pypsa-eur-getting-started.org

Installing PyPSA-Eur

1. If you don’t have Anaconda installed, install it from here. This will use up to 6GB of disk space and might take some time. A less heavy alternative is Miniconda.
2. Download PyPSA-Eur as a zip (and extract it) or using GitHub (if you are familiar with git).
3. Launch “Anaconda Prompt (Anaconda3)” from the Start Menu if using Windows. On Linux/Mac, open a terminal (making sure conda is available, if not add its path in the PATH environment variable).
4. If the prompt starts with (base), type

   conda deactivate
       

   press Enter and make sure (base) disappears.

5. Type

   conda update -n base conda
       

   then press Enter and follow the instructions to update conda (might need Admin rights depending on where Anaconda was installed).

6. Type

   conda install -n base conda-libmamba-solver
       

   then press Enter and follow the instructions to install a conda setup library faster than the default one.

7. Go to the path where you unzipped/cloned PyPSA-Eur, e.g.:

   cd "C:\Users\SomeUserName\Documents\pypsa-eur"
       

8. Type

   conda env create --experimental-solver=libmamba -f envs/environment.yaml
       

   then press Enter and follow the instructions to create the Python environment to use to run PyPSA-Eur.

9. Type

   conda install -n pypsa-eur -c conda-forge --experimental-solver=libmamba jupyterlab
       

   then press Enter and follow the instructions to install Jupyter Lab (the suggested development environment to run and interact with the model).

10. Type

    conda install -n pypsa-eur -c gurobi --experimental-solver=libmamba gurobi
        

    then press Enter and follow the instructions to install the Gurobi solver.

11. Get a free Gurobi academic license here. Then go to your current Gurobi licenses, click on an available license and copy the command that starts with grbgetkey followed by a long hexadecimal key (appearing at the bottom of the page).
12. Type

    conda activate pypsa-eur
        

    then press Enter to start the PyPSA-Eur Python environment.

13. Type

    grbgetkey long-hexadecimal-key-copied-from-gurobi-website
        

    then press Enter and follow the instructions to activate the Gurobi key on your computer.

Running Jupyter Lab

1. Launch “Anaconda Prompt (Anaconda3)” from the Start Menu if using Windows. On Linux/Mac, open a terminal (making sure conda is available, if not add its path in the PATH environment variable). Then type:

   conda activate pypsa-eur
       

   and press Enter to start the PyPSA-Eur Python environment.

2. If not already located in the path where PyPSA-Eur was placed, cd into it, e.g.

   cd "C:\Users\SomeUserName\Documents\pypsa-eur"
       

3. Type

   jupyter lab
       

   then press Enter to launch the web interface through which you can interact with the model.

Running the model for the first time

1. Open Jupyter Lab as explained in section 2.
2. Right click on the file config.default.yaml then duplicate.
3. Right click on the duplicated file, then rename it to config.yaml.
4. Double click on config.yaml to edit it.
5. Change the line

   clusters: [37, 128, 256, 512, 1024]
       

   to

   clusters: [37]
       

6. Change the line

   opts: [Co2L-3H]
       

   to

   opts: [Co2L-24H]
       

7. File -> Save
8. File -> Close all tabs
9. From the launcher within Jupyter Lab, launch a new terminal
10. Type

    snakemake -j1 solve_all_networks
        

    then press Enter to start downloading all the data files and eventually solve the network. This will take some time and use up to ~20GB of space! For a smaller footprint run just the tutorial as explained in the section below.

Running the tutorial configuration

1. Open Jupyter Lab as explained in section 2.
2. Right click on the file config.tutorial.yaml then duplicate.
3. Right click on the duplicated file, then rename it to config.yaml.
4. Double click on config.yaml to edit it.
5. Change the line

   name: cbc
       

   to

   name: gurobi
       

6. File -> Save
7. File -> Close all tabs
8. From the launcher within Jupyter Lab, launch a new terminal
9. Type

   snakemake -j1 solve_all_networks
       

   then press Enter to start downloading all the tutorial data files and eventually solve the network.