of Germany. |
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| 31 | |||
| 32 | Parameters |
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| 33 | ---------- |
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| 34 | sources : dict |
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| 35 | List of sources |
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| 36 | |||
| 37 | Returns |
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| 38 | ------- |
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| 39 | geopandas.GeoDataFrame |
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| 40 | Electricity buses outside of Germany |
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| 41 | |||
| 42 | """ |
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| 43 | return db.select_geodataframe( |
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| 44 | f""" |
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| 45 | SELECT * |
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| 46 | FROM {sources['electricity_buses']['schema']}. |
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| 47 | {sources['electricity_buses']['table']} |
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| 48 | WHERE |
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| 49 | NOT ST_INTERSECTS ( |
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| 50 | geom, |
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| 51 | (SELECT ST_Transform(ST_Buffer(geometry, 5), 4326) FROM |
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| 52 | {sources['german_borders']['schema']}. |
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| 53 | {sources['german_borders']['table']})) |
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| 54 | AND (bus_id IN ( |
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| 55 | SELECT bus0 FROM |
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| 56 | {sources['lines']['schema']}.{sources['lines']['table']}) |
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| 57 | OR bus_id IN ( |
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| 58 | SELECT bus1 FROM |
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| 59 | {sources['lines']['schema']}.{sources['lines']['table']})) |
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| 60 | AND scn_name = '{scenario}'; |
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| 61 | """, |
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| 62 | epsg=4326, |
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| 63 | ) |
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| 64 | |||
| 65 | |||
| 66 | def get_cross_border_lines(scenario, sources): |
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| 67 | """Returns lines from osmTGmod which end or start outside of Germany. |
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| 68 | |||
| 69 | Parameters |
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| 70 | ---------- |
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| 71 | sources : dict |
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| 72 | List of sources |
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| 73 | |||
| 74 | Returns |
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| 75 | ------- |
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| 76 | geopandas.GeoDataFrame |
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| 77 | AC-lines outside of Germany |
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| 78 | |||
| 79 | """ |
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| 80 | return db.select_geodataframe( |
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| 81 | f""" |
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| 82 | SELECT * |
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| 83 | FROM {sources['lines']['schema']}.{sources['lines']['table']} a |
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| 84 | WHERE |
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| 85 | ST_INTERSECTS ( |
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| 86 | a.topo, |
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| 87 | (SELECT ST_Transform(ST_boundary(geometry), 4326) |
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| 88 | FROM {sources['german_borders']['schema']}. |
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| 89 | {sources['german_borders']['table']})) |
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| 90 | AND scn_name = '{scenario}'; |
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| 91 | """, |
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| 92 | epsg=4326, |
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| 93 | ) |
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| 94 | |||
| 95 | |||
| 96 | def central_buses_egon100(sources): |
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| 97 | """Returns buses in the middle of foreign countries based on eGon100RE |
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| 98 | |||
| 99 | Parameters |
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| 100 | ---------- |
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| 101 | sources : dict |
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| 102 | List of sources |
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| 103 | |||
| 104 | Returns |
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| 105 | ------- |
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| 106 | pandas.DataFrame |
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| 107 | Buses in the center of foreign countries |
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| 108 | |||
| 109 | """ |
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| 110 | return db.select_dataframe( |
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| 111 | f""" |
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| 112 | SELECT * |
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| 113 | FROM {sources['electricity_buses']['schema']}. |
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| 114 | {sources['electricity_buses']['table']} |
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| 115 | WHERE country != 'DE' |
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| 116 | AND scn_name = 'eGon100RE' |
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| 117 | AND bus_id NOT IN ( |
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| 118 | SELECT bus_i |
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| 119 | FROM {sources['osmtgmod_bus']['schema']}. |
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| 120 | {sources['osmtgmod_bus']['table']}) |
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| 121 | AND carrier = 'AC' |
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| 122 | """ |
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| 123 | ) |
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| 124 | |||
| 125 | |||
| 126 | def buses(scenario, sources, targets): |
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| 127 | """Insert central buses in foreign countries per scenario |
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| 128 | |||
| 129 | Parameters |
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| 130 | ---------- |
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| 131 | sources : dict |
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| 132 | List of dataset sources |
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| 133 | targets : dict |
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| 134 | List of dataset targets |
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| 135 | |||
| 136 | Returns |
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| 137 | ------- |
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| 138 | central_buses : geoapndas.GeoDataFrame |
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| 139 | Buses in the center of foreign countries |
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| 140 | |||
| 141 | """ |
