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https://github.com/PyPSA/247-cfe
Explore the impacts of 24/7 Carbon-Free Energy PPAs
https://github.com/PyPSA/247-cfe
energy energy-model power-system pypsa snakemake
Last synced: 3 months ago
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Explore the impacts of 24/7 Carbon-Free Energy PPAs
- Host: GitHub
- URL: https://github.com/PyPSA/247-cfe
- Owner: PyPSA
- License: mit
- Created: 2022-01-10T13:56:14.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-05-08T16:04:59.000Z (6 months ago)
- Last Synced: 2024-06-11T17:30:27.838Z (5 months ago)
- Topics: energy, energy-model, power-system, pypsa, snakemake
- Language: Python
- Homepage:
- Size: 31.3 MB
- Stars: 26
- Watchers: 2
- Forks: 6
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSES/CC-BY-4.0.txt
Awesome Lists containing this project
- open-sustainable-technology - 24/7 CFE - This project explores the means, costs and impacts of 24/7 Carbon-Free Energy procurement in Europe. (Energy Systems / Regional Energy System Models)
README
[](https://irieo.github.io/247cfe.github.io/)
[](LICENSES/MIT.txt)
[](LICENSES/CC-BY-4.0.txt)
[](https://zenodo.org/record/7180097)
[](https://zenodo.org/record/8185849)
# PyPSA code for exploring the 24/7 Carbon-Free Energy procurement in Europe
## Project webpage
Visit our [webpage](https://irieo.github.io/247cfe.github.io/) for detailed insights about our research.
## Getting started
This project explores the means, costs and impacts of 24/7 Carbon-Free Energy procurement in Europe.
Three invididual studies are planned as deliverables of this research project. The three studies will be linked to GitHub releases and individual Zenodo repositories. All studies are focused on the topic of 24/7 Carbon-Free Energy procurement in Europe; however, studies will differ in terms of their focuses, model formulations, scenarios, etc.
We aim to make the scientific workflow and results for each study to be fully reproducible. To access code for published studies, clone a corresponding GitHub release, see sections [Study 1](#study-1) and [Study 2](#study-2). More information is in [Requirements](#requirements) and [Software](#software).
This research is supported by a grant from Google LLC.
### Study 1:
In this study, we investigate both the means and costs of pursuing different clean electricity procurement strategies for companies in a selection of European countries. We also explore how the 24/7 clean energy procurement affects the rest of the European electricity system.
- [Complete study](https://zenodo.org/record/7180097)
- [Twitter thread](https://twitter.com/nworbmot/status/1579810935702982656)
- [Blog post](https://blog.google/around-the-globe/google-europe/how-carbon-free-energy-around-the-clock-can-work/)
- [GitHub release](https://github.com/PyPSA/247-cfe/tree/v0.1)
- [Code is also at Zenodo](https://zenodo.org/record/7181236)
NB The Study 1 is now also available with [Linopy](https://github.com/pypsa/linopy) integration under the tag [v0.2](https://github.com/PyPSA/247-cfe/releases/tag/v0.2). Linopy is an open-source python package for linear or mixed-integer optimization.
### Study 2:
In this study, we explore how and why space-time load-shifting flexibility can be used to meet high 24/7 carbon-free energy targets, as well as what potential benefits it may offer to 24/7 participants and to the rest of the energy system. To answer these questions, we expand the mathematical model of 24/7 CFE procurement developed in the previous work by incorporating spatial and temporal demand flexibility provided by electricity consumers that follow 24/7 carbon-free energy goals.
- [Complete study](https://zenodo.org/record/8185850)
- [GitHub release](https://github.com/PyPSA/247-cfe/tree/v0.3)
### Study 3:
On the role of 24/7 CFE in accelerating advanced clean energy technologies
*(work in progress).*
### Research papers related to this project:
- [On the means, costs, and system-level impacts of 24/7 carbon-free energy procurement](https://zenodo.org/records/10407830)
- [Spatio-temporal load shifting for truly clean computing](https://zenodo.org/records/10869649)
## How to reproduce results of a study?
First, clone the repository:
```
git clone https://github.com/PyPSA/247-cfe --branch --single-branch
```
- `--single-branch` option allows for cloning only git history leading to tip of the tag. This saves a lot of unnecessary code from being cloned.
- `tag_name` is v0.2 for [Study 1](#study-1) or v0.3 for [Study 2](#study-2)
Second, install the necessary dependencies using `environment.yml` file. The following commands will do the job:
```
conda env create -f envs/environment.yml
conda activate 247-cfe
```
Third, to run all the scenarios from the study, run the [snakemake](https://snakemake.readthedocs.io/en/stable/) worflow:
```
snakemake -call
```
- Note that this call requires a high-performance computing environment.
- It is possible to run a smaller version of the model by adjusting the settings in `config.yaml`. For example, changing the config setting `area` from "EU" to "regions" reduces the regional coverage of the model, making the size of the problem feasible to solve on a private laptop with 8GB RAM.
Finally, when the workflow is complete, the results will be stored in `results` directory. The directory will contain solved networks, plots, summary csvs and logs.
4. At this point, you can also compile the LaTeX project to reproduce the study .pdf file.
## Requirements
### Data
Code is based on the brownfield networks exported from [PyPSA-Eur](https://github.com/PyPSA/pypsa-eur-sec) with `myopic` setting to get brownfield networks for 2025/2030. For convenience, sample networks are provided in the `input/` folder.
Technology data assumptions are automatically retrieved from [technology-data](https://github.com/PyPSA/technology-data) repository for `` and ``, as specified in `config.yaml`.
### Software
The code is known to work with python 3.11, PyPSA 0.25, pandas 1.5.3, numpy 1.24.2, linopy 0.2.7, and gurobi 10.0.1.
The complete list of package requirements is in the [envs/environment.yaml](envs/environment.yaml) file. The environment can be installed and activated using:
```
.../247-cfe % conda env create -f envs/environment.yaml
.../247-cfe % conda activate 247-env
```
If you have troubles with a slow [conda](https://docs.conda.io/en/latest/) installation, we recommend to install [mamba](https://mamba.readthedocs.io/en/latest/):
```
conda install -c conda-forge mamba
```
and then install the environment with a fast drop-in replacement via
```
mamba env create -f envs/environment.yaml
```
## License
This code is licensed under the open source [MIT License](LICENSES/MIT.txt).
Different open licenses apply to LaTeX files and input data, see [Specifications](.reuse/dep5).