Development of Effective & Accessible Approach to Analyze Unsteady State Plant Performance

Abstract

Measurements from chemical processes contain error. They are reconciled with the process model to improve their accuracy. A method to reconcile unsteady state, i.e. time dependent, plant data using process simulators and dedicated optimization software is presented. The reconciliation is carried out in the optimization software and the process model is supplied in the form of dynamic process simulations built in the simulator. The optimization software and the process simulator are interconnected using OLE (Object Linked Embedding) technology from Microsoft. Mathematical models representing dynamic process operation are in the form of Differential Algebraic Equations (DAE). Existing methods require the process engineer to program the reconciliation routine and a solution to the DAE model using advanced numerical techniques. This poses high entry barrier. Proposed method instead relies on rating based process simulation which is familiar to a typical process engineer. Many process plants maintain simulation models further reducing the effort needed to develop reconciliation program. The only additional requirements for using this method are working knowledge of mathematical optimization software and OLE technology. The Rating Based Reconciliation (RBR) method developed in this work is tested in three case studies of increasing complexity. Error in several of the measurements reduced after reconciliation. Accuracy of the results from the proposed method is comparable to those from literature. The accuracy improves significantly by using wavelet denoising prior to reconciliation.