etrago.tools package

etrago.tools.calc_results module

calc_results.py defines methods to calculate results of eTraGo

etrago.tools.calc_results.calc_investment_cost(self)

Function that calulates overall annualized investment costs.

Returns:

• network_costs (float) – Investments in line expansion (AC+DC)

• link_costs (float) – Investments in sectorcoupling link expansion

• stor_costs (float) – Investments in storage and store expansion

etrago.tools.calc_results.calc_marginal_cost(self)

Function that caluclates and returns marginal costs, considering generation and link and storage dispatch costs

Returns:

marginal_cost – Annual marginal cost in EUR

Return type:

float

etrago.tools.calc_results.german_network(self)

Cut out all network components in Germany

Returns:

new_network – Network with all components in Germany

Return type:

pypsa.Network

etrago.tools.calc_results.system_costs_germany(self)

Calculte system costs for Germany

Returns:

• marginal_cost (float) – Marginal costs for dispatch in Germany

• invest_cost (float) – Annualized investment costs for components in Germany

• import_costs (float) – Costs for energy imported to Germany minus costs for exports

etrago.tools.calc_results.ac_export(self)

Calculate electricity exports and imports over AC lines

Returns:

Electricity export (if negative: import) from Germany

Return type:

float

etrago.tools.calc_results.ac_export_per_country(self)

Calculate electricity exports and imports over AC lines per country

Returns:

Electricity export (if negative: import) from Germany in TWh

Return type:

float

etrago.tools.calc_results.dc_export(self)

Calculate electricity exports and imports over DC lines

Returns:

Electricity export (if negative: import) from Germany

Return type:

float

etrago.tools.calc_results.dc_export_per_country(self)

Calculate electricity exports and imports over DC lines per country

Returns:

Electricity export (if negative: import) from Germany in TWh

Return type:

float

etrago.tools.calc_results.calc_etrago_results(self)

Function that calculates main results of grid optimization and adds them to Etrago object.

Return type:

None.

etrago.tools.constraints module

etrago.tools.execute module

etrago.tools.extendable module

Extendable.py defines function to set PyPSA components extendable.

etrago.tools.extendable.extendable(self, grid_max_D=None, grid_max_abs_D={'110': {'circuits': 2, 'i': 1020, 'wires': 4}, '220': {'circuits': 4, 'i': 1020, 'wires': 4}, '380': {'circuits': 4, 'i': 1020, 'wires': 4}, 'dc': 0}, grid_max_foreign=4, grid_max_abs_foreign=None)

Function that sets selected components extendable.

Parameters:

• grid_max_D (int, optional) – Upper bounds for electrical grid expansion relative to existing capacity. The default is None.

• grid_max_abs_D (dict, optional) – Absolute upper bounds for electrical grid expansion in Germany.

• grid_max_foreign (int, optional) – Upper bounds for expansion of electrical foreign lines relative to the existing capacity. The default is 4.

• grid_max_abs_foreign (dict, optional) – Absolute upper bounds for expansion of foreign electrical grid. The default is None.

Return type:

None.

etrago.tools.extendable.snommax(i=1020, u=380, wires=4, circuits=4)

Function to calculate limitation for capacity expansion.

Parameters:

• i (int, optional) – Current. The default is 1020.

• u (int, optional) – Voltage level. The default is 380.

• wires (int, optional) – Number of wires per line. The default is 4.

• circuits (int, optional) – Number of circuits. The default is 4.

Returns:

s_nom_max – Limitation for capacity expansion.

Return type:

float

etrago.tools.extendable.line_max_abs(network, buses, line_max_abs={'110': {'circuits': 2, 'i': 1020, 'wires': 4}, '220': {'circuits': 4, 'i': 1020, 'wires': 4}, '380': {'circuits': 4, 'i': 1020, 'wires': 4}, 'dc': 0})

Function to calculate limitation for capacity expansion of lines in network.

Parameters:

• network (pypsa.Network object) – Container for all network components.

• buses (pypsa.Network buses) – Considered buses in network.

• line_max_abs (dict, optional) – Line parameters considered to calculate maximum capacity.

Return type:

None.

etrago.tools.extendable.transformer_max_abs(network, buses)

Function to calculate limitation for capacity expansion of transformers in network.

Parameters:

• network (pypsa.Network object) – Container for all network components.

