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)[source]¶
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.constraints module¶
Constraints.py includes additional constraints for eTraGo-optimizations
- etrago.tools.constraints.read_max_gas_generation(self)[source]¶
Return the values limiting the gas production in Germany
Read max_gas_generation_overtheyear from scenario.egon_scenario_parameters if the table is available in the database and return the dictionnary containing the values needed for the constraints to limit the gas production in Germany, depending of the scenario.
- Returns
arg
- Return type
- etrago.tools.constraints.add_ch4_constraints(self, network, snapshots)[source]¶
Add CH4 constraints for optimization with pyomo
Functionality that limits the dispatch of CH4 generators. In Germany, there is one limitation specific for biogas and one limitation specific for natural gas (natural gas only in eGon2035). Abroad, each generator has its own limitation contains in the column e_nom_max.
- Parameters
network (
pypsa.Network) – Overall container of PyPSAsnapshots (pandas.DatetimeIndex) – List of timesteps considered in the optimization
- Return type
None.
- etrago.tools.constraints.add_ch4_constraints_nmp(self, network, snapshots)[source]¶
Add CH4 constraints for optimization without pyomo
Functionality that limits the dispatch of CH4 generators. In Germany, there is one limitation specific for biogas and one limitation specific for natural gas (natural gas only in eGon2035). Abroad, each generator has its own limitation contains in the column e_nom_max.
- Parameters
network (
pypsa.Network) – Overall container of PyPSAsnapshots (pandas.DatetimeIndex) – List of timesteps considered in the optimization
- Return type
None.
- etrago.tools.constraints.snapshot_clustering_daily_bounds(self, network, snapshots)[source]¶
Bound the storage level to 0.5 max_level every 24th hour.
- Parameters
network (
pypsa.Network) – Overall container of PyPSAsnapshots (pandas.DatetimeIndex) – List of timesteps that will be constrained
- Return type
None
- etrago.tools.constraints.snapshot_clustering_daily_bounds_nmp(self, network, snapshots)[source]¶
Bound the storage level to 0.5 max_level every 24th hour.
- Parameters
network (
pypsa.Network) – Overall container of PyPSAsnapshots (pandas.DatetimeIndex) – List of timesteps that will be constrained
- Return type
None
- etrago.tools.constraints.snapshot_clustering_seasonal_storage(self, network, snapshots, simplified=False)[source]¶
Depicts intertemporal dependencies of storage units and stores when using snapshot clustering to typical periods for temporal complexity reduction.
- According to:
L. Kotzur et al: ‘Time series aggregation for energy system design: Modeling seasonal storage’, 2018
- Parameters
network (
pypsa.Network) – Overall container of PyPSAsnapshots (list) – A list of datetime objects representing the timestamps of the snapshots to be clustered.
simplified (bool, optional) – A flag indicating whether to use a simplified version of the model that does not include intra-temporal constraints and variables.
- Return type
None
- etrago.tools.constraints.snapshot_clustering_seasonal_storage_hourly(self, network, snapshots)[source]¶
Depicts intertemporal dependencies of storage units and stores when using snapshot clustering to typical periods for temporal complexity reduction.
- According to:
L. Kotzur et al: ‘Time series aggregation for energy system design: Modeling seasonal storage’, 2018
- Parameters
network (
pypsa.Network) – Overall container of PyPSAsnapshots (list) – A list of datetime objects representing the timestamps of the snapshots to be clustered.
- Return type
None
- etrago.tools.constraints.snapshot_clustering_seasonal_storage_nmp(self, n, sns, simplified=False)[source]¶
Depicts intertemporal dependencies of storage units and stores when using snapshot clustering to typical periods for temporal complexity reduction.
- According to:
L. Kotzur et al: ‘Time series aggregation for energy system design: Modeling seasonal storage’, 2018
- Parameters
n (
pypsa.Network) – Overall container of PyPSAsns (list) – A list of datetime objects representing the timestamps of the snapshots to be clustered.
simplified (bool, optional) – A flag indicating whether to use a simplified version of the model that does not include intra-temporal constraints and variables.
