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Modeling hourly electricity dynamics for policy making in long-term scenarios

  • Pina, André
  • Silva, Carlos
  • Ferrão, Paulo
Registered author(s):

    Energy policies are often related to the global effort in reducing greenhouse gas emissions through increased use of renewable energies in electricity production. The impact of these policies is usually calculated by energy planning tools. However, the modeling methodologies most currently used are not adequate to simulate long-term scenarios while considering the hourly dynamics of supply and demand. This paper presents an extension of the TIMES energy planning tool for investment decisions in electricity production that considers seasonal, daily and hourly supply and demand dynamics. The inclusion of these dynamics enables the model to produce more accurate results in what concerns the impact of introducing energy efficiency policies and the increased use of renewable energies. The model was validated in São Miguel (Azores, Portugal) for the years 2006-2009, where a comparison with real data showed that the model can simulate the supply and demand dynamics. Further, the long-term analysis shows that the inclusion of these dynamics contributes to a better assessment of the renewable energy potential, suggests the postponement of investments in new generation capacity, and demonstrates that using fine time resolution modeling is very valuable for the design of effective policy measures under high renewable penetration energy systems.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0301421511005180
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    Article provided by Elsevier in its journal Energy Policy.

    Volume (Year): 39 (2011)
    Issue (Month): 9 (September)
    Pages: 4692-4702

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    Handle: RePEc:eee:enepol:v:39:y:2011:i:9:p:4692-4702
    Contact details of provider: Web page: http://www.elsevier.com/locate/enpol

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    1. Rout, Ullash K. & Fahl, Ulrich & Remme, Uwe & Blesl, Markus & Voß, Alfred, 2009. "Endogenous implementation of technology gap in energy optimization models--a systematic analysis within TIMES G5 model," Energy Policy, Elsevier, vol. 37(7), pages 2814-2830, July.
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    4. Richard Loulou, 2008. "ETSAP-TIAM: the TIMES integrated assessment model. part II: mathematical formulation," Computational Management Science, Springer, vol. 5(1), pages 41-66, February.
    5. Simões, Sofia & Cleto, João & Fortes, Patri­cia & Seixas, Júlia & Huppes, Gjalt, 2008. "Cost of energy and environmental policy in Portuguese CO2 abatement--scenario analysis to 2020," Energy Policy, Elsevier, vol. 36(9), pages 3598-3611, September.
    6. Connolly, D. & Lund, H. & Mathiesen, B.V. & Leahy, M., 2010. "A review of computer tools for analysing the integration of renewable energy into various energy systems," Applied Energy, Elsevier, vol. 87(4), pages 1059-1082, April.
    7. Lund, H. & Mathiesen, B.V., 2009. "Energy system analysis of 100% renewable energy systems—The case of Denmark in years 2030 and 2050," Energy, Elsevier, vol. 34(5), pages 524-531.
    8. Ang, B.W. & Ng, T.T., 1992. "The use of growth curves in energy studies," Energy, Elsevier, vol. 17(1), pages 25-36.
    9. Blesl, Markus & Das, Anjana & Fahl, Ulrich & Remme, Uwe, 2007. "Role of energy efficiency standards in reducing CO2 emissions in Germany: An assessment with TIMES," Energy Policy, Elsevier, vol. 35(2), pages 772-785, February.
    10. Richard Loulou & Maryse Labriet, 2008. "ETSAP-TIAM: the TIMES integrated assessment model Part I: Model structure," Computational Management Science, Springer, vol. 5(1), pages 7-40, February.
    11. Vaillancourt, Kathleen & Labriet, Maryse & Loulou, Richard & Waaub, Jean-Philippe, 2008. "The role of nuclear energy in long-term climate scenarios: An analysis with the World-TIMES model," Energy Policy, Elsevier, vol. 36(7), pages 2296-2307, July.
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