• buses (pypsa.Network buses) – Considered buses in network.

Return type:

None.

etrago.tools.extendable.extension_preselection(etrago, method, days=3)

Function that preselects lines which are extendend in snapshots leading to overloading to reduce nubmer of extension variables.

Parameters:

• network (pypsa.Network object) – Container for all network components.

• args (dict) – Arguments set in appl.py.

• method (str) – Choose method of selection: ‘extreme_situations’ for remarkable timsteps (e.g. minimal resiudual load) ‘snapshot_clustering’ for snapshot clustering with number of days

• days (int) – Number of clustered days, only used when method = ‘snapshot_clustering’

Returns:

network – Container for all network components.

Return type:

pypsa.Network object

etrago.tools.extendable.print_expansion_costs(network)

Function that prints network and storage investment costs.

Parameters:

network (pypsa.Network object) – Container for all network components.

Return type:

None.

etrago.tools.io module

io.py

Input/output operations between powerflow schema in the oedb and PyPSA. Additionally oedb wrapper classes to instantiate PyPSA network objects.

etrago.tools.io.packagename

Package containing orm class definitions

Type:

str

etrago.tools.io.temp_ormclass

Orm class name of table with temporal resolution

Type:

str

etrago.tools.io.carr_ormclass

Orm class name of table with carrier id to carrier name datasets

Type:

str

Notes

A configuration file connecting the chosen optimization method with components to be queried is needed for NetworkScenario class.

class etrago.tools.io.ScenarioBase(engine, session, version=None)

Bases: object

Base class to address the dynamic provision of orm classes representing powerflow components from egoio

Parameters:

• session (sqla.orm.session.Session) – Handles conversations with the database.

• version (str) – Version number of data version control in grid schema of the oedb.

class etrago.tools.io.NetworkScenario(engine, session, scn_name='Status Quo', start_snapshot=1, end_snapshot=20, temp_id=1, **kwargs)

Bases: ScenarioBase

Adapter class between oedb powerflow data and PyPSA. Provides the method build_network to generate a pypsa.Network.

Parameters:

• scn_name (str) – Scenario name.

• method (str) – Objective function.

• start_snapshot (int) – First snapshot or timestep.

• end_snapshot (int) – Last timestep.

• temp_id (int) – Nummer of temporal resolution.

Methods

build_network([network])	Core method to construct PyPSA Network object.
configure_timeindex()	Construct a DateTimeIndex with the queried temporal resolution, start- and end_snapshot.
fetch_by_relname(name)	Construct DataFrame with component data from filtered table data.
series_fetch_by_relname(network, name, ...)	Construct DataFrame with component timeseries data from filtered table data.

id_to_source

configure_timeindex()

Construct a DateTimeIndex with the queried temporal resolution, start- and end_snapshot.

id_to_source()

fetch_by_relname(name)

Construct DataFrame with component data from filtered table data.

Parameters:

name (str) – Component name.

Returns:

Component data.

Return type:

pd.DataFrame

series_fetch_by_relname(network, name, pypsa_name)

Construct DataFrame with component timeseries data from filtered table data.

Parameters:

• name (str) – Component name.

• column (str) – Component field with timevarying data.

Returns:

Component data.

Return type:

pd.DataFrame

build_network(network=None, *args, **kwargs)

Core method to construct PyPSA Network object.

etrago.tools.io.clear_results_db(session)

Used to clear the result tables in the OEDB. Caution! This deletes EVERY RESULT SET!

etrago.tools.io.results_to_oedb(session, network, args, grid='hv', safe_results=False)

Return results obtained from PyPSA to oedb

Parameters:

• session –

• network (PyPSA network container) – Holds topology of grid including results from powerflow analysis

• args (dict) – Settings from appl.py

• grid (str) – Choose voltage-level, currently only ‘hv’ implemented

• safe_results (boolean) – If it is set to ‘True’ the result set will be saved to the versioned grid schema eventually apart from being saved to the model_draft by a SQL-script. ONLY set to True if you know what you are doing.

etrago.tools.io.run_sql_script(conn, scriptname='results_md2grid.sql')

This function runs .sql scripts in the folder ‘sql_scripts’

etrago.tools.io.extension(self, **kwargs)

Function that adds an additional network to the existing network container. The new network can include every PyPSA-component (e.g. buses, lines, links). To connect it to the existing network, transformers are needed.

