EnergyPLAN has been developed and expanded on a continuous basis since 1999 at Aalborg University, Denmark [1]. Approximately ten versions of EnergyPLAN have been created, and the current version can be downloaded for free from [2]. To date EnergyPLAN has been downloaded by more than 1,200 people. The training period required to use EnergyPLAN can take a few days up to a month depending on the level required.

EnergyPLAN is a user-friendly tool designed in a series of tab sheets and programmed in Delphi Pascal. Input is defined by the user in terms of technologies and cost specifications. The main purpose of the model is to assist the design of national or regional energy planning strategies on the basis of technical and economic analyses of the consequences of implementing different energy systems and investments. The model encompasses the whole national or regional energy system including heat and electricity supplies as well as the transport and industrial sectors. All thermal, renewable, storage and conversion and transport technologies can be modelled by EnergyPLAN. The model is a deterministic input/output model. General inputs are demands, renewable energy sources, energy station capacities, costs and a number of optional different regulation strategies emphasising import/export and excess electricity production. Outputs are energy balances and resulting annual productions, fuel consumption, import/export of electricity, and total costs including income from the exchange of electricity. Compared to other similar models, the following characteristics of EnergyPLAN can be highlighted: EnergyPLAN is a deterministic model as opposed to a stochastic model or models using Monte Carlo methods. Therefore, with the same input, it will always come to the same result.  EnergyPLAN is based on analytical programming as opposed to iterations, dynamic programming or advanced mathematical tools. This makes the calculations direct and the model very fast when performing calculations. In the programming, any procedures which would increase the calculation time have been avoided, and the computation of one year requires only a few seconds on a normal computer, even in the case of complicated national energy systems. EnergyPLAN is an hour simulation model as opposed to a model based on aggregated annual demands and productions. Consequently, the model is able to analyse the influence of fluctuating renewable energy sources on the system as well as weekly and seasonal differences in electricity and heat demands and water inputs to large hydro power systems. EnergyPLAN is aggregated in its system description as opposed to models in which each individual station and component is described, e.g. in EnergyPLAN district-heating systems are aggregated and defined as three principle groups. EnergyPLAN optimises the operation of a given system as opposed to models which optimise investments in the system. However, by analysing different systems (investments), the model can be used for identifying feasible investments. EnergyPLAN provides a choice between different regulation strategies for a given system as opposed to models in which a specific institutional framework is incorporated. EnergyPLAN analyses one year in steps of one hour as opposed to scenario models analysing a series of years. However, several analyses each covering one year may of course be combined into scenarios.

Previously, EnergyPLAN has been used to analyse the large-scale integration of wind [3] as well as optimal combinations of renewable energy sources [4], management of surplus electricity [5], the integration of wind power using V2G electric vehicles [6], the implementation of small-scale CHP [7], integrated systems and local energy markets [8], renewable energy strategies for sustainable development [9],  the use of waste for energy purposes [10], to investigate the potential of fuel cells and electrolysers in future energy-systems [11, 12], to analyse thermo electric generation (TEG) in thermal energy-systems [13], and the effect of energy storage [14], with specific work on compressed-air energy-storage [15, 16] and thermal energy-storage [1, 3, 17]. In addition, EnergyPLAN was used to analyse the potential of CHP and renewable energy in Estonia, Germany, Poland, Spain and the UK [18]. Other publications can be seen on the EnergyPLAN website [2], while an overview of the work completed using EnergyPLAN was completed by Lund [19]. Finally, EnergyPLAN has been used to simulate a 100% renewable energy system for the island of Mljet in Croatia [20], and to simulate a 100% renewable energy-system for Denmark [21].


  1. Lund, H. & Munster, E., Modelling of energy systems with a high percentage of CHP and wind power.Renewable Energy, 28(14), pp. 2179-2193, 2003.
  2. EnergyPLAN: Advanced Energy System Analysis Computer Model, 10th January 2009,
  3. Lund, H., Large-scale integration of wind power into different energy systems. Energy, 30(13), pp. 2402-2412, 2005.
  4. Lund, H., Large-scale integration of optimal combinations of PV, wind and wave power into the electricity supply. Renewable Energy, 31(4), pp. 503-515, 2006.
  5. Lund, H. & Munster, E., Management of surplus electricity-production from a fluctuating renewable-energy source. Applied Energy, 76(1-3), pp. 65-74, 2003.
  6. Lund, H. & Kempton, W., Integration of renewable energy into the transport and electricity sectors through V2G. Energy Policy, 36(9), pp. 3578-3587, 2008.
  7. Lund, H. & Andersen, A. N., Optimal designs of small CHP plants in a market with fluctuating electricity prices. Energy Conversion and Management, 46(6), pp. 893-904, 2005.
  8. Lund, H. & Munster, E., Integrated energy systems and local energy markets. Energy Policy, 34(10), pp. 1152-1160, 2006.
  9. Lund, H., Renewable energy strategies for sustainable development. Energy, 32(6), pp. 912-919, 2007.
  10. Münster, M. & Lund, H., Use of waste for heat, electricity and transport–Challenges when performing energy system analysis. Energy, 34(5), pp. 636-644, 2009.
  11. Mathiesen, B. V. Fuel cells and electrolysers in future energy systems, 2008. PhD Thesis, Department of Development and Planning, Aalborg University, Aalborg, Denmark. See also:
  12. Mathiesen, B. V. & Lund, H., Comparative analyses of seven technologies to facilitate the integration of fluctuating renewable energy sources. IET Renewable Power Generation, 3(2), pp. 190-204, 2009.
  13. Chen, M., Lund, H., Rosendahl, L. A. & Condra, T. J., Energy efficiency analysis and impact evaluation of the application of thermoelectric power cycle to today’s CHP systems. Applied Energy, 87(4), pp. 1231-1238.
  14. Blarke, M. B. & Lund, H., The effectiveness of storage and relocation options in renewable energy systems.Renewable Energy, 33(7), pp. 1499-1507, 2008.
  15. Lund, H. & Salgi, G., The role of compressed air energy storage (CAES) in future sustainable energy systems. Energy Conversion and Management, 50(5), pp. 1172-1179, 2009.
  16. Lund, H., Salgi, G., Elmegaard, B. & Andersen, A. N., Optimal operation strategies of compressed air energy storage (CAES) on electricity spot markets with fluctuating prices. Applied Thermal Engineering, 29(5-6), pp. 799-806, 2009.
  17. Lund, H. & Clark, W. W., Management of fluctuations in wind power and CHP comparing two possible Danish strategies. Energy, 27(5), pp. 471-483, 2002.
  18. Dissemination Strategy on Electricity Balancing for Large Scale Integration of Renewable Energy, DESIRE, 5th May 2009,
  19. Lund, H., Choice Awareness and Renewable Energy Systems, Department of Development and Planning, Aalborg University2009.
  20. Lund, H., Duic, N., Krajacic, G. & da Graça Carvalho, M., Two energy system analysis models: A comparison of methodologies and results. Energy, 32(6), pp. 948-954, 2007.
  21. Lund, H. & Mathiesen, B. V., Energy system analysis of 100% renewable energy systems–The case of Denmark in years 2030 and 2050. Energy, 34(5), pp. 524-531, 2009.