2026/07/01 by Dörthe Franzisca Hagedorn, Lukas Schulze Balhorn, Niklas von der Assen +1
Engineering · #Process Optimization and Integration #Advanced Control Systems Optimization #Scheduling and Optimization Algorithms
paper · doi:10.1016/j.compchemeng.2026.109819
The current endeavor in industry to decrease the dependence on fossil fuels leads to an increasing focus on energy efficiency, also for batch processes. One major approach for increasing energy efficiency in industry is heat integration, which is an established method for continuous production processes. For batch processes, however, the time-varying energy demands need to be considered, which makes the heat integration problem more complex. Moreover, to implement heat integration in practice, a heat exchanger network needs to be designed in coordination with the batch processes. In this work, we introduce the HENSling model for designing cost-efficient heat exchanger networks by exploiting the flexibility of production schedules. The model combines two existing models from the literature: a superstructure-based formulation for the heat exchanger network synthesis and a general scheduling formulation for multipurpose batch plants. The HENSling model overcomes typical simplifying assumptions of the current literature on combined scheduling and heat integration. For a literature case study, the HENSling model increases the total annual profit by 2.7 % up to 11.6 % in comparison to different benchmark approaches. To solve the complex MINLP optimization problem globally, we propose a decomposition approach based on outer approximation. The decomposition approach significantly reduces the computing time in comparison to an out-of-the-box solver, extending the applicability of the HENSling model to a broader variety of processes. We conclude that the HENSling model is a promising tool to economically increase energy efficiency in batch processes, helping to tackle the current challenges of climate change and uncertain energy availability.