All components and its timeseries of the additional scenario need to be inserted in the fitting ‘model_draft.ego_grid_pf_hv_extension_’ table. The scn_name in the tables have to be labled with ‘extension_’ + scn_name (e.g. ‘extension_nep2035’).

Until now, the tables include three additional scenarios: ‘nep2035_confirmed’: all new lines and needed transformers planed in the ‘Netzentwicklungsplan 2035’ (NEP2035) that have been confirmed by the Bundesnetzagentur (BNetzA)

‘nep2035_b2’: all new lines and needed transformers planned in the NEP 2035 in the scenario 2035 B2

‘BE_NO_NEP 2035’: DC-lines and transformers to connect the upcomming electrical-neighbours Belgium and Norway Generation, loads and its timeseries in Belgium and Norway for scenario ‘NEP 2035’

Parameters:

• network – The existing network container (e.g. scenario ‘NEP 2035’)

• session – session-data

• overlay_scn_name – Name of the additional scenario (WITHOUT ‘extension_’)

• start_snapshot –

• end_snapshot – Simulation time

Return type:

Network container including existing and additional network

etrago.tools.io.decommissioning(self, **kwargs)

Function that removes components in a decommissioning-scenario from the existing network container. Currently, only lines can be decommissioned.

All components of the decommissioning scenario need to be inserted in the fitting ‘model_draft.ego_grid_pf_hv_extension_’ table. The scn_name in the tables have to be labled with ‘decommissioning_’ + scn_name (e.g. ‘decommissioning_nep2035’).

Parameters:

• network – The existing network container (e.g. scenario ‘NEP 2035’)

• session – session-data

• overlay_scn_name – Name of the decommissioning scenario

Return type:

Network container including decommissioning

etrago.tools.io.distance(x0, x1, y0, y1)

Function that calculates the square of the distance between two points.

Parameters:

• x0 – x - coordinate of point 0

• x1 – x - coordinate of point 1

• y0 – y - coordinate of point 0

• y1 – y - coordinate of point 1

Returns:

distance – square of distance

Return type:

float

etrago.tools.io.calc_nearest_point(bus1, network)

Function that finds the geographical nearest point in a network from a given bus.

Parameters:

• bus1 (float) – id of bus

• network (Pypsa network container) – network including the comparable buses

Returns:

bus0 – bus_id of nearest point

Return type:

float

etrago.tools.io.add_ch4_h2_correspondence(self)

Method adding the database table grid.egon_etrago_ch4_h2 to self. It contains the mapping from H2 buses to their corresponding CH4 buses.

etrago.tools.network module

etrago.tools.plot module

etrago.tools.utilities module

Utilities.py includes a wide range of useful functions.

etrago.tools.utilities.filter_links_by_carrier(self, carrier, like=True)

Parameters:

• carrier (list or str) – name of the carriers of interest. Can be a list of carriers or single sting.

• like (bool, optional) – When like set to True, the links with carrier names that includes the carrier(s) supplied are returned, Not just exact matches. The default is True.

Returns:

df – Dataframe that contains just links with carriers of the types given in the argument carrier.

Return type:

pandas.DataFrame object

etrago.tools.utilities.buses_of_vlvl(network, voltage_level)

Get bus-ids of given voltage level(s).

Parameters:

• network (:class:`pypsa.Network) – Overall container of PyPSA

• voltage_level (list) –

Returns:

List containing bus-ids.

Return type:

list

etrago.tools.utilities.buses_grid_linked(network, voltage_level)

Get bus-ids of a given voltage level connected to the grid.

Parameters:

• network (:class:`pypsa.Network) – Overall container of PyPSA

• voltage_level (list) –

Returns:

List containing bus-ids.

Return type:

list

etrago.tools.utilities.geolocation_buses(self, apply_on='grid_model')

If geopandas is installed: Use geometries of buses x/y(lon/lat) and polygons of countries from RenpassGisParameterRegion in order to locate the buses

Else: Use coordinats of buses to locate foreign buses, which is less accurate.

TODO: Why not alway use geopandas??