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| 142 | sql_delete = f""" |
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| 143 | DELETE FROM {sources['electricity_buses']['schema']}. |
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| 144 | {sources['electricity_buses']['table']} |
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| 145 | WHERE country != 'DE' AND scn_name = '{scenario}' |
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| 146 | AND carrier = 'AC' |
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| 147 | AND bus_id NOT IN ( |
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| 148 | SELECT bus_i |
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| 149 | FROM {sources['osmtgmod_bus']['schema']}. |
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| 150 | {sources['osmtgmod_bus']['table']}) |
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| 151 | """ |
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| 152 | # Drop only buses with v_nom != 380 for eGon100RE |
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| 153 | # to keep buses from pypsa-eur-sec |
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| 154 | if scenario == "eGon100RE": |
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| 155 | sql_delete += "AND v_nom < 380" |
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| 156 | |||
| 157 | # Delete existing buses |
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| 158 | db.execute_sql(sql_delete) |
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| 159 | |||
| 160 | central_buses = central_buses_egon100(sources) |
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| 161 | |||
| 162 | next_bus_id = db.next_etrago_id("bus") + 1 |
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| 163 | |||
| 164 | # if in test mode, add bus in center of Germany |
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| 165 | if config.settings()["egon-data"]["--dataset-boundary"] != "Everything": |
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| 166 | central_buses = central_buses.append( |
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| 167 | { |
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| 168 | "scn_name": scenario, |
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| 169 | "bus_id": next_bus_id, |
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| 170 | "x": 10.4234469, |
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| 171 | "y": 51.0834196, |
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| 172 | "country": "DE", |
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| 173 | "carrier": "AC", |
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| 174 | "v_nom": 380.0, |
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| 175 | }, |
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| 176 | ignore_index=True, |
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| 177 | ) |
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| 178 | next_bus_id += 1 |
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| 179 | |||
| 180 | # Add buses for other voltage levels |
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| 181 | foreign_buses = get_cross_border_buses(scenario, sources) |
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| 182 | if config.settings()["egon-data"]["--dataset-boundary"] == "Everything": |
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| 183 | foreign_buses = foreign_buses[foreign_buses.country != "DE"] |
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| 184 | vnom_per_country = foreign_buses.groupby("country").v_nom.unique().copy() |
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| 185 | for cntr in vnom_per_country.index: |
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| 186 | print(cntr) |
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| 187 | View Code Duplication | if 110.0 in vnom_per_country[cntr]: |
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|
|
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| 188 | central_buses = central_buses.append( |
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| 189 | { |
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| 190 | "scn_name": scenario, |
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| 191 | "bus_id": next_bus_id, |
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| 192 | "x": central_buses[ |
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| 193 | central_buses.country == cntr |
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| 194 | ].x.unique()[0], |
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| 195 | "y": central_buses[ |
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| 196 | central_buses.country == cntr |
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| 197 | ].y.unique()[0], |
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| 198 | "country": cntr, |
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| 199 | "carrier": "AC", |
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| 200 | "v_nom": 110.0, |
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| 201 | }, |
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| 202 | ignore_index=True, |
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| 203 | ) |
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| 204 | next_bus_id += 1 |
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| 205 | View Code Duplication | if 220.0 in vnom_per_country[cntr]: |
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| 206 | central_buses = central_buses.append( |
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| 207 | { |
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| 208 | "scn_name": scenario, |
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| 209 | "bus_id": next_bus_id, |
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| 210 | "x": central_buses[ |
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| 211 | central_buses.country == cntr |
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| 212 | ].x.unique()[0], |
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| 213 | "y": central_buses[ |
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| 214 | central_buses.country == cntr |
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| 215 | ].y.unique()[0], |
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| 216 | "country": cntr, |
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| 217 | "carrier": "AC", |
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| 218 | "v_nom": 220.0, |
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| 219 | }, |
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| 220 | ignore_index=True, |
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| 221 | ) |
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| 222 | next_bus_id += 1 |
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| 223 | |||
| 224 | # Add geometry column |
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| 225 | central_buses = gpd.GeoDataFrame( |
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| 226 | central_buses, |
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| 227 | geometry=gpd.points_from_xy(central_buses.x, central_buses.y), |
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| 228 | crs="EPSG:4326", |
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| 229 | ) |
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| 230 | central_buses["geom"] = central_buses.geometry.copy() |
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| 231 | central_buses = central_buses.set_geometry("geom").drop( |
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| 232 | "geometry", axis="columns" |
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| 233 | ) |
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| 234 | central_buses.scn_name = scenario |
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| 235 | |||
| 236 | # Insert all central buses for eGon2035 |
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| 237 | if scenario == "eGon2035": |
