Skip to main content

Introduction to Energy Systems Modelling


The energy demand and supply projections of the Swiss government funded by the Swiss Federal Office of Energy and carried out by a consortium of institutes and consulting companies are based on two types of energy models: macroeconomic general equilibrium models and bottom-up models for each sector. While the macroeconomic models are used to deliver the economic, demographic and policy framework conditions as well as the macroeconomic impacts of particular scenarios, the bottom-up models simulate the technical developments in the final energy sectors and try to optimise electricity generation under the given boundary conditions of a particular scenario. This introductory article gives an overview of some of the energy models used in Switzerland and — more importantly — some insights into current advanced energy system modelling practice pointing to the characteristics of the two modelling types and their advantages and limitations.


  • Alexandridis, K. T., and B. C. Pijanowski (2006), “Modular Bayesian Inference and Learning of Decision Networks as Stand-Alone Mechanisms of the MABEL Model: Implications for Visualization, Comprehension, and Policy-Making”, Argonne National Laboratory and the University of Chicago.

  • Bahn, O., and C. Frei (2000), “GEM-E3 Switzerland: A Computable General Equilibrium Model applied for Switzerland”, Paul Scherrer Institut (PSI), General Energy Research Department (ENE), Villigen.

    Google Scholar 

  • Bataille, C. G. F. (2005), “Design and Application of a Technologically Explicit Hybrid Energy-Economy Policy Model with Micro and Macro Economic Dynamics”, Thesis in the School of Resource and Environmental Management, Simon Fraser University.

  • Bernard, A., and M. Vielle (2008), “GEMINI-E3, A General Equilibrium Model of International-National Interactions between Economy, Energy and Environment”, Computational Management Science, 5(3), pp. 173–206.

    Article  Google Scholar 

  • BFE (Bundesamt für Energie) (2007), Die Energieperspektiven 2035 — Band 1 Synthese, Bern.

  • Böhringer, C. (1998), “The Synthesis of Bottom-Up and Top-Down in Energy Policy Modelling”, Energy Economics, 20, pp. 233–248.

    Article  Google Scholar 

  • Böhringer, C., and A. Löschel (2006), “Promoting Renewable Energy in Europe: A Hybrid Computable General Equilibrium Approach”, Special Issue of the Energy Journal, Hybrid modeling of energy-environment policies: Reconciling bottom-up and top-down.

  • Böhringer, C., and T. Rutherford (2006), “Combining Top-Down and Bottom-Up Analysis in Energy Policy Analysis”, Technical Report Discussion paper 06-07, ZEW.

    Google Scholar 

  • Böhringer, C., and T. Rutherford (2008), “Combining Bottom-Up and Top-Down”, Energy Economics, 30, pp. 574–596.

    Article  Google Scholar 

  • CAMECON (2011), Cambridge Econometrics, website:

  • Capros, P., et al. (1996a), “Double Dividend Analysis: First Results of a General Equilibrium Model (GEM-E3) Linking the EU-12 Countries”, in Environmental Fiscal Reform and Unemployment, C. Carraro and D. Siniscalco, eds., Kluwer Academic Publishers.

  • Capros, P., and P. Georgakopoulos (1996b), “Coordinated versus Uncoordinated European Carbon Tax Solutions Analysed with GEM-E3 Linking the EU-12 Countries”, in Economic Aspects of Environmental Policy, S. Proost, eds., Kluwer Academic Publishers.

  • Catenazzi, G. (2009), “Advances in Techno-Economic Energy Modeling: Costs, Dynamics and Hybrid Aspects”, Dissertation, Swiss Federal Institute of Technology (ETH), Zürich.

  • CES (2008), “The GEM-E3 Model. A General Equilibrium Model for Europe and the World”, Centre for Economic Studies, KULeuven, Belgium.

    Google Scholar 

  • De Vries, B., M. Janssen, A. Beusen, et al. (1999), “Perspectives on Global Energy Futures: Simulations with the TIME Model”, Energy Policy, 27, pp, 477–494.

    Article  Google Scholar 

  • E3Mlab (2007), “The Primes Model: Version Used for the 2007 Scenarios for the European Commission including new Sub-Models Recently Added”, website:

  • Enerdata (2011), Enerdata global energy intelligence, website:

  • ETSAP (2001), ETSAP, website:

  • ETSAP (2005), “Documentation for the TIMES Model: Part 1”, April 2005, website:

  • Eurostat (2008), “Eurostat Manual of Supply, Use and Input-Output Tables”, Methodologies and Workingpapers, 2008 edition, Luxembourg.

