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Robust design optimization of renewable Hydrogen and dErIved energy cArrier systems
by UCLouvain
Authors:
Diederik Coppitters, Panagiotis Tsirikoglou, Ward De Paepe, Konstantinos Kyprianidis, Anestis Kalfas, Francesco Contino
Contact:
Diederik Coppitters
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The Robust design optimization of renewable Hydrogen and dErIved energy cArrier systems (RHEIA) framework provides multi-objective optimization (deterministic and stochastic) and uncertainty quantification algorithms. These algorithms can be applied on hydrogen-based energy systems, which are included in RHEIA. In addition, RHEIA allows to connect your own models to the algorithms as well.
Based on Python. Using Python for data processing.
Website / Documentation
Download
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 Open Source
MIT license (MIT)
Directly downloadable
Input data shipped
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| Model Scope |
Model type and solution approach |
| Model class
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distributed energy systems, energy planning
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| Sectors
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All
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| Technologies
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Renewables
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| Decisions
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| Regions
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| Geographic Resolution
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| Time resolution
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| Network coverage
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| Model type
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Optimization
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| Variables
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| Computation time
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minutes"minutes" is not a number. minutes
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| Objective
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| Uncertainty modeling
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probabilistic
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| Suited for many scenarios / monte-carlo
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Yes
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References
Scientific references
Coppitters et al., (2022). RHEIA: Robust design optimization of renewable Hydrogen and dErIved energy cArrier systems. Journal of Open Source Software, 7(75), 4370
https://dx.doi.org/doi.org/10.21105/joss.04370
Reports produced using the model
https://scholar.google.com/scholar?cites=14879586069709356648&as_sdt=2005&sciodt=0,5&hl=en
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