| Abstract: |
Optimization of cleaning schedule for heat exchanger network (HEN) subject to fouling is a well-known mixed integer nonlinear programing problem. In this study, we present a dynamic mathematical model to be able to describe the performance declination of HEN along with its fouling proceeding and explore how the uncertainty of model parameters can affect the decision of its optimal cleaning schedule by using Monte Carlo simulation approach and genetic algorithm. A case study with a HEN system consisting of 10 unit heat exchangers shows that the average cost saving expected by adopting the optimal cleaning schedule is only slightly varied even though the different extent of uncertainty is considered. However, the variation of the individual expected cost savings for different scenarios clearly increases with the increase of the extent of uncertainty, which implies that there is a risk that the determined optimal cleaning schedule can be far away from its actual one for a specific case. This risk arising from the uncertainty of the model parameters should be carefully considered in order to make a reasonable decision for the cleaning schedule of a HEN. |