Rigorously modelling steam utility systems for mixed integer optimization

Given that industrial utility systems are essentially large energy converters, it is surprising that they are so often forgotten or ignored when optimizing plant performance. Significant operational savings are possible simply by redistributing steam generation and consumption, without adding extra equipment, and with minimal investment. However due to the discrete nature of a utility system where equipment can switched in and out of service, steam flows redistributed, and zero-flow conditions are normal, the optimizing of utility system requires a rigorous model based on thermodynamics and state-of-the-art numerical algorithms. This paper proposes a mixed integer modelling strategy to approximate a rigorous simulator model, combining regressions from literature, industrial experience and process specific knowledge resulting in a model suitable for optimization. Two case studies are presented to demonstrate the efficiency of the modelling design, a hypothetical three header model with cogeneration and a four header refinery utility system. Both systems are optimized using BONMIN in less than a quarter of a second on a standard desktop PC and result in substantial economic improvements.

[1]  Mujtaba Hassan Agha,et al.  Integrated production and utility system approach for optimizing industrial unit operations , 2010 .

[2]  Cath Everett How to make the most of IT , 2006 .

[3]  Robin Smith,et al.  Design and Optimization of Flexible Utility Systems Subject to Variable Conditions: Part 1: Modelling Framework , 2007 .

[4]  Gérard Cornuéjols,et al.  An algorithmic framework for convex mixed integer nonlinear programs , 2008, Discret. Optim..

[5]  S. Bowler Make the most of it , 1999 .

[6]  L. C. Hardison Treating hydrogen sulfide: an alternative to Claus , 1985 .

[7]  Ignacio E. Grossmann,et al.  A structural optimization approach in process synthesis. II: Heat recovery networks , 1983 .

[8]  Antonis C. Kokossis,et al.  Conceptual optimisation of utility networks for operational variations—I. targets and level optimisation , 1998 .

[9]  Ignacio E. Grossmann,et al.  A structural optimization approach in process synthesis—I: Utility systems , 1983 .

[10]  H. Kretzschmar,et al.  The IAPWS Industrial Formulation 1997 for the Thermodynamic Properties of Water and Steam , 2000 .

[11]  Robin Smith,et al.  Modelling and Optimization of Utility Systems , 2004 .

[12]  Jonathan Currie,et al.  Opti: Lowering the Barrier Between Open Source Optimizers and the Industrial MATLAB User , 2012 .

[13]  Ignacio E. Grossmann,et al.  A Rigorous MINLP Model for the Optimal Synthesis and Operation of Utility Plants , 1998 .

[14]  Jonathan Currie,et al.  The efficient modelling of steam utility systems , 2012 .

[15]  Robin Smith,et al.  Design and Optimization of Flexible Utility Systems Subject to Variable Conditions: Part 2 Methodology and Applications , 2007 .

[16]  Nicola Knight,et al.  Real-time Utility System Optimization , 2005 .