Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics

Wood fuel quality attributes have to be considered by logistics planners if fuel procurement from forests and energy production at the plant are considered simultaneously. The single most important quality attribute is the moisture content (MC) of chips or raw material delivered to energy plants. It...

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Main Authors: Perttu Anttila, Lauri Sikanen, Robert Prinz, Antti Asikainen, Mauricio Acuna
Format: Article
Language:English
Published: University of Zagreb, Faculty of Forestry 2012-01-01
Series:Croatian Journal of Forest Engineering
Online Access:https://hrcak.srce.hr/file/172739
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spelling doaj-1ef28b221fa44475bc47d31ecf3fbf0c2020-11-25T00:52:55ZengUniversity of Zagreb, Faculty of ForestryCroatian Journal of Forest Engineering1845-57191848-96722012-01-01332225238116842Predicting and Controlling Moisture Content to Optimise Forest Biomass LogisticsPerttu Anttila0Lauri Sikanen1Robert Prinz2Antti Asikainen3Mauricio Acuna4Finnish Forest Research Institute P.O. Box 68 FI-80101, Joensuu FINLANDUniversity of Eastern Finland P.O. Box 111 FI-80101, Joensuu FINLANDFinnish Forest Research Institute P.O. Box 68 FI-80101, Joensuu FINLANDFinnish Forest Research Institute P.O. Box 68 FI-80101, Joensuu FINLANDAFORA – University of Sunshine Coast Private bag 12 Hobart, TAS AUSTRALIAWood fuel quality attributes have to be considered by logistics planners if fuel procurement from forests and energy production at the plant are considered simultaneously. The single most important quality attribute is the moisture content (MC) of chips or raw material delivered to energy plants. It affects heating value, storage properties, chipping and transport costs of the fuel. To assess the impact of forest biomass moisture content on supply chain costs, we devel­oped a linear programming-based tool for optimization decision support that minimizes sup­ply chain costs including harvesting, storage, chipping, and transportation of fuels. A CHP plant in Finland was used as the study case and three biomass raw materials (supply chains) were used for the analysis: whole trees from early thinnings, stemwood from early thinnings, and logging residues from final fellings. Our results indicate that both the proportion and volume of the biomass material delivered to the plant are very sensitive to specifications on MC range limits and the length of the storage (drying) period. Compared to a scenario with no storage, a reduction in volume harvested of up to 33% can be achieved to meet the monthly energy demand if proper drying methods, such as covering of biomass material, are imple­mented before chipping and delivering the biomass materials to the energy plant.https://hrcak.srce.hr/file/172739
collection DOAJ
language English
format Article
sources DOAJ
author Perttu Anttila
Lauri Sikanen
Robert Prinz
Antti Asikainen
Mauricio Acuna
spellingShingle Perttu Anttila
Lauri Sikanen
Robert Prinz
Antti Asikainen
Mauricio Acuna
Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics
Croatian Journal of Forest Engineering
author_facet Perttu Anttila
Lauri Sikanen
Robert Prinz
Antti Asikainen
Mauricio Acuna
author_sort Perttu Anttila
title Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics
title_short Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics
title_full Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics
title_fullStr Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics
title_full_unstemmed Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics
title_sort predicting and controlling moisture content to optimise forest biomass logistics
publisher University of Zagreb, Faculty of Forestry
series Croatian Journal of Forest Engineering
issn 1845-5719
1848-9672
publishDate 2012-01-01
description Wood fuel quality attributes have to be considered by logistics planners if fuel procurement from forests and energy production at the plant are considered simultaneously. The single most important quality attribute is the moisture content (MC) of chips or raw material delivered to energy plants. It affects heating value, storage properties, chipping and transport costs of the fuel. To assess the impact of forest biomass moisture content on supply chain costs, we devel­oped a linear programming-based tool for optimization decision support that minimizes sup­ply chain costs including harvesting, storage, chipping, and transportation of fuels. A CHP plant in Finland was used as the study case and three biomass raw materials (supply chains) were used for the analysis: whole trees from early thinnings, stemwood from early thinnings, and logging residues from final fellings. Our results indicate that both the proportion and volume of the biomass material delivered to the plant are very sensitive to specifications on MC range limits and the length of the storage (drying) period. Compared to a scenario with no storage, a reduction in volume harvested of up to 33% can be achieved to meet the monthly energy demand if proper drying methods, such as covering of biomass material, are imple­mented before chipping and delivering the biomass materials to the energy plant.
url https://hrcak.srce.hr/file/172739
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