Abstract
Abstract Fouling in heat exchangers, a slow dynamic process, significantly reduces their thermal and hydraulic performance. For heat exchanger networks (HENs) in particular, mitigation alternatives are needed to restore a profitable and safe operation. Controlling the flow rate distribution in parallel branches of the network is one option, periodically cleaning selected heat exchangers another. These two strategies have been traditionally addressed separately or sequentially, but there is a strong interaction between them. We propose i) a general formulation to model heat exchanger networks under fouling, suitable for ii) the simultaneous optimal control and optimal cleaning scheduling. The resulting large scale dynamic optimization problem with binary variables (MINLP) is reformulated as a mathematical program with complementarity constraints (MPCC) which is solved efficiently for networks of industrially relevant size. The benefit of integrating the two decision layers is demonstrated in a case study for a crude oil preheat train, where the simultaneous solution of the two problems leads to a 25 % savings in operational cost.
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