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| 238 | central_buses.to_postgis( |
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| 239 | targets["buses"]["table"], |
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| 240 | schema=targets["buses"]["schema"], |
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| 241 | if_exists="append", |
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| 242 | con=db.engine(), |
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| 243 | index=False, |
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| 244 | ) |
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| 245 | # Insert only buses for eGon100RE that are not coming from pypsa-eur-sec |
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| 246 | # (buses with another voltage_level or inside Germany in test mode) |
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| 247 | else: |
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| 248 | central_buses[ |
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| 249 | (central_buses.v_nom != 380) | (central_buses.country == "DE") |
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| 250 | ].to_postgis( |
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| 251 | targets["buses"]["table"], |
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| 252 | schema=targets["buses"]["schema"], |
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| 253 | if_exists="append", |
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| 254 | con=db.engine(), |
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| 255 | index=False, |
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| 256 | ) |
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| 257 | |||
| 258 | return central_buses |
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| 259 | |||
| 260 | |||
| 261 | def cross_border_lines(scenario, sources, targets, central_buses): |
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| 262 | """Adds lines which connect border-crossing lines from osmtgmod |
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| 263 | to the central buses in the corresponding neigbouring country |
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| 264 | |||
| 265 | Parameters |
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| 266 | ---------- |
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| 267 | sources : dict |
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| 268 | List of dataset sources |
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| 269 | targets : dict |
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| 270 | List of dataset targets |
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| 271 | central_buses : geopandas.GeoDataFrame |
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| 272 | Buses in the center of foreign countries |
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| 273 | |||
| 274 | Returns |
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| 275 | ------- |
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| 276 | new_lines : geopandas.GeoDataFrame |
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| 277 | Lines that connect cross-border lines to central bus per country |
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| 278 | |||
| 279 | """ |
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| 280 | # Delete existing data |
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| 281 | db.execute_sql( |
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| 282 | f""" |
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| 283 | DELETE FROM {targets['lines']['schema']}. |
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| 284 | {targets['lines']['table']} |
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| 285 | WHERE scn_name = '{scenario}' |
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| 286 | AND line_id NOT IN ( |
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| 287 | SELECT branch_id |
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| 288 | FROM {sources['osmtgmod_branch']['schema']}. |
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| 289 | {sources['osmtgmod_branch']['table']} |
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| 290 | WHERE result_id = 1 and (link_type = 'line' or |
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| 291 | link_type = 'cable')) |
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| 292 | AND bus0 IN ( |
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| 293 | SELECT bus_i |
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| 294 | FROM {sources['osmtgmod_bus']['schema']}. |
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| 295 | {sources['osmtgmod_bus']['table']}) |
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| 296 | AND bus1 NOT IN ( |
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| 297 | SELECT bus_i |
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| 298 | FROM {sources['osmtgmod_bus']['schema']}. |
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| 299 | {sources['osmtgmod_bus']['table']}) |
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| 300 | """ |
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| 301 | ) |
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| 302 | |||
| 303 | # Calculate cross-border busses and lines from osmtgmod |
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| 304 | foreign_buses = get_cross_border_buses(scenario, sources) |
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| 305 | if config.settings()["egon-data"]["--dataset-boundary"] == "Everything": |
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| 306 | foreign_buses = foreign_buses[foreign_buses.country != "DE"] |
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| 307 | lines = get_cross_border_lines(scenario, sources) |
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| 308 | |||
| 309 | # Select bus outside of Germany from border-crossing lines |
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| 310 | lines.loc[ |
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| 311 | lines[lines.bus0.isin(foreign_buses.bus_id)].index, "foreign_bus" |
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| 312 | ] = lines.loc[lines[lines.bus0.isin(foreign_buses.bus_id)].index, "bus0"] |
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| 313 | lines.loc[ |
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| 314 | lines[lines.bus1.isin(foreign_buses.bus_id)].index, "foreign_bus" |
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| 315 | ] = lines.loc[lines[lines.bus1.isin(foreign_buses.bus_id)].index, "bus1"] |
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| 316 | |||
| 317 | # Drop lines with start and endpoint in Germany |
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| 318 | lines = lines[lines.foreign_bus.notnull()] |
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| 319 | lines.loc[:, "foreign_bus"] = lines.loc[:, "foreign_bus"].astype(int) |
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| 320 | |||
| 321 | # Copy all parameters from border-crossing lines |
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| 322 | new_lines = lines.copy() |
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| 323 | |||
| 324 | # Set bus0 as foreign_bus from osmtgmod |
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| 325 | new_lines.bus0 = new_lines.foreign_bus.copy() |
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| 326 | |||
| 327 | # Add country tag and set index |
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| 328 | new_lines["country"] = ( |
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| 329 | foreign_buses.set_index("bus_id") |
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| 330 | .loc[lines.foreign_bus, "country"] |
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| 331 | .values |
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| 332 | ) |
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| 333 | |||
