HIM
Hydrogen Infrastructure model for the analysis of spatially resolved hydrogen infrastructure pathways.
https://github.com/FZJ-IEK3-VSA/HIM
Category: Energy Storage
Sub Category: Hydrogen
Last synced: about 9 hours ago
JSON representation
Repository metadata
Hydrogen Infrastructure Model for the analysis of spatially resolved hydrogen infrastructure pathways
- Host: GitHub
- URL: https://github.com/FZJ-IEK3-VSA/HIM
- Owner: FZJ-IEK3-VSA
- License: mit
- Created: 2019-09-25T11:01:02.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2022-11-28T16:16:27.000Z (over 2 years ago)
- Last Synced: 2025-04-20T09:03:33.484Z (8 days ago)
- Language: Jupyter Notebook
- Size: 26.3 MB
- Stars: 18
- Watchers: 2
- Forks: 5
- Open Issues: 1
- Releases: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
README.md
HIM- Hydrogen Infrastructure Model for Python
HSC offers the functionality to calculate predefined hydrogen supply chain architectures with respect to spatial resolution for the analysis of explicit nationwide infrastructures.
Installation and application
First, download and install Anaconda. Then, clone a local copy of this repository to your computer with git
git clone https://github.com/FZJ-IEK3-VSA/HSCPathways.git
or download it directly. Move to the folder
cd HIM
and install the required Python environment via
conda env create -f environment.yml
To determine the optimal pipeline design, a mathematical optimization solver is required. Gurobi is used as default solver, but other optimization solvers can be used as well.
Examples
A number of examples shows the capabilities of HIM. Either for abstract costs analyses
or for exact infrastructure design
License
MIT License
Copyright (C) 2016-2019 Markus Reuss (FZJ IEK-3), Thomas Grube (FZJ IEK-3), Martin Robinius (FZJ IEK-3), Detlef Stolten (FZJ IEK-3)
You should have received a copy of the MIT License along with this program.
If not, see https://opensource.org/licenses/MIT
About Us
We are the Techno-Economic Energy Systems Analysis department at the Institute of Energy and Climate Research: Electrochemical Process Engineering (IEK-3) belonging to the Forschungszentrum Jülich. Our interdisciplinary department's research is focusing on energy-related process and systems analyses. Data searches and system simulations are used to determine energy and mass balances, as well as to evaluate performance, emissions and costs of energy systems. The results are used for performing comparative assessment studies between the various systems. Our current priorities include the development of energy strategies, in accordance with the German Federal Government’s greenhouse gas reduction targets, by designing new infrastructures for sustainable and secure energy supply chains and by conducting cost analysis studies for integrating new technologies into future energy market frameworks.
Acknowledgment
This work was supported by the Helmholtz Association under the Joint Initiative "Energy System 2050 – A Contribution of the Research Field Energy".
Owner metadata
- Name: Forschungszentrum Jülich - Jülich Systems Analysis
- Login: FZJ-IEK3-VSA
- Email:
- Kind: organization
- Description: Institute of Climate and Energy Systems (ICE)
- Website: https://www.fz-juelich.de/iek/iek-3/EN/Home/home_node.html
- Location: Forschungszentrum Jülich
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/28654423?v=4
- Repositories: 16
- Last ynced at: 2024-12-23T04:12:17.721Z
- Profile URL: https://github.com/FZJ-IEK3-VSA
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Last Year
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Last synced: 7 days ago
Total Commits: 12
Total Committers: 4
Avg Commits per committer: 3.0
Development Distribution Score (DDS): 0.5
Commits in past year: 0
Committers in past year: 0
Avg Commits per committer in past year: 0.0
Development Distribution Score (DDS) in past year: 0.0
| Name | Commits | |
|---|---|---|
| l-kotzur | l****r@f****e | 6 |
| Markus Reuß | m****s@i****e | 3 |
| Markus Reuß | m****s@f****e | 2 |
| noah80 | n****0 | 1 |
Committer domains:
Issue and Pull Request metadata
Last synced: 1 day ago
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Total pull requests: 2
Average time to close issues: N/A
Average time to close pull requests: 6 minutes
Total issue authors: 0
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Merged pull request: 1
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Past year issues: 0
Past year pull requests: 0
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Dependencies
- coolprop
- descartes
- geopandas
- jupyter
- matplotlib
- networkx 1.*
- olefile
- openpyxl
- pillow
- pip
- pyomo
- python 3.6.*
- scikit-learn
- xlrd
- xlsxwriter
- CoolProp *
- Pyomo *
- XlsxWriter *
- descartes *
- geopandas *
- jupyter *
- networkx <2.0
- openpyxl *
- xlrd *
Score: 4.330733340286331