pypsa-zm-data

This repository mostly hosts data required to run energy system planning scenarions for Zambia within PyPSA-Earth. Hence, it is not a standalone repository, and needs to be executed in conjunction with PyPSA-Earth.

It also contains customised pieces of code to run those scenarios, instructions on how to run them, and validation notebooks for Zambia.

Model Execution

Combining pypsa-earth and pypsa-zm-data repositories

The provided workflow builds on PyPSA-Earth. Therefore, first, the PyPSA-Earth repository must be forked and the fork should then be cloned. A fork can be created by navigating to the PyPSA-Earth website. By clicking on the fork-symbol in the upper right corner, a fork is created and linked to the specific user.

Next, we also need to fork the pypsa-zm-data repository. A fork can be created by navigating to the pypsa-zm-data website and clicking the fork symbol in the upper right corner.

To clone both forks to the correct locations on a local machine, the following commands can be used using the local machines shell:

git clone https://github.com/<user-name>/pypsa-earth

<user-name> must be replaced with your personal github-username.

After that, one must change to the freshly created pypsa-earth repository.

cd pypsa-earth/

and repeat the cloning, this time for the pypsa-zm-data repository.

git clone https://github.com/<user-name>/pypsa-zm-data

Again, <user-name> must be replaced with your personal github-username. At the end of this process, the following folder structure should have been created (where <user-name> is your personal github-username):

• ../<user-name>/pypsa-earth that contains the pypsa-earth repository.

• ../<user-name>/pypsa-earth/pypsa-zm-data that contains the pypsa-zm-data repository. Note that this is inside the directory of the pypsa-earth repository.

In order to install the pypsa-earth environment, instructions are provided in the pypsa-earth documentation, see Install dependencies and Python dependencies. Note that you should be in the directory ../<user-name>/pypsa-earth at the beginning this process. After installing the environment, activate it using

conda activate pypsa-earth

Before the whole workflow can be executed, the databundle must be retrieved. This can be done via:

snakemake -j 1 retrieve_databundle_light

This step can optionally be skipped if the data/ folder with all relevant subfolders already exists.

Feeding pypsa-earth with customized data from pypsa-zm-data

Work in progress. See the pypsa-kz-data repository for an example on how to do this.

So far, we can feed pypsa-earth with an updated list of power plants from the Energy Sector Report 2022 by the Energy Regulation Board.

1. Copy a Configuration File for Zambia

Configuration files for Zambia are stored in the pypsa-zm-data/configs/ folder. The desired configuration file should be copied from that folder into the pypsa-earth directory with the name config.yaml.

To do so in the terminal at the pypsa-earth directory you can type the following instruction:

...\pypsa-earth> cp pypsa-zm-data/configs/[desired config file] config.yaml

where [desired config file] can be any configuration file for Zambia. For instance, the default config for Zambia config.zm-default.yaml.

The main changes introduced in the default config file for Zambia config.zm-default.yaml are:

1. Remove offwind-ac and offwind-dc from extendable_carriers and renewable_carriers.

2. Set up the option replace to custom_powerplants. This considers only the customized list of power plants in pypsa-earth/data/custom_powerplants.csv (see Section 2 below).

2. Update the Zambian Powerplants

An complete list of power plants in Zambia can be found in pypsa-zm-data/data/powerplants_zm_all.csv. This includes all power plants with installed capacity >= 1 MW from the Energy Sector Report 2022 by the Energy Regulation Board.

To execute the workflow with these power plants, two steps must be done:

1. Copy the file pypsa-zm-data/data/powerplants_zm_all.csv to the folder pypsa-earth/data with the name custom_powerplants.csv.

To do so from the terminal at the pypsa-earth directory you can type the following instruction:

...\pypsa-earth> cp pypsa-zm-data/data/powerplants_zm_all.csv data/custom_powerplants.csv

2. In the config file the workflow will execute (pypsa-earth/config.yaml) set the option custom_powerplants to replace. This makes the rule build_powerplants only use the powerplants from the file custom_powerplants.csv. See the documentation of the rule build_powerplants for more details.

Repository Structure

configs folder

The configs folder contains config.yaml's for all scenarios. These are the option files that allow pypsa-earth to create model outputs.

data folder

The data folder contains any extra data or data deletion requirements.

image folder

The image folder contains all images used in this repository.

scripts folder

The scripts folder contains the source code required to execute Snakemake rules that are specific for Zambia. The execution of these rules is controlled by the Snakefile zm.smk (see below).

validation folder

The validation folder contains all the resources used to validate the PyPSA-Earth in Zambia. It is divided in two subfolders:

1. notebooks contains modified versions of the validation notebook template given in the pypsa-earth/documentation for Zambia.

2. report contains a report, written in paper format, of the model validation for Zambia. It is inspired in section 4 of the PyPSA-Earth paper (Parzen et al. (2023)). For now, the most updated version of the report is stored in Overleaf, and can be edited through the following link. The version in this repository will be updated regularly from Overleaf.

Beyond the templates used, the validation of PyPSA-Earth in Zambia focuses on key features of the Zambian electricity system (e.g., hydro).

Snakefile zm.smk

The Snakefile zm.smk defines the Snakemake rules that are specific for Zambia.

Note that the code to execute those rules should be stored in the scripts folder, and called as a script in the Snakefile zm.smk.

Acknowledgements

This projects is funded by the Climate Compatible Growth through the following projects:

• Macroeconomic implications of the Green Growth Strategy in Zambia
• Energy System Chef – The energy system implications of transitions to clean cooking in Zambia