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Provides an optimization model for the electricity market and its coupling with other energy sectors (e.g., hydrogen, heat, natural gas, etc.) with the main objective to determine the optimal investment and operation decisions for different types of assets.

electricity-market-modelling energy-transition julia-language modelling-tool optimization

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Tulipa Energy Model



# Developer documentation

Welcome to TulipaEnergyModel.jl developer documentation. Here is how you can
contribute to our Julia-based toolkit for modeling and optimization of electric
energy systems.

## Before You Begin

Before you can start contributing, please read our [](

Also make sure that you have installed the
required software, and that it is properly configured. You only need to do this

### Installing Software

To contribute to TulipaEnergyModel.jl, you need the following:

1. [Julia]( programming language.
2. [Git]( for version control.
3. [VSCode]( or any other editor. For VSCode, we recommend
to install a few extensions. You can do it by pressing Ctrl + Shift + X (or + + X on MacOS) and searching by the extension name.
- [Julia for Visual Studio Code](;
- [Git Graph](
4. [EditorConfig]( for consistent code formatting.
In VSCode, it is available as
[an extension](
5. [pre-commit]( to run the linters and formatters.

You can install `pre-commit` globally using

pip install --user pre-commit

If you prefer to create a local environment with it, do the following:

python -m venv env
. env/bin/activate
pip install --upgrade pip setuptools pre-commit

On Windows, you need to active the environment using the following command instead of the previous one:

. env/Scrips/activate

6. [JuliaFormatter.jl]( for code
formatting. To install it, open Julia REPL, for example, by typing in the
command line:


> **Note**:
> `julia` must be part of your environment variables to call it from the
> command line.

Then press ] to enter the package mode.
In the package mode, enter the following:

pkg> activate
pkg> add JuliaFormatter

In VSCode, you can activate "Format on Save" for `JuliaFormatter`. To do so,
open VSCode Settings (Ctrl + ,), then in "Search
Settings", type "Format on Save" and tick the first result:

![Screenshot of Format on Save option](docs/FormatOnSave.png)

7. [LocalCoverage]( for coverage
testing. You can install it the same way you installed `JuliaFormatter`,
that is, by opening Julia REPL in the package mode and typing:

pkg> activate
pkg> add LocalCoverage

### Forking the Repository

Any changes should be done in a [fork]( You can fork this repository directly on GitHub:

![Screenshot of Fork button on GitHub](docs/Fork.png)

After that, clone your fork and add this repository as upstream:

git clone # use the fork URL
git remote add upstream # use the original repository URL

### Configuring Git

Because operating systems use different line endings for text files, you need to configure Git to ensure code consistency across different platforms. You can do this with the following commands:

cd /path/to/TulipaEnergyModel.jl
git config --unset core.autocrlf # disable autocrlf in the EnergyModel repo
git config --global core.autocrlf false # explicitly disable autocrlf globally
git config --global --unset core.eol # disable explicit file-ending globally
git config core.eol lf # set Linux style file-endings in EnergyModel

### Activating and Testing the Package

Start Julia REPL either via the command line or in the editor.

In the terminal, do:

cd /path/to/TulipaEnergyModel.jl # change the working directory to the repo directory if needed
julia # start Julia REPL

In VSCode, first open your cloned fork as a new project. Then open the command palette with Ctrl + Shift + P (or + + P on MacOS) and use the command called `Julia: Start REPL`.

In Julia REPL, enter the package mode by pressing ].

In the package mode, first activate and instantiate the project, then run the
tests to ensure that everything is working as expected:

pkg> activate . # activate the project
pkg> instantiate # instantiate to install the required packages
pkg> test # run the tests

### Configuring Linting and Formatting

With `pre-commit` installed, activate it as a pre-commit hook:

pre-commit install

To run the linting and formatting manually, enter the command below:

pre-commit run -a

Do it once now to make sure that everything works as expected.

Now, you can only commit if all the pre-commit tests pass.

