This file provides the information required to set up the integer programming-based __resite__ tool. At this stage, the IP version is not integrated in the broader __resite__ package.
This repository hosts the main development work around `resite_ip`, a tool relying on integer programming to site
renewable generation assets based on various deplyoment criteria.
# Setup
## Setup
This module runs in any 3.x version of Python. The Python packages required to run this module are listed
in the `requirements.yml` file included in the repository. Their installation can be easily achieved via the the following
command that builds a separate environment for this module from the `yml` file:
conda env create -f environment.yml
The code runs in `Python 3.6` or older. In addition, running the code requires installation of `Julia 1.5` or older.
Furthermore, the some of the siting algorithm available in this repository will require a branch-and-bound solver. Currently,
only `gurobi` (with a valid license) is supported.
The tool requires to installation of an MILP solver. At the time of writing, `gurobi` is the only solver this
model supports (see installation details [here](https://www.gurobi.com/documentation/8.1/remoteservices/installation.html)).
# Minimal working example
## Repository structure
This structure of this package is as follows:
*`resite_ip` as a container for:
...
...
@@ -23,17 +19,15 @@ This structure of this package is as follows:
* the `config` files
* auxiliary files required to set up the package
The `data` folder (whose path must be specified in the first line of `config_model.yml`) is provided in a different zenodo-like repository. In order to run the model, the following steps must be taken:
* Ensure input data is available according to the structure provided in the `data` folder
The `data` folder (whose path must be specified in the first line of `config_model.yml`) is needed to instantiate the
model. Currently, the data available covers solely the European continent and is available [here](https://dox.uliege.be/index.php/s/L9jH5aCQdZ7ie4W).
In order to run the model and assuming that this repository has been obtained via `git clone` the following steps must be taken:
* Install all package dependencies listed in the `requirements.yml` file
* Configure run via the `config` files
* Run `python main.py` from the `src` folder
Results of these runs are stored in an `output` directory at the same level as the `data` folder.
# Citing
Please cite the following paper if you use this software in your research.
To be added.
Results of these runs are stored in an `output` directory in the `data` folder.
# License
This software is released as free software under the [GPLv3](http://www.gnu.org/licenses/gpl-3.0.en.html).
