Optimum Biorefinery Pathways Selection Using the Integer-Cuts Constraint Method Applied to a MILP Problem

Biorefineries are multi-product facilities that convert biomass into a broad variety of products (energy, biofuels, chemicals, feed, and food). In this paper, a new systematic approach to select and rank different biorefinery conversion pathways is proposed using the Integer-Cut Constraint (ICC) method applied to a MILP problem. In particular, two different statements of the constraints are analyzed. The first step is building a superstructure collecting several biomass conversion models. The ICC method allows different conversion pathways to be evaluated inside the superstructure and ordered according to the objective function values. The key value of a rank of pathways including suboptimal routes allows a fair comparison between alternative biorefinery options and may widen the choice to suboptimal ones. The method is applied to a case study in which various biomass-to-fuel technologies are analyzed to set up a rank of the most promising conversion processes in the current Swiss market.

[1]  F. Maréchal,et al.  Thermochemical production of liquid fuels from biomass: Thermo-economic modeling, process design and process integration analysis , 2010 .

[2]  E. Galindo,et al.  Production of 6-pentyl-α-pyrone by Trichoderma harzianum cultured in unbaffled and baffled shake flasks , 2004 .

[3]  Mahmoud M. El-Halwagi,et al.  Framework for margins-based planning: Forest biorefinery case study , 2014, Comput. Chem. Eng..

[4]  Raymond R. Tan,et al.  A fuzzy multiple-objective approach to the optimization of bioenergy system footprints , 2009 .

[5]  Himadri Roy Ghatak,et al.  Biorefineries from the perspective of sustainability: Feedstocks, products, and processes , 2011 .

[6]  Aidong Yang,et al.  On the use of systems technologies and a systematic approach for the synthesis and the design of future biorefineries , 2010, Comput. Chem. Eng..

[7]  Michael Kamm,et al.  International biorefinery systems , 2007 .

[8]  Pravat K. Swain,et al.  Biomass to liquid: A prospective challenge to research and development in 21st century , 2011 .

[9]  Fengqi You,et al.  Sustainable design and synthesis of hydrocarbon biorefinery via gasification pathway: Integrated life cycle assessment and technoeconomic analysis with multiobjective superstructure optimization , 2013, Comput. Chem. Eng..

[10]  Francesco Cherubini,et al.  The biorefinery concept: Using biomass instead of oil for producing energy and chemicals , 2010 .

[11]  Ioannis V. Skiadas,et al.  Toward a common classification approach for biorefinery systems , 2009 .

[12]  Mahmoud M. El-Halwagi,et al.  A shortcut method for the preliminary synthesis of process-technology pathways: An optimization approach and application for the conceptual design of integrated biorefineries , 2011, Comput. Chem. Eng..

[13]  Paul Stuart,et al.  Integrating product portfolio design and supply chain design for the forest biorefinery , 2010, Comput. Chem. Eng..

[14]  Viknesh Andiappan,et al.  A systematic methodology for optimal mixture design in an integrated biorefinery , 2015, Comput. Chem. Eng..

[15]  Mahmoud M. El-Halwagi,et al.  Optimal planning and site selection for distributed multiproduct biorefineries involving economic, environmental and social objectives. , 2014 .

[16]  Denny K. S. Ng,et al.  Automated targeting for the synthesis of an integrated biorefinery , 2010 .

[17]  Hong Yan,et al.  Logic cuts for processing networks with fixed charges , 1994, Comput. Oper. Res..

[18]  Jay H. Lee,et al.  Optimal processing pathway for the production of biodiesel from microalgal biomass: A superstructure based approach , 2013, Comput. Chem. Eng..

[19]  S. Adhikari,et al.  Biorefineries: Current Status, Challenges, and Future Direction , 2006 .

[20]  Rafiqul Gani,et al.  Optimal design of a multi-product biorefinery system , 2011, Comput. Chem. Eng..

[21]  Denny K. S. Ng,et al.  Novel Methodology for the Synthesis of Optimal Biochemicals in Integrated Biorefineries via Inverse Design Techniques , 2015 .

[22]  Denny K. S. Ng,et al.  Fuzzy Optimization Approach for the Synthesis of a Sustainable Integrated Biorefinery , 2011 .

[23]  Josef Kallrath,et al.  Mixed Integer Optimization in the Chemical Process Industry: Experience, Potential and Future Perspectives , 2000 .

[24]  V. Menon,et al.  Trends in bioconversion of lignocellulose: Biofuels, platform chemicals & biorefinery concept , 2012 .

[25]  K. Gernaey,et al.  Toward a Computer-Aided Synthesis and Design of Biorefinery Networks: Data Collection and Management Using a Generic Modeling Approach , 2014 .

[26]  J. M. Ponce-Ortega,et al.  Optimal Planning of a Biomass Conversion System Considering Economic and Environmental Aspects , 2011 .

[27]  B. Kamm,et al.  Principles of biorefineries , 2004, Applied Microbiology and Biotechnology.

[28]  François Maréchal,et al.  Thermo-economic optimisation of the polygeneration of synthetic natural gas (SNG), power and heat from lignocellulosic biomass by gasification and methanation , 2012 .

[29]  Alexander Bockmayr,et al.  Detecting infeasibility and generating cuts for mixed integer programming using constraint programming , 2006, Comput. Oper. Res..

[30]  Ignacio E. Grossmann,et al.  On the Systematic Synthesis of Sustainable Biorefineries , 2013 .

[31]  Pascale Champagne,et al.  A biorefinery processing perspective: treatment of lignocellulosic materials for the production of value-added products. , 2010, Bioresource technology.

[32]  François Maréchal,et al.  Methods for multi-objective investment and operating optimization of complex energy systems , 2012 .

[33]  Krist V. Gernaey,et al.  Upgrading of lignocellulosic biorefinery to value-added chemicals: Sustainability and economics of bioethanol-derivatives , 2015 .

[34]  Anders Hammer Strømman,et al.  Chemicals from lignocellulosic biomass: opportunities, perspectives, and potential of biorefinery systems , 2011 .

[35]  Carlos A. Cardona,et al.  Selection of Process Pathways for Biorefinery Design Using Optimization Tools: A Colombian Case for Conversion of Sugarcane Bagasse to Ethanol, Poly-3-hydroxybutyrate (PHB), and Energy , 2013 .

[36]  Alexandre C. Dimian Renewable raw materials: chance and challenge for computer-aided process engineering , 2007 .

[37]  Nikolaos V. Sahinidis,et al.  Optimization model for long range planning in the chemical industry , 1989 .

[38]  A. Heiningen,et al.  Larch Biorefinery: Technical and Economic Evaluation , 2014 .

[39]  Rainer Zah,et al.  Identifying environmentally and economically optimal bioenergy plant sizes and locations: A spatial model of wood-based SNG value chains , 2014 .

[40]  Mahmoud M. El-Halwagi,et al.  A Disjunctive Programming Formulation for the Optimal Design of Biorefinery Configurations , 2012 .

[41]  Christos T. Maravelias,et al.  An optimization-based assessment framework for biomass-to-fuel conversion strategies , 2013 .