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A Supply Chain Model for Optimizing Fixed and Mobile Bio-oil Refineries on a Regional Scale

A Supply Chain Model for Optimizing Fixed and Mobile Bio-oil Refineries on a Regional Scale
Author: Pantea Mirzaie
Publisher:
Total Pages: 103
Release: 2013
Genre: Biomass energy
ISBN:
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The use of fossil fuels and their related impact on the environment and global warming have encouraged societies to pursue more sustainable and renewable alternatives, e.g., forest-based bio-oil. Thus, a vital need to decrease the level of greenhouse gas emissions and the tendency of nations to reduce their dependency on imported oil have created a new mission for society: To increase the robustness of the environmental and economic aspects of woody biomass to bio-oil supply chains. Prior studies have focused on developing novel methods and approaches for improving single stages of biomass supply chains. Others have focused on ameliorating biomass supply chain performance from a systems perspective for a host of different biomass types, e.g., agricultural residues and forest residues, and logistics issues, e.g., transportation distance and storage. Bio-oil can be produced from woody biomass through the fast pyrolysis process, among different methods. Mobile processing has been developed in recent years to facilitate bio-oil production from woody waste and to reduce overall bio-oil supply chain cost, however, questions surrounding the environmental and economic benefits of using mobile processing plants in combination with large-scale non-mobile (fixed) processing plants remain unanswered. The research presented develops a mathematical model capable of assisting decision makers in determining the optimal combination and location of fixed and mobile bio-refinery plants for a known woody waste supply stream and set of harvesting areas. The major cost elements in the optimization model are transportation costs and capital costs. The model is applied to hypothetical case for northwest Oregon by using historical harvesting data for state-owned and private forests in the region. Distances between locations are obtained by using a geographical information system to elucidate roadway effects. The model is optimized for cost by using an integer linear programming solver. Supply chain environmental impacts are then assessed by considering the carbon footprint (CO2 equivalent mass) of transportation activities and the bio-refinery infrastructure. Sensitivity analysis is conducted for six major factors within the mathematical model to assess their effects on the estimated supply chain cost and carbon footprint, as well as on the number and location of the mobile and fixed bio-refineries. The application of the model indicates that the utility of a mobile processing plant aligned with a fixed processing plant is more obvious when transportation cost and distance increase. In addition, this study seems to confirm the premise that transferring bio-oil to a processing facility is often more preferable than transporting woody biomass. However, results indicate that the capital intensity (cost and environmental impact) of mobile processing plants can greatly degrade their relative utility within a mixed mode supply chain.

Biomass to Biofuel Supply Chain Design and Planning under Uncertainty

Biomass to Biofuel Supply Chain Design and Planning under Uncertainty
Author: Mir Saman Pishvaee
Publisher: Academic Press
Total Pages: 284
Release: 2020-11-25
Genre: Science
ISBN: 0128209003
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Biomass to Biofuel Supply Chain Design and Planning under Uncertainty: Concepts and Quantitative Methods explores the design and optimization of biomass-to-biofuel supply chains for commercial-scale implementation of biofuel projects by considering the problems and challenges encountered in real supply chains. By offering a fresh approach and discussing a wide range of quantitative methods, the book enables researchers and practitioners to develop hybrid methods that integrate the advantages and features of two or more methods in one decision-making framework for the efficient optimization of biofuel supply chains, especially for complex supply chain models. Combining supply chain management and modeling techniques in a single volume, the book is beneficial for graduate students who no longer need to consult subject-specific books alongside mathematical modeling textbooks. The book consists of two main parts. The first part describes the key components of biofuel supply chains, including biomass production, harvesting, collection, storage, preprocessing, conversion, transportation, and distribution. It also provides a comprehensive review of the concepts, problems, and opportunities associated with biofuel supply chains, such as types and properties of the feedstocks and fuel products, decision-making levels, sustainability concepts, uncertainty analysis and risk management, as well as integration of biomass supply chain with other supply chains. The second part focuses on modeling and optimization of biomass-to-biofuel supply chains under uncertainty, using different quantitative methods to determine optimal design. Proposes a general multi-level framework for the optimal design and operation of biomass-to-biofuel supply chains through quantitative analysis and modeling, including different biomass and waste biomass feedstock, production pathways, technology options, transportation modes, and final products Explores how modeling and optimization tools can be utilized to address sustainability issues in biofuel supply chains by simultaneously assessing and identifying sustainable solutions Presents several case studies with different regional constraints to evaluate the practical applicability of different optimization methods and compares their performance in real-world situations Includes General Algebraic Modeling System (GAMS) codes for solving biomass supply chain optimization problems discussed in different chapters