Parameters:

• etrago (etrago.Etrago) – Transmission grid object

• apply_on (str) – State if this function is applied on the grid_model or the market_model. The market_model options can only be used if the method type is “market_grid”.

etrago.tools.utilities.buses_by_country(self, apply_on='grid_model')

Find buses of foreign countries using coordinates and return them as Pandas Series

Parameters:

• self (Etrago object) – Overall container of PyPSA

• apply_on (str) – State if this function is applied on the grid_model or the market_model. The market_model options can only be used if the method type is “market_grid”.

Return type:

None

etrago.tools.utilities.clip_foreign(network)

Delete all components and timelines located outside of Germany. If applied after optimization, transborder flows divided by country of origin are added as network.foreign_trade.

Parameters:

network (:class:`pypsa.Network) – Overall container of PyPSA

Returns:

network – Overall container of PyPSA

Return type:

:class:`pypsa.Network

etrago.tools.utilities.foreign_links(self)

Change transmission technology of foreign lines from AC to DC (links).

Parameters:

network (:class:`pypsa.Network) – Overall container of PyPSA

Returns:

network – Overall container of PyPSA

Return type:

:class:`pypsa.Network

etrago.tools.utilities.set_q_national_loads(self, cos_phi)

Set q component of national loads based on the p component and cos_phi

Parameters:

• network (pypsa.Network) – Overall container of PyPSA

• cos_phi (float) – Choose ration of active and reactive power of foreign loads

Returns:

network – Overall container of PyPSA

Return type:

pypsa.Network

etrago.tools.utilities.set_q_foreign_loads(self, cos_phi)

Set reative power timeseries of loads in neighbouring countries

Parameters:

• etrago (:class:`etrago.Etrago) – Transmission grid object

• cos_phi (float) – Choose ration of active and reactive power of foreign loads

Return type:

None

etrago.tools.utilities.connected_grid_lines(network, busids)

Get grid lines connected to given buses.

Parameters:

• network (:class:`pypsa.Network) – Overall container of PyPSA

• busids (list) – List containing bus-ids.

Returns:

PyPSA lines.

Return type:

class:`pandas.DataFrame

etrago.tools.utilities.connected_transformer(network, busids)

Get transformer connected to given buses.

Parameters:

• network (:class:`pypsa.Network) – Overall container of PyPSA

• busids (list) – List containing bus-ids.

Returns:

PyPSA transformer.

Return type:

class:`pandas.DataFrame

etrago.tools.utilities.load_shedding(self, temporal_disaggregation=False, **kwargs)

Implement load shedding in existing network to identify feasibility problems

Parameters:

• network (:class:`pypsa.Network) – Overall container of PyPSA

• marginal_cost (int) – Marginal costs for load shedding

• p_nom (int) – Installed capacity of load shedding generator

etrago.tools.utilities.set_control_strategies(network)

Sets control strategies for AC generators and storage units

Parameters:

network (:class:`pypsa.Network) – Overall container of PyPSA

Return type:

None.

etrago.tools.utilities.data_manipulation_sh(network)

Adds missing components to run calculations with SH scenarios.

Parameters:

network (:class:`pypsa.Network) – Overall container of PyPSA

Return type:

None

etrago.tools.utilities.export_to_csv(self, path)

Write calculation results to csv-files in path.

Parameters:

• network (pypsa.Network) – Overall container of PyPSA

• args (dict) – Contains calculation settings of appl.py

• path (str or False or None) – Choose path for csv-files. Specify “”, False or None to not do anything.

Return type:

None

etrago.tools.utilities.loading_minimization(network, snapshots)

Minimizes the sum of the products of each element in the passive_branches of the model.

Parameters:

• network (:class:`pypsa.Network) – Overall container of PyPSA

• snapshots ('pandas.core.indexes.datetimes.DatetimeIndex') – snapshots to perform the minimization

Return type:

None

etrago.tools.utilities.agg_series_lines(l0, network)

Given a pandas DataFrame l0 containing information about lines in a network and a network object, aggregates the data in l0 for all its attributes. Returns a pandas Series containing the aggregated data.

Parameters:

• l0 (pandas.DataFrame) – contain information about lines in a network.

• network (:class:`pypsa.Network) – Overall container of PyPSA

Returns:

A pandas Series containing aggregated data for the lines in the network.

