Deployment and Relocation of Semi-mobile Facilities in a Thermal Power Plant Supply Chain

Tobias Zimmer (), Patrick Breun and Frank Schultmann
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Tobias Zimmer: Karlsruhe Institute of Technology (KIT), Institute for Industrial Production
Patrick Breun: Karlsruhe Institute of Technology (KIT), Institute for Industrial Production
Frank Schultmann: Karlsruhe Institute of Technology (KIT), Institute for Industrial Production

A chapter in Operations Research Proceedings 2016, 2018, pp 185-190 from Springer

Abstract: Abstract Co-firing of biomass in coal-fired power plants is considered one of the most economic ways of carbon dioxide abatement. We investigate the deployment and relocation of several semi-mobile processing facilities in order to supply a large coal-fired power plant with high-quality renewable energy carriers. Semi-mobile facilities are characterized by a containerized design and can be relocated in case of changes in supply and demand. The energy carriers which are produced by different types of semi-mobile technologies are bulky goods with high density and properties comparable to those of coal and fuel oil. Thus, intermodal transportation is required to achieve transportation costs which are competitive with the delivered cost of fossil fuels at the plant’s gate. The optimization of the investigated supply chain therefore requires simultaneous planning of semi-mobile facility deployment and intermodal transportation. To this end, we present a mixed-integer linear problem which optimizes the number of semi-mobile facilities, their respective relocation over time and the intermodal transportation of produced energy carriers to the power plant. In the presented case, train transportation is characterized by a low geographical coverage of the railway network and restrictions representing minimum shipping volumes per railway line. The model minimizes the objective function of total supply chain costs including electricity generation, transportation, the operation and relocation of the semi-mobile plants and the necessary forestry operations associated with the deployed facilities. The model is implemented in GAMS and solved using the CPLEX solver. We discuss a numerical example based on data from the forestry and energy sector in Chile.

Date: 2018
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DOI: 10.1007/978-3-319-55702-1_26

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