Model Factsheets
| Name | Renewable Electricity Supply and Storage in Europe |
| Acronym | RESTORE |
| Methodical Focus | None |
| Institution(s) | Wuppertal Institut; |
| Author(s) (institution, working field, active time period) | Mathis Buddeke; Christine Krüger; Arjuna Nebel |
| Current contact person | Christine Krüger |
| Contact (e-mail) | christine.krueger@wupperinst.org |
| Website | www.wupperinst.org |
| Logo | |
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| Primary Purpose | Optimised dispatch of flexibility options (Storage, Demand Side Management, Transmission grid). Minimising and leveling backup eneregy (non renewable energy). Europe, temporal and spatial resolution are adaptable (min resolution: countrywise, hourly) |
| Primary Outputs | Technical component dispatch. Residual load. Redispatch of fluctuating RES. |
| Support / Community / Forum | |
| Framework | |
| Link to User Documentation | |
| Link to Developer/Code Documentation | |
| Documentation quality | expandable |
| Source of funding | BMBF - RESTORE2050 Project |
| Number of developers | less than 10 |
| Number of users | less than 10 |
| Open Source | |
| Planned to open up in the future | |
| Costs | - |
| Modelling software | Matlab, R |
| Internal data processing software | fmincon |
| External optimizer | |
| Additional software | |
| 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 | Demand Side Management is realized for different sectors as a "storage" with time-dependent boundaries | ||||||
| Changes in efficiency | - | ||||||
| Market models | - | ||||||
| Geographical coverage | Europe and North africa (32 countries) | ||||||
| Geographic (spatial) resolution |
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| Time resolution | hour | ||||||
| Comment on geographic (spatial) resolution | Fully flexible, adaptable to the object of investigation. | ||||||
| Observation period | 1 year, adaptable observation period | ||||||
| Additional dimensions (sector) |
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| Model class (optimisation) | fmincon |
| Model class (simulation) | - |
| Other | |
| Short description of mathematical model class | Quadratic objective function: minimization of the square of the residual load, resulting in - reduced overall residual load - reduced load peaks - reduced gradients |
| Mathematical objective | RE share and load levelling |
| Approach to uncertainty | Rolling horizon optimization |
| Suited for many scenarios / monte-carlo | |
| typical computation time | more than a day |
| Typical computation hardware | 12 Core 64GB |
| Technical data anchored in the model | - |
| Interfaces | |
| Model file format | mat |
| Input data file format | .csv |
| Output data file format | *.mat, *.pdf |
| Integration with other models | |
| Integration of other models |
| Citation reference | Kruger, C.; Buddeke, M.; Merten, F.; Nebel, A. (2015) Modelling the interdependencies of storage, DSM and grid-extension for Europe In: 12th International Conference on the European Energy Market (EEM), Lisbon Portugal, 19-22 May 2015, Inst. of Electrical and Electronics Engineers, New York, pp. 1-5 |
| Citation DOI | http://dx.doi.org/10.1109/EEM.2015.7216669 |
| Reference Studies/Models | Vogt et al. (2016): „RESTORE 2050 - Regenerative Stromversorgung & Speicherbedarf im Jahr 2050, Projektabschlussbericht: Ergebnisse und Handlungsempfehlungen |
| Example research questions | Interdependencies of flexibility options such as storage, DSM or grid extension in renewable based energy systems |
| Model usage | |
| Model validation |
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| Example research questions | Interdependencies of flexibility options such as storage, DSM or grid extension in renewable based energy systems |
| further properties | |
| Model specific properties | target function not cost-based, but minimization of residual loads |