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Methodology for improving the reliability of biomass energy potential estimation

  • This paper presents a novel approach to address uncertainty and improve reliability of the estimation of the biomass energy potential at a country level, particularly suitable for situations when quality and availability of data are limited. The proposed methodology improves the prediction reliability by following four steps: 1) using a simple accounting framework, 2) using a robust selection of probability density functions, 3) using a probabilistic propagation of uncertainty and 4) using sensitivity analysis to identify key variables contributing to uncertainty as well as a root cause analysis and a set of sub-models to improve estimation of key variables. The application of the methodology to the energy scenario in Colombia shows that the improved estimation of the theoretical energy potential has an almost identical mean value compared to the preliminary estimate, but the uncertainty is significantly lower (less than 50%). Moreover, the mean value of the technical energy potential obtained through the methodology is 25% lowerThis paper presents a novel approach to address uncertainty and improve reliability of the estimation of the biomass energy potential at a country level, particularly suitable for situations when quality and availability of data are limited. The proposed methodology improves the prediction reliability by following four steps: 1) using a simple accounting framework, 2) using a robust selection of probability density functions, 3) using a probabilistic propagation of uncertainty and 4) using sensitivity analysis to identify key variables contributing to uncertainty as well as a root cause analysis and a set of sub-models to improve estimation of key variables. The application of the methodology to the energy scenario in Colombia shows that the improved estimation of the theoretical energy potential has an almost identical mean value compared to the preliminary estimate, but the uncertainty is significantly lower (less than 50%). Moreover, the mean value of the technical energy potential obtained through the methodology is 25% lower than the preliminary potential and the uncertainty reduces by one third.show moreshow less

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Metadaten
Author:Miguel Angel Gonzalez-Salazar, Mauro Venturini, Witold-Roger Poganietz, Matthias FinkenrathORCiDGND, Pier Ruggero Spina
DOI:https://doi.org/10.1016/j.biombioe.2016.03.026
Identifier:0961-9534 OPAC HS OPAC extern
Parent Title (English):Biomass and Bioenergy
Publisher:Elsevier
Document Type:Article
Language:English
Year of first Publication:2016
Tag:Biomass
Volume:2016
Issue:Volume 88
Number of pages:16 Seiten
First Page:43
Last Page:58
Institutes:Fakultät Maschinenbau
IEAT - Institut für Energie- und Antriebstechnik
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften
Research focus:FSP1: Energie
Publication Lists:Finkenrath, Matthias
Publication reviewed:begutachtet
Release Date:2021/06/17
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