Controlling moisture content and truck configurations to model and optimise biomass supply chain logistics in Ireland
|Title:||Controlling moisture content and truck configurations to model and optimise biomass supply chain logistics in Ireland||Authors:||Sosa, Amanda
|Permanent link:||http://hdl.handle.net/10197/6356||Date:||1-Jan-2015||Abstract:||In the coming years, Ireland will continue to face an increasing demand for wood biomass as a renewable source of energy. This will result in strained supply/demand scenarios, which will call for new planning and logistics systems capable of optimizing the efficient use of the biomass resources. In this study, a linear programming tool was developed which includes moisture content (MC) as a driving factor for the cost optimisation of two supply chains that use short wood and whole trees from thinnings as material feedstock. The tool was designed and implemented to analyse the impact of moisture content and truck configurations (5-axle and 6-axle trucks) on supply chain costs and spatial distribution of the supply materials. The results indicate that the inclusion of wood chips from whole trees reduces the costs of wood energy supply in comparison with only producing wood chips from short wood to satisfy the demand, with 9.8% and 10.2% cost reduction when transported with 5-axle and 6-axle trucks respectively. Constraining the MC of the wood chips delivered to the power plant increases both transport and overall supply chain costs, due, firstly to an increase in the haulage distance and secondly, to the number of counties providing the biomass material. In terms of truck configuration, the use of 6-axle trucks resulted in a 14.8% reduction in the number of truckloads and a 12.3% reduction in haulage costs in comparison to the use of 5-axle trucks across the MC scenarios analysed.||Funding Details:||Science Foundation Ireland||Type of material:||Journal Article||Publisher:||Elsevier||Copyright (published version):||2014 Elsevier||Keywords:||Biomass supply chain; Moisture content; Logistics planning; Truck configuration; Payload efficiency||DOI:||10.1016/j.apenergy.2014.10.018||Language:||en||Status of Item:||Peer reviewed|
|Appears in Collections:||Biosystems and Food Engineering Research Collection|
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