- Return type
None
- etrago.tools.constraints.snapshot_clustering_seasonal_storage_hourly_nmp(self, n, sns)[source]¶
Depicts intertemporal dependencies of storage units and stores when using snapshot clustering to typical periods for temporal complexity reduction.
- According to:
L. Kotzur et al: ‘Time series aggregation for energy system design: Modeling seasonal storage’, 2018
- Parameters
n (
pypsa.Network) – Overall container of PyPSAsns (list) – A list of datetime objects representing the timestamps of the snapshots to be clustered.
- Return type
None
- etrago.tools.constraints.split_dispatch_disaggregation_constraints(self, n, sns)[source]¶
Add constraints for state of charge of storage units and stores when separating the optimization into smaller subproblems while conducting thedispatch_disaggregation in temporally fully resolved network
The state of charge at the end of each slice is set to the value calculated in the optimization with the temporally reduced network to account to ensure compatibility and to reproduce saisonality
- Parameters
network (
pypsa.Network) – Overall container of PyPSAsnapshots (pandas.DatetimeIndex) – List of timesteps considered in the optimization
- Return type
None.
- class etrago.tools.constraints.Constraints(args, conduct_dispatch_disaggregation)[source]¶
Bases:
objectMethods
functionality(network, snapshots)Add constraints to pypsa-model using extra-functionality.
- functionality(network, snapshots)[source]¶
Add constraints to pypsa-model using extra-functionality. Serveral constraints can be choosen at once. Possible constraints are set and described in the above functions.
- Parameters
network (
pypsa.Network) – Overall container of PyPSAsnapshots (pandas.DatetimeIndex) – List of timesteps considered in the optimization
- etrago.tools.constraints.add_chp_constraints_nmp(n)[source]¶
Limits the dispatch of combined heat and power links based on T.Brown et. al : Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system, 2018
- Parameters
n (pypsa.Network) – Network container
- Return type
None.
- etrago.tools.constraints.add_chp_constraints(network, snapshots)[source]¶
Limits the dispatch of combined heat and power links based on T.Brown et. al : Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system, 2018
- Parameters
network (pypsa.Network) – Network container
snapshots (pandas.DataFrame) – Timesteps to optimize
- Return type
None.
etrago.tools.execute module¶
execute.py defines optimization and simulation methods for the etrago object.
- etrago.tools.execute.update_electrical_parameters(network, l_snom_pre, t_snom_pre)[source]¶
Update electrical parameters of active branch components considering s_nom of previous iteration.
- Parameters
network (pypsa.Network object) – Container for all network components.
l_snom_pre (pandas.Series) – s_nom of ac-lines in previous iteration.
t_snom_pre (pandas.Series) – s_nom of transformers in previous iteration.
- Return type
None.
- etrago.tools.execute.run_lopf(etrago, extra_functionality, method)[source]¶
Function that performs lopf with or without pyomo
- Parameters
etrago (etrago object) – eTraGo containing all network information and a PyPSA network.
extra_functionality (dict) – Define extra constranits.
method (dict) – Choose ‘n_iter’ and integer for fixed number of iterations or ‘threshold’ and derivation of objective in percent for variable number of iteration until the threshold of the objective function is reached.
- Return type
None.
- etrago.tools.execute.iterate_lopf(etrago, extra_functionality, method={'n_iter': 4, 'pyomo': True})[source]¶
Run optimization of lopf. If network extension is included, the specified number of iterations is calculated to consider reactance changes.
- Parameters
etrago (etrago object) – eTraGo containing all network information and a PyPSA network.
extra_functionality (dict) – Define extra constranits.
method (dict) – Choose ‘n_iter’ and integer for fixed number of iterations or ‘threshold’ and derivation of objective in percent for variable number of iteration until the threshold of the objective function is reached.
