Publications
85 results found
Panteli A, Giarola S, Shah N, 2015, Supply chain optimization tools for the strategic planning of biorefining systems, Pages: 150-152
A crucial element of biobased economies is the development of economically sustainable biorefining systems enabling a full exploitation of biomass (and its macrocomponents, i.e. cellulose, hemicellulose and lignin) for the production of chemicals, materials and energy. The huge variety of biomass processing paths in second generation biorefineries leads to complex product portfolios indicating the necessity of maximizing the value derived from biomass feedstock when treated in a biorefinery with the aim to create economically feasible and environmentally sustainable biobased production systems (Kokossis and Yang, 2010). One of the most important and challenging aspects in the quest of producing a set of more sustainable biobased products, is the design of a more profitable, better integrated and more sustainable biorefinery supply chain network (Akgul et al., 2011; Martín and Grossmann, 2010; Čuček et al., 2014). The biomass pretreatment, which fractionates biomass into its three macrocomponents, usually represents the highest costing part of the entire biorefining system (CIMV, 2015). Optimization tools could play a decisive role supporting the decision making process in new biorefinery systems, through the performance of sensitivity analysis, the assessment of technical or economic uncertainties as well as the identification of the major cost drivers (Kim et al., 2013).
Giarola S, Bezzo F, 2015, Bioethanol Supply Chain Design and Optimization: Some Achievements and Future Challenges for the Development of Sustainable Biorefineries, Computer Aided Chemical Engineering, Pages: 555-581
Energy security and climate change concerns have endangered the reliability of the current hydrocarbon-based energy system. Biofuels, and bioethanol in particular, have been acknowledged to have a relevant role in leading this paradigm change in the transport energy sector. Quantitative design tools based on mathematical programming may play a relevant role in driving the decision-making progress on well-advised investments in the energy sector.This chapter focuses on the application of mathematical tools to some of the most challenging aspects concerning the actual feasibility and sustainability of biofuel infrastructures. In particular, the optimization of biofuel networks toward economic and environmental objectives will be tackled. Also, the effect of market and technology uncertainties will be discussed as key factors affecting planning strategies in the biofuel sector.
Annevelink B, de Groot H, Shah N, et al., 2015, S2BIOM DATABASE WITH LOGISTICAL COMPONENTS OF THE BIOMASS VALUE CHAIN, 23rd European Biomass Conference and Exhibition (EU BC and E), Publisher: ETA-FLORENCE RENEWABLE ENERGIES, Pages: 339-343
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- Citations: 1
Giarola S, Romain C, Williams CK, et al., 2015, Production of phthalic anhydride from biorenewables: process design, 12TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING AND 25TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PT C, Vol: 37, Pages: 2561-2566, ISSN: 1570-7946
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- Citations: 3
Ortiz-Gutierrez RA, Giarola S, Shah N, et al., 2015, An approach to optimize multi-enterprise biofuel supply chains including Nash equilibrium models, 12TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING AND 25TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, PT C, Vol: 37, Pages: 2255-2260, ISSN: 1570-7946
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- Citations: 6
Giarola S, Patel M, Shah N, 2014, Biomass supply chain optimisation for Organosolv-based biorefineries (vol 159, pg 387, 2014), BIORESOURCE TECHNOLOGY, Vol: 172, Pages: 467-467, ISSN: 0960-8524
Pantaleo AM, Giarola S, Bauen A, et al., 2014, Integration of biomass into urban energy systems for heat and power. Part I: An MILP based spatial optimization methodology, ENERGY CONVERSION AND MANAGEMENT, Vol: 83, Pages: 347-361, ISSN: 0196-8904
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- Citations: 48
Pantaleo AM, Giarola S, Bauen A, et al., 2014, Integration of biomass into urban energy systems for heat and power. Part II: Sensitivity assessment of main techno-economic factors, ENERGY CONVERSION AND MANAGEMENT, Vol: 83, Pages: 362-376, ISSN: 0196-8904
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- Citations: 36
Giarola S, Bezzo F, Shah N, 2013, A risk management approach to the economic and environmental strategic design of ethanol supply chains, BIOMASS & BIOENERGY, Vol: 58, Pages: 31-51, ISSN: 0961-9534
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- Citations: 63
Bernardi A, Giarola S, Bezzo F, 2013, Spatially Explicit Multiobjective Optimization for the Strategic Design of First and Second Generation Biorefineries Including Carbon and Water Footprints, INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 52, Pages: 7170-7180, ISSN: 0888-5885
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- Citations: 44
Giarola S, Shah N, 2013, Techno-economic and environmental assessment of ionic liquid-based biorefineries, Pages: 127-128
