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Evaluation of delivery strategies for forest fuels applying a model for Weather-driven Analysis of Forest Fuel Systems (WAFFS)

Publikation: Bidrag till tidskriftArtikel i vetenskaplig tidskriftPeer review

Sammanfattning

Earlier studies have highlighted the importance of quality and quantity in forest fuel supply chains, since these parameters affect product value and handling properties, but both are constantly changing over time. Great monetary losses can be incurred if forest fuel material has to be delivered to end-users in non-optimal condition, e.g. to meet seasonal fuel demand with its large short-term variations. Thus earlier studies have also highlighted the importance of more information on the forest fuel supply chain. This paper describes development of a model for Weather-driven Analysis of Forest Fuel Systems (WAFFS) that can be used when analysing forest fuel supply chains and that accounts for both active machine activities and passive activities such as quality changes during storage. The aim was to develop a methodology that can be used to evaluate forest fuel supply chain scenarios and analyse various delivery strategies under different conditions. Application of WAFFS to evaluate delivery strategies for forest fuels showed that system improvements were possible when the right biomass was delivered at the right time. The WAFFS model gives an overview of biomass actually stored at different geographical locations and places (heaps or windrows) in terms of both quality and quantity. Delivery strategies actively prioritising biomass storage proved capable of delivering more energy when most needed, thereby improving yearly machine utilisation for contractors in the supply chain. (C) 2016 Elsevier Ltd. All rights reserved.
OriginalspråkEngelska
Sidor (från-till)420-430
Antal sidor11
TidskriftApplied Energy
Volym188
DOI
StatusPublicerad - 2017

FN:s SDG:er

Detta resultat bidrar till följande hållbara utvecklingsmål:

  1. SDG 7 – Hållbar energi för alla
    SDG 7 – Hållbar energi för alla

Nyckelord

  • Bioenergy
  • Forest fuel
  • Supply chain
  • Storage
  • Fuel quality
  • Discrete-event simulation

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