Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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✓Committers with academic emails
6 of 11 committers (54.5%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (15.0%) to scientific vocabulary
Keywords
Repository
Balmorel Model
Basic Info
Statistics
- Stars: 40
- Watchers: 4
- Forks: 41
- Open Issues: 4
- Releases: 4
Topics
Metadata Files
README.md
Balmorel
Check out the documentation for tutorials on getting started with the Balmorel energy system model.
Data is included in the Balmorel_data repository, which we recommend cloning to base/ for version control of both base data and framework. Note: The cloned folder should be renamed from "Balmorel_data" to "data" to function properly.
A scenario that's possible to run with an academic trial license of GAMS can be found in the balmorel-demo branch.
What is Balmorel?
Balmorel is a partial equilibrium model for analysing the electricity and combined heat and power sectors in an international perspective. It is highly versatile and may be applied for long range planning as well as shorter time operational analysis. Balmorel is implemented as a mainly linear programming optimisation problem.
The model is developed in a model language, and the source code is readily available under open source conditions, thus providing complete documentation of the functionalities. Moreover, the user may modify the model according to specific requirements, making the model suited for any purpose within the focus parts of the energy system.
What can Balmorel be used for?
The Balmorel model has been applied in projects or other activities in a number of countries, e.g., in Denmark, Norway, Sweden, Estonia, Latvia, Lithuania, Poland, Germany, Austria, Ghana, Mauritius, Canada and China. It has been used for analyses of, i.a., security of electricity supply, the role of flexible electricity demand, hydrogen technologies, wind power development, the role of natural gas, development of international electricity markets, market power, heat transmission and pricing, expansion of electricity transmission, international markets for green certificates and emission trading, electric vehicles in the energy system, environmental policy evaluation.
See "Activities" and "Publications" sections in the menu for description of ongoing and past projects using the Balmorel model.
Who can use Balmorel?
Balmorel is a modelling tool that can be used by energy system experts, energy companies, authorities, transmission system operators, researchers and others for the analyses of future developments of a regional energy sector.
How is Balmorel supported and further developed?
The model is developed and distributed under open source ideals. The source code has been provided on its homepage since 2001 and was assigned the ISC license in 2017. Ample documentation is available in the folder within this repository. We also refer to information on openmod. Presently the model development is mainly project driven, with a users' network around it, supporting the open source development idea.
Procedure for Merging Changes to Master
The Balmorel team of DTU Management, Energy Economics and Modelling has decided on the following procedure for merging new changes to the master: 1. A decision to merge should be agreed upon in a Balmorel meeting with the admins 2. Create a new branch from master, which will be used as a temporary branch to do all the changes 3. Make the desired changes in a new scenario:
a. Add a new scenario called 'changes', which the following files and folder structure (copy Balmorel.gms and cplex.op4 from base/model if nothing is to be changed in these files):
Balmorel
├── base
├── changes
│ ├── data
│ └── model
│ ├── cplex.op4
│ └── Balmorel.gms
├── simex
├── README.md
├── .gitignore
└── .gitattributes
b. Keep the base scenario identical to the current master and apply all changes to the 'changes' scenario
- Run the test script, make sure that the model stays feasible and that the results make sense
- Consider critically if the tests performed in 4. is enough to verify and validate the changes made
- Make a pull request with the changes and report them in general terms, including the KPI outputs from the tests in 4. in ... (todo: check where it makes sense to put these descriptions, as simple as possible)
Owner
- Name: Balmorel Community
- Login: balmorelcommunity
- Kind: organization
- Repositories: 2
- Profile: https://github.com/balmorelcommunity
GitHub Events
Total
- Watch event: 7
- Delete event: 3
- Issue comment event: 4
- Push event: 33
- Pull request review event: 21
- Pull request event: 31
- Fork event: 13
- Create event: 4
Last Year
- Watch event: 7
- Delete event: 3
- Issue comment event: 4
- Push event: 33
- Pull request review event: 21
- Pull request event: 31
- Fork event: 13
- Create event: 4
Committers
Last synced: 6 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Juan Gea Bermudez | j****b@h****m | 339 |
| Martijn Backer | m****k@d****k | 48 |
| Mathias157 | m****s@g****m | 29 |
| Tim Aidan Graulich | 6****h | 11 |
| Olexandr@MS | o****l@d****k | 7 |
| TheisUM | t****d@d****k | 4 |
| tilseb | 3****b | 2 |
| tilseb | t****b@d****k | 2 |
| njbca | 6****a | 1 |
| fraukewiese | f****i@d****k | 1 |
| RasmusBramstoft | r****e@d****k | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 6
- Total pull requests: 53
- Average time to close issues: 11 months
- Average time to close pull requests: 5 months
- Total issue authors: 4
- Total pull request authors: 11
- Average comments per issue: 0.33
- Average comments per pull request: 0.34
- Merged pull requests: 28
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 4
- Pull requests: 31
- Average time to close issues: 1 day
- Average time to close pull requests: 18 days
- Issue authors: 2
- Pull request authors: 7
- Average comments per issue: 0.0
- Average comments per pull request: 0.19
- Merged pull requests: 20
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- Mathias157 (4)
- gorkemgungormetu (1)
- SteffenMeinecke (1)
- tgraulich (1)
Pull Request Authors
- jgeab (15)
- Mathias157 (15)
- tgraulich (12)
- TheisUM (10)
- lilanger (2)
- njbca (2)
- GustavKirkerud (2)
- TheoBalanza (1)
- juanjerezm (1)
- thbal (1)
- IdaGJ (1)