GRIMSEL-FLEX
From wiki.openmod-initiative.org
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| | |deterministic=Perfect foresight, Sensitivity analisys, Scenarios | | |deterministic=Perfect foresight, Sensitivity analisys, Scenarios |
| | |is_suited_for_many_scenarios=No | | |is_suited_for_many_scenarios=No |
| | + | |number_of_variables=5000000 |
| | |montecarlo=No | | |montecarlo=No |
| | + | |computation_time_minutes=30 |
| | |Model input file format=Yes | | |Model input file format=Yes |
| | |Model file format=Yes | | |Model file format=Yes |
| | |Model output file format=Yes | | |Model output file format=Yes |
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Latest revision as of 18:50, 20 December 2021
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General Integrated Modeling environment for the Supply of Electricity and Low-temperature heat
by University of Geneva
Authors:
Martin Soini, Arthur Rinaldi
Contact:
Arthur Rinaldi
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Based on Python (Pyomo). Using Python (pandas et al) for data processing.
Download
|
 Open Source
BSD 2-Clause "Simplified" or "FreeBSD" License (BSD-2-Clause)
Directly downloadable
Input data shipped
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| Model Scope |
Model type and solution approach |
| Model class
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Energy System Model, Optimization, Social Planner
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| Sectors
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Electricity, Heat, Hydrogen, Buildings, Transport
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| Technologies
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Renewables, Conventional Generation
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| Decisions
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dispatch
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| Regions
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Switzerland, Austria, Italy, France, Germany
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| Geographic Resolution
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Consumer types and Urban settings
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| Time resolution
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Hour
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| Network coverage
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transmission, net transfer capacities
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| Model type
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Optimization
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Quadratic dipatch sector-coupling model
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| Variables
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5000000
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| Computation time
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30 minutes
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| Objective
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Minimization of total system costs
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| Uncertainty modeling
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Perfect foresight, Sensitivity analisys, Scenarios
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| Suited for many scenarios / monte-carlo
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No
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References
Scientific references
◀ back to model list
Facts about "GRIMSEL-FLEX"RDF feed
| Author institution | University of Geneva + |
| Authors | Martin Soini, Arthur Rinaldi + |
| Computation time minutes | 30 + |
| Contact email | arthur.rinaldi@unige.ch + |
| Contact persons | Arthur Rinaldi + |
| Data availability | all + |
| Decisions | dispatch + |
| Deterministic | Perfect foresight, Sensitivity analisys, Scenarios + |
| Full Model Name | General Integrated Modeling environment for the Supply of Electricity and Low-temperature heat + |
| Georegions | Switzerland, Austria, Italy, France, Germany + |
| Georesolution | Consumer types and Urban settings + |
| Is suited for many scenarios | false + |
| License | BSD 2-Clause "Simplified" or "FreeBSD" License (BSD-2-Clause) + |
| Math modeltype | Optimization + |
| Math modeltype shortdesc | Quadratic dipatch sector-coupling model + |
| Math objective | Minimization of total system costs + |
| Model class | Energy System Model +, Optimization + and Social Planner + |
| Model source public | true + |
| Modelling software | Python (Pyomo) + |
| Network coverage | transmission + and net transfer capacities + |
| Number of variables | 5,000,000 + |
| Open future | false + |
| Open source licensed | true + |
| Processing software | Python (pandas et al) + |
| Sectors | Electricity +, Heat +, Hydrogen +, Buildings + and Transport + |
| Source download | https://github.com/arthurrinaldi/grimsel + |
| Technologies | Renewables + and Conventional Generation + |
| Timeresolution | Hour + |
| Website | |