Giarola S, Shah N, 2013, Techno-economic and environmental assessment of ionic liquid-based biorefineries, Pages: 338-339
Giarola S, Shah N, 2013, Techno-economic and environmental assessment of ionic liquid-based biorefineries, Pages: 301-302
Gutierrez RAO, Penazzi S, Bernardi A, et al., 2013, A spatially-explicit approach to the design of ethanol supply chains considering multiple technologies and carbon trading effects, 23 EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, Vol: 32, Pages: 643-648, ISSN: 1570-7946
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- Citations: 1
Ortiz-Gutiérrez RA, Giarola S, Bezzo F, 2013, Optimal design of ethanol supply chains considering carbon trading effects and multiple technologies for side-product exploitation., Environ Technol, Vol: 34, Pages: 2189-2199, ISSN: 0959-3330
This work proposes a spatially explicit mixed integer linear programming modelling framework representing the dynamic evolution of a bioethanol supply chain (SC) under increasing biofuel demand and greenhouse gas (GHG) emission savings over time. Key features of the proposed framework comprise: (i) the incorporation of available set-aside rural surfaces for energy crop cultivation; (ii) the acknowledgement ofan economic value to the overall GHG emissions through the introduction of an Emission Trading System. Multiple technological options are assessed to exploit the co-product Distiller's Dried Grains with Solubles either as animal fodder (standard usage) or as fuel for heat and power generation or as raw material for biogas production (and hence heat and power). Bioethanol production in Northern Italy is chosen as a demonstrative case study.
Bernardi A, Giarola S, Bezzo F, 2012, Optimizing the economics and the carbon and water footprints of bioethanol supply chains, BIOFUELS BIOPRODUCTS & BIOREFINING-BIOFPR, Vol: 6, Pages: 656-672, ISSN: 1932-104X
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- Citations: 38
Giarola S, Zamboni A, Bezzo F, 2012, Environmentally conscious capacity planning and technology selection for bioethanol supply chains, Renewable Energy, Vol: 43, Pages: 61-72, ISSN: 0960-1481
Concerns about energy supply security and climate change have been pushing world countries towards the promotion of renewable sources of energy and more sustainable liquid fuels. Initially indicated as the most viable solution within the transport sector, corn bioethanol is now incurring increasing discredits relating to its profitability and to its effective sustainability. Lignocellulosic ethanol is commonly viewed as a better solution over the long term due to its potential to overcome first generation limitations. This paper addresses the design of bioethanol supply chains where both corn grain and stover are considered as suitable biomass. A Mixed Integer Linear Program is proposed to simultaneously optimise the environmental and financial performances by taking into account a wide number of technological options. Results show the effect of different strategic objectives on the main design feature and it is demonstrated how environmental objectives may strongly affect technological choices as well as the supply chain design in terms of both system profitability and sustainability. © 2011 Elsevier Ltd.
Giarola S, Shah N, Bezzo F, 2012, A comprehensive approach to the design of ethanol supply chains including carbon trading effects, BIORESOURCE TECHNOLOGY, Vol: 107, Pages: 175-185, ISSN: 0960-8524
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- Citations: 105
Bernardi A, Giarola S, Bezzo F, 2012, A framework for water footprint optimisation in the bioethanol supply chain, 11TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING, PTS A AND B, Vol: 31, Pages: 1372-1376, ISSN: 1570-7946
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- Citations: 2
Giarola S, Zamboni A, Bezzo F, 2011, Spatially explicit multi-objective optimisation for design and planning of hybrid first and second generation biorefineries, Computers and Chemical Engineering, Vol: 35, Pages: 1782-1797, ISSN: 0098-1354
Climate change mitigation has become a binding driver in biofuels production. First generation bioethanol, initially indicated as the most competitive option, is now incurring in ever increasing discredits forcing the transition towards more sustainable productions (i.e. second and third generation technologies). This paper addresses the strategic design and planning of corn grain- and stover-based bioethanol supply chains through first and second generation technologies. A Mixed Integer Linear Programming framework is proposed to optimise the environmental and financial performances simultaneously. Multi-period, multi-echelon and spatially explicit features are embodied within the formulation to steer decisions and investments through a global approach. A demonstrative case study is proposed involving the future Italian biomass-based ethanol production. Results show the effectiveness of the optimisation tool at providing decision makers with a quantitative analysis assessing the economic and environmental performance of different design configuration and their effect in terms of technologies, plant sizes and location, and raw materials. © 2011 Elsevier Ltd.
