Energy saving and pollution reduction through optimal scheduling of cleaning actions in a heat exchanger network

Heat exchanger fouling may impair energy recovery in Heat Exchanger Networks (HENs), thereby increasing the energy intensity of production processes. Fouling growth on the heat-transfer surfaces of the exchangers can be monitored to mitigate its adverse effects, using measurement data that also enable scheduling exchanger cleaning when economically justified. The research builds on the authors' previous work devoted to different measurement-aided monitoring methods of fouling thermal resistance, where the method based on the least -square approach to measurement data is the preferred one. The aim is to apply the preferred approach to and perform a case study on the optimization of scheduling of cleaning actions on heat exchangers operated in a HEN. The avoided HEN operating cost is employed as an objective function to be maximized by the optimal cleaning schedule that also has to satisfy a set of constraints related to the timing of cleaning actions. The mathematical formulation of the schedule optimization problem is simplified to make solution finding easier. The case study uses historical operation records covering three years of the real-life HEN composed of 26 shell-and-tube heat exchangers working continuously in connection with a Crude Distillation Unit. Having identified historical time characteristics of the thermal resistance of fouling in all the heat exchangers, one can retroactively determine optimal HEN cleaning schedules. The optimization results are discussed, considering their economic aspects and potential for energy saving and pollution reduction.

Automated summary

Heat exchanger fouling can increase the energy intensity of production processes by impairing energy recovery in Heat Exchanger Networks (HENs). Measurement data can be used to monitor fouling growth and schedule exchanger cleaning. This research applies a preferred measurement-aided method to optimize scheduling of cleaning actions in a HEN, with the objective of maximizing avoided operating costs while satisfying timing constraints. A case study using historical operation records demonstrates the economic and energy-saving benefits of the optimization results.