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  • Conference paper
    Panteli A, Giarola S, Shah N, 2017,

    Biobased Supply Chain Optimisation Model under Uncertainties

    , 27th European Symposium on Computer-Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 961-966, ISSN: 1570-7946
  • Conference paper
    Sechi S, Giarola S, Lanzini A, Gandiglio M, Oluleye O, Santarelli M, Hawkes Aet al., 2017,

    Techno-economic assessment of the effects of biogas rate fluctuations on industrial applications of solid-oxide fuel cells

    , ESCAPE-27, Publisher: Elsevier, ISSN: 1570-7946

    Wastewater treatment is an energy and greenhouse gas intensive process. An important opportunity to reduce both of these quantities is via the use of biogas in co-generation systems. Solid-oxide fuel cells (SOFCs) are the generator types studied in this work.The feasibility of the retrofitting of a wastewater treatment facility fitted with a SOFC combined heat and power energy provision system is assessed including effects of uncertainties in biogas availability on cost and energy performance. A two-stage stochastic optimization framework is proposed to provide feedback on the energy co-generation system design.Results quantify standard deviations in the biogas rate beyond which the SOFC capacity factor might drop below 80 % and change the optimal size of the modules to install.Keywords: solid-oxide fuel cells, stochastic optimization, wastewater treatment, biogas.

  • Conference paper
    Sachs J, Giarola S, Hawkes AD, 2017,

    Agent-based model for energy-related investment decisions in the residential building sector

    , International Energy Workshop, Publisher: International Energy Workshop
  • Conference paper
    Giarola S, Budinis S, Sachs J, Hawkes ADet al., 2017,

    Long-term decarbonisation scenarios in the industrial sector

    , International Energy Workshop

    Decarbonisation targets will drive every sector in the energy system to rapidly adopt innovativetechnologies to achieve the dramatic emissions reductions required. Among all, sectors like in-dustry, which currently exhibit a very high energy intensity, are likely to undergo major changes.This manuscript focuses on the appraisal of the effects of a CO2tax in the investment and operationdecisions in industry. Within the larger modelling framework typical of an integrated assessmentmodel, the sector is modelled including the top-energy intensive industries, such as those man-ufacturing pulp and paper, iron and steel, chemicals and petrochemicals, the non-ferrous metalsas well as non-metallic minerals. The simulations are carried out using a novel energy systemsmodel, MUSE, the Modular Universal energy systems Simulation Environment model.

  • Conference paper
    Crow D, Giarola S, Hawkes AD, 2016,

    Modelling imperfect foresight in investment decisions in the upstream gas industry

    , Energy Systems Conference
  • Journal article
    Giarola S, Romain C, Williams C, Hallett JP, Shah Net al., 2016,

    Techno-economic assessment of the production of phthalic anhydride from corn stover

    , Chemical Engineering Research & Design, Vol: 107, Pages: 181-194, ISSN: 1744-3563

    Phthalic anhydride is used worldwide for an extremely broad range of applications spanning from the plastics industry to the synthesis of resins, agricultural fungicides and amines. This work proposes a conceptual design of a process for the production of phthalic anhydride from an agricultural residue (i.e. corn stover), energy integration alternatives as well as water consumption and life cycle greenhouse emissions assessment. The techno-economic and financial appraisal of the flowsheet proposed is performed. Results show how the valorization of all the carbohydrate-rich fractions present in the biomass as well as energy savings and integration is crucial to obtain an economically viable process and that it is in principle possible to produce renewable phthalic anhydride in a cost-competitive fashion with a lower impact on climate change compared to the traditional synthetic route.

  • Conference paper
    Panteli A, Giarola S, Shah N, 2016,

    A generic MILP modelling framework for the systematic design of lignocellulosic biorefining supply chains

    , Pages: 197-199

    The development of sustainable biobased economies could help overcome the high societal dependency on fossil resources. Therefore, research has focused on the study of advanced biorefining networks. The complexity of such production systems requires the use of efficient decision-making tools, enabling a full exploitation of biomass (and its macrocomponents, i.e. cellulose, hemicellulose and lignin) for the production of biobased products and platform chemicals (Kokossis and Yang, 2010). Therefore, it is also essential to identify the most promising pretreatment process that fractionates biomass into cellulose, hemicellulose and lignin and usually represents the highest cost part of the entire biorefining system. In addition, the deployment of second-generation technologies is still hindered by high capital costs as well as the existence of uncertainties (e.g. demand and price of biobased products) in the so far immature biobased market. Consequently, one of the most important and challenging aspects in the quest of producing a set of sustainable biobased products, is the design of an integrated and economically viable biorefinery supply network (Akgul et al., 2011; Martín and Grossmann, 2010; Čuček et al., 2014). Optimisation tools could play a powerful role supporting decision in such novel production systems, through the identification of the major cost drivers, the performance of sensitivity analysis as well as the assessment of economic and technical uncertainties (Kim et al., 2013). The aim of this work is the modelling and optimization of biorefining chain systems using an integrated approach to the modelling of all the entities involved across the technology chain, with the purpose of achieving a long-term, decision-making regarding the systematic design and planning of advanced biorefining networks.

  • Conference paper
    Giarola S, Crow DJG, Hawkes A, 2016,

    A framework for modelling investment decisions in gas infrastructures

    , 26th European Symposium on Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 259-264, ISSN: 1570-7946
  • Book chapter
    Panteli A, Giarola S, Shah N, 2016,

    Lignocellulosic supply chain MILP model: a Hungarian case study

    , Editors: Kravanja, Bogataj, Publisher: ELSEVIER SCIENCE BV, Pages: 253-258
  • Conference paper
    Annevelink B, Staristky I, Krajnc N, Lammens T, Gonzalez DS, Lenz K, Kuhner S, Anttila P, Prinz R, Leduc S, Giarola S, Shah N, Gabrielle B, Galindo DGet al., 2016,


    , 24th International European Biomass Conference on Setting the Course for a Biobased Economy, Publisher: ETA-FLORENCE RENEWABLE ENERGIES, Pages: 108-113

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