> **Note**:
> On subsequent occasions when you need to run pre-commit in a new shell, you
> will need to activate the Python virtual environment. If so, do the following:
> ```bash
> . env/bin/activate # for Windows the command is: . env/Scripts/activate
> pre-commit run -a
> ```

## Contributing Workflow

When the software is installed and configured, and you have forked the
TulipaEnergyModel.jl repository, you can start contributing to it.

We use the following workflow for all contributions:

1. Make sure that your fork is up to date
2. Create a new branch
3. Implement the changes
4. Run the tests
5. Run the linter
6. Commit the changes
7. Repeat steps 3-6 until all necessary changes are done
8. Make sure that your fork is still up to date
9. Create a pull request

Below you can find detailed instructions for each step.

### 1. Make Sure That Your Fork Is Up to Date

Fetch from org remote, fast-forward your local main:

git switch main
git fetch --all --prune
git merge --ff-only origin/main

> **Warning**:
> If you have a conflict on your main, it will appear now. You can delete
> your old `main` branch using
> ```bash
> git reset --hard origin/main
> ```

### 2. Create a New Branch

Create a branch to address the issue:

git switch -c

- If there is an associated issue, add the issue number to the branch name,
for example, `123-short-description` for issue \#123.
- If there is no associated issue **and the changes are small**, add a prefix such as "typo", "hotfix", "small-refactor", according to the type of update.
- If the changes are not small and there is no associated issue, then create the issue first, so we can properly discuss the changes.

> **Note**:
> Always branch from `main`, i.e., the main branch of your own fork.

### 3. Implement the Changes

Implement your changes to address the issue associated with the branch.

### 4. Run the Tests

In Julia:

TulipaEnergyModel> test

To run the tests with code coverage, you can use the `LocalCoverage` package:

julia> using LocalCoverage
# ]
pkg> activate .
julia> cov = generate_coverage()

This will run the tests, track line coverage and print a report table as output.
Note that we want to maintain 100% test coverage. If any file does not show 100%
coverage, please add tests to cover the missing lines.

If you are having trouble reaching 100% test coverage, you can set your pull
request to 'draft' status and ask for help.

### 5. Run the Linter

In the bash/git bash terminal, run pre-commit:

. env/bin/activate # if necessary (for Windows the command is: . env/Scripts/activate)
pre-commit run -a

If any of the checks failed, find in the pre-commit log what the issues are and
fix them. Then, add them again (`git add`), rerun the tests & linter, and commit.

### 6. Commit the Changes

When the test are passing, commit the changes and push them to the remote
repository. Use:

git commit -am "A short but descriptive commit message" # Equivalent to: git commit -a -m "commit msg"
git push -u myfork

When writing the commit message:

- use imperative, present tense (Add feature, Fix bug);
- have informative titles;
- if necessary, add a body with details.

> **Note**:
> Try to create "atomic git commits". Read
> [*The Utopic Git History*](
> to learn more.

### 7. Make Sure That Your Fork Is Still Up to Date

If necessary, fetch any `main` updates from upstream and rebase your branch into
`origin/main`. For example, do this if it took some time to resolve the issue
you have been working on. If you don't resolve conflicts locally, you will
get conflicts in your pull request.

Do the following steps:

git switch main # switch to the main branch
git fetch --all --prune # fetch the updates
git merge --ff-only origin/main # merge as a fast-forward
git switch # switch back to the issue branch
git rebase main # rebase it

If it says that you have conflicts, resolve them by opening the file(s) and
editing them until the code looks correct to you. You can check the changes

git diff # Check that changes are correct.
git add
git diff --staged # Another way to check changes, i.e., what you will see in the pull request.

Once the conflicts are resolved, commit and push.

git status # Another way to show that all conflicts are fixed.
git rebase --continue
git push --force myfork

### 8. Create a Pull Request

When there are no more conflicts and all the test are passing, create a pull
request to merge your remote branch into the org main. You can do this on
GitHub by opening the branch in your fork and clicking "Compare & pull request".

