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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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Author Info
Johannes Schmidt () (Doctoral School Sustainable Development (dokNE), University of Natural Resources and Applied Life Sciences, Vienna)
Sylvain Leduc (International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria)
Erik Dotzauer (Mälardalen University, Box 883, SE-72123 Västerås, Sweden)
Georg Kindermann (International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria)
Erwin Schmid () (Institute for Sustainable Economic Development, Department of Economics and Social Sciences, University of Natural Resources and Applied Life Sciences, Vienna)
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.

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Publisher Info
Paper provided by Institute for Sustainable Economic Development, Department of Economics and Social Sciences, University of Natural Resources and Applied Life Sciences, Vienna in its series Working Papers with number 432009.

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Length: 22 pages
Date of creation: Jun 2009
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Handle: RePEc:sed:wpaper:432009

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Related research
Keywords: Combined Heat and Power; District Heating; Bioenergy; Biomass; Mixed Integer Programming; Monte-Carlo Simulation;

Find related papers by JEL classification:
C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis
C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques

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  1. Streicher, Gerhard & Schmid, Erwin & Salhofer, Klaus, 2006. "Testing for the Efficiency of a Policy Intended to Meet Objectives: General Model and Application," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 31(02), August. [Downloadable!]
  2. Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June. [Downloadable!] (restricted)
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This page was last updated on 2009-12-10.


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