Zamboni A, Giarola S, Bezzo F, 2011, Towards Second Generation Bioethanol. Supply Chain Design and Capacity Planning
This work proposes a multi-period and spatially explicit framework conceived to drive strategic policies on biofuels. A Mixed Integer Linear Programming (MILP) model is proposed as quantitative tool to optimise the oncoming transition towards more sustainable infrastructures. This paper addresses the design of bioethanol supply chains where both corn grain and stover are considered as suitable biomass. A Mixed Integer Linear Program is proposed to optimise the system financial performance and to comply with EU environmental regulation by taking into account a wide number of technological options. Bioethanol production in Northern Italy is chosen as a demonstrative case study. © 2011 Elsevier B.V.
Dal-Mas M, Giarola S, Zamboni A, et al., 2011, Strategic design and investment capacity planning of the ethanol supply chain under price uncertainty, Biomass and Bioenergy, Vol: 35, Pages: 2059-2071, ISSN: 0961-9534
Fossil fuel depletion and the increase of greenhouse gases emissions has been pushing the search for alternative fuels for automotive transport. The European Union has identified biofuel technology as one option for reducing its dependence on imported energy. Ethanol is a promising biofuel, but great uncertainty on the business profitability has recently determined a slowdown in the industry expansion. In particular, geographical plant location, biomass price fluctuation and fuel demand variability severely constrain the economic viability of new ethanol facilities. In this work a dynamic, spatially explicit and multi-echelon Mixed Integer Linear Program (MILP) modeling framework is presented to help decision-makers and potential investors assessing economic performances and risk on investment of the entire biomass-based ethanol supply chain. A case study concerning the corn-to-ethanol production supply chain in Northern Italy is used to demonstrate the effectiveness of the proposed modeling approach. The mathematical pattern addresses the issue of optimizing the ethanol supply network over a ten years' time period under uncertainty on biomass production cost and product selling price. The model allows optimizing economic performances and minimize financial risk on investment by identifying the best network topology in terms of biomass cultivation site locations, ethanol production plant capacities, location and transport logistics. © 2011 Elsevier Ltd.
Giarola S, Zamboni A, Bezzo F, 2011, Supply chain design and capacity planning: From first to second generation biofuel systems, Pages: 253-258, ISSN: 2283-9216
Supply Chain optimisation tools may help managing the oncoming transition from first to second generation bioethanol productions. A multi-objective Mixed Integer Linear Programming is developed to design bioethanol supply chains where both corn grain and stover are considered as suitable biomass. Environmental and financial performance are simultaneously taken as design drivers and alternative process design options are considered, too. Northern Italy is taken as geographical benchmark to assess a real-world case study. Results show how the design transition from first to second generation bioethanol systems substantially depends on the specific trade-off between environmental and financial objectives. © 2011, AIDIC Servizi S.r.l.
Khor CS, Giarola S, Chachuat B, et al., 2011, An optimization-based framework for process planning under uncertainty with risk management, Pages: 449-450
Dal Mas M, Giarola S, Zamboni A, et al., 2010, Capacity planning and financial optimization of the bioethanol supply chain under price uncertainty, Computer Aided Chemical Engineering, Vol: 28, Pages: 97-102, ISSN: 1570-7946
This work addresses the development of a dynamic spatially explicit MILP (Mixed Integer Linear Programming) modeling framework devised to optimize the design and planning of biomass-based fuel supply networks according to financial criteria and accounting for uncertainty on market conditions. The model capabilities in steering strategic decisions are assessed through a real-world case study related to the emerging corn-based bioethanol production system in Northern Italy. Two optimization criteria are considered, based on a risk-seeking or, alternatively, on a risk-adverse-approach. © 2010 Elsevier B.V.
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