Model Factsheet

General Information

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
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

Openness

Open Source
Planned to open up in the future
Costs	-

Software

Modelling software	Matlab, R
Internal data processing software	fmincon
External optimizer
Additional software
GUI

Coverage

Modeled energy sectors (final energy)	electricity
Modeled demand sectors	Households, Industry, Commercial sector, Transport
Modeled technologies: components for power generation or conversion	Renewables PV, Wind, Hydro, Solar thermal Conventional gas
Modeled technologies: components for transfer, infrastructure or grid	Electricity transmission Gas - Heat -
Properties electrical grid	-
Modeled technologies: components for storage	battery, kinetic, compressed air, pump hydro, chemical, gas
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	national states
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)	ecological, additional dimensions sector ecological text

Mathematical Properties

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	-

Model Integration

Interfaces
Model file format	mat
Input data file format	.csv
Output data file format	*.mat, *.pdf
Integration with other models
Integration of other models

References

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	-
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

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grid Europe MODEX Storage DSM