| 334 | if config.settings()["egon-data"]["--dataset-boundary"] == "Everything": |
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| 335 | new_lines = new_lines[~new_lines.country.isnull()] |
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| 336 | new_lines.line_id = range( |
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| 337 | db.next_etrago_id("line"), db.next_etrago_id("line") + len(new_lines) |
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| 338 | ) |
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| 339 | |||
| 340 | # Set bus in center of foreogn countries as bus1 |
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| 341 | for i, row in new_lines.iterrows(): |
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| 342 | print(row) |
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| 343 | new_lines.loc[i, "bus1"] = central_buses.bus_id[ |
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| 344 | (central_buses.country == row.country) |
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| 345 | & (central_buses.v_nom == row.v_nom) |
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| 346 | ].values[0] |
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| 347 | |||
| 348 | # Create geometry for new lines |
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| 349 | new_lines["geom_bus0"] = ( |
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| 350 | foreign_buses.set_index("bus_id").geom[new_lines.bus0].values |
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| 351 | ) |
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| 352 | new_lines["geom_bus1"] = ( |
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| 353 | central_buses.set_index("bus_id").geom[new_lines.bus1].values |
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| 354 | ) |
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| 355 | new_lines["topo"] = new_lines.apply( |
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| 356 | lambda x: LineString([x["geom_bus0"], x["geom_bus1"]]), axis=1 |
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| 357 | ) |
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| 358 | |||
| 359 | # Set topo as geometry column |
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| 360 | new_lines = new_lines.set_geometry("topo") |
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| 361 | |||
| 362 | # Calcultae length of lines based on topology |
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| 363 | old_length = new_lines["length"].copy() |
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| 364 | new_lines["length"] = new_lines.to_crs(3035).length / 1000 |
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| 365 | |||
| 366 | # Set electrical parameters based on lines from osmtgmod |
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| 367 | for parameter in ["x", "r"]: |
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| 368 | new_lines[parameter] = ( |
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| 369 | new_lines[parameter] / old_length * new_lines["length"] |
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| 370 | ) |
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| 371 | for parameter in ["b", "g"]: |
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| 372 | new_lines[parameter] = ( |
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| 373 | new_lines[parameter] * old_length / new_lines["length"] |
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| 374 | ) |
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| 375 | |||
| 376 | # Drop intermediate columns |
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| 377 | new_lines.drop( |
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| 378 | ["foreign_bus", "country", "geom_bus0", "geom_bus1", "geom"], |
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| 379 | axis="columns", |
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| 380 | inplace=True, |
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| 381 | ) |
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| 382 | |||
| 383 | new_lines = new_lines[new_lines.bus0 != new_lines.bus1] |
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| 384 | |||
| 385 | # Set scn_name |
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| 386 | |||
| 387 | # Insert lines to the database |
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| 388 | new_lines.to_postgis( |
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| 389 | targets["lines"]["table"], |
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| 390 | schema=targets["lines"]["schema"], |
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| 391 | if_exists="append", |
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| 392 | con=db.engine(), |
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| 393 | index=False, |
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| 394 | ) |
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| 395 | |||
| 396 | return new_lines |
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| 397 | |||
| 398 | |||
| 399 | def choose_transformer(s_nom): |
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| 400 | """Select transformer and parameters from existing data in the grid model |
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| 401 | |||
| 402 | It is assumed that transformers in the foreign countries are not limiting |
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| 403 | the electricity flow, so the capacitiy s_nom is set to the minimum sum |
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| 404 | of attached AC-lines. |
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| 405 | The electrical parameters are set according to already inserted |
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| 406 | transformers in the grid model for Germany. |
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| 407 | |||
| 408 | Parameters |
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| 409 | ---------- |
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| 410 | s_nom : float |
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| 411 | Minimal sum of nominal power of lines at one side |
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| 412 | |||
| 413 | Returns |
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| 414 | ------- |
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| 415 | int |
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| 416 | Selected transformer nominal power |
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| 417 | float |
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| 418 | Selected transformer nominal impedance |
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| 419 | |||
| 420 | """ |
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| 421 | |||
| 422 | if s_nom <= 600: |
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| 423 | return 600, 0.0002 |
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| 424 | elif (s_nom > 600) & (s_nom <= 1200): |
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| 425 | return 1200, 0.0001 |
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| 426 | elif (s_nom > 1200) & (s_nom <= 1600): |
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| 427 | return 1600, 0.000075 |
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| 428 | elif (s_nom > 1600) & (s_nom <= 2100): |
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| 429 | return 2100, 0.00006667 |
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| 430 | elif (s_nom > 2100) & (s_nom <= 2600): |
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| 431 | return 2600, 0.0000461538 |
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| 432 | elif (s_nom > 2600) & (s_nom <= 4800): |
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| 433 | return 4800, 0.000025 |
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| 434 | elif (s_nom > 4800) & (s_nom <= 6000): |
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| 435 | return 6000, 0.0000225 |
