Default configuration data

Following you find the default configuration files.

config_db_tables

The config file config_db_tables.cfg holds data about which database connection to use from your saved database connections and which dataprocessing version.

# This file is part of eDisGo, a python package for distribution grid
# analysis and optimization.
#
# It is developed in the project open_eGo: https://openegoproject.wordpress.com
#
# eDisGo lives on github: https://github.com/openego/edisgo/
# The documentation is available on RTD: http://edisgo.readthedocs.io

[db_connection]

section = oedb

[data_source]

oedb_data_source = versioned

[model_draft]

conv_generators_prefix = t_ego_supply_conv_powerplant_
conv_generators_suffix = _mview
re_generators_prefix = t_ego_supply_res_powerplant_
re_generators_suffix = _mview
res_feedin_data = EgoRenewableFeedin
load_data = EgoDemandHvmvDemand
load_areas = EgoDemandLoadarea

#conv_generators_nep2035 = t_ego_supply_conv_powerplant_nep2035_mview
#conv_generators_ego100 = ego_supply_conv_powerplant_ego100_mview
#re_generators_nep2035 = t_ego_supply_res_powerplant_nep2035_mview
#re_generators_ego100 = t_ego_supply_res_powerplant_ego100_mview

[versioned]

conv_generators_prefix = t_ego_dp_conv_powerplant_
conv_generators_suffix = _mview
re_generators_prefix = t_ego_dp_res_powerplant_
re_generators_suffix = _mview
res_feedin_data = EgoRenewableFeedin
load_data = EgoDemandHvmvDemand
load_areas = EgoDemandLoadarea

version = v0.4.5

config_grid_expansion

The config file config_grid_expansion.cfg holds data mainly needed to determine grid expansion needs and costs - these are standard equipment to use in grid expansion and its costs, as well as allowed voltage deviations and line load factors.

# This file is part of eDisGo, a python package for distribution grid
# analysis and optimization.
#
# It is developed in the project open_eGo: https://openegoproject.wordpress.com
#
# eDisGo lives on github: https://github.com/openego/edisgo/
# The documentation is available on RTD: http://edisgo.readthedocs.io

[grid_expansion_standard_equipment]

# standard equipment
# ==================
# Standard equipment for grid expansion measures. Source: Rehtanz et. al.: "Verteilnetzstudie für das Land Baden-Württemberg", 2017.
hv_mv_transformer = 40 MVA
mv_lv_transformer = 630 kVA
mv_line = NA2XS2Y 3x1x185 RM/25
lv_line = NAYY 4x1x150

[grid_expansion_allowed_voltage_deviations]

# allowed voltage deviations
# ==========================
# COMBINED MV+LV
# --------------
# hv_mv_trafo_offset:
#     offset which is set at HV-MV station
#     (pos. if op. voltage is increased, neg. if decreased)
hv_mv_trafo_offset = 0.0

# hv_mv_trafo_control_deviation:
#     control deviation of HV-MV station
#     (always pos. in config; pos. or neg. usage depending on case in edisgo)
hv_mv_trafo_control_deviation = 0.0

# mv_lv_max_v_deviation:
#     max. allowed voltage deviation according to DIN EN 50160
#     caution: offset and control deviation at HV-MV station must be considered in calculations!
mv_lv_feedin_case_max_v_deviation = 0.1
mv_lv_load_case_max_v_deviation = 0.1

# MV ONLY
# -------
# mv_load_case_max_v_deviation:
#     max. allowed voltage deviation in MV grids (load case)
mv_load_case_max_v_deviation = 0.015

# mv_feedin_case_max_v_deviation:
#     max. allowed voltage deviation in MV grids (feedin case)
#     according to BDEW
mv_feedin_case_max_v_deviation = 0.05

# LV ONLY
# -------
# max. allowed voltage deviation in LV grids (load case)
lv_load_case_max_v_deviation = 0.065

# max. allowed voltage deviation in LV grids (feedin case)
#     according to VDE-AR-N 4105
lv_feedin_case_max_v_deviation = 0.035

# max. allowed voltage deviation in MV/LV stations (load case)
mv_lv_station_load_case_max_v_deviation = 0.02

# max. allowed voltage deviation in MV/LV stations (feedin case)
mv_lv_station_feedin_case_max_v_deviation = 0.015

[grid_expansion_load_factors]

# load factors
# ============
# Source: Rehtanz et. al.: "Verteilnetzstudie für das Land Baden-Württemberg", 2017.
mv_load_case_transformer = 0.5
mv_load_case_line = 0.5
mv_feedin_case_transformer = 1.0
mv_feedin_case_line = 1.0

lv_load_case_transformer = 1.0
lv_load_case_line = 1.0
lv_feedin_case_transformer = 1.0
lv_feedin_case_line = 1.0

# costs
# ============

[costs_cables]

