OEP

Name	Regenerative Energien Modell
Acronym	REMod
Methodical Focus	sector coupling , transformation pathway , net-zero emissions
Institution(s)	Fraunhofer Institute for Solar Energy Systems
Author(s) (institution, working field, active time period)	Andreas Palzer (Fraunhofer ISE; 2012-2019), Philipp Sterchele (Fraunhofer ISE; 2013-2020), Julian Brandes (Fraunhofer ISE; 2018-2023), Markus Kaiser (Fraunhofer ISE; since 2020), Patrick Jürgens (Fraunhofer ISE; since 2020)
Current contact person	Patrick Jürgens
Contact (e-mail)	patrick.juergens@ise.fraunhofer.de
Website	https://www.ise.fraunhofer.de/en/business-areas/system-integration/energy-system-analysis/energy-system-models-at-fraunhofer-ise/remod.html
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Primary Purpose	Determine the cost-optimal transformation pathway of national energy systems until reaching net-zero emissions.
Primary Outputs	Dimensioning of all generators, stores, converters, and consumers in the energy system. Hourly data of the interaction between all energy sectors: electricity, heat, mobility and industry on the transformation pathway
Support / Community / Forum
Framework
Link to User Documentation	-
Link to Developer/Code Documentation	-
Documentation quality	excellent
Source of funding	self funding
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	Julia
Internal data processing software	Python
External optimizer
Additional software
GUI

Coverage

Modeled energy sectors (final energy)

electricity, heat, Hydrogen, Gas

Modeled demand sectors

Households, Industry, Commercial sector, Transport

Modeled technologies: components for power generation or conversion

Renewables

PV, Wind, Hydro, Biomass,Biogas,Biofuels, Solar thermal, Geothermal heat

Conventional

gas, lignite, hard coal, oil, liquid fuels, nuclear

Modeled technologies: components for transfer, infrastructure or grid

Electricity

distribution, transmission

Gas

transmission

Heat

distribution

Properties electrical grid

simulated energy exchange between nodes

Modeled technologies: components for storage

battery, pump hydro, chemical, heat, gas

User behaviour and demand side management

Flexible operation of heating systems and V2G and G2V in transport sector

Changes in efficiency

Heat pumps

Market models

-

Geographical coverage

Europe / Germany

Geographic (spatial) resolution

national states, federal states

Time resolution

hour

Comment on geographic (spatial) resolution

Depending on parametrization. At the moment either one-node or multi-node with (aggregated) national or federal states as nodes.

Observation period

>1 year

Additional dimensions (sector)

ecological, additional dimensions sector ecological text, economic, additional dimensions sector economic text

Model class (optimisation)	-
Model class (simulation)	-
Other	Simulation-based optimization
Short description of mathematical model class	Simulation-based optimization: operation is simulated on hourly basis, transformation path is optimized using the evolutionary algorithm CMA-ES.
Mathematical objective	costs
Approach to uncertainty	Stochastic
Suited for many scenarios / monte-carlo
typical computation time	more than a day
Typical computation hardware	80 core server
Technical data anchored in the model	-