- etrago.tools.execute.lopf(self)[source]¶
Functions that runs lopf according to arguments.
- Return type
None.
- etrago.tools.execute.dispatch_disaggregation(self)[source]¶
Function running the tempral disaggregation meaning the optimization of dispatch in the temporally fully resolved network; therfore, the problem is reduced to smaller subproblems by slicing the whole considered time span while keeping inforation on the state of charge of storage units and stores to ensure compatibility and to reproduce saisonality.
- Return type
None.
- etrago.tools.execute.run_pf_post_lopf(self)[source]¶
Function that runs pf_post_lopf according to arguments.
- Return type
None.
- etrago.tools.execute.pf_post_lopf(etrago, calc_losses=False)[source]¶
Function that prepares and runs non-linar load flow using PyPSA pf. If crossborder lines are DC-links, pf is only applied on german network. Crossborder flows are still considerd due to the active behavior of links. To return a network containing the whole grid, the optimised solution of the foreign components can be added afterwards.
- Parameters
etrago (etrago object) – eTraGo containing all network information and a PyPSA network.
add_foreign_lopf (boolean) – Choose if foreign results of lopf should be added to the network when foreign lines are DC.
q_allocation (str) – Choose allocation of reactive power. Possible settings are listed in distribute_q function.
calc_losses (bolean) – Choose if line losses will be calculated.
- etrago.tools.execute.distribute_q(network, allocation='p_nom')[source]¶
Function that distributes reactive power at bus to all installed generators and storages.
- Parameters
network (pypsa.Network object) – Container for all network components.
allocation (str) – Choose key to distribute reactive power: ‘p_nom’ to dirstribute via p_nom ‘p’ to distribute via p_set.
- Return type
None.
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)[source]¶
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)[source]¶
Function to calculate limitation for capacity expansion.
- Parameters
- Returns
s_nom_max – Limitation for capacity expansion.
- Return type
- 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})[source]¶
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)[source]¶
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)[source]¶
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.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.carr_ormclass¶
Orm class name of table with carrier id to carrier name datasets
- Type
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)[source]¶
Bases:
objectBase 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)[source]¶
Bases:
ScenarioBaseAdapter class between oedb powerflow data and PyPSA. Provides the method build_network to generate a pypsa.Network.
- Parameters
Methods
build_network([network])Core method to construct PyPSA Network object.
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()[source]¶
Construct a DateTimeIndex with the queried temporal resolution, start- and end_snapshot.
- fetch_by_relname(name)[source]¶
Construct DataFrame with component data from filtered table data.
- Parameters
name (str) – Component name.
- Returns
Component data.
- Return type
pd.DataFrame
- etrago.tools.io.clear_results_db(session)[source]¶
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)[source]¶
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')[source]¶
This function runs .sql scripts in the folder ‘sql_scripts’
- etrago.tools.io.extension(self, **kwargs)[source]¶
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)[source]¶
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)[source]¶
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
etrago.tools.network module¶
etrago.tools.plot module¶
Plot.py defines functions necessary to plot results of eTraGo.
- etrago.tools.plot.set_epsg_network(network)[source]¶
Change EPSG from 4326 to 3857. Needed when using osm-background.
- Parameters
network (PyPSA network container) –
- etrago.tools.plot.plot_osm(x, y, zoom, alpha=0.4)[source]¶
Plots openstreetmap as background of network-plots
- etrago.tools.plot.coloring()[source]¶
Return a dictionary with a color assign to each kind of carrier used in etrago.network. This is used for plotting porpuses.
- Returns
colors – Color for each kind of carrier.