![Screenshot of Compare & pull request button on GitHub](docs/CompareAndPR.png)

Fill in the pull request details:

1. Describe the changes.
2. List the issue(s) that this pull request closes.
3. Fill in the collaboration confirmation.
4. (Optional) Choose a reviewer.
5. When all of the information is filled in, click "Create pull request".

![Screenshot of the pull request information](docs/PRInfo.png)

You pull request will apper in the list of pull requests in the
TulipaEnergyModel.jl repository, where you can track the review process.

Sometimes reviewers request changes. After pushing any changes,
the pull request will be automatically updated. Do not forget to re-request a

Once your reviewer approves the pull request, you need to merge it with the
main branch using "Squash and Merge".
You can also delete the branch that originated the pull request by clicking the button that appears after the merge.
For branches that were pushed to the main repo, it is recommended that you do so.

## Performance Considerations

If you updated something that might impact the performance of the package, you
can run the `Benchmark.yml` workflow from your pull request. To do that, add
the tag `benchmark` in the pull request. This will trigger the workflow and
post the results as a comment in you pull request.

> **Warning**:
> This requires that your branch was pushed to the main repo.
> If you have created a pull request from a fork, the Benchmark.yml workflow does not work.
> Instead, close your pull request, push your branch to the main repo, and open a new pull request.

If you want to manually run the benchmarks, you can do the following:

- Navigate to the benchmark folder
- Run `julia --project=.`
- Enter `pkg` mode by pressing `]`
- Run `dev ..` to add the development version of TulipaEnergyModel
- Now run

results = run(SUITE, verbose=true)

### Profiling

To profile the code in a more manual way, here are some tips:

- Wrap your code into functions.
- Call the function once to precompile it. This must be done after every change to the function.
- Prefix the function call with `@time`. This is the most basic timing, part of Julia.
- Prefix the function call with `@btime`. This is part of the BenchmarkTools package, which you might need to install. `@btime` will evaluate the function a few times to give a better estimate.
- Prefix the function call with `@benchmark`. Also part of BenchmarkTools. This will produce a nice histogram of the times and give more information. `@btime` and `@benchmark` do the same thing in the background.
- Call `@profview`. This needs to be done in VSCode, or using the ProfileView package. This will create a flame graph, where each function call is a block. The size of the block is proportional to the aggregate time it takes to run. The blocks below a block are functions called inside the function above.

See the file for an example of profiling code.

## Building the Documentation Locally

To build and see the documentation locally, first, navigate to the `docs` folder
in your file explorer and open a terminal. Then, run `julia --project`. With the
`julia` open, enter the `pkg` mode by pressing `]`.
Check that the environment name is `docs`. The first time here, you have to run:

docs> dev ..
docs> update

Then, to build the documentation, run

julia> include("make.jl")

If you intend to rerun the build step, ensure you have the package `Revise`
installed in your global environment, and run `using Revise` before including
`make.jl`. Alternatively, close `julia` and reopen it.

After building, the documentation will be available in the folder `docs/build/`.
Open the `index.html` file on the browser to see it.

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit to generate yours today!

cff-version: 1.2.0
title: Tulipa Energy Model
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
  - given-names: Diego A.
    family-names: Tejada-Arango
    email: [email protected]
    affiliation: TNO
    orcid: ''
  - given-names: Germán
    family-names: Morales-España
    email: [email protected]
    affiliation: TNO
    orcid: ''
  - given-names: Lauren
    family-names: Clisby
    email: [email protected]
    affiliation: TNO
    orcid: ''
  - given-names: Ni
    family-names: Wang
    email: [email protected]
    affiliation: TNO
    orcid: ''
  - given-names: Abel
    family-names: Soares Siqueira
    email: [email protected]
    affiliation: Netherlands eScience Center
    orcid: ''
  - given-names: Suvayu
    family-names: Ali
    email: [email protected]
    affiliation: Netherlands eScience Center
  - given-names: Laurent
    family-names: Soucasse
    email: [email protected]
    affiliation: Netherlands eScience Center
    orcid: ''
  - given-names: Grigory
    family-names: Neustroev
    email: [email protected]
    affiliation: Delft University of Technology
    orcid: ''
  - type: other
    value: arXiv.2309.07711
    description: The ArXiv preprint of the mathematical formulation
  - type: doi
    value: 10.5281/zenodo.8363262
    description: Concept DOI for Zenodo deposition
repository-code: ''
abstract: >-
  The Tulipa Energy Model is a Julia package for energy
  planning that considers the electricity market and sector
  - Open source tool
  - Energy system modelling
  - Energy system analysis
  - Integrated energy systems
  - Investment planning
  - Sector coupling
license: Apache-2.0

