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Published VersionCC BY V4.0, Open Access
Journal article
A Two-Stage DSS to Evaluate Optimal Locations for Bioenergy Facilities
Forests, Vol.11(9), pp.1-22
2020
Abstract
Research Highlights: A set of 128 potential bioenergy facility locations is established and evaluated based on the transport cost to select optimal locations. Background and Objectives: The identification of optimal facility locations to process recovered forest biomass is an important decision in designing a bioenergy supply chain at the strategic planning level. The result of this analysis can affect supply chain costs and the overall efficiency of the network, due to the low density and dispersed nature of forest biomass and the high costs associated with its logistics operations. In this study, we develop a two-stage decision support system to identify the optimal site locations for forest biomass conversion based on biomass availability, transport distance and cost. Materials and Methods: In the first stage, a GIS-based analysis is designed to identify strategic locations of potential bioenergy sites. The second stage evaluates the most cost-effective locations individually using a transportation cost model, based on the results from stage one. The sensitivity of inputs, such as maximum allowable transport cost, the distance of transport and their relations to the profit balance, and changes in fuel price are tested. The method is applied to a real case study in the state of Queensland, Australia. Results and Conclusions: The GIS analysis resulted in 128 strategic candidate locations being suggested for bioenergy conversion sites. The logistics analysis estimated the optimal cost and transportation distance of each one of the locations and ranked them according to the overall performance between capacities of 5 and 100 MW.
Details
- Title
- A Two-Stage DSS to Evaluate Optimal Locations for Bioenergy Facilities
- Authors
- Sam Van Holsbeeck (Author) - University of the Sunshine Coast, Queensland, Forest Research InstituteSättar Ezzati (Author) - Université LavalDominik Röser (Author) - University of British ColumbiaMark Brown (Author) - University of the Sunshine Coast, Queensland, Forest Industries Research Centre
- Publication details
- Forests, Vol.11(9), pp.1-22
- Publisher
- MDPI AG
- Date published
- 2020
- DOI
- 10.3390/f11090968
- ISSN
- 1999-4907
- Copyright note
- © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
- Organisation Unit
- University of the Sunshine Coast, Queensland; USC Business School - Legacy; Forest Industries Research Centre; Forest Research Institute
- Language
- English
- Record Identifier
- 99482300502621
- Output Type
- Journal article
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