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| 436 | elif (s_nom > 6000) & (s_nom <= 7200): |
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| 437 | return 7200, 0.0000194444 |
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| 438 | elif (s_nom > 7200) & (s_nom <= 8000): |
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| 439 | return 8000, 0.000016875 |
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| 440 | elif (s_nom > 8000) & (s_nom <= 9000): |
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| 441 | return 9000, 0.000015 |
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| 442 | elif (s_nom > 9000) & (s_nom <= 13000): |
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| 443 | return 13000, 0.0000103846 |
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| 444 | elif (s_nom > 13000) & (s_nom <= 20000): |
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| 445 | return 20000, 0.00000675 |
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| 446 | elif (s_nom > 20000) & (s_nom <= 33000): |
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| 447 | return 33000, 0.00000409091 |
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| 448 | |||
| 449 | |||
| 450 | def central_transformer(scenario, sources, targets, central_buses, new_lines): |
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| 451 | """Connect central foreign buses with different voltage levels |
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| 452 | |||
| 453 | Parameters |
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| 454 | ---------- |
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| 455 | sources : dict |
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| 456 | List of dataset sources |
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| 457 | targets : dict |
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| 458 | List of dataset targets |
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| 459 | central_buses : geopandas.GeoDataFrame |
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| 460 | Buses in the center of foreign countries |
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| 461 | new_lines : geopandas.GeoDataFrame |
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| 462 | Lines that connect cross-border lines to central bus per country |
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| 463 | |||
| 464 | Returns |
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| 465 | ------- |
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| 466 | None. |
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| 467 | |||
| 468 | """ |
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| 469 | # Delete existing transformers in foreign countries |
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| 470 | db.execute_sql( |
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| 471 | f""" |
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| 472 | DELETE FROM {targets['transformers']['schema']}. |
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| 473 | {targets['transformers']['table']} |
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| 474 | WHERE scn_name = '{scenario}' |
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| 475 | AND trafo_id NOT IN ( |
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| 476 | SELECT branch_id |
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| 477 | FROM {sources['osmtgmod_branch']['schema']}. |
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| 478 | {sources['osmtgmod_branch']['table']} |
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| 479 | WHERE result_id = 1 and link_type = 'transformer') |
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| 480 | """ |
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| 481 | ) |
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| 482 | |||
| 483 | # Initalize the dataframe for transformers |
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| 484 | trafo = gpd.GeoDataFrame( |
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| 485 | columns=["trafo_id", "bus0", "bus1", "s_nom"], dtype=int |
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| 486 | ) |
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| 487 | trafo_id = db.next_etrago_id("transformer") |
||
| 488 | |||
| 489 | # Add one transformer per central foreign bus with v_nom != 380 |
||
| 490 | for i, row in central_buses[central_buses.v_nom != 380].iterrows(): |
||
| 491 | |||
| 492 | s_nom_0 = new_lines[new_lines.bus0 == row.bus_id].s_nom.sum() |
||
| 493 | s_nom_1 = new_lines[new_lines.bus1 == row.bus_id].s_nom.sum() |
||
| 494 | if s_nom_0 == 0.0: |
||
| 495 | s_nom = s_nom_1 |
||
| 496 | elif s_nom_1 == 0.0: |
||
| 497 | s_nom = s_nom_0 |
||
| 498 | else: |
||
| 499 | s_nom = min([s_nom_0, s_nom_1]) |
||
| 500 | |||
| 501 | s_nom, x = choose_transformer(s_nom) |
||
| 502 | |||
| 503 | trafo = trafo.append( |
||
| 504 | { |
||
| 505 | "trafo_id": trafo_id, |
||
| 506 | "bus0": row.bus_id, |
||
| 507 | "bus1": central_buses[ |
||
| 508 | (central_buses.v_nom == 380) |
||
| 509 | & (central_buses.country == row.country) |
||
| 510 | ].bus_id.values[0], |
||
| 511 | "s_nom": s_nom, |
||
| 512 | "x": x, |
||
| 513 | }, |
||
| 514 | ignore_index=True, |
||
| 515 | ) |
||
| 516 | trafo_id += 1 |
||
| 517 | |||
| 518 | # Set data type |
||
| 519 | trafo = trafo.astype({"trafo_id": "int", "bus0": "int", "bus1": "int"}) |
||
| 520 | trafo["scn_name"] = scenario |
||
| 521 | |||
| 522 | # Insert transformers to the database |
||
| 523 | trafo.to_sql( |
||
| 524 | targets["transformers"]["table"], |
||
| 525 | schema=targets["transformers"]["schema"], |
||
| 526 | if_exists="append", |
||
| 527 | con=db.engine(), |
||
| 528 | index=False, |
||
| 529 | ) |
||
| 530 | |||
| 531 | |||
| 532 | def foreign_dc_lines(scenario, sources, targets, central_buses): |
||
| 533 | """Insert DC lines to foreign countries manually |
||
| 534 | |||
| 535 | Parameters |
||
| 536 | ---------- |
||
| 537 | sources : dict |
||
| 538 | List of dataset sources |
||
| 539 | targets : dict |
||
| 540 | List of dataset targets |
||
| 541 | central_buses : geopandas.GeoDataFrame |
||
| 542 | Buses in the center of foreign countries |
||
| 543 | |||
| 544 | Returns |
||
| 545 | ------- |
||
| 546 | None. |
||
| 547 | |||
| 548 | """ |
||
| 549 | # Delete existing dc lines to foreign countries |
||
| 550 | db.execute_sql( |
||
| 551 | f""" |
||
| 552 | DELETE FROM {targets['links']['schema']}. |
||
| 553 | {targets['links']['table']} |
||
| 554 | WHERE scn_name = '{scenario}' |
||
| 555 | AND carrier = 'DC' |
||
| 556 | AND bus0 IN ( |
||
| 557 | SELECT bus_id |
||
| 558 | FROM {sources['electricity_buses']['schema']}. |
||
| 559 | {sources['electricity_buses']['table']} |
||
| 560 | WHERE scn_name = '{scenario}' |
||
| 561 | AND carrier = 'AC' |
||
| 562 | AND country = 'DE') |
||
| 563 | AND bus1 IN ( |
||
| 564 | SELECT bus_id |
||
| 565 | FROM {sources['electricity_buses']['schema']}. |
||
| 566 | {sources['electricity_buses']['table']} |
||
| 567 | WHERE scn_name = '{scenario}' |
||
| 568 | AND carrier = 'AC' |
||
| 569 | AND country != 'DE') |
||
| 570 | """ |
||
| 571 | ) |
||
| 572 | capital_cost = get_sector_parameters("electricity", "eGon2035")[ |
||
| 573 | "capital_cost" |
||
| 574 | ] |
||
| 575 | |||
| 576 | # Add DC line from Lübeck to Sweden |
||
| 577 | converter_luebeck = db.select_dataframe( |
||
| 578 | f""" |
||
| 579 | SELECT bus_id FROM |
||
| 580 | {sources['electricity_buses']['schema']}. |
||
| 581 | {sources['electricity_buses']['table']} |
||
| 582 | WHERE x = 10.802358024202768 |
||
| 583 | AND y = 53.897547401787 |
||
| 584 | AND v_nom = 380 |
||
| 585 | AND scn_name = '{scenario}' |
||
| 586 | AND carrier = 'AC' |
||
| 587 | """ |
||
| 588 | ).squeeze() |
||
| 589 | |||
| 590 | foreign_links = pd.DataFrame( |
||
| 591 | index=[0], |
||
| 592 | data={ |
||
| 593 | "link_id": db.next_etrago_id("link"), |
||
| 594 | "bus0": converter_luebeck, |
||
| 595 | "bus1": central_buses[ |
||
