The BALMOREL energy model is a partial equilibrium model, which supports modelling and analysis of the energy sector with emphasis on the electricity and the combined heat and power sectors. BALMOREL is developed, maintained and distributed under open source ideals since 2000. Hence, the model as well as project generated information, including all details, can be freely downloaded from [1]. This in particular includes the model source code and a working data set. The model development is mainly project driven, with a users’ network and forum around it, supporting the open source development idea. The model is formulated in the GAMS modelling language [2] and a GAMS license is needed to run  the model; additionally it has a graphical user interface facilitating input data handling, output reporting etc. Approximately 10 versions of the BALMOREL model have been created (and the number of users is not monitored). In addition to providing 100% documentation at code level, any user can modify the model to suit specific requirements in a given application of it. Since the formulated model is solved in standard software, there is no need to write new optimization code. To run a typical analysis using BALMOREL, one week of training is necessary.

Input data and calculation results are given in relation to a geographical subdivision that allows identification of countries (for description of e.g. taxes, emissions, etc.), regions (for electricity transmission) and areas (for district heating systems, local cost elements, etc.). Time aspects are treated flexibly in relation to how many years to represent, and how many subdivisions of the time within the year. Typical choices are 250 time segments per year over a 20 year time-horizon, or 8,760 time segments per year over one year, according to the purpose of the study. BALMOREL can simulate the electricity sector and some of the heat sector (district heating), but not the transport sector (transport technologies are not represented as standard, but some projects [120] have developed transport sector modules). Technical and economic characteristics are given for an arbitrary number of production units, e.g. capacities, fuel efficiencies, operation and maintenance costs, fuel prices. The different types of units include electricity, heat, combined heat and power, short-term heat storages, hydro power, wind and solar. Specialties like electricity storage are provided to represent e.g. hydrogen storage or pumped hydro. Electricity transmission is described in relation to a number of nodes that are connected by transmission lines characterised by capacity, loss and cost. This flow model allows for the identification of bottlenecks in the transmission system, and thereby can show differences in electricity prices according to geography. In relation to generation capacity, the model may invest optimally in electricity and combined heat and power technologies. The investments respect specified restrictions e.g. in relation to maximum investment addition per year, or maximum fuel available. The model also handles environmental and other taxes, subsidies and quotas. Due to the model being formulated in a modelling system additional functionalities may be (and have been) developed as needed in relation to specific project needs, as indicated in some of the references below.

The BALMOREL model has been applied to projects in Denmark [3-5], Norway [6], Estonia [6], Latvia [7], Lithuania [8], Germany [9], as well as in countries outside of Europe [10]. It has been used for analyses of security of electricity supply [11, 12], the role of demand response [13], wind power development [5, 10], the role of natural gas [4], development of international electricity markets [14], market power [15], expansion of electricity transmission [6], international markets for green certificates and emission trading as well as environmental policy evaluation [16], unit commitment [3-5], CAES technology [17] and learning curves [18]. To date the BALMOREL has not simulated a 100% renewable-energy electricity sector or a 100% renewable-energy system: the highest renewable-penetrations simulated to date are 50% of the electricity sector [5], and 10% of the transport sector [19].


  1. BALMOREL, 22nd April 2009,
  2. Welcome to the GAMS Home Page, GAMS Development Corporation, 22nd April 2009,
  3. Andersen, F. M., Jensen, S. G., Larsen, H. V., Meibom, P., Ravn, H., Skytte, K. & Togeby, M. Analyses of Demand Response in Denmark. Risø National Laboratory, 2006,
  4. Danmarks Tekniske Universitet, Risø National Laboratory, Dansk Gasteknisk Center, Rambøll, EA Energy Analyses,, RAM-løse edb. Det Danske Gas Og Elsystem (The Danish Gas and Electricity System). Danish Energy Agency, 2007. See also:
  5.  50% Wind Power in Denmark in 2025, Ea Energy Analyses, 2007,
  6.  Marte-Heggedal, A. Investment in new transmission capacity between Estonia and Finland – effects on the electricity market and welfare, 2006. Masters Thesis, Department of Economics and Natural Resource Management, Norwegian University of Life Sciences, Ås. See also:
  7. Eesti Energia, Latvenergo, Lietuvos Energija, Elkraft System, COWI, Danish Energy Agency. Power sector development in a Common Baltic Electricity Market. Elkraft System, COWI, 2005. See also:
  8. Economic analyses in the electricity sector in Lithuania, Elkraft System, COWI, Lietuvos Energija, Lithuanian Energy Institute, 2002,
  9. Ball, M., Wietschel, M. & Rentz, O., Integration of a hydrogen economy into the German energy system: an optimising modelling approach. International Journal of Hydrogen Energy, 32(10-11), pp. 1355-1368, 2007.
  10. Large Scale Wind Power in New Brunswick – A regional scenario towards 2025, Ea Energy Analyses, 2008,
  11. Erik-Morthorst, P., Grenaa-Jensen, S. & Meibom, P. Investering og prisdannelse på et liberaliseret elmarked. Risø, 2005,
  12. Jensen, S. G. & Meibom, P., Investments in liberalised power markets: Gas turbine investment opportunities in the Nordic power system. International Journal of Electrical Power & Energy Systems, 30(2), pp. 113-124, 2008.
  13. Møller-Andersen, F., Grenaa-Jensen, S., Larsen, H. V., Meibom, P., Ravn, H., Skytte, K. & Togeby, M. Analyses of Demand Response in Denmark. Risø-R-1565(EN), 2006,
  14. Ea Energy Analyses, Hagman Energy, COWI. Congestion Management in the Nordic Market – evaluation of different market models. Nordic Council of Ministers, 2008. See also:
  15. Modelling Imperfect Competition on the Nordic Electricity Market with Balmorel, Danish Energy Research Program 2003, 2005,
  16. Lindboe, H. H., Werling, J., Kofoed-Wiuff, A. & Bregnbæk, L. Impact of CO2 quota allocation to new entrants in the electricity market. Ea Energy Analyses, Energy Modelling, 2007,
  17. Rud, J. Systemanalyse af Compressed Air Energy Storage: Optimering, drift og implementering i det danske energimarked (System analysis of a potential Compressed Air Energy Storage: Optimization, operation and implementation in the Danish energy market), 2008. Masters Thesis, Institut for Mekanisk Teknologi, Danmarks Tekniske Universitet, Copenhagen, Denmark. See also:
  18. Dittmar, L. Integration of energy savings technologies and learning curves into the BALtic MOdel of Regional Electricity Liberalisation – BALMOREL, 2006. Masters Thesis, University of Flensburg, Flensburg, Germany. See also:
  19. Karlsson, K. & Meibom, P. Integration of Hydrogen as Energy Carrier in the Nordic Energy System. Risø National Laboratory, 2006,