  • EWI (2011), Energiewirtschaftliches Institut an der Universität zu Köln, website:

  • Fichtner, W., D. Möst, M. Wietschel, C. Weinhardt, and O. Rentz (2003), „Zur strategischen Planung bei Energieversorgern in liberalisierten Energiemärkten“, WiSt- Wirtschaftswissenschaftliches Studium, 32 (12), pp. 707–713.

    Article  Google Scholar 

  • FSO (2010), Federal Statistical Office, website:

  • Foley, J., et al. (2005), “Global Consequences of Land Use”, Science, 309, 570, DOI: 10.1126/science.1111772.

  • Forrester, J. W. (1958), “Industrial Dynamics — A Major Breakthrough for Decision Makers”, Harvard Business Review, 36(4), pp. 37–66.

    Google Scholar 

  • Forrester, J. W. (1962), Industrial Dynamics, 2nd edition, MIT Press, John Wiley & Sons, New York.

    Google Scholar 

  • Forrester, J. W. (1971), World Dynamics, Wright-Allen Press, Cambridge MA.

    Google Scholar 

  • Forrester, J. W. (1980), “System Dynamics — Future Opportunities”, in System Dynamics. TIMS Series in the Management Sciences, Augusto A. Legasto, Jay W. Forrester, and James M. Lyneis, eds., vol. 14, pp. 7–21, Amsterdam: North-Holland.

    Google Scholar 

  • Genoese, M., F. Sensfuss, and D. Moest (2007), “Power Plant Investments under Different Emission Allocation Schemes”, Proceedings of the 9th IAEE European Conference on Energy Economics (10–12 June 2007), Florence, Italy.

    Google Scholar 

  • Greene, W. H. (2003), Econometric Analysis, Fifth Edition, New York University, Pearson Education, New Jersey.

    Google Scholar 

  • Heaps, C. (2002), “Global Scenario Group Futures”, SEI, technical notes, report 9.

  • Heemskerk, M., K. Wilson, and M. Pavao-Zuckerman (2003), “Conceptual models as tools for communication across disciplines”, Conservation Ecology, 7(3): 8.

    Article  Google Scholar 

  • Hourcade, J. C., et al. (2006), “Hybrid Modeling: New Answers to Old Challenges”, The Energy Journal 2, Special issue (2006) pp. 1–12, C.I.R.E.D., Nogent-sur-Marne cedex.

    Google Scholar 

  • IEA (2010), “World Energy Outlook 2010”, International Energy Agency, Paris Cedex, France.

    Google Scholar 

  • IEA (2011), “World Energy Model — Methodology And Assumptions”, International Energy Agency, Paris Cedex, France.

    Google Scholar 

  • Jochem, E., T. Barker, S. Scrieciu, W. Schade, N. Helfrich, O. Edenhofer, N. Bauer, S. Marchand, J. Neuhaus, S. Mima, P. Criqui, J. Morel, B. Chateau, A. Kitous, G. J. Nabuurs,, M. J. Schelhaas, T. Groen, L. Riffeser, F. Reitze, E. Jochem, G. Catenazzi, M. Jakob, B. Aebischer, K. Kartsoni, W. Eichhammer, A. Held, M. Ragwitz, U. Reiter, S. Kypreos, and H. Turton (2007), “EU-Project ADAM: Adaption and Mitigation Strategies: Supporting European Climate Policy — Deliverable M1.1: Report of the Base Case Scenario for Europe and Full Description of the Model System”, Fraunhofer ISI, Karlsruhe, November 2007.

    Google Scholar 

  • Jochem, E., T. Barker, S. Scrieciu, W. Schade, N. Helfrich, O. Edenhofer, N. Bauer, S. Marchand, J. Neuhaus, S. Mima, P. Criqui, J. Morel, B. Chateau, A. Kitous, G. J. Nabuurs,, M. J. Schelhaas, T. Groen, L. Riffeser, F. Reitze, E. Jochem, G. Catenazzi, M. Jakob, B. Aebischer, K. Kartsoni, W. Eichhammer, A. Held, M. Ragwitz, U. Reiter, S. Kypreos, and H. Turton (2007) (2008), “EU-Project ADAM: Adaption and Mitigation Strategies: Supporting European Climate Policy — Deliverable M1.2: Report of the Reference Case Scenario for Europe”, Fraunhofer ISI, Karlsruhe, November 2008.