Modeling and Optimization of Biomass Supply Chains

Modeling and Optimization of Biomass Supply Chains
Author: Calliope Panoutsou
Publisher: Academic Press
Total Pages: 294
Release: 2017-08-11
Genre: Technology & Engineering
ISBN: 0128123044
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Modeling and Optimization of Biomass Supply Chains: Top Down and Bottom Up Assessment for Agricultural, Forest and Waste Feedstock provides scientific evidence for assessing biomass supply and logistics, placing emphasis on methods, modeling capacities, large data collection, processing and storage. The information presented builds on recent relevant research work from the Biomass Futures, Biomass Policies and S2Biom projects. In addition to technical issues, the book covers the economic, social and environmental aspects with direct implications on biomass availability. Its chapters offer an overview of methodologies for assessing and modeling supply, biomass quality and requirements for different conversion processes, logistics and demand for biobased sectors. Case studies from the projects that inspire the book present practical examples of the implementation of these methodologies. The authors also compare methodologies for different regions, including Europe and the U.S. Biomass feedstock-specific chapters address the relevant elements for forest, agriculture, biowastes, post-consumer wood and non-food crops. Engineers in the bioenergy sector, as well as researchers and graduate students will find this book to be a very useful resource when working on optimization and modeling of biomass supply chains. For energy policymakers, analysts and consultants, the book provides consistent and technically sound projections for policy and market development decisions. Provides consistent ratios and indicators for assessing biomass supply and its logistical component Explores assumptions behind the assessment of different types of biomass, including key technical and non-technical factors Presents the existing modeling platforms, their input requirements and possible output projections

Strategic Planning for the Sustainable Production of Biofuels

Strategic Planning for the Sustainable Production of Biofuels
Author: José Maria Ponce-Ortega
Publisher: Elsevier
Total Pages: 532
Release: 2019-03-05
Genre: Technology & Engineering
ISBN: 0128181796
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Strategic Planning for the Sustainable Production of Biofuels presents several optimization models for the design and planning of sustainable biorefinery supply chains, including issues surrounding the potential of biomass feedstocks in multiple harvesting sites, availability and seasonality of biomass resources, different potential geographical locations for processing plants that produce multiple products using diverse production technologies, economies of scale for production technologies, demands and prices of multiple products, locations of storage facilities, and a number of transportation modes. Sustainability considerations are incorporated into the proposed models by including simultaneous economic, environmental and social performance in the evaluation of the supply chain designs. Covers different optimization models for the strategic planning of biorefining systems Includes the GAMS and MATLAB codes for solving various problems Considers sustainability criteria in the presented models Presents different approaches for obtained trade-off solutions Provides general software that can be used for solving different problems

