MODELLING RESSOURCES

The ETSAP-TIAM model

The ETSAP-TIAM (TIMES Integrated Assessment Model) is the official global model of IEA-ETSAP, available to Contracting Parties. It is a technology-rich, bottom-up optimization model that minimizes total system costs while exploring long-term decarbonization pathways. TIAM spans 16 global regions, five end-use sectors (industry, transport, households, commercial, agriculture), and covers the period 2018–2100, with detailed seasonal and intraday time slices.

ETSAP is committed to the highest levels of openness, transparency, and good governance:

  • A GitHub structure and ReadTheDocs Wiki were launched to manage documentation, collaboration, and version control.
  • Discussions are ongoing on creating a legally compliant open-source version, with positive signals from the Executive Committee, pending resolution of copyright issues related to IEA energy balances. Stay tune for updates.

References:

Loulou R. Labriet M. (2008). ETSAP-TIAM: The TIMES integrated assessment model Part I: Model structure Computational Management Science 5(1–2): 7–40.
Loulou R. (2008). ETSAP-TIAM: The TIMES integrated assessment model. Part II: Mathematical formulation Computational Management Science 5(1–2): 41–66.

The official version of ETSAP-TIAM, or other TIAM versions developed by partner organisations, are widely applied in research and policy planning.

 

Examples include:

Andrade C. Desport L. Selosse S. (2024). Net-negative emission opportunities for the iron and steel industry on a global scale Applied Energy 358: 122566.

Babonneau F. et al. (2012). Energy Security: A Robust Optimization Approach to Design a Robust European Energy Supply via TIAM-WORLD Environmental Modeling and Assessment 17(1–2): 19–37.

Dalla Longa F. van der Zwaan B. (2017). Do Kenyas climate change mitigation ambitions necessitate large-scale renewable energy deployment and dedicated low-carbon energy policy? Renewable Energy 113: 1559–1568.

Føyn T. H. Y. et al. (2011). A global renewable energy system: A modelling exercise in ETSAP/TIAM Applied Energy 88(2): 526–534.

Gracceva F. Zeniewski P. (2014). A systemic approach to assessing energy security in a low-carbon EU energy system Applied Energy 123: 335–348.

Gracceva F. Zeniewski P. (2013). Exploring the uncertainty around potential shale gas development – A global energy system analysis based on TIAM (TIMES Integrated Assessment Model) Energy 57: 443–457.

Kang S. Selosse S. Maïzi N. (2018). Contribution of global GHG reduction pledges to bioenergy expansion Biomass and Bioenergy: 142–153.

Kober T. Van Der Zwaan B. C. C. Rösler H. (2014). Emission certificate trade and costs under regional burden-sharing regimes for a 2°c climate change control target Climate Change Economics 5(1): 1–32.

Kypreos S. Lehtilä A. (2015). Decomposing TIAM-MACRO to Assess Climatic Change Mitigation Environmental Modeling and Assessment 20(6): 571–581.

Labriet M. Kanudia A. Loulou R. (2012). Climate mitigation under an uncertain technology future: A TIAM-World analysis Energy Economics 34(SUPPL. 3): S366–S377.

Labriet M. Drouet L. Vielle M. Loulou R. Kanudia K. Haurie A. (2015). Assessment of the Effectiveness of Global Climate Policies Using Coupled Bottom-Up and Top-Down Models SSRN Electronic Journal.

Labriet M. et al. (2015). Worldwide impacts of climate change on energy for heating and cooling Mitigation and Adaptation Strategies for Global Change 20(7): 1111–1136.

Labriet M. Loulou R. Kanudia A. (2010). Modeling uncertainty in a large scale integrated energy-climate model International Series in Operations Research and Management Science 138: 51–77.

Lippkau F. Rupakula G. D. Blesl M. (2024). Emission free energy carriers and the impact of trade to achieve the 1.5 °C target: A global perspective of hydrogen and ammonia. In M. Labriet K. Espegren G. Giannakidis B. Ó Gallachóir (Eds.): Springer Nature, Aligning the Energy Transition with the Sustainable Development Goals: Key Insights from Energy System Modelling: 249–268.

Lippkau F. Franzmann D. Addanki T. Buchenberg P. Heinrichs H. KuhnP. Hamacher T. Blesl M. (2023). Global Hydrogen and Synfuel Exchanges in an Emission-Free Energy System, Energies 16, 3277.

Loulou R. Labriet M. Kanudia A. (2009). Deterministic and stochastic analysis of alternative climate targets under differentiated cooperation regimes. Energy Economics 31(SUPPL. 2): S131–S143.

Panos E. Glynn J. Kypreos S. Lehtilä A. Yue X. Ó Gallachóir B. Daniels D. Dai H. (2023). Deep decarbonisation pathways of the energy system in times of unprecedented uncertainty in the energy sector. Energy Policy 180: 113642.

Ricci O. Selosse S. (2013). Global and regional potential for bioelectricity with carbon capture and storage. Energy Policy 52: 689–698.

Selosse S. Ricci O. (2017). Carbon capture and storage: Lessons from a storage potential and localization analysis. Applied Energy 188: 32–44.

Selosse S. Ricci O. (2014). Achieving negative emissions with BECCS (bioenergy with carbon capture and storage) in the power sector: New insights from the TIAM-FR (TIMES Integrated Assessment Model France) model. Energy 76: 967–975.

Selosse S. Ricci O. Maïzi N. (2013). Fukushimas impact on the European power sector: The key role of CCS technologies. Energy Economics 39: 305–312.

Syri S. et al. (2008). Global energy and emissions scenarios for effective climate change mitigation-Deterministic and stochastic scenarios with the TIAM model, International Journal of Greenhouse Gas Control, 2(2): 274–285.

van der Zwaan B. Lamboo S. Dalla Longa F. (2021). Timmermans dream: An electricity and hydrogen partnership between Europe and North Africa. Energy Policy 159: 112613.

van der Zwaan B. Kober T. Dalla Longa F. van der Laan A. Kramer G.J. (2018). An integrated assessment of pathways for low-carbon development in Africa Energy Policy 117: 387–395.