    Google Scholar 

  • Jochem, P. (2009), “A CO2 Emission Trading Scheme for German Road Transport — Assessing the Impacts using a Meso Economic Model with Multi-Agent Attributes”, Nomos, Baden-Baden

    Book  Google Scholar 

  • Krail, M., and W. Schade (2010), “The Potential of Alternative Fuel Cars for Achieving CO2 Reduction Targets in EU27”.

  • krause, F. (1996), “The Costs of Mitigating Carbon Emissions: A Review of Methods and Findings from European Studies”, Energy Policy Vol 24, no 10, p. 899–915.

    Article  Google Scholar 

  • Kumbaroglu, G., and R. Madlener (2001), “A Description of the Hybrid Bottom-Up CGE Model SCREEN with an Application to Swiss Climate Policy Analysis”, CEPE Working Paper No. 10, Zürich.

  • Linares, P., F. J. Santos, M. Ventosa, and L. Lapiedra (2008), “Incorporating Oligopoly, CO2 Emissions Trading and Green Certificates into a Power Generation Expansion Model”, Automatica, vol. 44, no. 6, pp. 1608–1620.

    Article  Google Scholar 

  • Löschel, A. (2002), “Technological Change in Economic Models of Environmental Policy: A Survey”, Ecological Economics, 43, pp. 105–126.

    Article  Google Scholar 

  • Loulou, R., G. Goldstein, and K. Noble (2004), “Documentation for the MARKAL Family of Models”, Energy Technology Systems Analysis Programme (ETSAP), website:

  • Manne, A, and R. G. Richels (1990), “CO2 Emission Limits: An Economic Cost Analysis for the USA”, The Energy Journal Vol. 11(2), pp. 51–74

    Article  Google Scholar 

  • Manne, A., and R. G. Richels (2004), “MERGE: A Model for Evaluating the Regional and Global Effects of GHG Reduction Policies”, website:

  • Mayer, H. (2007), “Calculation and Analysis of a Hybrid Energy Input-Output Table for Germany within the Environmental-Economic Accounting (EEA)”, Paper presented at the 16th International Input-Output Conference 2–6 July 2007 Istanbul/Turkey, Statistisches Bundesamt, Wiesbaden.

  • Messner, S., and M. Strubegger (1995), “User’s Guide for MESSAGE III”, WP-95-69. International Institute for Applied Systems Analysis, Laxenburg, Austria.

    Google Scholar 

  • Möst, D., and M. Genoese (2009), “Market Power in the German Wholesale Electricity Market”, The Journal of Energy Markets, 2 (2), pp. 47–74.

    Article  Google Scholar 

  • Mundaca, L., and L. Neij (2009), “A Multi-Criteria Evaluation Framework for ‘Tradable White Certificate’ Schemes”, Energy Policy, 37(11), pp. 4557–4573.

    Article  Google Scholar 

  • Nathani, C., M. Wickart, R. Oleschak, and R. van Nieuwkoop (2006), “Estimation of a Swiss Input-Output Table for 2001”, CEPE Report No. 6, Centre for Energy Policy and Economics (CEPE), Zürich.

  • Nathani, C. (2006), “Material Use and Induced Energy Demand: an Input-Output Analysis,”, ETH Zürich, Paper to be presented at the Intermediate International Input-Output Meeting on Sustainability, Trade and Productivity, Japan.

    Google Scholar 

  • Prognos AG (2011), „Das Energiewirtschaftliche Gesamtkonzept. Konzept eines beschleunigten Ausstiegs aus der Kernenergie in Deutschland“, im Auftrag der Vereinigung der Bayerischen Wirtschaft e. V.

  • Russ, P., and P. Criqui (2007), “Post-Kyoto CO2 Emission Reduction: The Soft Landing Scenario Analysed with POLES and Other World Models”, IPTS and Grenoble University.

  • Schade, W. (2004), “Strategic Sustainability Analysis: Concept and Application for the Assessment of European Transport Policy”, Dissertation, NOMOS-Verlag, Baden-Baden.

