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3815. Important features when modeling hydrogen as part of integrated energy systems
Invited abstract in session WD-9: Hydrogen and Electricity Modeling and Regulation II, stream Energy Markets.
Wednesday, 14:30-16:00Room: 10 (building: 116)
Authors (first author is the speaker)
| 1. | Marie Münster
|
| DTU Management Engineering, Technical University of Denmark | |
| 2. | Rasmus Bramstoft
|
| Technical University of Denmark | |
| 3. | Dimitrios Eleftheriou
|
| EA Energy Analysis | |
| 4. | Kenneth Karlsson
|
| Energy Modelling Lab | |
| 5. | Mathias Kjærgård Hald
|
| Energinet | |
| 6. | Magdalena Komoszynska
|
| PlanEnergi | |
| 7. | HENRIK LUND
|
| University of Aalborg |
Abstract
Recently, a number of energy system analyses have emerged, which highlight the potential roles of hydrogen in future energy systems. The results however differ substantially in terms of the outcomes. This is partly due to hydrogen being an expensive energy carrier, which requires a number of conditions to become feasible in large scale some of which include e.g. high carbon taxes, the availability of low-cost renewable electricity and low availability of biomass. To investigate in more detail where the differences stem from, a number of studies of the role of hydrogen in Denmark has been compared and a modeling and reporting framework is proposed. The goal of the framework is to ensure transparency and understanding of results highlighting important input parameters and conditions. The 7 main features identified can be summarized as:
1. Model type
2. Modeling of time (aggregation, pathways and foresight etc.)
3. Modeling of space (aggregation, scope, grids etc.)
4. Scenario boundary conditions (e.g. CO2 tax/cap, import/export possibility etc.)
5. Resource assumptions (potentials, prices, variance etc.)
6. Technology assumptions (conversion, storages etc.)
7. Demands (energy carriers, sectors included, amounts & timing & flexibility etc.)
In order to be able to compare and understand differences between different studies it is recommended to document and reflect upon these model characteristics as well as the main assumptions and modeling choices.
Keywords
- Energy Policy and Planning
- Programming, Linear
- OR in Energy
Status: accepted
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