| 596 | (central_buses.country == "SE") & (central_buses.v_nom == 380) |
||
| 597 | ] |
||
| 598 | .squeeze() |
||
| 599 | .bus_id, |
||
| 600 | "p_nom": 600, |
||
| 601 | "length": 262, |
||
| 602 | }, |
||
| 603 | ) |
||
| 604 | |||
| 605 | # When not in test-mode, add DC line from Bentwisch to Denmark |
||
| 606 | if config.settings()["egon-data"]["--dataset-boundary"] == "Everything": |
||
| 607 | converter_bentwisch = db.select_dataframe( |
||
| 608 | f""" |
||
| 609 | SELECT bus_id FROM |
||
| 610 | {sources['electricity_buses']['schema']}. |
||
| 611 | {sources['electricity_buses']['table']} |
||
| 612 | WHERE x = 12.213671694775988 |
||
| 613 | AND y = 54.09974494662279 |
||
| 614 | AND v_nom = 380 |
||
| 615 | AND scn_name = '{scenario}' |
||
| 616 | AND carrier = 'AC' |
||
| 617 | """ |
||
| 618 | ).squeeze() |
||
| 619 | |||
| 620 | foreign_links = foreign_links.append( |
||
| 621 | pd.DataFrame( |
||
| 622 | index=[1], |
||
| 623 | data={ |
||
| 624 | "link_id": db.next_etrago_id("link") + 1, |
||
| 625 | "bus0": converter_bentwisch, |
||
| 626 | "bus1": central_buses[ |
||
| 627 | (central_buses.country == "DK") |
||
| 628 | & (central_buses.v_nom == 380) |
||
| 629 | & (central_buses.x > 10) |
||
| 630 | ] |
||
| 631 | .squeeze() |
||
| 632 | .bus_id, |
||
| 633 | "p_nom": 600, |
||
| 634 | "length": 170, |
||
| 635 | }, |
||
| 636 | ) |
||
| 637 | ) |
||
| 638 | |||
| 639 | # Set parameters for all DC lines |
||
| 640 | foreign_links["capital_cost"] = ( |
||
| 641 | capital_cost["dc_cable"] * foreign_links.length |
||
| 642 | + 2 * capital_cost["dc_inverter"] |
||
| 643 | ) |
||
| 644 | foreign_links["p_min_pu"] = -1 |
||
| 645 | foreign_links["p_nom_extendable"] = True |
||
| 646 | foreign_links["p_nom_min"] = foreign_links["p_nom"] |
||
| 647 | foreign_links["scn_name"] = scenario |
||
| 648 | foreign_links["carrier"] = "DC" |
||
| 649 | foreign_links["efficiency"] = 1 |
||
| 650 | |||
| 651 | # Add topology |
||
| 652 | foreign_links = etrago.link_geom_from_buses(foreign_links, scenario) |
||
| 653 | |||
| 654 | # Insert DC lines to the database |
||
| 655 | foreign_links.to_postgis( |
||
| 656 | targets["links"]["table"], |
||
| 657 | schema=targets["links"]["schema"], |
||
| 658 | if_exists="append", |
||
| 659 | con=db.engine(), |
||
| 660 | index=False, |
||
| 661 | ) |
||
| 662 | |||
| 663 | |||
| 664 | def grid(): |
||
| 665 | """Insert electrical grid compoenents for neighbouring countries |
||
| 666 | |||
| 667 | Returns |
||
| 668 | ------- |
||
| 669 | None. |
||
| 670 | |||
| 671 | """ |
||
| 672 | # Select sources and targets from dataset configuration |
||
| 673 | sources = config.datasets()["electrical_neighbours"]["sources"] |
||
| 674 | targets = config.datasets()["electrical_neighbours"]["targets"] |
||
| 675 | |||
| 676 | for scenario in ["eGon2035"]: |
||
| 677 | |||
| 678 | central_buses = buses(scenario, sources, targets) |
||
| 679 | |||
| 680 | foreign_lines = cross_border_lines( |
||
| 681 | scenario, sources, targets, central_buses |
||
| 682 | ) |
||
| 683 | |||
| 684 | central_transformer( |
||
| 685 | scenario, sources, targets, central_buses, foreign_lines |
||
| 686 | ) |
||
| 687 | |||
| 688 | foreign_dc_lines(scenario, sources, targets, central_buses) |
||
| 689 | |||
| 690 | |||
| 691 | def map_carriers_tyndp(): |
||
| 692 | """Map carriers from TYNDP-data to carriers used in eGon |
||
| 693 | Returns |
||
| 694 | ------- |
||
| 695 | dict |
||
| 696 | Carrier from TYNDP and eGon |
||
| 697 | """ |
||
| 698 | return { |
||
| 699 | "Battery": "battery", |
||
| 700 | "DSR": "demand_side_response", |
||
| 701 | "Gas CCGT new": "gas", |
||
| 702 | "Gas CCGT old 2": "gas", |
||
| 703 | "Gas CCGT present 1": "gas", |
||
| 704 | "Gas CCGT present 2": "gas", |
||
| 705 | "Gas conventional old 1": "gas", |
||
| 706 | "Gas conventional old 2": "gas", |
||
| 707 | "Gas OCGT new": "gas", |
||
| 708 | "Gas OCGT old": "gas", |
||
| 709 | "Gas CCGT old 1": "gas", |
||
| 710 | "Gas CCGT old 2 Bio": "biogas", |
||
| 711 | "Gas conventional old 2 Bio": "biogas", |
||
| 712 | "Hard coal new": "coal", |
||
| 713 | "Hard coal old 1": "coal", |
||
| 714 | "Hard coal old 2": "coal", |
||
| 715 | "Hard coal old 2 Bio": "coal", |
||
| 716 | "Heavy oil old 1": "oil", |
||
| 717 | "Heavy oil old 1 Bio": "oil", |
||
| 718 | "Heavy oil old 2": "oil", |
||
| 719 | "Light oil": "oil", |
||
| 720 | "Lignite new": "lignite", |
||
| 721 | "Lignite old 1": "lignite", |
||
| 722 | "Lignite old 2": "lignite", |
||
| 723 | "Lignite old 1 Bio": "lignite", |
||
| 724 | "Lignite old 2 Bio": "lignite", |
||
| 725 | "Nuclear": "nuclear", |
||
| 726 | "Offshore Wind": "wind_offshore", |
||
| 727 | "Onshore Wind": "wind_onshore", |
||
| 728 | "Other non-RES": "others", |
||
| 729 | "Other RES": "others", |
||
| 730 | "P2G": "power_to_gas", |
||
| 731 | "PS Closed": "pumped_hydro", |
||
| 732 | "PS Open": "reservoir", |
||
| 733 | "Reservoir": "reservoir", |
||
| 734 | "Run-of-River": "run_of_river", |
||
| 735 | "Solar PV": "solar", |
||
| 736 | "Solar Thermal": "others", |
||
| 737 | "Waste": "Other RES", |
||
| 738 | } |
||
| 739 | |||
| 740 | |||
| 741 | View Code Duplication | def get_foreign_bus_id(): |
|
| 742 | """Calculte the etrago bus id from Nodes of TYNDP based on the geometry |
||
| 743 | |||
| 744 | Returns |
||
| 745 | ------- |
||
| 746 | pandas.Series |
||
| 747 | List of mapped node_ids from TYNDP and etragos bus_id |
||
| 748 | |||
| 749 | """ |
||
| 750 | |||
| 751 | sources = config.datasets()["electrical_neighbours"]["sources"] |
||
| 752 | |||
| 753 | bus_id = db.select_geodataframe( |
||
| 754 | """SELECT bus_id, ST_Buffer(geom, 1) as geom, country |
||
| 755 | FROM grid.egon_etrago_bus |
||
| 756 | WHERE scn_name = 'eGon2035' |
||
| 757 | AND carrier = 'AC' |
||
| 758 | AND v_nom = 380. |
||
| 759 | AND country != 'DE' |
||
| 760 | AND bus_id NOT IN ( |
||
| 761 | SELECT bus_i |
||
| 762 | FROM osmtgmod_results.bus_data) |
||
| 763 | """, |
||
| 764 | epsg=3035, |
||
| 765 | ) |
||
| 766 | |||
| 767 | # insert installed capacities |
||
| 768 | file = zipfile.ZipFile(f"tyndp/{sources['tyndp_capacities']}") |
||
| 769 | |||
| 770 | # Select buses in neighbouring countries as geodataframe |
||
| 771 | buses = pd.read_excel( |
||
| 772 | file.open("TYNDP-2020-Scenario-Datafile.xlsx").read(), |
||
| 773 | sheet_name="Nodes - Dict", |
||
| 774 | ).query("longitude==longitude") |
||
| 775 | buses = gpd.GeoDataFrame( |
||
| 776 | buses, |
||
| 777 | crs=4326, |
||
| 778 | geometry=gpd.points_from_xy(buses.longitude, buses.latitude), |
||
| 779 | ).to_crs(3035) |
||
| 780 | |||
| 781 | buses["bus_id"] = 0 |
||
| 782 | |||
| 783 | # Select bus_id from etrago with shortest distance to TYNDP node |
||
| 784 | for i, row in buses.iterrows(): |
||
| 785 | distance = bus_id.set_index("bus_id").geom.distance(row.geometry) |
||
| 786 | buses.loc[i, "bus_id"] = distance[ |
||
| 787 | distance == distance.min() |
||
| 788 | ].index.values[0] |
||
| 789 | |||
| 790 | return buses.set_index("node_id").bus_id |
||
| 791 | |||
| 792 | |||
| 793 | @db.session_scoped |
||
| 794 | def calc_capacities(session=None): |
||
| 795 | """Calculates installed capacities from TYNDP data |
||
| 796 | |||
| 797 | Returns |
||
| 798 | ------- |
||
| 799 | pandas.DataFrame |
||
| 800 | Installed capacities per foreign node and energy carrier |
||
| 801 | |||
| 802 | """ |
||
| 803 | |||
| 804 | sources = config.datasets()["electrical_neighbours"]["sources"] |
||
| 805 | |||
| 806 | countries = [ |
||
| 807 | "AT", |
||
| 808 | "BE", |
||
| 809 | "CH", |
||
| 810 | "CZ", |
||
| 811 | "DK", |
||
| 812 | "FR", |
||
| 813 | "NL", |
||
| 814 | "NO", |
||
| 815 | "SE", |
||
| 816 | "PL", |
||
| 817 | "UK", |
||
| 818 | ] |
||
| 819 | |||
| 820 | # insert installed capacities |
||
| 821 | file = zipfile.ZipFile(f"tyndp/{sources['tyndp_capacities']}") |
||
| 822 | df = pd.read_excel( |
||
| 823 | file.open("TYNDP-2020-Scenario-Datafile.xlsx").read(), |
||
| 824 | sheet_name="Capacity", |
||
| 825 | ) |
||
| 826 | |||
| 827 | # differneces between different climate years are very small (<1MW) |
||