Biomass Supply Chains for Bioenergy and Biorefining

Biomass Supply Chains for Bioenergy and Biorefining
Author: Jens Bo Holm-Nielsen
Publisher: Woodhead Publishing
Total Pages: 412
Release: 2016-02-23
Genre: Science
ISBN: 1782423877
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Biomass Supply Chains for Bioenergy and Biorefining highlights the emergence of energy generation through the use of biomass and the ways it is becoming more widely used. The supply chains that produce the feedstocks, harvest, transport, store, and prepare them for combustion or refinement into other forms of fuel are long and complex, often differing from feedstock to feedstock. Biomass Supply Chains for Bioenergy and Biorefining considers every aspect of these supply chains, including their design, management, socioeconomic, and environmental impacts. The first part of the book introduces supply chains, biomass feedstocks, and their analysis, while the second part looks at the harvesting, handling, storage, and transportation of biomass. The third part studies the modeling of supply chains and their management, with the final section discussing, in minute detail, the supply chains involved in the production and usage of individual feedstocks, such as wood and sugar starches, oil crops, industrial biomass wastes, and municipal sewage stocks. Focuses on the complex supply chains of the various potential feedstocks for biomass energy generation Studies a wide range of biomass feedstocks, including woody energy crops, sugar and starch crops, lignocellulosic crops, oil crops, grass crops, algae, and biomass waste Reviews the modeling and optimization, standards, quality control and traceability, socioeconomic, and environmental impacts of supply chains

Spatial and Temporal Optimization of Advanced Biofuel Supply Chains in the United States

Spatial and Temporal Optimization of Advanced Biofuel Supply Chains in the United States
Author: Mohamed Laila
Publisher:
Total Pages:
Release: 2017
Genre:
ISBN:
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"Biofuels are one of the promising energy alternatives to reduce fossil fuel consumption and combat climate change. Growing civilian and military interest in acquiring cost competitive biofuels have inspired research to develop models that optimize their supply chains. Such models are constrained by several factors, namely the time-consuming data collection and processing, the complexity of formulating a mathematical optimization model, the need to use proprietary solvers, and the requirement for computational resources. To overcome these hurdles, researchers proposed the development of integrated platforms that streamline these activities and increase accessibility to the required algorithms and hardware. Hence, the objectives of this thesis were to 1) formulate deterministic and stochastic mathematical optimization models to optimize biofuel supply chains in a spatially and temporally explicit manner, and test their resilience under uncertainty, 2) design a web-based platform that integrates the proposed model with Application Program Interfaces and publicly available databases to construct user-defined case studies and solve optimization problems on third-party cloud servers, and 3) demonstrate the suitability of the integrated platform to generate military biofuel supply chains in several case studies from the Pacific region of the United States. The integrated platform is called the Biofuel supply chain Geospatial and Temporal Optimizer (BioGeSTO). The first version of BioGeSTO included a deterministic, spatial and temporal explicit, Mixed-Integer Linear Programming (MILP) model that accounts for improvements in conversion yields due to technology learning and account for future oil prices. The model was applied to a case study in California between 2020 and 2040 to determine whether direct financial incentives, provided to conversion facilities, expedited the development of the military biofuel supply chain for three oil price scenarios. It was concluded that direct financial incentives will have little or no effect on the development of the supply chain. The second version of BioGeSTO expanded the platform to include a stochastic MILP that was used to evaluate the impact of uncertainty pertaining to the availability and cost of biomass, and oil prices on the same supply chain. The supply chain had approximately 65% chance of emerging under these scenarios. I found that a Hydrotreatment of Esters and Fatty Acids (HEFA) facility dedicated to processing camelina oil (obtained from agricultural land in central California, where it is grown in rotation with wheat) could be introduced between 2020 and 2027 as a reliable and financially feasible option for military biofuels supply in the state. The final version of BioGeSTO, which included an interactive web interface, was used to determine how carbon pricing affected the military biofuel supply chain in the Pacific states of California, Oregon, and Washington. Introducing a carbon price improved the net present value and total cumulative production of the military biofuel supply chain under several oil price scenarios. Overall, BioGeSTO, an integrated platform for modelling and optimizing biofuel supply chain, is a suitable tool for researchers and decision makers to evaluate their case studies. It can be used to test the impact of introducing new policy schemes, technologies, or uncertainties on the design and performance of civilian and military biofuel supply chains. In future research projects, BioGeSTO can be expanded to include tactical and operational decisions (shorter time scales), while user defined heuristics may be added to accelerate the solution times of optimization problems." --

