| Open Source | |
| Planned to open up in the future | |
| Costs | - |
| Modelling software | GAMS, Java |
| Internal data processing software | |
| External optimizer | |
| Additional software | Large Scale Professional Solvers such as CPLEX or Mosek |
| GUI |
| Modeled energy sectors (final energy) |
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| Modeled demand sectors |
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| Modeled technologies: components for power generation or conversion |
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| Modeled technologies: components for transfer, infrastructure or grid |
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| Properties electrical grid |
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| Modeled technologies: components for storage |
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| User behaviour and demand side management | |||||||
| Changes in efficiency | The model can account for prospective efficiency changes across times and plant ages/refurbishment | ||||||
| Market models | fundamental model | ||||||
| Geographical coverage | |||||||
| Geographic (spatial) resolution |
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| Time resolution | hour, 15 min | ||||||
| Comment on geographic (spatial) resolution | Different elements are modelled at different regional granularities | ||||||
| Observation period | >1 year | ||||||
| Additional dimensions (sector) |
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| Model class (optimisation) | LP, Quadratic constraints allowed in core solves |
| Model class (simulation) | Agent-based, Game Theoretic Model |
| Other | |
| Short description of mathematical model class | A complex framework is built around a linear/quadratic core model; the iterative architecture adjusts the core model gradually such as to take into account strategic and agent-specific behavior of all involved market actors to obtain a solution in line with idiosyncratic properties and historic data. |
| Mathematical objective | Complex adjusted cost accounting in iterative framework |
| Approach to uncertainty | Stochastic elements accounted for to bring the deterministic core solves in line with imperfect foresight and an unknown future |
| Suited for many scenarios / monte-carlo | |
| typical computation time | less than a day |
| Typical computation hardware | Servers |
| Technical data anchored in the model | - |
| Interfaces | GUI for launching the model Database output Excel Pivot Inspection tools |
| Model file format | .gms and/or .exe |
| Input data file format | .csv |
| Output data file format | .csv |
| Integration with other models | Global energy commodity model, Global/regional gas model |
| Integration of other models |
| Citation reference | - |
| Citation DOI | - |
| Reference Studies/Models | https://www.auroraer.com/insight/auroras-commentary-potential-game-changers-roll-flexible-capacity-gb-power-market/ |
| Example research questions | How will the renewables and flexible generation revolution affect particular types of assets? How will particular policies affect the flexible generation revolution? |
| Model usage | Aurora's Subscriber Groups |
| Model validation |
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| Example research questions | How will the renewables and flexible generation revolution affect particular types of assets? How will particular policies affect the flexible generation revolution? |
| further properties | |
| Model specific properties | - |