Cost optimization of biofuel production – The impact of scale, integration, transport and supply chain configurationsShow others and affiliations
2017 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 195, p. 1055-1070Article in journal (Refereed) Published
Abstract [en]
This study uses a geographically-explicit cost optimization model to analyze the impact of and interrelation between four cost reduction strategies for biofuel production: economies of scale, intermodal transport, integration with existing industries, and distributed supply chain configurations (i.e. supply chains with an intermediate pre-treatment step to reduce biomass transport cost). The model assessed biofuel production levels ranging from 1 to 150 PJ a−1 in the context of the existing Swedish forest industry. Biofuel was produced from forestry biomass using hydrothermal liquefaction and hydroprocessing. Simultaneous implementation of all cost reduction strategies yielded minimum biofuel production costs of 18.1–18.2 € GJ−1 at biofuel production levels between 10 and 75 PJ a−1. Limiting the economies of scale was shown to cause the largest cost increase (+0–12%, increasing with biofuel production level), followed by disabling integration benefits (+1–10%, decreasing with biofuel production level) and allowing unimodal truck transport only (+0–6%, increasing with biofuel production level). Distributed supply chain configurations were introduced once biomass supply became increasingly dispersed, but did not provide a significant cost benefit (<1%). Disabling the benefits of integration favors large-scale centralized production, while intermodal transport networks positively affect the benefits of economies of scale. As biofuel production costs still exceeds the price of fossil transport fuels in Sweden after implementation of all cost reduction strategies, policy support and stimulation of further technological learning remains essential to achieve cost parity with fossil fuels for this feedstock/technology combination in this spatiotemporal context. © 2017 The Authors
Place, publisher, year, edition, pages
Elsevier Ltd , 2017. Vol. 195, p. 1055-1070
Keywords [en]
Biofuel, Cost optimization, Distributed supply chain, Economies of scale, Integration, Intermodal transport, Biofuels, Biomass, Cost benefit analysis, Costs, Economics, Forestry, Fossil fuels, Industrial economics, Intermodal transportation, Optimization, Supply chains, Truck transportation, Biofuel production, Biomass transports, Hydrothermal liquefactions, Supply chain configuration, Technological learning, Cost reduction
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-29395DOI: 10.1016/j.apenergy.2017.03.109Scopus ID: 2-s2.0-85016928741OAI: oai:DiVA.org:ri-29395DiVA, id: diva2:1093668
2017-05-082017-05-082023-05-23Bibliographically approved