This repository contains the source code for a two-stage stochastic program of an electricity network.
Our research question is inspired by the recent invasion of Ukraine by Russia, in which the electricity grid is repeatedly attacked, which leads to the suffering of innocent civilians. In order to prevent the damage we want to investigate the possibility of reinforcing the grid in a way that minimizes the impact on civilians. In addition we compare how an increase of renewable energy sources would affect such attacks.
The source code of the model is contained in the src folder.
The data folder contains the data for the model, which could take on different
forms, depending on the parser used. Currently, we only implement one parser,
which accepts an dataset generated from the RWTH Aachen University.
In order to use this data, place the files Scenario_20XX.xlsx in the data
folder.
The results folder is intended to contain the results of the model/simulation,
which will stored as .csv files.
| file | description |
|---|---|
| rwth_parser.jl | loads the data from the RWTH Aachen University dataset |
| scenarios/ | contains mulitple files intended for scenario generation and reduction |
| types.jl | contains the data types used in the model |
| process.jl | contains the model and the simulation (4 different electricity architectures in 12 different months) |
| main.jl | cli wrapper for the model and the simulation |
| notebooks/ | contains jupyter notebooks |
| notebooks/01_single_model.ipynb | explains how to build and solve a single model |
| notebooks/01a_approximation_renewables.ipynb | explains conversion between wind speed/solar irradiance and maximum power generation |
| notebooks/02_simulation.ipynb | explains how to run a simulation consisting of multiple models |
| notebooks/02a_architectures.ipynb | explains the data used |
| notebooks/03_results.ipynb | visualizes results |
- Place the data in the
datafolder. (folder should containScenario_XXX.xlsx) - Install
Gurobi or
change the solver in
src/model.jl. - Run
julia ./src/main.jl ./results/sample/config.jsonto run a simulation. Look into theconfig.jsonfile to see how to configure the simulation. For a description of the variables read./notebooks/03_simulation.ipynb.
The visualization of results is done with Python and requires additional setup:
- Install conda
- Run
conda env create -f environment.yml - Run
conda activate AMO