Model Factsheet

Overview / Balmorel (Bal)
Name Balmorel
Acronym Bal
Methodical Focus None
Institution(s) RAM-lose, DTU Danish Technical University, NMBU, TTU, EA Energy Analysis
Author(s) (institution, working field, active time period) Hans Ravn
Current contact person Hans Ravn
Contact (e-mail) Hans.Ravn@aeblevangen.dk
Website http://balmorel.com/
Logo
Primary Purpose Balmorel is a model for analysing the electricity and combined heat and power sectors in an international perspective. It is highly versatile and may be applied for long range planning as well as shorter time operational analysis. The model is developed in a model language, and the source code is readily available, thus providing complete documentation of the functionalities. Moreover, the user may modify the model according to specific requirements, making the model suited for any purpose within the focus parts of the energy system. Balmorel is a partial equilibrium model for simultaneous optimisation of generation, transmission and consumption of electricity and heat under the assumption of perfectly competitive markets. The model finds the optimal way to satisfy the energy demand maximising social welfare, viz., consumers' utility minus producers' cost of electricity and district heat generation, storage, transmission and distribution; subject to technical, physical and regulatory constraints.
Primary Outputs
Support / Community / Forum
Framework Unclear if it can be classified as model or framework
Link to User Documentation http://balmorel.com/index.php/downloadmodel/getting-started; http://balmorel.com/images/downloads/model/BMS303-20160907.pdf
Link to Developer/Code Documentation http://balmorel.com/images/downloads/model/
Documentation quality good
Source of funding project-based
Number of developers less than 10
Number of users less than 100
Open Source
License ISC license
Source code available
GitHub
Access to source code https://github.com/balmorelcommunity/Balmorel/
Data provided none
Collaborative programming
GitHub Organisation
GitHub Contributions Graph
Modelling software GAMS
Internal data processing software
External optimizer
Additional software
GUI
Modeled energy sectors (final energy) electricity, heat
Modeled demand sectors Households, Industry, Commercial sector
Modeled technologies: components for power generation or conversion
Renewables PV, Wind, Hydro, Solar thermal
Conventional gas, oil, liquid fuels, nuclear
Modeled technologies: components for transfer, infrastructure or grid
Electricity transmission
Gas transmission
Heat distribution, transmission
Properties electrical grid -
Modeled technologies: components for storage battery, pump hydro, chemical, heat, gas
User behaviour and demand side management Elastic Demand
Changes in efficiency
Market models -
Geographical coverage
Geographic (spatial) resolution national states, TSO regions, regions, municipalities, districts
Time resolution -
Comment on geographic (spatial) resolution Many resolutions possible with electricity modelled in regions and district heat modelled in areas which are submodules of the regions. One example: For EU-Nordic Model Application: Electricity modelled in grid regions (mostly Nordpool Spot and along major grid bottlenecks in Germany) Heat modelled in district heat areas with a higher resolution
Observation period <1 year, 1 year, >1 year, Typically one or more years, but also applied to parts of a year, e.g. a week
Additional dimensions (sector) ecological, additional dimensions sector ecological text, economic, additional dimensions sector economic text
Model class (optimisation) LP, MILP
Model class (simulation) Bottom up
Other
Short description of mathematical model class The Balmorel core model is linear, but mixed-integer modelling may be applied, e.g. in order to represent economies of scale and unit commitment.
Mathematical objective CO2, costs, RE-share
Approach to uncertainty Deterministic, Stochastic
Suited for many scenarios / monte-carlo
typical computation time less than a day
Typical computation hardware Since Hardware and Model dimension differ significantly, the computation time ranges from seconds to days
Technical data anchored in the model Model Code and Data are kept separate
Interfaces
Model file format .gms
Input data file format text
Output data file format comes out as gdx, but .db (sqlite) or xlsx can also be chosen
Integration with other models Integration with the network flow model OptiFlow http://balmorel.com/index.php/downloadmodel/optiflow
Integration of other models Balmorel has several addons; which are supplied with the main model and can be turned on by the user if necessary, Examples are unit commitment; endogenous investments with discrete size units and flowbased transmission
Citation reference current published version: Ravn, Hans, & all other contributors. (2011, September 20). balmorelcommunity/balmorel v3.02 (Version v3.02). Zenodo. http://doi.org/10.5281/zenodo.823693
Citation DOI 10.5281/zenodo.823692
Reference Studies/Models http://balmorel.com/index.php/activities; http://balmorel.com/index.php/publications
Example research questions Least-cost climate emission reduction pathway for electricity and heat in the Nordic Countries: Technology Options, Robust Strategies, Grade of Electrification, Usage of Flexibility Options
Model usage DTU, NMBU, TTU, EA Energy Analysis, COWI, HOFOR, Danish Energy Association, Estonian Transmission System Operator Elering, Mexican Energy Minsitery, Eastern African Power Pool (EAPP), Sino-Danish Renewable Energy Development (RED) programme
Model validation -
Example research questions Least-cost climate emission reduction pathway for electricity and heat in the Nordic Countries: Technology Options, Robust Strategies, Grade of Electrification, Usage of Flexibility Options
further properties Simultaneous endogenous optimization and economic dispatch; price dependent consumption
Model specific properties strong in representation of district heat; flexible handling of time segmentation

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Electricity Heat MODEX open-EU2018 EMP-E market