Dyn2Heat – MILP Heat Exchanger Network Design for Batch Processes via Dynamic Optimization

Nowadays, the energy efficiency of batch processes is getting increasing attention. Heat integration is an established approach to increase energy efficiency. However, compared to continuous processes, the temporally dynamic behaviour of batch processes introduces additional complexity to the heat exchanger network design problem. Furthermore, including investment costs of heat exchangers in the economic optimization problem requires spatial modelling of the heat exchangers. The spatial modelling usually leads to nonlinearities, which can lead to computational intractability. In our work, we demonstrate that both, the temporal and the spatial temperature profiles in a heat exchanger network for batch processes, can be modelled efficiently by differential equations. We introduce the Dyn2Heat model, a dynamic optimization model for heat exchanger network design for batch processes. The Dyn2Heat model considers the economic trade-off between process duration, investment costs for heat exchangers and operational costs for utility supply. At the same time, the dynamic formulation makes the model computationally efficient in comparison to a nonlinear algebraic formulation and applicable to complex systems involving several possible heat exchangers.