- Return type
- etrago.tools.plot.plot_line_loading_diff(networkA, networkB, timestep=0, osm=False)[source]¶
Plot difference in line loading between two networks (with and without switches) as color on lines
Positive values mean that line loading with switches is bigger than without Plot switches as small dots
- Parameters
networkA (PyPSA network container) – Holds topology of grid with switches including results from powerflow analysis
networkB (PyPSA network container) – Holds topology of grid without switches including results from powerflow analysis
filename (str) – Specify filename If not given, figure will be show directly
timestep (int) – timestep to show, default is 0
osm (bool or dict, e.g. {'x': [1,20], 'y': [47, 56], 'zoom' : 6}) –
If not False, osm is set as background with the following settings as dict:
’x’: array of two floats, x axis boundaries (lat)
’y’: array of two floats, y axis boundaries (long)
’zoom’ : resolution of osm
- etrago.tools.plot.network_expansion_diff(networkA, networkB, filename=None, boundaries=[], osm=False)[source]¶
Plot relative network expansion derivation of AC- and DC-lines.
- Parameters
networkA (PyPSA network container) – Holds topology of grid including results from powerflow analysis
networkB (PyPSA network container) – Holds topology of grid including results from powerflow analysis
filename (str or None) – Save figure in this direction
boundaries (array) – Set boundaries of heatmap axis
osm (bool or dict, e.g. {'x': [1,20], 'y': [47, 56], 'zoom' : 6}) –
If not False, osm is set as background with the following settings as dict:
’x’: array of two floats, x axis boundaries (lat)
’y’: array of two floats, y axis boundaries (long)
’zoom’ : resolution of osm
- etrago.tools.plot.plot_residual_load(network)[source]¶
Plots residual load summed of all exisiting buses.
- Parameters
network (PyPSA network containter) –
- Return type
Plot
- etrago.tools.plot.plot_stacked_gen(network, bus=None, resolution='GW', filename=None)[source]¶
Plot stacked sum of generation grouped by carrier type
- Parameters
network (PyPSA network container) –
bus (string) – Plot all generators at one specific bus. If none, sum is calulated for all buses
resolution (string) – Unit for y-axis. Can be either GW/MW/KW
- Return type
Plot
- etrago.tools.plot.plot_gen_diff(networkA, networkB, leave_out_carriers=['geothermal', 'oil', 'other_non_renewable', 'reservoir', 'waste'])[source]¶
Plot difference in generation between two networks grouped by carrier type
- Parameters
networkA (PyPSA network container with switches) –
networkB (PyPSA network container without switches) –
leave_out_carriers – list of carriers to leave out (default to all small carriers)
- Return type
Plot
- etrago.tools.plot.plot_voltage(network, boundaries=[], osm=False)[source]¶
Plot voltage at buses as hexbin
- Parameters
network (PyPSA network container) –
boundaries (list of 2 values, setting the lower and upper bound of colorbar) –
osm (bool or dict, e.g. {'x': [1,20], 'y': [47, 56], 'zoom' : 6}) –
If not False, osm is set as background with the following settings as dict:
’x’: array of two floats, x axis boundaries (lat)
’y’: array of two floats, y axis boundaries (long)
’zoom’ : resolution of osm
- Return type
Plot
- etrago.tools.plot.curtailment(network, carrier='solar', filename=None)[source]¶
Plot curtailment of selected carrier
- etrago.tools.plot.calc_dispatch_per_carrier(network, timesteps)[source]¶
Function that calculates dispatch per carrier in given timesteps
- Parameters
network (PyPSA network container) – Holds topology of grid including results from powerflow analysis
timesteps (array) – Timesteps considered in dispatch calculation
- Returns
dist – dispatch per carrier
- Return type
pandas.Series
- etrago.tools.plot.calc_storage_expansion_per_bus(network)[source]¶
Function that calculates storage expansion per bus and technology
- Parameters
network (PyPSA network container) – Holds topology of grid including results from powerflow analysis
- Returns
dist – storage expansion per bus and technology
- Return type
pandas.Series
- etrago.tools.plot.gen_dist_diff(networkA, networkB, techs=None, snapshot=0, n_cols=3, gen_size=0.2, filename=None, buscmap=<matplotlib.colors.LinearSegmentedColormap object>)[source]¶
Difference in generation distribution Green/Yellow/Red colors mean that the generation at a location is bigger with switches than without Blue colors mean that the generation at a location is smaller with switches than without
- Parameters
networkA (PyPSA network container) – Holds topology of grid with switches including results from powerflow analysis
networkB (PyPSA network container) – Holds topology of grid without switches including results from powerflow analysis
techs (dict) – type of technologies which shall be plotted
snapshot (int) – snapshot
n_cols (int) – number of columns of the plot
gen_size (num) – size of generation bubbles at the buses
filename (str) – Specify filename If not given, figure will be show directly
- Return type
None.