| 828 | # choose 1984 because it is the mean value |
||
| 829 | df_2030 = ( |
||
| 830 | df.rename({"Climate Year": "Climate_Year"}, axis="columns") |
||
| 831 | .query( |
||
| 832 | 'Scenario == "Distributed Energy" & Year == 2030 & ' |
||
| 833 | "Climate_Year == 1984" |
||
| 834 | ) |
||
| 835 | .set_index(["Node/Line", "Generator_ID"]) |
||
| 836 | ) |
||
| 837 | |||
| 838 | df_2040 = ( |
||
| 839 | df.rename({"Climate Year": "Climate_Year"}, axis="columns") |
||
| 840 | .query( |
||
| 841 | 'Scenario == "Distributed Energy" & Year == 2040 & ' |
||
| 842 | "Climate_Year == 1984" |
||
| 843 | ) |
||
| 844 | .set_index(["Node/Line", "Generator_ID"]) |
||
| 845 | ) |
||
| 846 | |||
| 847 | # interpolate linear between 2030 and 2040 for 2035 accordning to |
||
| 848 | # scenario report of TSO's and the approval by BNetzA |
||
| 849 | df_2035 = pd.DataFrame(index=df_2030.index) |
||
| 850 | df_2035["cap_2030"] = df_2030.Value |
||
| 851 | df_2035["cap_2040"] = df_2040.Value |
||
| 852 | df_2035.fillna(0.0, inplace=True) |
||
| 853 | df_2035["cap_2035"] = ( |
||
| 854 | df_2035["cap_2030"] + (df_2035["cap_2040"] - df_2035["cap_2030"]) / 2 |
||
| 855 | ) |
||
| 856 | df_2035 = df_2035.reset_index() |
||
| 857 | df_2035["carrier"] = df_2035.Generator_ID.map(map_carriers_tyndp()) |
||
| 858 | |||
| 859 | # group capacities by new carriers |
||
| 860 | grouped_capacities = ( |
||
| 861 | df_2035.groupby(["carrier", "Node/Line"]).cap_2035.sum().reset_index() |
||
| 862 | ) |
||
| 863 | |||
| 864 | # choose capacities for considered countries |
||
| 865 | return grouped_capacities[ |
||
| 866 | grouped_capacities["Node/Line"].str[:2].isin(countries) |
||
| 867 | ] |
||
| 868 | |||
| 869 | |||
| 870 | def insert_generators(capacities): |
||
| 871 | """Insert generators for foreign countries based on TYNDP-data |
||
| 872 | |||
| 873 | Parameters |
||
| 874 | ---------- |
||
| 875 | capacities : pandas.DataFrame |
||
| 876 | Installed capacities per foreign node and energy carrier |
||
| 877 | |||
| 878 | Returns |
||
| 879 | ------- |
||
| 880 | None. |
||
| 881 | |||
| 882 | """ |
||
| 883 | targets = config.datasets()["electrical_neighbours"]["targets"] |
||
| 884 | map_buses = get_map_buses() |
||
| 885 | |||
| 886 | # Delete existing data |
||
| 887 | db.execute_sql( |
||
| 888 | f""" |
||
| 889 | DELETE FROM |
||
| 890 | {targets['generators']['schema']}.{targets['generators']['table']} |
||
| 891 | WHERE bus IN ( |
||
| 892 | SELECT bus_id FROM |
||
| 893 | {targets['buses']['schema']}.{targets['buses']['table']} |
||
| 894 | WHERE country != 'DE' |
||
| 895 | AND scn_name = 'eGon2035') |
||
| 896 | AND scn_name = 'eGon2035' |
||
| 897 | AND carrier != 'CH4' |
||
| 898 | """ |
||
| 899 | ) |
||
| 900 | |||
| 901 | db.execute_sql( |
||
| 902 | f""" |
||
| 903 | DELETE FROM |
||
| 904 | {targets['generators_timeseries']['schema']}. |
||
| 905 | {targets['generators_timeseries']['table']} |
||
| 906 | WHERE generator_id NOT IN ( |
||
| 907 | SELECT generator_id FROM |
||
| 908 | {targets['generators']['schema']}.{targets['generators']['table']} |
||
| 909 | ) |
||
| 910 | AND scn_name = 'eGon2035' |
||
| 911 | """ |
||
| 912 | ) |
||
| 913 | |||
| 914 | # Select generators from TYNDP capacities |
||
| 915 | gen = capacities[ |
||
| 916 | capacities.carrier.isin( |
||
| 917 | [ |
||
| 918 | "others", |
||
| 919 | "wind_offshore", |
||
| 920 | "wind_onshore", |
||
| 921 | "solar", |
||
| 922 | "reservoir", |
||
| 923 | "run_of_river", |
||
| 924 | "lignite", |
||
| 925 | "coal", |
||
| 926 | "oil", |
||
| 927 | "nuclear", |
||
| 928 | ] |
||
| 929 | ) |
||
| 930 | ] |
||
| 931 | |||
| 932 | # Set bus_id |
||
| 933 | gen.loc[ |
||
| 934 | gen[gen["Node/Line"].isin(map_buses.keys())].index, "Node/Line" |
||
| 935 | ] = gen.loc[ |
||
| 936 | gen[gen["Node/Line"].isin(map_buses.keys())].index, "Node/Line" |
||
| 937 | ].map( |
||
| 938 | map_buses |
||
| 939 | ) |
||
| 940 | |||
| 941 | gen.loc[:, "bus"] = ( |
||
| 942 | get_foreign_bus_id().loc[gen.loc[:, "Node/Line"]].values |
||
| 943 | ) |
||
| 944 | |||
| 945 | # Add scenario column |
||
| 946 | gen["scenario"] = "eGon2035" |
||
| 947 | |||
| 948 | # Add marginal costs |
||
| 949 | gen = add_marginal_costs(gen) |
||
| 950 | |||
| 951 | # insert generators data |
||
| 952 | session = sessionmaker(bind=db.engine())() |
||
| 953 | for i, row in gen.iterrows(): |
||
| 954 | entry = etrago.EgonPfHvGenerator( |
||
| 955 | scn_name=row.scenario, |
||
| 956 | generator_id=int(db.next_etrago_id("generator")), |
||
| 957 | bus=row.bus, |
||
| 958 | carrier=row.carrier, |
||
| 959 | p_nom=row.cap_2035, |
||
| 960 | marginal_cost=row.marginal_cost, |
||
| 961 | ) |
||
| 962 | |||
| 963 | session.add(entry) |
||
| 964 | session.commit() |
||
| 965 | session.close() |
||
| 966 | |||
| 967 | # assign generators time-series data |
||
| 968 | renew_carriers_2035 = ["wind_onshore", "wind_offshore", "solar"] |
||
| 969 | |||
| 970 | sql = f"""SELECT * FROM |
||
| 971 | {targets['generators_timeseries']['schema']}. |
||
| 972 | {targets['generators_timeseries']['table']} |
||
| 973 | WHERE scn_name = 'eGon100RE' |
||
| 974 | """ |
||
| 975 | series_egon100 = pd.read_sql_query(sql, db.engine()) |
||
| 976 | |||
| 977 | sql = f""" SELECT * FROM |
||
| 978 | {targets['generators']['schema']}.{targets['generators']['table']} |
||
| 979 | WHERE bus IN ( |
||
| 980 | SELECT bus_id FROM |
||
| 981 | {targets['buses']['schema']}.{targets['buses']['table']} |
||
| 982 | WHERE country != 'DE' |
||
| 983 | AND scn_name = 'eGon2035') |
||
| 984 | AND scn_name = 'eGon2035' |
||
| 985 | """ |
||
| 986 | gen_2035 = pd.read_sql_query(sql, db.engine()) |
||
| 987 | gen_2035 = gen_2035[gen_2035.carrier.isin(renew_carriers_2035)] |
||
| 988 | |||
| 989 | sql = f""" SELECT * FROM |
||
| 990 | {targets['generators']['schema']}.{targets['generators']['table']} |
||
| 991 | WHERE bus IN ( |
||
| 992 | SELECT bus_id FROM |
||
| 993 | {targets['buses']['schema']}.{targets['buses']['table']} |
||
| 994 | WHERE country != 'DE' |
||
| 995 | AND scn_name = 'eGon100RE') |
||
| 996 | AND scn_name = 'eGon100RE' |
||
| 997 | """ |
||
| 998 | gen_100 = pd.read_sql_query(sql, db.engine()) |
||
| 999 | gen_100 = gen_100[gen_100["carrier"].isin(renew_carriers_2035)] |
||
| 1000 | |||
| 1001 | # egon_2035_to_100 map the timeseries used in the scenario eGon100RE |
||
| 1002 | # to the same bus and carrier for the scenario egon2035 |
||
| 1003 | egon_2035_to_100 = {} |
||
| 1004 | for i, gen in gen_2035.iterrows(): |
||
| 1005 | gen_id_100 = gen_100[ |
||
| 1006 | (gen_100["bus"] == gen["bus"]) |
||
| 1007 | & (gen_100["carrier"] == gen["carrier"]) |
||
| 1008 | ]["generator_id"].values[0] |
||
| 1009 | |||
| 1010 | egon_2035_to_100[gen["generator_id"]] = gen_id_100 |
||
| 1011 | |||
| 1012 | # insert generators_timeseries data |
||
| 1013 | session = sessionmaker(bind=db.engine())() |
||
| 1014 | |||
| 1015 | for gen_id in gen_2035.generator_id: |
||
| 1016 | serie = series_egon100[ |
||
| 1017 | series_egon100.generator_id == egon_2035_to_100[gen_id] |
||
| 1018 | ]["p_max_pu"].values[0] |
||
| 1019 | entry = etrago.EgonPfHvGeneratorTimeseries( |
||
| 1020 | scn_name="eGon2035", generator_id=gen_id, temp_id=1, p_max_pu=serie |
||
| 1021 | ) |
||
| 1022 | |||
| 1023 | session.add(entry) |
||
| 1024 | session.commit() |
||
| 1025 | session.close() |
||
| 1026 | |||
| 1027 | |||
| 1028 | @db.session_scoped |
||
| 1029 | def insert_storage(capacities, session=None): |
||
| 1030 | """Insert storage units for foreign countries based on TYNDP-data |
||
| 1031 | |||
| 1032 | Parameters |
||
| 1033 | ---------- |
||
| 1034 | capacities : pandas.DataFrame |
||
| 1035 | Installed capacities per foreign node and energy carrier |
||
| 1036 | |||
| 1037 | |||
| 1038 | Returns |
||
| 1039 | ------- |
||
| 1040 | None. |
||
| 1041 | |||
| 1042 | """ |
||
| 1043 | targets = config.datasets()["electrical_neighbours"]["targets"] |
||
| 1044 | map_buses = get_map_buses() |
||
| 1045 | |||
| 1046 | # Delete existing data |
||
| 1047 | db.execute_sql( |
||
| 1048 | f""" |
||
| 1049 | DELETE FROM {targets['storage']['schema']}.{targets['storage']['table']} |
