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Using Monte Carlo Simulation to Account for Uncertainties in the Spatial Explicit Modeling of Biomass Fired Combined Heat and Power Potentials in Austria

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  • Schmidt, Johannes
  • Leduc, Sylvain
  • Dotzauer, Erik
  • Kindermann, Georg
  • Schmid, Erwin

Abstract

Austria aims at increasing its share of renewable energy production by 11% until 2020. Combined Heat and Power (CHP) plants fired by forest wood can significantly contribute to attaining this target. However, the spatial distribution of biomass supply and of heat demand limits the potentials of CHP production. This paper assesses CHP potentials using a mixed integer programming model that optimizes locations of bioenergy plants. Investment costs of district heating infrastructure are modeled as a function of heat demand densities, which can differ substantially. Gasification of biomass in a combined cycle process is assumed as production technology. Some model parameters have a broad range according to a literature review. Monte-Carlo simulations have therefore been performed to account for model parameter uncertainty in our analysis. Optimal locations of plants are clustered around big cities in the East of Austria. At current power prices, biomass based CHP production allows producing around 3% of Austria's total current energy demand. Yet, the heat utilization decreases when CHP production increases due to limited heat demand that is suitable for district heating.

Suggested Citation

  • Schmidt, Johannes & Leduc, Sylvain & Dotzauer, Erik & Kindermann, Georg & Schmid, Erwin, 2009. "Using Monte Carlo Simulation to Account for Uncertainties in the Spatial Explicit Modeling of Biomass Fired Combined Heat and Power Potentials in Austria," Discussion Papers DP-43-2009, University of Natural Resources and Life Sciences, Vienna, Department of Economics and Social Sciences, Institute for Sustainable Economic Development.
    • Handle: RePEc:zbw:inwedp:dp432009
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    Cited by:

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    2. Awudu, Iddrisu & Zhang, Jun, 2012. "Uncertainties and sustainability concepts in biofuel supply chain management: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1359-1368.

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    More about this item

    Keywords

    Combined Heat and Power; District Heating; Bioenergy; Biomass; Mixed Integer Programming; Monte-Carlo Simulation;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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