Return type:

pandas.Series

etrago.tools.utilities.group_parallel_lines(network)

Function that groups parallel lines of the same voltage level to one line component representing all parallel lines

Parameters:

network (:class:`pypsa.Network) – Overall container of PyPSA

Return type:

None.

etrago.tools.utilities.delete_dispensable_ac_buses(etrago)

Function that identifies and delete AC buses without links, transformers, generators, loads, stores or storage_units, which also are connected to just one or two other buses

Parameters:

etrago (etrago object) –

Return type:

None.

etrago.tools.utilities.delete_irrelevant_oneports(etrago)

etrago.tools.utilities.set_line_costs(self, cost110=230, cost220=290, cost380=85, costDC=375)

Set capital costs for extendable lines in respect to PyPSA [€/MVA]

Parameters:

• network (:class:`pypsa.Network) – Overall container of PyPSA

• args (dict) – containing settings from appl.py

• cost110 – capital costs per km for 110kV lines and cables default: 230€/MVA/km, source: costs for extra circuit in dena Verteilnetzstudie, p. 146)

• cost220 – capital costs per km for 220kV lines and cables default: 280€/MVA/km, source: costs for extra circuit in NEP 2025, capactity from most used 220 kV lines in model

• cost380 – capital costs per km for 380kV lines and cables default: 85€/MVA/km, source: costs for extra circuit in NEP 2025, capactity from most used 380 kV lines in NEP

• costDC – capital costs per km for DC-lines default: 375€/MVA/km, source: costs for DC transmission line in NEP 2035

etrago.tools.utilities.set_trafo_costs(self, cost110_220=7500, cost110_380=17333, cost220_380=14166)

Set capital costs for extendable transformers in respect to PyPSA [€/MVA]

Parameters:

• network (:class:`pypsa.Network) – Overall container of PyPSA

• cost110_220 – capital costs for 110/220kV transformer default: 7500€/MVA, source: costs for extra trafo in dena Verteilnetzstudie, p. 146; S of trafo used in osmTGmod

• cost110_380 – capital costs for 110/380kV transformer default: 17333€/MVA, source: NEP 2025

• cost220_380 – capital costs for 220/380kV transformer default: 14166€/MVA, source: NEP 2025

etrago.tools.utilities.add_missing_components(self)

Add a missing transformer at Heizkraftwerk Nord in Munich and a missing transformer in Stuttgart.

Parameters:

network (:class:`pypsa.Network) – Overall container of PyPSA

Returns:

network – Overall container of PyPSA

Return type:

:class:`pypsa.Network

etrago.tools.utilities.convert_capital_costs(self)

Convert capital_costs to fit to considered timesteps

Parameters:

etrago (:class:`etrago.Etrago) – Transmission grid object

etrago.tools.utilities.find_snapshots(network, carrier, maximum=True, minimum=True, n=3)

Function that returns snapshots with maximum and/or minimum feed-in of selected carrier.

Parameters:

• network (:class:`pypsa.Network) – Overall container of PyPSA

• carrier (str) – Selected carrier of generators

• maximum (bool) – Choose if timestep of maximal feed-in is returned.

• minimum (bool) – Choose if timestep of minimal feed-in is returned.

• n (int) – Number of maximal/minimal snapshots

Returns:

calc_snapshots – List containing snapshots

Return type:

‘pandas.core.indexes.datetimes.DatetimeIndex’

etrago.tools.utilities.ramp_limits(network)

Add ramping constraints to thermal power plants.

Parameters:

network (:class:`pypsa.Network) – Overall container of PyPSA

etrago.tools.utilities.get_args_setting(self, jsonpath='scenario_setting.json')

Get and open json file with scenaio settings of eTraGo args. The settings incluedes all eTraGo specific settings of arguments and parameters for a reproducible calculation.

Parameters:

json_file (str) – Default: scenario_setting.json Name of scenario setting json file

Returns:

args – Dictionary of json file

Return type:

dict

etrago.tools.utilities.merge_dicts(dict1, dict2)

Return a new dictionary by merging two dictionaries recursively.

Parameters:

• dict1 (dict) – dictionary 1.

• dict2 (dict) – dictionary 2.

Returns:

result – Union of dict1 and dict2

Return type:

dict

etrago.tools.utilities.get_clustering_data(self, path)

Import the final busmap and the initial buses, lines and links

Parameters:

path (str) – Name of folder from which to import CSVs of network data.

