Skip to content

PeterKlein11/pypsa-earth

 
 

Repository files navigation

PyPSA-Earth

by

Development Status: Stable and Active

Status Linux Status Mac Status Windows Documentation Status Size License: AGPL v3 REUSE status Code style: black pre-commit.ci status Discord Google Drive

PyPSA-Earth is the first open-source global energy system model with data in high spatial and temporal resolution. It enables large-scale collaboration by providing a tool that can model the world energy system or any subset of it. This work is derived from the European PyPSA-Eur model using new data and functions. It is suitable for operational as well as combined generation, storage and transmission expansion studies. The model provides two main features: (1) customizable data extraction and preparation scripts with global coverage and (2) a PyPSA energy modelling framework integration. The data includes electricity demand, generation and medium to high-voltage networks from open sources, yet additional data can be further integrated. A broad range of clustering and grid meshing strategies help adapt the model to computational and practical needs.

The model is described in the Applied Energy article "PyPSA-Earth. A new global open energy system optimization model demonstrated in Africa", 2023, https://doi.org/10.1016/j.apenergy.2023.12109 (BibTeX). The documentation provides additional information.

PyPSA meets Earth is a free and open source software initiative aiming to develop a powerful energy system model for Earth. We work on open data, open source modelling, open source solver support and open communities. Stay tuned and join our mission - We look for users, co-developers and leaders! Check out our website for results and our projects. Happy coding!

Livetracker. Most popular global models:

Get involved

There are multiple ways to get involved and learn more about our work. That's how we organise ourselves:

  • Discord NEW! (Open)
    • chat with the community, team up on features, exchange with developers, code in voice channels
    • registration and usage is for free

  • General initiative meeting (Open)
    • every forth Thursday each month Thursday 16-17:00 (UK time) download .ics
    • join for project news and high-level code updates
    • meeting hosted on Discord
    • open agenda. See what we will discuss. Invited members have edit rights.
  • Buddy talk (Open)
  • Specific code meeting (Open)
    • meeting hosted on Discord
    • join updates, demos, Q&A's, discussions and the coordination of each work package
      1. Demand creation and prediction meeting, on demand
      2. AI asset detection meeting, on demand
      3. Sector coupling meeting, every Thursday 09:00 (UK time), download .ics
      4. PyPSA-Earth meeting, every Thursday 16:00 (UK time), download .ics
  • Outreach meeting (Open)
    • every second week, Tuesday 17:00 (UK time)
    • planning, discussing events, workshops, communication, community activities
  • Google Drive
    • access to minutes, presentations, lists, documents (access to minutes)

Installation

  1. Open your terminal at a location where you want to install pypsa-earth. Type the following in your terminal to download the package from GitHub:

       .../some/path/without/spaces % git clone https://github.com/pypsa-meets-earth/pypsa-earth.git
  2. The python package requirements are curated in the envs/environment.yaml file. The environment can be installed using:

    .../pypsa-earth % conda env create -f envs/environment.yaml

If the above takes longer than 30min, you might want to try mamba for faster installation:

    (base) conda install -c conda-forge mamba

    .../pypsa-earth % mamba env create -f envs/environment.yaml
  1. For running the optimization one has to install the solver. We can recommend the open source HiGHs solver which installation manual is given here.

  2. To use jupyter lab (new jupyter notebooks) continue with the ipython kernel installation and test if your jupyter lab works:

       .../pypsa-earth % ipython kernel install --user --name=pypsa-earth
       .../pypsa-earth % jupyter lab
  3. Verify or install a java redistribution from the official website or equivalent. To verify the successful installation the following code can be tested from bash:

       .../pypsa-earth % java -version

    The expected output should resemble the following:

       java version "1.8.0_341"
       Java(TM) SE Runtime Environment (build 1.8.0_341-b10)
       Java HotSpot(TM) 64-Bit Server VM (build 25.341-b10, mixed mode)

Test run on tutorial

  • In the folder open a terminal/command window to be located at this path ~/pypsa-earth/

  • Activate the environment conda activate pypsa-earth

  • Rename config.tutorial.yaml to config.yaml. For instance in Linux:

    mv config.tutorial.yaml config.yaml
  • Run a dryrun of the Snakemake workflow by typing simply in the terminal:

    snakemake -j 1 solve_all_networks -n

    Remove the -n to do a real run. Follow the tutorial of PyPSA-Eur 1 and 2 on YouTube to continue with an analysis.

Training

  • We recently updated some hackathon material for PyPSA-Earth. The hackathon contains jupyter notebooks with exercises. After going through the 1 day theoretical and practical material you should have a suitable coding setup and feel confident about contributing.
  • The get a general feeling about the PyPSA functionality, we further recommend going through the PyPSA and Atlite examples.

Questions and Issues

  • We are happy to answer questions and help with issues if they are public. Through being public the wider community can benefit from the raised points. Some tips. Bugs and feature requests should be raised in the GitHub Issues. General workflow or user questions as well as discussion points should be posted at the GitHub Discussions tab. Happy coding.

Documentation

The documentation is available here: documentation.

Collaborators

PeterKlein11
Null
davide-f
Davide-f
pz-max
Max Parzen
ekatef
Ekaterina
DeniseGiub
DeniseGiub
mnm-matin
Mnm-matin
hazemakhalek
Hazem
energyLS
EnergyLS
yerbol-akhmetov
Yerbol Akhmetov
Tomkourou
Thomas Kouroughli
giacfalk
Giacomo Falchetta
Ekaterina-Vo
Ekaterina-Vo
euronion
Euronion
AnasAlgarei
AnasAlgarei
LukasFrankenQ
Lukas Franken
cschau-ieg
Cschau-ieg
Tooblippe
Tobias
martacki
Martha Frysztacki
koen-vg
Koen Van Greevenbroek
asolavi
Null
carlosfv92
Carlos Fernandez
EmreYorat
EmreYorat
GridGrapher
GridGrapher
HanaElattar
HanaElattar
jarry7
Jarrad Wright
pitmonticone
Pietro Monticone
squoilin
Sylvain Quoilin
juli-a-ko
Juli-a-ko
stephenjlee
Stephen J Lee

About

PyPSA-Earth: An Open Optimisation Model of the Earth Energy System.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 100.0%