An Minlp Formulation for Scheduling the Cleaning of Heat Exchanger Networks Subject to Fouling and Ageing

Fouling is an age-old problem in many process industries. It is responsible for large energy and throughput losses, resulting in financial penalties and negative environmental impact. One effective mitigation strategy is the regular cleaning of fouled heat transfer devices. Optimization tools can be used to schedule the timing of cleaning actions in order to minimize the cost of fouling and impact on productivity. In this work, the case where two cleaning methods are available is considered; therefore, the cleaning mode as well as the optimal cleaning intervals and the unit to be cleaned have to be determined. The two cleaning modes differ in their effectiveness in removing aged material. Ageing is assumed to transform the initial, soft, deposit, named ‘gel’, to a more cohesive material, named ‘coke’. An example would be a crude-oil preheat train where the operator has a choice between cleaning-inplace using solvents or mechanical cleaning wherein the unit has to be isolated for treatment. This aspect of choice has not been considered in previous studies of heat exchanger cleaning optimization. A mixed integer nonlinear programming (MINLP) problem is formulated for a heat exchanger network (HEN). Solutions are generated for the cases where ageing is quantified using a (i) simple twolayer model; (ii) temperature dependent two-layer model. The benefits of mixed-cleaning campaigns and the need for experimental data are highlighted.