- etrago.tools.plot.nodal_gen_dispatch(network, networkB=None, techs=['wind_onshore', 'solar'], item='energy', direction=None, scaling=1, filename=None, osm=False)[source]¶
Plot nodal dispatch or capacity. If networkB is given, difference in dispatch is plotted.
- Parameters
network (PyPSA network container) – Holds topology of grid including results from powerflow analysis
networkB (PyPSA network container) – If given and item is ‘energy’, difference in dispatch between network and networkB is plotted. If item is ‘capacity’, networkB is ignored. default None
techs (None or list,) – Techs to plot. If None, all techs are plotted. default [‘wind_onshore’, ‘solar’]
item (str) – Specifies the plotted item. Options are ‘energy’ and ‘capacity’. default ‘energy’
direction (str) – Only considered if networkB is given and item is ‘energy’. Specifies the direction of change in dispatch between network and networkB. If ‘positive’, generation per tech which is higher in network than in networkB is plotted. If ‘negative’, generation per tech whcih is lower in network than in networkB is plotted. If ‘absolute’, total change per node is plotted. Green nodes have higher dispatch in network than in networkB. Red nodes have lower dispatch in network than in networkB. default None
scaling (int) – Scaling to change plot sizes. default 1
filename (path to folder) –
osm (bool or dict, e.g. {'x': [1,20], 'y': [47, 56], 'zoom' : 6}) –
If not False, osm is set as background with the following settings as dict:
’x’: array of two floats, x axis boundaries (lat)
’y’: array of two floats, y axis boundaries (long)
’zoom’ : resolution of osm
- Return type
None.
- etrago.tools.plot.nodal_production_balance(network, timesteps, scaling=1e-05)[source]¶
Function that calculates residual load per node in given timesteps
- Parameters
network (PyPSA network container) – Holds topology of grid including results from powerflow analysis
timesteps (array) – timesteps considered in calculation
scaling (float, optional) – Scaling factor for bus size. The default is 0.00001.
- Returns
bus_sizes (pandas.Series) – scaled residual load per node
bus_colors (pandas.Series) – ‘green’ for producer and ‘red’ for consumer
- etrago.tools.plot.storage_p_soc(network, mean='1H', filename=None)[source]¶
Plots the dispatch and state of charge (SOC) of extendable storages.
- Parameters
network (PyPSA network container) – Holds topology of grid including results from powerflow analysis
mean (str) – Defines over how many snapshots the p and soc values will averaged.
filename (path to folder) –
- Return type
None.
- etrago.tools.plot.storage_soc_sorted(network, filename=None)[source]¶
Plots the soc (state-pf-charge) of extendable storages
- Parameters
network (PyPSA network container) – Holds topology of grid including results from powerflow analysis
filename (path to folder) –
- Return type
None.
- etrago.tools.plot.mul_weighting(network, timeseries)[source]¶
Returns timeseries considering snapshot_weighting
- Parameters
network (:class:`pypsa.Network) – Overall container of PyPSA
timeseries (pd.Series) – timeseries not considering snapshot_weighting
- Returns
timeseries considering snapshot_weightings
- Return type
pd.Series
- etrago.tools.plot.plotting_colors(network)[source]¶
Add color values to network.carriers
- Parameters
network (:class:`pypsa.Network) – Overall container of PyPSA
- Return type
None.
