OEP

General Information

Name	REMix (Renewable Energy Mix)
Acronym	REMix
Methodical Focus	Sector coupling , Model speed-up , Multi-criteria optimization
Institution(s)	DLR - German Aerospace Center
Author(s) (institution, working field, active time period)	Y. Scholz; H.C. Gils; K.-K. Cao; M. Wetzel; K.von Krbek; N. Wulff; S. Sasanpour; H. Gardian; M. Yeligeti; J. Schmugge; E. Arellano; A. Sahin; G. Recht (all DLR); T. Fichter; F. Cebulla; D. Luce de Tena; D. Heide; F. Borggrefe; D. Hess; A. Rubbert (ex-DLR)
Current contact person	Hans Christian Gils
Contact (e-mail)	hans-christian.gils@dlr.de
Website	https://www.dlr.de/ve/desktopdefault.aspx/tabid-15971/25909_read-66550/
Logo
Primary Purpose	development and analysis of energy supply scenarios with focus on infrastructures
Primary Outputs	least cost configuration and operation of the considered system, least cost paths for future energy system development, systems costs, CO2 emissions, indicators for security of power supply, renewable energy usage, storage demand, sector coupling implementation
Support / Community / Forum
Framework	REMix
Link to User Documentation	https://dlr-ve.gitlab.io/esy/remix/framework/dev/documentation/index.html
Link to Developer/Code Documentation	https://dlr-ve.gitlab.io/esy/remix/framework/dev/documentation/tech-docs/index.html
Documentation quality	good
Source of funding	German Federal Ministry of Economc Affairs and Energy
Number of developers	less than 20
Number of users	less than 100

Openness

Open Source
License	BSD 3-clause 'New' or 'Revised' license
Source code available
GitHub
Access to source code	https://gitlab.com/dlr-ve/esy/remix/framework
Data provided	example data
Collaborative programming

Software

Modelling software	GAMS; Python
Internal data processing software	JavaScript; Excel; Python
External optimizer	CPLEX; gurobi; PIPS-IPM++
Additional software
GUI

Coverage

Modeled energy sectors (final energy)

electricity, heat, Transport

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

transmission

Gas

transmission

Heat

distribution

Properties electrical grid

DC load flow, transshipment model, single-node / copper plate model

Modeled technologies: components for storage

battery, kinetic, compressed air, pump hydro, chemical, heat, gas

User behaviour and demand side management

Consideration of demand response in industry, household and tertiary sector, see http://dx.doi.org/10.1016/j.apenergy.2015.10.083

Changes in efficiency

Considered only in input data

Market models

fundamental model

Geographical coverage

Global

Geographic (spatial) resolution

continents, national states, TSO regions, federal states, regions, NUTS 3

Time resolution

hour

Comment on geographic (spatial) resolution

Global renewable energy database. Past model applications mostly to Germany and Europe, but also Brazil, USA, China and others

Observation period

1 year, >1 year

Additional dimensions (sector)

ecological

Mathematical Properties

Model class (optimisation)	LP, MILP
Model class (simulation)	-
Other
Short description of mathematical model class
Mathematical objective	CO2, costs, RE-share, any considered, could also be e.g. material demand
Approach to uncertainty	Deterministic, Stochastic
Suited for many scenarios / monte-carlo
typical computation time	more than a day
Typical computation hardware	-
Technical data anchored in the model	no

Model Integration

Interfaces	Own Python API
Model file format	.gms
Input data file format	.dat, .csv
Output data file format	.gdx, .csv, .xls
Integration with other models	EnDAT (global wind and solar power generation potential database), AMIRIS, venco.py
Integration of other models

References

Citation reference

see below

Citation DOI

Reference Studies/Models

http://elib.dlr.de/107961/ , http://elib.dlr.de/93240/ , http://elib.dlr.de/103733/ , http://elib.dlr.de/103522/ , http://elib.dlr.de/99778/ , http://elib.dlr.de/95863/ , http://elib.dlr.de/94979/ , http://elib.dlr.de/77130/ , http://elib.dlr.de/76043/ , http://fp7-advance.eu/sites/default/files/documents/WP7/ADVANCE-Synthesis-Report.pdf,

Example research questions

How do overall power generation costs develop at high variable renewable energy (VRE) shares and at different proportions of wind and solar power? How does VRE power generation interact with transmission, storage, sector coupling and backup power generation? Which infrastructural developments and investments are required to maintain security of supply? Which technologies can provide backup at the lowest cost? To what extent are curtailments expected as an ultimate balancing measure after transmission and storage?

Model usage

-

Model validation

cross-checked with other models, checked with measurements (measured data)

Example research questions

How do overall power generation costs develop at high variable renewable energy (VRE) shares and at different proportions of wind and solar power? How does VRE power generation interact with transmission, storage, sector coupling and backup power generation? Which infrastructural developments and investments are required to maintain security of supply? Which technologies can provide backup at the lowest cost? To what extent are curtailments expected as an ultimate balancing measure after transmission and storage?

further properties

Model specific properties

-

Model Factsheet

Model REMix (Renewable Energy Mix) (REMix)

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