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Assessing effects of exogenous assumptions in GHG emissions forecasts – a 2020 scenario study for Portugal using the Times energy technology model

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  • Simoes, Sofia
  • Fortes, Patrícia
  • Seixas, Júlia
  • Huppes, Gjalt

Abstract

Energy-economy-environment models are fundamental in developing realistic cost-effective climate policy. However, such models by necessity are simplified based on assumptions which co-determine the outcomes of scenario modelling. Major assumptions relate to demographic and economic development, technology evolution and deployment and policy decisions. The core of this analysis is to quantify how specific assumptions influence the outcomes of scenarios; not taking them together as usually in the literature but instead looking into them apiece. The TIMES modelling framework is broadly used for climate policy support and here we used the Portuguese version as an example. As the structure of TIMES modelling is similar in other countries and also for larger aggregates as the EU and the World, the method can be applied there quite directly, although outcomes will differ between countries due to differences in energy technologies and energy markets. The outcomes for the Portugal Baseline scenario using TIMES_PT show the relevance of this exercise in this sensitivity analysis on assumptions. Contrary to what might be expected, varying assumptions on the availability and price of energy resources lead to minor variations on GHG emissions in the modelling outcomes, less than 2% of the Baseline scenario emissions in 2020. The more relevant assumptions to overall uncertainty are related to socio-economic development, followed by assumptions on technology deployment. This detailed uncertainty analysis on assumptions helps to assess the robustness of modelling outcomes in the TIMES model framework, next to other aspects like model structure and validity.

Suggested Citation

  • Simoes, Sofia & Fortes, Patrícia & Seixas, Júlia & Huppes, Gjalt, 2015. "Assessing effects of exogenous assumptions in GHG emissions forecasts – a 2020 scenario study for Portugal using the Times energy technology model," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 221-235.
    • Handle: RePEc:eee:tefoso:v:94:y:2015:i:c:p:221-235
    DOI: 10.1016/j.techfore.2014.09.016
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    2. Liu, Xi & Du, Huibin & Brown, Marilyn A. & Zuo, Jian & Zhang, Ning & Rong, Qian & Mao, Guozhu, 2018. "Low-carbon technology diffusion in the decarbonization of the power sector: Policy implications," Energy Policy, Elsevier, vol. 116(C), pages 344-356.
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