3d_milp
Energy Arbitrage Optimization With Battery Storage.
https://github.com/ElektrikAkar/3d_milp
Category: Energy Storage
Sub Category: Battery
Last synced: about 9 hours ago
JSON representation
Repository metadata
Public repository for 3D-MILP paper.
- Host: GitHub
- URL: https://github.com/ElektrikAkar/3d_milp
- Owner: ElektrikAkar
- License: other
- Created: 2020-11-06T13:20:26.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2022-07-22T01:16:21.000Z (almost 3 years ago)
- Last Synced: 2025-04-17T20:37:08.365Z (10 days ago)
- Language: MATLAB
- Size: 2.08 MB
- Stars: 8
- Watchers: 1
- Forks: 1
- Open Issues: 0
- Releases: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
README.md
Energy Arbitrage Optimization With Battery Storage: 3D-MILP for Electro-Thermal Performance and Semi-Empirical Aging Models
The tool was created by Volkan Kumtepeli at the Energy Research Institute at Nanyang Technological University
in collaboration with Institute for Electrical Energy Storage Technology at the Technical University of Munich.
How to cite:
V. Kumtepeli, HC. Hesse, M. Schimpe, A. Tripathi, Y. Wang, and A. Jossen,
Energy Arbitrage Optimization With Battery Storage: 3D-MILP for Electro-Thermal Performance and Semi-Empirical Aging Models.
IEEE Access, vol. 8, pp. 204325-204341, 2020. [Online]. Available:
https://doi.org/10.1109/ACCESS.2020.3035504
@article{kumtepeli2020energy,
title={Energy Arbitrage Optimization With Battery Storage: 3D-MILP for Electro-Thermal Performance and Semi-Empirical Aging Models},
author={Kumtepeli, Volkan and Hesse, Holger C and Schimpe, Michael and Tripathi, Anshuman and Youyi, Wang and Jossen, Andreas},
journal={IEEE Access},
volume={8},
pages={204325--204341},
year={2020},
publisher={IEEE}
doi={10.1109/ACCESS.2020.3035504},
ISSN={2169-3536},
}
Dependencies / Requirements:
- Gurobi 9.03
- YALMIP R20200116
- MATLAB >=2017a for string operations and >=2019a for readmatrix function.
- Robust Statistical Toolbox (not used but may be necessary for some functions in RainCloudPlots library)
- Partially provided external libraries:
How to use:
Run Optimization_single.m or Optimization_batch.m file. Default settings are given in simulationSettings which can be called with additional settings.
Owner metadata
- Name: Volkan Kumtepeli
- Login: ElektrikAkar
- Email:
- Kind: user
- Description: Yet another person.
- Website:
- Location: United Kingdom
- Twitter: VolkanKumtepeli
- Company:
- Icon url: https://avatars.githubusercontent.com/u/8674942?u=2d0db3d7307a64778d9dc4a8c4ea8a2420ad5bb9&v=4
- Repositories: 25
- Last ynced at: 2024-06-11T15:52:02.256Z
- Profile URL: https://github.com/ElektrikAkar
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- Watch event: 2
Last Year
- Watch event: 2
Committers metadata
Last synced: 7 days ago
Total Commits: 9
Total Committers: 1
Avg Commits per committer: 9.0
Development Distribution Score (DDS): 0.0
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 | |
|---|---|---|
| Volkan Kumtepeli | v****i@g****m | 9 |
Committer domains:
Issue and Pull Request metadata
Last synced: 1 day ago
Total issues: 0
Total pull requests: 2
Average time to close issues: N/A
Average time to close pull requests: less than a minute
Total issue authors: 0
Total pull request authors: 1
Average comments per issue: 0
Average comments per pull request: 0.0
Merged pull request: 2
Bot issues: 0
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Past year merged pull request: 0
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Dependencies
- matplotlib *
- numpy *
- ptitprince ==0.1.3
- scipy *
- seaborn >=0.9
Score: 2.0794415416798357