# costs in kEUR/km
# costs for cables without earthwork are taken from [1] (costs for standard
# cables are used here as representative since they have average costs), costs
# including earthwork are taken from [2]
# [1] https://www.bundesnetzagentur.de/SharedDocs/Downloads/DE/Sachgebiete/Energie/Unternehmen_Institutionen/Netzentgelte/Anreizregulierung/GA_AnalytischeKostenmodelle.pdf?__blob=publicationFile&v=1
# [2] https://shop.dena.de/fileadmin/denashop/media/Downloads_Dateien/esd/9100_dena-Verteilnetzstudie_Abschlussbericht.pdf
# costs including earthwork costs depend on population density according to [2]
# here "rural" corresponds to a population density of <= 500 people/km²
# and "urban" corresponds to a population density of > 500 people/km²
lv_cable = 9
lv_cable_incl_earthwork_rural = 60
lv_cable_incl_earthwork_urban = 100
mv_cable = 20
mv_cable_incl_earthwork_rural = 80
mv_cable_incl_earthwork_urban = 140

[costs_transformers]

# costs in kEUR, source: DENA Verteilnetzstudie
lv = 10
mv = 1000

config_timeseries

The config file config_timeseries.cfg holds data to define the two worst-case scenarions heavy load flow (‘load case’) and reverse power flow (‘feed-in case’) used in conventional grid expansion planning, power factors and modes (inductive or capacitative) to generate reactive power time series, as well as configurations of the demandlib in case load time series are generated using the oemof demandlib.

# This file is part of eDisGo, a python package for distribution grid
# analysis and optimization.
#
# It is developed in the project open_eGo: https://openegoproject.wordpress.com
#
# eDisGo lives on github: https://github.com/openego/edisgo/
# The documentation is available on RTD: http://edisgo.readthedocs.io

# This file contains relevant data to generate load and feed-in time series.
# Peakload consumption ratios and scale factors are used in worst-case scenarios.
# Power factors are used to generate reactive power time series.

[peakload_consumption_ratio]

# peakload consumption ratios
# ===========================
# ratios of peak load to annual consumption per sector based on BDEW synthetic
# load profiles; used only in worst case analyses
residential = 0.00021372
retail = 0.0002404
industrial = 0.000132
agricultural = 0.00024036

[worst_case_scale_factor]

# scale factors
# ===========================
# scale factors describe actual power to nominal power ratio of generators and loads in worst-case scenarios
# following values provided by "dena-Verteilnetzstudie. Ausbau- und
# Innovationsbedarf der Stromverteilnetze in Deutschland bis 2030", .p. 98

mv_feedin_case_load = 0.15
lv_feedin_case_load = 0.1
mv_load_case_load = 1.0
lv_load_case_load = 1.0

feedin_case_feedin_pv = 0.85
feedin_case_feedin_other = 1
load_case_feedin_pv = 0
load_case_feedin_other = 0

[reactive_power_factor]

# power factors
# ===========================
# power factors used to generate reactive power time series for loads and generators

mv_gen = 0.9
mv_load = 0.9
mv_storage = 0.9
lv_gen = 0.95
lv_load = 0.95
lv_storage = 0.95

[reactive_power_mode]

# power factor modes
# ===========================
# power factor modes used to generate reactive power time series for loads and generators

mv_gen = inductive
mv_load = inductive
mv_storage = inductive
lv_gen = inductive
lv_load = inductive
lv_storage = inductive

[demandlib]

# demandlib data
# ===========================
# data used in the demandlib to generate industrial load profile
# see IndustrialProfile in https://github.com/oemof/demandlib/blob/master/demandlib/particular_profiles.py
# for further information

# scaling factors for night and day of weekdays and weekend days
week_day = 0.8
week_night = 0.6
weekend_day = 0.6
weekend_night = 0.6
# tuple specifying the beginning/end of a workday (e.g. 18:00)
day_start = 6:00
day_end = 22:00







config_grid

The config file config_grid.cfg holds data to specify parameters used when connecting new generators to the grid and where to position disconnecting points.

# This file is part of eDisGo, a python package for distribution grid
# analysis and optimization.
#
# It is developed in the project open_eGo: https://openegoproject.wordpress.com
#
# eDisGo lives on github: https://github.com/openego/edisgo/
# The documentation is available on RTD: http://edisgo.readthedocs.io

# Config file to specify parameters used when connecting new generators to the grid and
# where to position disconnecting points.

[geo]

# WGS84: 4326
srid = 4326

[grid_connection]

# branch_detour_factor:
#     normally, lines do not go straight from A to B due to obstacles etc. Therefore, a detour factor is used.
#     unit: -
branch_detour_factor = 1.3

# conn_buffer_radius:
#     radius used to find connection targets
#     unit: m
conn_buffer_radius = 2000

# conn_buffer_radius_inc:
#     radius which is incrementally added to connect_buffer_radius as long as no target is found
#     unit: m
conn_buffer_radius_inc = 1000

# conn_diff_tolerance:
#     threshold which is used to determine if 2 objects are on the same position
#     unit: -
conn_diff_tolerance = 0.0001

random_seed = 111344501344111


[disconnecting_point]

# Positioning of disconnecting points: Can be position at location of most
# balanced load or generation. Choose load, generation, loadgen
position = load