- etrago.tools.plot.calc_network_expansion(network, method='abs', ext_min=0.1)[source]¶
Calculates absolute or relative expansion per AC- and DC-line
- Parameters
- Returns
all_network (:class:`pypsa.Network) – Whole network including not extended lines
extension_lines (pandas.Series) – AC-line expansion
extension_links (pandas.Series) – DC-line expansion
- etrago.tools.plot.plot_background_grid(network, ax)[source]¶
Plots grid topology in background of other network.plot
- Parameters
network (:class:`pypsa.Network) – Overall container of PyPSA
ax (matplotlib.axes._subplots.AxesSubplot) – axes of plot
- Return type
None.
- etrago.tools.plot.demand_side_management(self, buses, snapshots, agg='5h', used=False)[source]¶
Calculate shifting potential of demand side management
- Parameters
buses (array) – List of electricity buses.
snapshots (array) – List of snapshots.
agg (str, optional) – Temporal resolution. The default is ‘5h’.
used (boolean, optional) – State if usage should be included in the results. The default is False.
- Returns
df – Shifting potential (and usage) of power (MW) and energy (MWh)
- Return type
pandas.DataFrame
- etrago.tools.plot.bev_flexibility_potential(self, buses, snapshots, agg='5h', used=False)[source]¶
Calculate shifting potential of electric vehicles
- Parameters
buses (array) – List of electricity buses.
snapshots (array) – List of snapshots.
agg (str, optional) – Temporal resolution. The default is ‘5h’.
used (boolean, optional) – State if usage should be included in the results. The default is False.
- Returns
df – Shifting potential (and usage) of power (MW) and energy (MWh)
- Return type
pandas.DataFrame
- etrago.tools.plot.heat_stores(self, buses, snapshots, agg='5h', used=False)[source]¶
Calculate shifting potential (and usage) of heat stores
- Parameters
buses (array) – List of electricity buses.
snapshots (array) – List of snapshots.
agg (str, optional) – Temporal resolution. The default is ‘5h’.
used (boolean, optional) – State if usage should be included in the results. The default is False.
- Returns
df – Shifting potential (and usage) of power (MW) and energy (MWh)
- Return type
pandas.DataFrame
- etrago.tools.plot.hydrogen_stores(self, buses, snapshots, agg='5h', used=False)[source]¶
Calculate shifting potential (and usage) of heat stores
- Parameters
buses (array) – List of electricity buses.
snapshots (array) – List of snapshots.
agg (str, optional) – Temporal resolution. The default is ‘5h’.
used (boolean, optional) – State if usage should be included in the results. The default is False.
- Returns
df – Shifting potential (and usage) of power (MW) and energy (MWh)
- Return type
pandas.DataFrame
- etrago.tools.plot.flexibility_usage(self, flexibility, agg='5h', snapshots=[], buses=[], pre_path=None)[source]¶
Plots temporal distribution of potential and usage for flexibilities
- Parameters
flexibility (str) – Name of flexibility option.
agg (str, optional) – Temporal resolution. The default is “5h”.
snapshots (list, optional) – Considered snapshots, if empty all are considered. The default is [].
buses (list, optional) – Considered components at AC buses, if empty all are considered. The default is [].
pre_path (str, optional) – State of and where you want to store the figure. The default is None.
- Return type
None.
- etrago.tools.plot.plot_carrier(network, carrier_links=['AC'], carrier_buses=['AC'])[source]¶
- Parameters
network (:class:`pypsa.Network) – Overall container of PyPSA
carrier_links (list) – List of links to be plotted. The default is [“AC”].
carrier_buses (list) – List of buses to be plotted. The default is [“AC”].
cartopy (bool, optional) – Provide data about the availability of Cartopy. The default is True.
- Return type
None.
