Model Factsheet

Overview / Regenerative Energien Modell (REMod)

Model Regenerative Energien Modell (REMod)

General Information
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
Mathematical Properties
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 -
Model Integration
Interfaces
Model file format .jl
Input data file format .csv
Output data file format text
Integration with other models
Integration of other models
References

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