The MARKAL/TIMES family are energy/economic/environmental models supporting a rich technology detail. MARKAL/TIMES were developed in a collaborative effort under the auspices of the International Energy Agency’s Energy Technology Systems Analysis Programme, which started in 1978 [1]. MARKAL has been developed since 1980 and TIMES since 2000. New versions of TIMES are being released every few months. At the moment, MARKAL/TIMES is used in 70 countries by 250 institutions (of which 75% are active users). The source code is distributed free of charge by signing a Letter of Agreement not to provide any part of the ETSAP models generator to any third party. The code is written in GAMS, which is a commercial language and has to be purchased. 99% of the users manage the system by means of a shell, ANSWER or VEDA. The commercial software costs US$3000 – US$5,000 (€2,150 – €3,775) for an educational license and US$20,000 (€15,103) for a commercial license [2]. The most demanding part is training and learning, which takes some months.

MARKAL/TIMES are general purpose model generators tailored by the input data to represent the evolution over a period of usually 20 to 50 or 100 years, of a specific energy-environment system at the global, multi-regional, national, state/province, or community level. Each annual load duration curve, hence each annual variable can be detailed by as many as desired time slices, which is user-defined at three levels: seasonal (or monthly), week days – weekends, and hour of the day. The entire energy system can be modelled and it is represented as a network, depicting all possible flows of energy (usually as many as reported by the detailed energy balances) from resource extraction, through energy transformation and end-use devices, to demand for useful energy services – as many as desired, in the desired units. For instance the demand for space heating can be specified by as many as desired categories such as single or multifamily, urban or rural, existing or new, etc., and in the desired units such as PJ, number of households, m2 or m3. Each link in the network is characterized by a set of technical characteristics (e.g., capacity in place, availability factors, efficiency), environmental emission coefficients (e.g., CO2, SOx, NOx), and economic factors (e.g., capital and costs). All thermal, renewable, storage and conversion and transportation technologies can be simulated by the model. Many different energy networks or Reference Energy Systems (RES) are feasible for each time period. MARKAL/TIMES finds the “best” RES for each time period by selecting the set of options that minimizes total discounted system cost or the total discounted surplus over the entire planning horizon, within the limits of all imposed policy and physical constraints.

MARKAL/TIMES have been used for countless studies [3], some of which include an investigation into the potential of carbon capture and storage [4, 5],  studies on the future prospects of hydrogen and fuel cells [6-8], as well as hydrogen vehicles [9, 10], examinations into the future role of nuclear power [11] and nuclear fusion [12-14]. Also, MARKAL/TIMES models have been used to simulate European Commission integrated policies on the use of renewable sources, climate change mitigation and energy efficiency improvement, the so called 20-20-20 targets, and far more stringent targets in the longer term, at the national and pan EU level [15].


  1. Tosato, G. C. Introduction to ETSAP and the MARKAL-TIMES models generators. International Energy Agency: NEET Workshop on Energy Technology Collaboration, 2008,
  2. Tools, International Energy Agency, 12th June 2009,
  3. Goldstein, G. A. & Tosato, G. C. Global Energy Systems and Common Analyses: Final Report of Annex X (2005-2008). International Energy Agency, 2008,
  4. Gielen, D., Podkański, J. & Unander, F. Prospects for CO2 Capture and Storage. International Energy Agency, 2004,
  5. Wenying, C., Jia, L., Linwei, M., Ulanowsky, D. & Burnard, G. K., Role for carbon capture and storage in China. Energy Procedia, 1(1), pp. 4209-4216, 2009.
  6. Contaldi, M., Gracceva, F. & Mattucci, A., Hydrogen perspectives in Italy: Analysis of possible deployment scenarios. International Journal of Hydrogen Energy, 33(6), pp. 1630-1642, 2008.
  7. Tseng, P., Lee, J. & Friley, P., A hydrogen economy: opportunities and challenges. Energy, 30(14), pp. 2703-2720, 2005.
  8. Gielen, D. & Simbolotti, G. Prospects for Hydrogen and Fuel Cells. International Energy Agency, 2005,
  9. Contreras, A., Guervós, E. & Posso, F., Market penetration analysis of the use of hydrogen in the road transport sector of the Madrid region, using MARKAL. International Journal of Hydrogen Energy, 34(1), pp. 13-20, 2009.
  10. Endo, E., Market penetration analysis of fuel cell vehicles in Japan by using the energy system model MARKAL. International Journal of Hydrogen Energy, 32(10-11), pp. 1347-1354, 2007.
  11. Vaillancourt, K., Labriet, M., Loulou, R. & Waaub, J.-P., The role of nuclear energy in long-term climate scenarios: An analysis with the World-TIMES model. Energy Policy, 36(7), pp. 2296-2307, 2008.
  12. Hamacher, T., Lako, P., Ybema, J. R., Korhonen, R., Aquilonius, K., Cabal, H., Hallberg, B., Lechón, Y., Lepicard, S., Sáez, R. M., Schneider, T. & Ward, D., Can fusion help to mitigate greenhouse gas emissions?Fusion Engineering and Design, 58-59, pp. 1087-1090, 2001.
  13. Lechon, Y., Cabal, H., Varela, M., Saez, R., Eherer, C., Baumann, M., Düweke, J., Hamacher, T. & Tosato, G. C., A global energy model with fusion. Fusion Engineering and Design, 75-79, pp. 1141-1144, 2005.
  14. Biberacher, M. Fusion in the global energy system – GIS and TIMES. International Energy Agency, 2006,
  15. Monitoring and Evaluation of the RES directives implementation in EU27 and policy recommendations for 2020, Centre for Renewable Energy Sources (CRES: Geece), 12th June 2009,