- etrago.tools.plot.plot_grid(self, line_colors, bus_sizes=0.001, bus_colors='grey', timesteps=range(0, 2), osm=False, boundaries=None, filename=None, disaggregated=False, ext_min=0.1, ext_width=False)[source]¶
Function that plots etrago.network and results for lines and buses
- Parameters
line_colors (str) –
Set static line color or attribute to plot e.g. ‘expansion_abs’ Current options:
’line_loading’: mean line loading in p.u. in selected timesteps
’v_nom’: nominal voltage of lines
’expansion_abs’: absolute network expansion in MVA
’expansion_rel’: network expansion in p.u. of existing capacity
’q_flow_max’: maximal reactive flows
bus_sizes (float, optional) – Size of buses. The default is 0.001.
bus_colors (str, optional) –
Set static bus color or attribute to plot. The default is ‘grey’. Current options:
’nodal_production_balance’: net producer/consumer in selected timeteps
’storage_expansion’: storage expansion per bus and technology
’storage_distribution’: installed storage units per bus
’gen_dist’: dispatch per carrier in selected timesteps
timesteps (array, optional) – Timesteps consideredd in time depended plots. The default is range(2).
osm (bool or dict, e.g. {'x': [1,20], 'y': [47, 56], 'zoom' : 6}) –
If not False, osm is set as background with the following settings as dict:
’x’: array of two floats, x axis boundaries (lat)
’y’: array of two floats, y axis boundaries (long)
’zoom’ : resolution of osm. The default is False.
boundaries (array) – Set fixed boundaries of heatmap axis. The default is None.
filename (str or None) – Save figure in this direction. The default is None.
disaggregated (bool, optional) – Choose if disaggregated network is shown. The default is False.
ext_min (float) – Choose minimum relative line extension shown in plot in p.u..
ext_width (float or bool) – Choose if line_width respects line extension. Turn off with ‘False’ or set linear factor to decremise extension line_width. The default is False.
- Return type
None.
- etrago.tools.plot.plot_clusters(self, carrier='AC', save_path=False, transmission_lines=False, gas_pipelines=False)[source]¶
- Parameters
carrier (str, optional) – This variable set the carrier of the buses that will be plotted. The default is “AC”.
cartopy (bool, optional) – Set it to True when cartopy is installed and the map is supposed to include country’s boundaries and bodies of water
save_path (bool, optional) – Path to save the generated plot. The default is False.
transmission_lines (bool, optional) – The default is False. Define if the original transmission lines are plotted or not.
gas_pipelines (bool, optional) – The default is False. Define if the original gas pipelines are plotted or not.
- Return type
None.
- etrago.tools.plot.plot_gas_generation(self, t_resolution='20H', save_path=False)[source]¶
Plots timeseries data for gas generation
- etrago.tools.plot.plot_gas_summary(self, t_resolution='20H', stacked=True, save_path=False)[source]¶
Plots timeseries data for gas loads (and generation)
- Parameters
self (:class:`Etrago) – Overall container of Etrago
t_resolution (str, optional) – sets the resampling rate of timeseries data to allow for smoother line plots
stacked (bool, optional) – If True all TS data will be shown as stacked area plot. Total gas generation will then also be plotted to check for matching demand and generation.
save_path (bool, optional) – Path to save the generated plot. The default is False.
- Return type
None.
- etrago.tools.plot.plot_h2_generation(self, t_resolution='20H', save_path=False)[source]¶
Plots timeseries data for H2 generation
- etrago.tools.plot.plot_h2_summary(self, t_resolution='20H', stacked=True, save_path=False)[source]¶
Plots timeseries data for H2 loads (and generation)
- Parameters
self (:class:`Etrago) – Overall container of Etrago
t_resolution (str, optional) – sets the resampling rate of timeseries data to allow for smoother line plots
stacked (bool, optional) – If True all TS data will be shown as stacked area plot. Total H2 generation will then also be plotted to check for matching demand and generation.
save_path (bool, optional) – Path to save the generated plot. The default is False.
- Return type
None.