Owner metadata

GitHub Events

Last Year

Committers metadata

Last synced: 24 days ago

Total Commits: 195
Total Committers: 11
Avg Commits per committer: 17.727
Development Distribution Score (DDS): 0.585

Commits in past year: 195
Committers in past year: 11
Avg Commits per committer in past year: 17.727
Development Distribution Score (DDS) in past year: 0.585

Name Email Commits
Abel Soares Siqueira a****a@g****m 81
Diego Alejandro Tejada Arango 1****a 31
Lauren Clisby l****y@g****m 28
Ni Wang 1****n 16
github-actions[bot] 4****] 13
Lauren Clisby l****y@t****l 9
Greg Neustroev G****v@t****l 5
datejada d****o@t****l 4
Sander van Rijn s****n@e****l 4
Suvayu Ali s****u 3
Germán Morales 4****a 1

Committer domains:

Issue and Pull Request metadata

Last synced: 1 day ago

Total issues: 131
Total pull requests: 98
Average time to close issues: 27 days
Average time to close pull requests: 3 days
Total issue authors: 9
Total pull request authors: 9
Average comments per issue: 2.04
Average comments per pull request: 1.61
Merged pull request: 90
Bot issues: 0
Bot pull requests: 11

Past year issues: 131
Past year pull requests: 98
Past year average time to close issues: 27 days
Past year average time to close pull requests: 3 days
Past year issue authors: 9
Past year pull request authors: 9
Past year average comments per issue: 2.04
Past year average comments per pull request: 1.61
Past year merged pull request: 90
Past year bot issues: 0
Past year bot pull requests: 11

More stats:

Top Issue Authors

  • abelsiqueira (50)
  • clizbe (31)
  • datejada (30)
  • gnawin (11)
  • greg-neustroev (2)
  • gzclarence (2)
  • lsoucasse (2)
  • suvayu (2)
  • JuliaTagBot (1)

Top Pull Request Authors

  • abelsiqueira (33)
  • gnawin (23)
  • datejada (15)
  • github-actions[bot] (11)
  • clizbe (11)
  • greg-neustroev (2)
  • suvayu (1)
  • g-moralesespana (1)
  • sjvrijn (1)

Top Issue Labels

  • Type: improvement (72)
  • Zone: documentation (35)
  • Type: addition (34)
  • Zone: optimisation model (23)
  • Zone: setup/admin (18)
  • Zone: data & import (18)
  • good first issue (16)
  • Type: bug (13)
  • Zone: code architecture (11)
  • Type: research (11)
  • Zone: testing (11)
  • Type: epic (7)
  • Zone: export & visualisation (4)
  • question (1)

Top Pull Request Labels

  • benchmark (3)
  • Zone: data & import (1)
  • question (1)

Package metadata TulipaEnergyModel

Tulipa Energy Model

  • Homepage:
  • Documentation:
  • Licenses: Apache-2.0
  • Latest release: 0.6.1 (published 13 days ago)
  • Last Synced: 2024-02-24T17:02:53.904Z (1 day ago)
  • Versions: 9
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Rankings:
    • Dependent repos count: 10.054%
    • Forks count: 15.872%
    • Average: 30.449%
    • Dependent packages count: 36.985%
    • Stargazers count: 58.886%


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Score: -Infinity