23 European Symposium on Computer Aided Process Engineering

23 European Symposium on Computer Aided Process Engineering
Author: Mingyen Yu
Publisher: Elsevier Inc. Chapters
Total Pages: 19
Release: 2013-06-10
Genre: Science
ISBN: 0128086114
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Renewable energy, especially biofuels, is seen as a viable solution to replace fossil fuels. Tighter environmental regulations have encouraged countries to develop strategic approaches to utilize alternative resources and new technologies. In retrospect, the performances of supply chains (SCs) are important from economic and environmental perspectives. Current research mainly focuses on the optimization of biofuel SCs in terms of economics, and distribution networks for other products and markets. There has been less work addressing the design of the distribution network for biofuel SC, in centralised/decentralised distribution, covering financial and environmental aspects. In this paper, we propose the optimization framework for biofuel SC with respect to the type of distribution network, and geographical locations of the facilities. Our research focuses on finding the optimal locations of the biofuel plant, considering biomass dispersions and customer locations based on candidate points. We also investigate the effects of using different transportation modes and the environmental effects on the type of distribution network used. A case study of a lignocellulosic plant distributing ethanol to its customers in various cities within UK has been used to validate the above framework. The result shows that the total distances of travel, as well as the unit transportation cost dominate the strategic application of either a centralised or decentralised distribution network. The concept presented in this research can be applied to other distribution design cases in various geographical locations and countries.

Lignocellulosic Biomass-to-biofuel Supply Chain Optimization with Mobile Densification and Farmers' Choices

Lignocellulosic Biomass-to-biofuel Supply Chain Optimization with Mobile Densification and Farmers' Choices
Author: Nibal Tawfiq Albashabsheh
Publisher:
Total Pages:
Release: 2018
Genre:
ISBN:
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This dissertation focuses on logistics challenges arising in the biofuels industry. Studies have found that logistics costs in the biomass-to-biofuel supply chain (BBSC) account for 35%-65% of total biofuel production cost. This is mainly due to the low density of biomass that results in high costs associated with biomass transportation, storage, and handling in the biomass-to-biofuel supply chain. Densification provides an as-yet-unexplored opportunity to reduce logistic costs associated with biomass-to-biofuel supply chains. This research advances understanding about biomass-to-biofuel supply chain management through new optimization models. As a first step, the author presents an extensive overview of densification techniques and BBSC optimization models that account for biomass densification. This literature review helps the author to recognize the gaps and future research areas in BBSC studies. These gaps direct the author toward the remaining components of the dissertation. In particular, the literature review highlights two research gaps. First, the review indicates that mobile pelleting holds promise for improved BBSC management, but that there is no mathematical optimization model that addresses this opportunity. Second, currently, there does not exist a model that explicitly accounts for farmers' objectives and their probability to sell biomass to the bioenergy plant in BBSC optimization. To fill the first gap, the author focuses on managing the BBSC considering mobile densification units to account for chances to minimize logistics costs. A mixed integer linear programming model is proposed to manage the BBSC with different types and forms of biomass feedstock and mobile densification units. Sensitivity analysis and scenario analysis are presented to quantify conditions that make mobile densification an attractive choice. The author conducts a case study to demonstrate model applicability and type of analysis that can be drawn from this type of models. The result indicates that mobile pelleting is not an attractive choice under the current economic status. However, modest changes in pelleting cost, satellite storage location fixed cost, and/or travel distances are enough to make mobile pelleting an attractive choice. To fill the second gap, the author introduces a model that explicitly accounts for mobile densification and farmers' probability to supply a bioenergy plant with biomass feedstock. Farmers' probability to provide biomass to the bioenergy plant depends on contract attributes, including expected net return and services provided by the bioenergy plant. The proposed model helps the bioenergy plant to meet biofuel demand while considering farmers' choices that satisfy their own objectives and preferences. The model makes it possible to determine most important factors that influence type of contract offered to each supplier and optimal BBSC design. A case study based on the state of Kansas is conducted to demonstrate how bioenergy plant can benefit from this type of model.