STREAM is a scenario building tool that produces results for decision-making, by providing a good overview of a complete energy system on both demand and supply side for national energy-systems. The model is maintained by the Danish company Ea Energy Analyses [1] who distribute the model for free [2] and all the datasets used by Stream are from other publicly available sources. So far three versions have been created and it only takes a few hours to learn how to use the model.

STREAM consists of three spreadsheet models: (1) The energy flow model, (2) the energy savings model and (3) the duration curve model. The models are based on a bottom-up approach. This means that the user defines the input to the models, e.g. x per cent power produced from wind turbines in the electricity sector or x per cent bioethanol in the transport sector, and on this basis, a financial output is calculated. Hence, the model does not perform an economic optimisation specifying exactly which set of measures are the most advantageous to combine under the given conditions. All costs are accounted for as socio-economic costs, i.e. excluding VAT and other taxes. The purpose of the energy flow model is to create an overview of GHG emissions, energy resources, fuel consumption and conversion in the energy system. The model also contains assumptions as regards investment and operation costs of the technologies used to convert fuels into energy services, which enables it to compute the costs of investing in production facilities. It is possible to break down the fuel consumption by end consumption of energy services or by sectors. All thermal and renewable technologies can be simulated by the model, but there is only one storage device considered, pumped-hydroelectric energy-storage, and no hydrogen technologies. In addition, all transport technologies can be simulated except smart electric-vehicles and vehicle-to-grid electric-vehicles. By means of energy savings model, the demand for energy services in the given year is projected. The demand for energy services is assumed to increase with the economic growth multiplied by an energy intensity factor reflecting the fact, that not all economic growth is translated into increased demand for energy services The purpose of the duration curve model is to analyse correlations in the electricity and CHP system at an hourly level. The analyses made by the duration curve model form the basis for the input to the overall energy flow and economy calculations in the energy flow model – for example, the expected number of operation hours at the various energy production facilities.

Previous studies that have been completed using STREAM are a study on the potential of GHG and demand reductions in the Baltic Sea region (including all or part of ten countries in total) [3], as well as developing scenarios for greenhouse gas [4] and fossil-fuel [5] reductions in Denmark.


  1. Ea Energianalyse a/s, Ea Energianalyse a/s, 13th June 2009,
  2. The STREAM modelling tool, Ea Energy Analyses, 30th June 2009,
  3. Energy Perspectives of the Baltic Sea Region Interim Report: Study on the enhance regional energy cooperation, Ea Energy Analyses, 2009,
  4. Danish Greenhouse Gas Reduction Scenarios for 2020 and 2050, Ea Energy Analyses, Risø National Laboratory, 2008,
    Kofoed-Wiuff, A., Werling, J., Markussen, P., Behrmann, M., Pedersen, J. & Karlsson, K. The Future Danish Energy System: Technology Scenarios. The Danish Board of Technology, 2007,