BLOMST—An Optimization Model for the Bioenergy Supply Chain
In this chapter, we present a new model for optimal strategic and tactical planning of the bioenergy supply chain under uncertainty. We discuss specific challenges, characteristics and issues related to this type of model. The technological details, variability in supply and demand, and uncertainty in virtually all aspects of the supply chain require advanced modeling techniques. Our model provides a broad modeling approach that addresses the entire supply chain using an integrated perspective. The broad applicability of the approach is illustrated by the two cases discussed at the end of the chapter. The first case presents a forest to bioenergy supply chain in a region of the Norwegian west coast. The second case presents the miscanthus supply chain to a transformation plant in Burgundy, France and takes into consideration uncertain final demand.
KeywordsSupply Chain Forest Owner Expected Profit Storage Node Storage Level
This work was partly funded under the EU seventh Framework Programme by the LogistEC project No. 550 311858: Logistics for Energy Crops’ Biomass. The views expressed in this work are the sole responsibility of the authors and do not necessary reflect the views of the European Commission. This work was partly funded by Regionalt forskningsfond Midt-Norge through the project ‘Fra skog til energi’ (ES 217558).
We are grateful to Philippe Béjot (Bourgogne Pellets Cooperative) who kindly provided details on the miscanthus case.
Maps and distance matrices were created using data from OpenStreetMap, © OpenStreetMap contributors.
- Cundiff JS, Dias N, Sherali HD (1997) A linear programming approach for designing a herbaceous biomass delivery system. Bioresour Technol 59(1):47–55Google Scholar
- ecoprog GmbH (2013) Biomass to energy 2013/2014—The world market for biomass power plants. Technical report. http://www.ecoprog.com/en/publications/energy-industry/biomass-to-energy.htm
- Ekşioğlu SD, Acharya A, Leightley LE, Arora S (2009) Analyzing the design and management of biomass-to-biorefinery supply chain. Comput Ind Eng 57(4):1342–1352Google Scholar
- Kanzian C, Holzleitner F, Stampfer K, Ashton S (2009) Regional energy wood logistics—optimizing local fuel supply. Silva Fennica 43(1):113–128. http://www.metla.fi/silvafennica/full/sf43/sf431113.pdf
- Mafakheri F, Nasiri F (2013) Modeling of biomass-to-energy supply chain operations: applications, challenges and research directions. Energy Policy 67:116–126Google Scholar
- Marufuzzaman M, Eksioglu SD, Huang YE (2014a) Two-stage stochastic programming supply chain model for biodiesel production via wastewater treatment. Comput Oper Res 49(0):1–17. ISSN:0305-0548. doi:http://dx.doi.org/10.1016/j.cor.2014.03.010. http://www.sciencedirect.com/science/article/pii/S0305054814000653 Google Scholar
- Marufuzzaman M, Li X, Eksioglu SD, Wang J (2014b) Designing a reliable intermodal hub and spoke system for biofuel supply chain network. In: Transportation research board 93rd annual meeting compendium of papersGoogle Scholar
- van Tilburg X, Egging R, Londo H (2006) Biotrans functional and technical description. ECN Policy Studies ECN-RX–06-013, Energy research Centre of the Netherlands. http://www.ecn.nl/publications/ECN-RX–06-013
- U.S. Energy Information Agency (2013) International energy outlook 2013. Technical Report DOE/EIA-0484(2013). http://www.eia.gov/forecasts/ieo/
- Walther G, Schatka A, Spengler TS (2012) Design of regional production networks for second generation synthetic bio-fuel–a case study in northern germany. Eur J Oper Res 218(1):280–292Google Scholar