Quickstart

This page gets you from a fresh installation to your first grid analysis in a few minutes. It assumes eDisGo is installed (see Installation) and that you have a ding0 grid (a directory of CSV files describing the grid topology — see Grid data). Small test grids ship with the eDisGo repository under tests/data/ (the smallest self-constructed one is ding0_test_network_1); note that a pip-installed eDisGo does not include the tests/ directory.

The five-minute example

The shortest meaningful study is a worst-case analysis: eDisGo builds the two classic grid-planning situations (heavy load / reverse feed-in), runs a power flow and reinforces the grid until all voltage and loading limits are met.

from edisgo import EDisGo

# 1. Load a ding0 grid. The EDisGo object is the top-level API.
edisgo = EDisGo(ding0_grid="path/to/ding0_grid")

# 2. Add a future generator park (optional, from the OpenEnergy DataBase).
#    Scenario names depend on the grid format: "nep2035"/"ego100" for legacy
#    grids, "eGon2035"/"eGon100RE" (with an engine=... argument) for current
#    geo-referenced grids.
edisgo.import_generators(generator_scenario="nep2035")

# 3. Create worst-case load and feed-in time series.
edisgo.set_time_series_worst_case_analysis()

# 4. Run a non-linear power flow to find voltage and loading problems.
edisgo.analyze()

# 5. Reinforce the grid to solve those problems.
edisgo.reinforce()

# 6. Read the resulting grid-expansion costs (in kEUR).
costs = edisgo.results.grid_expansion_costs

That is the whole core loop: load → time series → analyze → reinforce → results. Every other feature plugs into this loop. The canonical order in which the steps must be called (and the typical pitfalls) is summarised in The eDisGo workflow.

The guided walkthrough notebook

For a complete, realistic study — loading a real ding0 grid, pulling scenario data from the OpenEnergy Platform, adding electric vehicles, heat pumps, demand side management and storage, optimising their operation and then reinforcing — work through the guided notebook, which builds the full workflow up in seven stages:

If you prefer reading over running, the same steps are explained in prose in the User Guide, and the engineering behind them in Methodology & Physics.

Where to go next