    Google Scholar 

  • Schade, W., and M. Krail (2006), Modeling and Calibration of Large Scale System Dynamics Models: The Case of the ASTRA Model.

  • Schade, W., E. Jochem, T. Barker, G. Catenazzi, W. Eichhammer, T. Fleiter, A. Held, N. Helfrich, M. Jakob, P. Criqui, S. Mima, L. Quandt, A. Peters, M. Ragwitz, U. Reiter, F. Reitze, M. Schelhaas, S. Scrieciu, and H. Turton (2009), “ADAM — 2 degree scenario for Europe — policies and impacts. Deliverable M1.3 of ADAM (Adaptation and Mitigation Strategies: Supporting European Climate Policy)”, Project funded by the European Commission 6th RDT Programme. Karlsruhe, Germany.

    Google Scholar 

  • Seebregts, A. J., G. A. Goldstein, and K. E. Smekens (2002), “Energy/environmental modeling with the MARKAL family of models”, in Operations Research Proceedings 2001, Chamoni, R., Leisten, A., Martin, J., Minneman, Stadtler, H., eds., pp. 75–82, Duisburg, Germany.

    Chapter  Google Scholar 

  • Sensfuss, F. (2008), “Assessment of the Impact of Renewable Electricity Generation on the German Electricity Sector — An Agent-Based Simulation Approach”, Doctoral Thesis, University of Karlsruhe.

  • Sensfuss, F., M. Ragwitz, and M. Genoese (2008), “The Merit-Order Effect: A Detailed Analysis of the Price Effect of Renewable Electricity Generation on Spot Market Prices in Germany”, Energy Policy, 36 (8), pp. 3086–3094.

    Article  Google Scholar 

  • Tinter, G. (1953), “The Definition of Econometrics”, Econometrica, 21(1), pp. 31–40.

    Article  Google Scholar 

  • UNEP (2011), “Recycling Rates of Metals — A Status Report”, 2nd Report of the Global Metal Flows working group of the International Panel of Sustainable Resource Management of UNEP.

  • United Nations (1999), “Handbook of Input-Output Table Compilation and Analysis”, Studies in Methods, Series F No. 74, UN, New York.

  • Ventosa, M., A. Baíllo, A. Ramos, and M. Rivier (2005), “Electricity Market Modeling Trends”, Energy Policy, 33(7), pp. 897–913.

    Article  Google Scholar 

  • Weidlich, A., and D. Veit (2008), “A Critical Survey of Agent-Based Wholesale Electricity Market Models”, Energy Economics, 30(4), pp. 1728–1759.

    Article  Google Scholar 

  • Wittmann, T. (2008), “Agent-Based Models of Energy Investment Decisions”, Doctoral Thesis, Technical University of Berlin, Physica-Verlag Heidelberg.

  • Wooldridge, M., and N. R. Jennings (1995), “Intelligent Agents: Theory and Practice”, Knowledge Engineering Review, 10 (2), pp. 115–152.

    Article  Google Scholar 

  • Wooldridge, J. M. (2002), Econometric Analysis of Cross Section and Panel Data, Massachusetts Institute of Technology, The MIT Press, Cambridge, London.

    Google Scholar 

  • Wooldridge, M. (2009), An Introduction to MultiAgent Systems, John Wiley & Sons, Chichester.

    Google Scholar 

  • Worrel, E., S. Ramesohl, and G. Boyd, (2004), “Advances in Energy Forecasting Models Based on Engineering Economics”, Annu. Rev. Environ. Resour., 29, 345–81.

    Article  Google Scholar 

  • WWF (2009), „Modell Deutschland. Klimaschutz bis 2050: Vom Ziel her denken“, WWF Deutschland, Prognos AG, Öko-Institut e.V., Basel/Freiburg/ Berlin.

  • Yao, J., S. S. Oren, and B. F. Hobbs (2010), “Hybrid Bertrand-Cournot Models of Electricity Markets with Multiple Strategic Subnetworks and Common Knowledge Constraints”, in Restructured Electric Power Systems, X.-P. Zhang, eds., John Wiley & Sons, Inc., Hoboken, NJ, USA.

    Google Scholar 

Download references


Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Herbst, A., Toro, F., Reitze, F. et al. Introduction to Energy Systems Modelling. Swiss J Economics Statistics 148, 111–135 (2012).

Download citation

  • Published:

  • Issue Date:

  • DOI: