Global optimization for the synthesis of property-based recycle and reuse networks including environmental constraints

This paper presents a new formulation and a mathematical programming model for the direct recycle and reuse of mass exchange networks considering simultaneously process and environmental constraints. The model is based on mass and property integration. The properties constrained by the sinks include composition, density, viscosity, pH, and reflectivity, whereas the environmental constraints include the composition for hazardous materials, toxicity, chemical oxygen demand, color, and odor. The model eliminates most of the nonlinearities of the system, and the bilinear terms that remain are handled with a relaxation approach that yields a global optimal solution. The model minimizes the total annual cost that includes the cost of fresh sources and the annualized cost for property interceptors. Two examples are presented to show the effectiveness of the proposed model. The results show that even for a large size problem, the computation effort is relatively small as a result of the linearization procedure.

[1]  Ignacio E. Grossmann,et al.  Global optimization for the synthesis of integrated water systems in chemical processes , 2006, Comput. Chem. Eng..

[2]  G. T. Polley,et al.  Design Better Water Networks , 2000 .

[3]  Christodoulos A. Floudas,et al.  Global optimization of a combinatorially complex generalized pooling problem , 2006 .

[4]  Mahmoud M. El-Halwagi,et al.  A property‐based optimization of direct recycle networks and wastewater treatment processes , 2009 .

[5]  Mahmoud M. El-Halwagi,et al.  Surplus diagram and cascade analysis technique for targeting property-based material reuse network , 2006 .

[6]  Ignacio E. Grossmann,et al.  A global optimization algorithm for linear fractional and bilinear programs , 1995, J. Glob. Optim..

[7]  Mahmoud M. El-Halwagi,et al.  Optimal synthesis and scheduling of hybrid dynamic/steady-state property integration networks , 2005, Comput. Chem. Eng..

[8]  M. El‐Halwagi.  Pollution prevention through process integration : systematic design tools , 1997 .

[9]  Mikhail Sorin,et al.  The Global Pinch Point in Water Reuse Networks , 1999 .

[10]  NORBERT BENKÕ,et al.  THE USE OF NONLINEAR PROGRAMMING TO OPTIMAL WATER ALLOCATION , 2000 .

[11]  Miguel J. Bagajewicz,et al.  Algorithmic procedure to design water utilization systems featuring a single contaminant in process plants , 2001 .

[12]  Antonis C. Kokossis,et al.  Wastewater minimisation of industrial systems using an integrated approach , 1998 .

[13]  James E. Falk,et al.  Jointly Constrained Biconvex Programming , 1983, Math. Oper. Res..

[14]  Z. Putra,et al.  Two-Step Optimization Approach for Design of A Total Water System , 2008 .

[15]  Ana Carolina Hortua.  Chemical process optimization and pollution prevention via mass and property integration , 2009 .

[16]  Mahmoud M. El-Halwagi,et al.  Property integration: Componentless design techniques and visualization tools , 2004 .

[17]  A. E. Greenberg,et al.  Standard methods for the examination of water and wastewater : supplement to the sixteenth edition , 1988 .

[18]  Miguel J. Bagajewicz,et al.  On the necessary conditions of optimality of water utilization systems in process plants with multiple contaminants , 2003 .

[19]  Juan M. Zamora,et al.  Superstructure Decomposition and Parametric Optimization Approach for the Synthesis of Distributed Wastewater Treatment Networks , 2004 .

[20]  Miguel J. Bagajewicz,et al.  On the optimality conditions of water utilization systems in process plants with single contaminants , 2000 .

[21]  C. Adjiman,et al.  Global optimization of mixed‐integer nonlinear problems , 2000 .

[22]  Mahmoud M. El-Halwagi,et al.  Process integration technology review: background and applications in the chemical process industry , 2003 .

[23]  Fernando L.P. Pessoa,et al.  Design procedure for water/wastewater minimization: single contaminant , 2007 .

[24]  Robin Smith,et al.  Targeting Water Reuse with Multiple Contaminants , 1997 .

[25]  U. V. Shenoy,et al.  Unified conceptual approach to targeting and design of water and hydrogen networks , 2006 .

[26]  Yin Ling Tan,et al.  Targeting the minimum water flow rate using water cascade analysis technique , 2004 .

[27]  I. Grossmann,et al.  Optimal Design of Distributed Wastewater Treatment Networks , 1998 .

[28]  Robin Smith,et al.  Effluent treatment system design , 1997 .

[29]  Mahmoud M. El-Halwagi,et al.  Solve design puzzles with mass integration , 1998 .

[30]  Mahmoud M. El-Halwagi,et al.  RIGOROUS GRAPHICAL TARGETING FOR RESOURCE CONSERVATION VIA MATERIAL RECYCLE/REUSE NETWORKS , 2003 .

[31]  Mahmoud M. El-Halwagi,et al.  Targeting optimum resource allocation using reverse problem formulations and property clustering techniques , 2005, Comput. Chem. Eng..

[32]  Mahmoud M. El-Halwagi,et al.  Simultaneous synthesis of waste interception and material reuse networks: Problem reformulation for global optimization , 2005 .

[33]  Antonis C. Kokossis,et al.  A multi-contaminant transhipment model for mass exchange networks and wastewater minimisation problems , 1999 .

[34]  Xiao Feng,et al.  On the use of graphical method to determine the targets of single-contaminant regeneration recycling water systems , 2007 .

[35]  M. Wasilewski,et al.  Make your process water pay for itself , 1996 .

[36]  Pedro M. Castro,et al.  LP-based solution strategies for the optimal design of industrial water networks with multiple contaminants , 2008 .

[37]  Nick Hallale,et al.  A NEW GRAPHICAL TARGETING METHOD FOR WATER MINIMISATION , 2002 .

[38]  Robin Smith,et al.  Automated design of total water systems , 2005 .

[39]  Mahmoud M. El-Halwagi,et al.  Algebraic Techniques for Property Integration via Componentless Design , 2004 .

[40]  Garth P. McCormick,et al.  Computability of global solutions to factorable nonconvex programs: Part I — Convex underestimating problems , 1976, Math. Program..

[41]  Mahmoud M. El-Halwagi,et al.  Component-less design of recovery and allocation systems: a functionality-based clustering approach , 2000 .

[42]  E. Coro,et al.  Color removal in groundwater through the enhanced softening process. , 2001, Water research.