Name GENESYS-2
Last updated -
Version Version 1.6.0
Open Source
License Other
Logo
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Name GENESYS-2
Acronym GENESYS-2
Contact (e-mail) christian.bussar@isea.rwth-aachen.de, genesys@isea.rwth-aachen.de
Current contact person Christian Bussar
Website http://www.genesys.rwth-aachen.de/wordpress/
Institution(s) RWTH Aachen University Institut ISEA, RWTH Aachen University Institut IAEW
Geographical Scope Global, Regional, National
Sectoral Scope Electricity
General Problem Scope Forecasting, Exploring
Specific Problem Scope Energy demand, Energy supply, Environmental, Modular build-up, Energy dispatch, Capacity expansion planning, Unit commitment, Rule based operation management
Inital purpose Optimisation of the development corridor from today till 2050 under political boundaries like co2 emission targets, emission certificate prices (that are set in the framework);Standard parametrisation of several European countries Operation and unit dispatch on hourly basis of the whole optimisation time span;Time series for Renewable Energy Generation with support for lookup table to simulate location details of optimal generator locations (wind) or less optimal sites; Flexibility of model settings to investigate targeted time span based on existing components, new investments, green field; Operation on hourly basis, but flexible adaptions can be implemented Investigation of need for long term, seasonal storage, synergies of renewable generation with different storage types; Investigation of policy effects on system structure like co2 emission allowance cost development trajectories, phase out of technologies, retarded investment incentives on certain technologies
Inital purpose change -
Research questions What does the optimal system development pathway look like to reach Co2 mitigation targets from today towards year x ?, What does the power system configuration in year x look like?, What are the generation prices for technology X in an optimal system look like and is it competitive with other carriers?, How is the demand for storage in a specific year; in what year is investment into long term storage inevitable?
Inital Release Date 2017-01-01
Parent Framework -
Version Version 1.6.0
Source of funding Bundesministerium für Wirtschaft und Energy (BMWi), Federal Ministry for Economics Affairs and Energy (BMWi)
GUI
Programming Framework C++, Python used for result analysis
External Solver Heuristic search algorithms are used, cmaes could be replaced by Particle Swarm etc.
Input Data Format CSV
Auto model generator
data preprocessing
Output Data Format XML
data postprocessing python scripts for generating input files and preprocessing the output-file to a readable excel-format
plotting functionalities
The analytical approach Bottom up, false
Additional software Linux-based system, additional libraries: libcmaes; eigen3
interfaces -
The mathematical approach Heuristic optimisation with a bottom up model for dispatch
The underlying methodology Optimization
Objective function type Minimize Total System Cost, Minimizing Levelized Cost of Energy
Open Source
License GNU LGPL
Code availability -
Data availability -
Data provided none
Open to developers
Support Mail
Fixed units
Renewable Technology Inclusion Hydro, Solar, Wind, Biomass
Storage Technology Inclusion Pumped-hydro energy storage, Battery energy storage, Hydrogen production / storage / consumption
Transport Demand -
Residential Demand -
Commercial Demand -
Agricultural demand
Grid model Single-node model
Cost Inclusion Fuel prices, Fixed Operation & Maintenance, CO2 cost
New components
Variable time step
Variable rolling
Commonly used time step Hourly
Commonly modelled time horizon long term (>=15)
Reference Studies/Models -
Citation reference Bussar, C. ; Stöcker, Philipp ; Moraes Jr., Luiz ; Jacqué, Kevin ; Axelsen, Hendrik ; Sauer, D.U.: The Long-Term Power System Evolution – First Optimisation Results. In: Energy Procedia 135 (2017), p. 347–357
Citation https://doi.org/10.1016/j.egypro.2017.09.526
Projects using the framework FlexMex
Model usage -

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