Supply Chain Mixed Integer Linear Program Model Integrating a Biorefining Technology Superstructure

Panteli, Anna; Giarola, Sara; Shah, Nilay

doi:10.1021/acs.iecr.7b05228

Cited by 11 publications

(4 citation statements)

References 32 publications

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“…An alternative is the use of renewable, bio-based resources as raw materials for both chemicals and transportation fuels. This possibility has been widely studied, − often in the context of an integrated “biorefinery”. As a practical matter, the structure of the industry and the resources it uses will evolve based on many factors, including economics, sustainability and life cycle analysis, and government policies.…”

Section: Discussionmentioning

confidence: 99%

Probing the Impact of an Energy and Transportation Paradigm Shift on the Petrochemicals Industry

Giannikopoulos

Skouteris

Edgar

et al. 2022

Ind. Eng. Chem. Res.

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A paradigm shift in energy and transportation, away from fossil fuels and toward renewables, has begun. Driven by climate and sustainability considerations, consumer preferences and corporate aspirations favoring electric vehicles, powered by electricity generated renewably, are accelerating. As a result, the long-term future outlook for fossil-based fuels and the petroleum refining industry is subject to significant uncertainty. Since the production of petrochemicals is closely connected to petroleum refining, it is also likely to be impacted by this paradigm shift. In this paper, these potential impacts are probed using an optimization-based, network superstructure model of the U.S. petrochemicals industry. The model is used to investigate the response of the industry under extreme-case scenarios involving complete loss of demand for liquid transportation fuels and/or complete loss of crude oil supply and petroleum refining capacity. The model is also used to perform an assessment of new, natural-gas-based technologies that might be implemented in the context of a residual, limited-demand market for liquid transportation fuels. The production of green hydrogen for use in this context is also considered.

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Section: Discussionmentioning

confidence: 99%

Probing the Impact of an Energy and Transportation Paradigm Shift on the Petrochemicals Industry

Giannikopoulos

Skouteris

Edgar

et al. 2022

Ind. Eng. Chem. Res.

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“…A number of research papers reviewed, deal with the question of how biomass supply chains can be organized in a cost-efficient manner to collect, process, and transfer available biomass to a specific biorefinery plant [23][24][25][26]. As stated by Iakovou et al [27], one of the most crucial bottlenecks in increased biomass utilization is the costs of logistics operations.…”

Section: Improving Efficiency In Biomass Supply Chainsmentioning

confidence: 99%

Optimizing Resource Utilization in Biomass Supply Chains by Creating Integrated Biomass Logistics Centers

Guo¹,

Voogt²,

Annevelink³

et al. 2020

Energies

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Bio-based supply chains are by nature complex to optimize. The new logistic concept of integrated biomass logistical center (IBLC) provides us the opportunity to make full use of the idle capacity for a food/feed plant to produce biobased products so that the entire chain efficiency can be improved. Although research has been conducted to analyze the IBLC concept, is yet to be an optimization model that can optimally arrange the activities in the supply chain where an IBLC stands in the middle. To fill the knowledge gap in the literature, this paper makes the first step to develop a MILP model that enables biobased supply chain optimization with the IBLC concept, which supports logistic and processing decisions in the chain. The model is applied in a case study for a feed and fodder plant in Spain where managerial insights have been derived for transferring the plant to a profitable IBLC.

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“…Several research papers have investigated how biomass supply chains can be organized in a cost-efficient manner to collect, process, and transfer available biomass to a specific biorefinery plant [28][29][30][31]. One of the main methods used is mathematical programming (or optimization theory), including linear programming (LP), nonlinear programming (NLP), mixed integer linear programming (MILP), and mixed integer nonlinear programming (MINLP) models [32][33][34][35][36][37][38][39][40][41].…”

Section: Introductionmentioning

confidence: 99%

Integrated Land Suitability Assessment for Depots Siting in a Sustainable Biomass Supply Chain

Toba

Paudel

Lin

et al. 2023

Sensors

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A sustainable biomass supply chain would require not only an effective and fluid transportation system with a reduced carbon footprint and costs, but also good soil characteristics ensuring durable biomass feedstock presence. Unlike existing approaches that fail to account for ecological factors, this work integrates ecological as well as economic factors for developing sustainable supply chain development. For feedstock to be sustainably supplied, it necessitates adequate environmental conditions, which need to be captured in supply chain analysis. Using geospatial data and heuristics, we present an integrated framework that models biomass production suitability, capturing the economic aspect via transportation network analysis and the environmental aspect via ecological indicators. Production suitability is estimated using scores, considering both ecological factors and road transportation networks. These factors include land cover/crop rotation, slope, soil properties (productivity, soil texture, and erodibility factor) and water availability. This scoring determines the spatial distribution of depots with priority to fields scoring the highest. Two methods for depot selection are presented using graph theory and a clustering algorithm to benefit from contextualized insights from both and potentially gain a more comprehensive understanding of biomass supply chain designs. Graph theory, via the clustering coefficient, helps determine dense areas in the network and indicate the most appropriate location for a depot. Clustering algorithm, via K-means, helps form clusters and determine the depot location at the center of these clusters. An application of this innovative concept is performed on a case study in the US South Atlantic, in the Piedmont region, determining distance traveled and depot locations, with implications on supply chain design. The findings from this study show that a more decentralized depot-based supply chain design with 3depots, obtained using the graph theory method, can be more economical and environmentally friendly compared to a design obtained from the clustering algorithm method with 2 depots. In the former, the distance from fields to depots totals 801,031,476 miles, while in the latter, it adds up to 1,037,606,072 miles, which represents about 30% more distance covered for feedstock transportation.

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Supply Chain Mixed Integer Linear Program Model Integrating a Biorefining Technology Superstructure

Cited by 11 publications

References 32 publications

Probing the Impact of an Energy and Transportation Paradigm Shift on the Petrochemicals Industry

Probing the Impact of an Energy and Transportation Paradigm Shift on the Petrochemicals Industry

Optimizing Resource Utilization in Biomass Supply Chains by Creating Integrated Biomass Logistics Centers

Integrated Land Suitability Assessment for Depots Siting in a Sustainable Biomass Supply Chain

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