Scaled steady state models for effective on-line applications

Tore Lid, Sigurd Skogestad
2008 Computers and Chemical Engineering  
Applications for on-line data reconciliation and optimization must be efficient and numerically robust. The models in these applications are rarely changed and the same optimization problem is solved thousands of times with only minor changes in the parameters. This paper describes a suitable modeling framework for this type of applications that, with the aim of simplifying the creation of new models, makes the application robust and avoids numerical difficulties. The model is based on a unit
more » ... del structure where first-order derivatives, scaling and initial values are properties of the unit model. A new scaling procedure is proposed based on equation and variable pairing. The modeling framework and the use of the proposed scaling procedure are demonstrated in two case studies, case 1 is simulation of a simple pipe model, case 2 is simulation, data reconciliation and optimization of a flash process. .no (S. Skogestad). AspenTech. See Marquardt (1996) for an overview of these tools and others. The strength of the generic modeling tools mentioned above are the modeling capability, i.e. creation of new models, but this is rarely needed in on-line optimization applications. Online optimization of a process plant is typically separated into three main tasks: estimation of current state (data reconciliation), optimization and implementation (White, 1997) . Models for online applications should be derived with the following in mind: 0098-1354/$ -see front matter
doi:10.1016/j.compchemeng.2007.04.003 fatcat:do4qe2ja3ndozaytbwsz7b5xo4