||
| 1050 | WHERE bus IN ( |
||
| 1051 | SELECT bus_id FROM |
||
| 1052 | {targets['buses']['schema']}.{targets['buses']['table']} |
||
| 1053 | WHERE country != 'DE' |
||
| 1054 | AND scn_name = 'eGon2035') |
||
| 1055 | AND scn_name = 'eGon2035' |
||
| 1056 | """ |
||
| 1057 | ) |
||
| 1058 | |||
| 1059 | # Add missing information suitable for eTraGo selected from |
||
| 1060 | # scenario_parameter table |
||
| 1061 | parameters_pumped_hydro = scenario_parameters.electricity("eGon2035")[ |
||
| 1062 | "efficiency" |
||
| 1063 | ]["pumped_hydro"] |
||
| 1064 | |||
| 1065 | parameters_battery = scenario_parameters.electricity("eGon2035")[ |
||
| 1066 | "efficiency" |
||
| 1067 | ]["battery"] |
||
| 1068 | |||
| 1069 | # Select storage capacities from TYNDP-data |
||
| 1070 | store = capacities[capacities.carrier.isin(["battery", "pumped_hydro"])] |
||
| 1071 | |||
| 1072 | # Set bus_id |
||
| 1073 | store.loc[ |
||
| 1074 | store[store["Node/Line"].isin(map_buses.keys())].index, "Node/Line" |
||
| 1075 | ] = store.loc[ |
||
| 1076 | store[store["Node/Line"].isin(map_buses.keys())].index, "Node/Line" |
||
| 1077 | ].map( |
||
| 1078 | map_buses |
||
| 1079 | ) |
||
| 1080 | |||
| 1081 | store.loc[:, "bus"] = ( |
||
| 1082 | get_foreign_bus_id().loc[store.loc[:, "Node/Line"]].values |
||
| 1083 | ) |
||
| 1084 | |||
| 1085 | # Add columns for additional parameters to df |
||
| 1086 | ( |
||
| 1087 | store["dispatch"], |
||
| 1088 | store["store"], |
||
| 1089 | store["standing_loss"], |
||
| 1090 | store["max_hours"], |
||
| 1091 | ) = (None, None, None, None) |
||
| 1092 | |||
| 1093 | # Insert carrier specific parameters |
||
| 1094 | |||
| 1095 | parameters = ["dispatch", "store", "standing_loss", "max_hours"] |
||
| 1096 | |||
| 1097 | for x in parameters: |
||
| 1098 | store.loc[store["carrier"] == "battery", x] = parameters_battery[x] |
||
| 1099 | store.loc[ |
||
| 1100 | store["carrier"] == "pumped_hydro", x |
||
| 1101 | ] = parameters_pumped_hydro[x] |
||
| 1102 | |||
| 1103 | # insert data |
||
| 1104 | for i, row in store.iterrows(): |
||
| 1105 | entry = etrago.EgonPfHvStorage( |
||
| 1106 | scn_name="eGon2035", |
||
| 1107 | storage_id=int(db.next_etrago_id("storage")), |
||
| 1108 | bus=row.bus, |
||
| 1109 | max_hours=row.max_hours, |
||
| 1110 | efficiency_store=row.store, |
||
| 1111 | efficiency_dispatch=row.dispatch, |
||
| 1112 | standing_loss=row.standing_loss, |
||
| 1113 | carrier=row.carrier, |
||
| 1114 | p_nom=row.cap_2035, |
||
| 1115 | ) |
||
| 1116 | |||
| 1117 | session.add(entry) |
||
| 1118 | session.commit() |
||
| 1119 | |||
| 1120 | |||
| 1121 | def get_map_buses(): |
||
| 1122 | """Returns a dictonary of foreign regions which are aggregated to another |
||
| 1123 | |||
| 1124 | Returns |
||
| 1125 | ------- |
||
| 1126 | Combination of aggregated regions |
||
| 1127 | |||
| 1128 | |||
| 1129 | """ |
||
| 1130 | return { |
||
| 1131 | "DK00": "DKW1", |
||
| 1132 | "DKKF": "DKE1", |
||
| 1133 | "FR15": "FR00", |
||
| 1134 | "NON1": "NOM1", |
||
| 1135 | "NOS0": "NOM1", |
||
| 1136 | "NOS1": "NOM1", |
||
| 1137 | "PLE0": "PL00", |
||
| 1138 | "PLI0": "PL00", |
||
| 1139 | "SE00": "SE02", |
||
| 1140 | "SE01": "SE02", |
||
| 1141 | "SE03": "SE02", |
||
| 1142 | "SE04": "SE02", |
||
| 1143 | "RU": "RU00", |
||
| 1144 | } |
||
| 1145 | |||
| 1146 | |||
| 1147 | def tyndp_generation(): |
||
| 1148 | """Insert data from TYNDP 2020 accordning to NEP 2021 |
||
| 1149 | Scenario 'Distributed Energy', linear interpolate between 2030 and 2040 |
||
| 1150 | |||
| 1151 | Returns |
||
| 1152 | ------- |
||
| 1153 | None. |
||
| 1154 | """ |
||
| 1155 | |||
| 1156 | capacities = calc_capacities() |
||
| 1157 | |||
| 1158 | insert_generators(capacities) |
||
| 1159 | |||
| 1160 | insert_storage(capacities) |
||
| 1161 | |||
| 1162 | |||
| 1163 | @db.session_scoped |
||
| 1164 | def tyndp_demand(session=None): |
||
| 1165 | """Copy load timeseries data from TYNDP 2020. |
||
| 1166 | According to NEP 2021, the data for 2030 and 2040 is interpolated linearly. |
||
| 1167 | |||
| 1168 | Returns |
||
| 1169 | ------- |
||
| 1170 | None. |
||
| 1171 | |||
| 1172 | """ |
||
| 1173 | map_buses = get_map_buses() |
||
| 1174 | |||
| 1175 | sources = config.datasets()["electrical_neighbours"]["sources"] |
||
| 1176 | targets = config.datasets()["electrical_neighbours"]["targets"] |
||
| 1177 | |||
| 1178 | # Delete existing data |
||
| 1179 | db.execute_sql( |
||
| 1180 | f""" |
||
| 1181 | DELETE FROM {targets['loads']['schema']}. |
||
| 1182 | {targets['loads']['table']} |
||
| 1183 | WHERE |
||
| 1184 | scn_name = 'eGon2035' |
||
| 1185 | AND carrier = 'AC' |
||
| 1186 | AND bus NOT IN ( |
||
| 1187 | SELECT bus_i |
||
| 1188 | FROM {sources['osmtgmod_bus']['schema']}. |
||
| 1189 | {sources['osmtgmod_bus']['table']}) |
||
| 1190 | """ |
||
| 1191 | ) |
||
| 1192 | |||
| 1193 | nodes = [ |
||
| 1194 | "AT00", |
||
| 1195 | "BE00", |
||
| 1196 | "CH00", |
||
| 1197 | "CZ00", |
||
| 1198 | "DKE1", |
||
| 1199 | "DKW1", |
||
| 1200 | "FR00", |
||
| 1201 | "NL00", |
||
| 1202 | "LUB1", |
||
| 1203 | "LUF1", |
||
| 1204 | "LUG1", |
||
| 1205 | "NOM1", |
||
| 1206 | "NON1", |
||
| 1207 | "NOS0", |
||
| 1208 | "SE01", |
||
| 1209 | "SE02", |
||
| 1210 | "SE03", |
||
| 1211 | "SE04", |
||
| 1212 | "PL00", |
||
| 1213 | "UK00", |
||
| 1214 | "UKNI", |
||
| 1215 | ] |
||
| 1216 | # Assign etrago bus_id to TYNDP nodes |
||
| 1217 | buses = pd.DataFrame({"nodes": nodes}) |
||
| 1218 | buses.loc[ |
||
| 1219 | buses[buses.nodes.isin(map_buses.keys())].index, "nodes" |
||
| 1220 | ] = buses[buses.nodes.isin(map_buses.keys())].nodes.map(map_buses) |
||
| 1221 | buses.loc[:, "bus"] = ( |
||
| 1222 | get_foreign_bus_id().loc[buses.loc[:, "nodes"]].values |
||
| 1223 | ) |
||
| 1224 | buses.set_index("nodes", inplace=True) |
||
| 1225 | buses = buses[~buses.index.duplicated(keep="first")] |
||
| 1226 | |||
| 1227 | # Read in data from TYNDP for 2030 and 2040 |
||
| 1228 | dataset_2030 = pd.read_excel( |
||
| 1229 | f"tyndp/{sources['tyndp_demand_2030']}", sheet_name=nodes, skiprows=10 |
||
| 1230 | ) |
||
| 1231 | |||
| 1232 | dataset_2040 = pd.read_excel( |
||
| 1233 | f"tyndp/{sources['tyndp_demand_2040']}", sheet_name=None, skiprows=10 |
||
| 1234 | ) |
||
| 1235 | |||
| 1236 | # Transform map_buses to pandas.Series and select only used values |
||
| 1237 | map_series = pd.Series(map_buses) |
||
| 1238 | map_series = map_series[map_series.index.isin(nodes)] |
||
| 1239 | |||
| 1240 | # Calculate and insert demand timeseries per etrago bus_id |
||
| 1241 | for bus in buses.index: |
||
| 1242 | nodes = [bus] |
||
| 1243 | |||
| 1244 | if bus in map_series.values: |
||
| 1245 | nodes.extend(list(map_series[map_series == bus].index.values)) |
||
| 1246 | |||
| 1247 | load_id = db.next_etrago_id("load") |
||
| 1248 | |||
| 1249 | # Some etrago bus_ids represent multiple TYNDP nodes, |
||
| 1250 | # in this cases the loads are summed |
||
| 1251 | data_2030 = pd.Series(index=range(8760), data=0.0) |
||
| 1252 | for node in nodes: |
||
| 1253 | data_2030 = dataset_2030[node][2011] + data_2030 |
||
| 1254 | |||
| 1255 | try: |
||
| 1256 | data_2040 = pd.Series(index=range(8760), data=0.0) |
||
| 1257 | |||
| 1258 | for node in nodes: |
||
| 1259 | data_2040 = dataset_2040[node][2011] + data_2040 |
||
| 1260 | except: |
||
| 1261 | data_2040 = data_2030 |
||
| 1262 | |||
| 1263 | # According to the NEP, data for 2030 and 2040 is linear interpolated |
||
| 1264 | data_2035 = ((data_2030 + data_2040) / 2)[:8760] |
||
| 1265 | |||
| 1266 | entry = etrago.EgonPfHvLoad( |
||
| 1267 | scn_name="eGon2035", |
||
| 1268 | load_id=int(load_id), |
||
| 1269 | carrier="AC", |
||
| 1270 | bus=int(buses.bus[bus]), |
||
| 1271 | ) |
||
| 1272 | |||
| 1273 | entry_ts = etrago.EgonPfHvLoadTimeseries( |
||
| 1274 | scn_name="eGon2035", |
||
| 1275 | load_id=int(load_id), |
||
| 1276 | temp_id=1, |
||
| 1277 | p_set=list(data_2035.values), |
||
| 1278 | ) |
||
| 1279 | |||
| 1280 | session.add(entry) |
||
| 1281 | session.add(entry_ts) |
||
| 1282 | session.commit() |
||
| 1283 |