Plant-Wide Simulation Model for Modified Claus Process Based on Simultaneous Data Reconciliation and Parameter Estimation

The modified Claus process is characterized by several problems, namely poor instrumentation and no precise kinetic model for predicting the behaviour of the reactors. Using operational data of an industrial plant, this paper proposes a general framework for development of a plant-wide simulation model for modified Claus process based on simultaneous data reconciliation and parameter estimation (DRPE) using Genetic algorithm (GA). HYSYS as a commercial process simulator that provides a high-level of accuracy as well as redundancy which all is favoured for DRPE has been utilized in this work. Building a communication framework between HYSYS and MATLAB, data pre-processing of raw measurement data, and then simultaneous data reconciliation and parameter estimation together with gross error detection were performed in the proposed algorithm. As a result, reconciled values of redundant data, inferred values of unmeasured observable data, as well as optimal estimated values of key parameters of the process were obtained. The key parameters of the modified Claus process have been considered as the kinetic parameters of the main reactions taking place in the reactors. Analysis of the results showed that the standard deviation of the reconciled data are reasonably reduced comparing with their raw measured values. Accordingly, measuring errors caused by various unfavourable problems in the plant such as instrumentation inaccuracy were reduced. Having developed simulation model with accurate values of process variables, the behavior of the plant was precisely monitored. Moreover, the developed simulation model can be used for process optimization and controlling purposes.