Return type:

None

etrago.tools.utilities.set_random_noise(self, sigma=0.01)

Sets random noise to marginal cost of each generator.

Parameters:

• etrago (:class:`etrago.Etrago) – Transmission grid object

• seed (int) – seed number, needed to reproduce results

• sigma (float) – Default: 0.01 standard deviation, small values reduce impact on dispatch but might lead to numerical instability

etrago.tools.utilities.set_line_country_tags(network)

Set country tag for AC- and DC-lines.

Parameters:

network (:class:`pypsa.Network) – Overall container of PyPSA

etrago.tools.utilities.crossborder_capacity_tyndp2020()

This function downloads and extracts a scenario datafile for the TYNDP 2020 (Ten-Year Network Development Plan), reads a specific sheet from the file, filters it based on certain criteria, and then calculates the minimum cross-border capacities for a list of European countries. The minimum cross-border capacity is the minimum of the export and import capacities between two countries.

Returns:

Dictionary with cossborder capacities.

Return type:

dict

etrago.tools.utilities.crossborder_capacity(self)

Adjust interconnector capacties.

Parameters:

• network (:class:`pypsa.Network) – Overall container of PyPSA

• method (string) – Method of correction. Options are ‘ntc_acer’ and ‘thermal_acer’. ‘ntc_acer’ corrects all capacities according to values published by the ACER in 2016. ‘thermal_acer’ corrects certain capacities where our dataset most likely overestimates the thermal capacity.

etrago.tools.utilities.set_branch_capacity(etrago)

Set branch capacity factor of lines and transformers, different factors for HV (110kV) and eHV (220kV, 380kV).

Parameters:

etrago (:class:`etrago.Etrago) – Transmission grid object

etrago.tools.utilities.check_args(etrago)

Function that checks the consistency of etragos input parameters.

Parameters:

etrago (:class:`etrago.Etrago) – Overall container of eTraGo

Return type:

None.

etrago.tools.utilities.drop_sectors(self, drop_carriers)

Manually drop secors from network. Makes sure the network can be calculated without the dropped sectors.

Parameters:

drop_carriers (array) – List of sectors that will be dropped. e.g. [‘dsm’, ‘CH4’, ‘H2_saltcavern’, ‘H2_grid’, ‘central_heat’, ‘rural_heat’, ‘central_heat_store’, ‘rural_heat_store’, ‘Li ion’] means everything but AC

Return type:

None.

etrago.tools.utilities.update_busmap(self, new_busmap)

Update busmap after any clustering process

Parameters:

new_busmap (dictionary) – busmap used to clusted the network.

Return type:

None.

etrago.tools.utilities.adjust_CH4_gen_carriers(self)

Precise the carrier for the generators with CH4 carrier

For the eGon2035 scenario, the generators with carrier CH4 represent the prodution od biogas and methan. In the data model, these two differents types are differenciated only by the marginal cost of the generator. This function introduces a carrier distion (CH4_biogas and CH4_NG) in order to avoid the clustering of these two types of generator together and facilitate the contraint applying differently to each of them.

etrago.tools.utilities.residual_load(network, sector='electricity')

Calculate the residual load for the specified sector.

In case of the electricity sector residual load is calculated using all AC loads and all renewable generators with carriers ‘wind_onshore’, ‘wind_offshore’, ‘solar’, ‘solar_rooftop’, ‘biomass’, ‘run_of_river’, and ‘reservoir’.

In case of the central heat sector residual load is calculated using all central heat loads and all renewable generators with carriers ‘solar_thermal_collector’ and ‘geo_thermal’.

Parameters:

• network (PyPSA network) – Network to retrieve load and generation time series from, needed to determine residual load.

• sector (str) – Sector to determine residual load for. Possible options are ‘electricity’ and ‘central_heat’. Default: ‘electricity’.

Returns:

Dataframe with residual load for each bus in the network. Columns of the dataframe contain the corresponding bus name and index of the dataframe is a datetime index with the corresponding time step.

Return type:

pd.DataFrame

etrago.tools.utilities.manual_fixes_datamodel(etrago)

Apply temporal fixes to the data model until a new egon-data run is there

Parameters:

etrago (:class:`Etrago) – Overall container of Etrago

Return type:

None.