- etrago.tools.plot.plot_heat_loads(self, t_resolution='20H', save_path=False)[source]¶
Plots timeseries data for heat loads
- etrago.tools.plot.plot_heat_summary(self, t_resolution='20H', stacked=True, save_path=False)[source]¶
Plots timeseries data for heat generation (and demand)
- Parameters
self (:class:`Etrago) – Overall container of Etrago
t_resolution (str, optional) – sets the resampling rate of timeseries data to allow for smoother line plots
stacked (bool, optional) – If True all TS data will be shown as stacked area plot. Total heat demand will then also be plotted to check for matching generation and demand.
save_path (bool, optional) – Path to save the generated plot. The default is False.
- Return type
None.
etrago.tools.utilities module¶
Utilities.py includes a wide range of useful functions.
- etrago.tools.utilities.filter_links_by_carrier(self, carrier, like=True)[source]¶
- Parameters
- 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)[source]¶
Get bus-ids of given voltage level(s).
- etrago.tools.utilities.buses_grid_linked(network, voltage_level)[source]¶
Get bus-ids of a given voltage level connected to the grid.
- etrago.tools.utilities.geolocation_buses(self)[source]¶
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
- etrago.tools.utilities.buses_by_country(self)[source]¶
Find buses of foreign countries using coordinates and return them as Pandas Series
- Parameters
self (Etrago object) – Overall container of PyPSA
- Return type
None
- etrago.tools.utilities.clip_foreign(network)[source]¶
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.
- etrago.tools.utilities.foreign_links(self)[source]¶
Change transmission technology of foreign lines from AC to DC (links).
- etrago.tools.utilities.set_q_national_loads(self, cos_phi)[source]¶
Set q component of national loads based on the p component and cos_phi
- Parameters
network (
pypsa.Network) – Overall container of PyPSAcos_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)[source]¶
Set reative power timeseries of loads in neighbouring countries
- etrago.tools.utilities.connected_grid_lines(network, busids)[source]¶
Get grid lines connected to given buses.
- etrago.tools.utilities.connected_transformer(network, busids)[source]¶
Get transformer connected to given buses.
- etrago.tools.utilities.load_shedding(self, temporal_disaggregation=False, **kwargs)[source]¶
Implement load shedding in existing network to identify feasibility problems
- etrago.tools.utilities.data_manipulation_sh(network)[source]¶
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)[source]¶
Write calculation results to csv-files in path.
- etrago.tools.utilities.loading_minimization(network, snapshots)[source]¶
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)[source]¶
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)[source]¶
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)[source]¶
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.set_line_costs(self, cost110=230, cost220=290, cost380=85, costDC=375)[source]¶
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)[source]¶
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)[source]¶
Add a missing transformer at Heizkraftwerk Nord in Munich and a missing transformer in Stuttgart.
- etrago.tools.utilities.convert_capital_costs(self)[source]¶
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)[source]¶
Function that returns snapshots with maximum and/or minimum feed-in of selected carrier.
- Parameters
- Returns
calc_snapshots – List containing snapshots
- Return type
‘pandas.core.indexes.datetimes.DatetimeIndex’
- etrago.tools.utilities.ramp_limits(network)[source]¶
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')[source]¶
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.
- etrago.tools.utilities.merge_dicts(dict1, dict2)[source]¶
Return a new dictionary by merging two dictionaries recursively.
- etrago.tools.utilities.get_clustering_data(self, path)[source]¶
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)[source]¶
Sets random noise to marginal cost of each generator.
- etrago.tools.utilities.set_line_country_tags(network)[source]¶
Set country tag for AC- and DC-lines.
- Parameters
network (:class:`pypsa.Network) – Overall container of PyPSA
- etrago.tools.utilities.crossborder_capacity_tyndp2020()[source]¶
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
- etrago.tools.utilities.crossborder_capacity(self)[source]¶
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)[source]¶
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)[source]¶
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)[source]¶
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)[source]¶
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)[source]¶
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')[source]¶
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