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Short-term uncertainty in long-term energy system models — A case study of wind power in Denmark

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  • Seljom, Pernille
  • Tomasgard, Asgeir

Abstract

When wind power constitutes a larger share of the electricity production mix, credible and reliable modelling of its operation in long-term investment models becomes increasingly important. In this paper the intermittent characteristics of wind power are modelled as a stochastic parameter in a long-term TIMES model of the Danish heat and electricity sector. To our knowledge, this is not a common approach in long-term investment models, and has not been done previously in TIMES, where the short-term uncertainty of wind power is normally taken into account by a deterministic constraint that ensures excess back-up capacity. In our model, the stochasticity gives lower total energy system costs, significant lower investments in wind power, less expected electricity export and higher expected biomass consumption compared to using the traditional deterministic approach. Also, the deterministic investment strategy can be insufficient in periods with poor wind conditions. Based on our findings, we recommend using a stochastic representation of intermittent renewables in long-term investment models to provide more solid results for decision makers.

Suggested Citation

  • Seljom, Pernille & Tomasgard, Asgeir, 2015. "Short-term uncertainty in long-term energy system models — A case study of wind power in Denmark," Energy Economics, Elsevier, vol. 49(C), pages 157-167.
    • Handle: RePEc:eee:eneeco:v:49:y:2015:i:c:p:157-167
    DOI: 10.1016/j.eneco.2015.02.004
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    More about this item

    Keywords

    Energy system; TIMES model; Wind power; Stochastic optimization; Short-term uncertainty;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • Q21 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Demand and Supply; Prices
    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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