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Distillation is an energy-intensive process, and it is vital that strategies are developed to improve these processes’ sustainability. Synthesis of heat-integrated distillation sequences (HIDiS) plays a vital role in such a task. By identifying and integrating heat sources and sinks within distillation sequences, these configurations enable effective heat recovery and utilization, leading to reduced energy consumption and environmental impacts. The present work presents a new superstructure-based model with a Pinch-based operator for implicit heat integration (i.e., prediction of heat integration costs) and a stochastic solution approach for developing efficient HIDiS. Explicit heat integration (definition of heat exchanger matches) is then performed in the second part of the method. Two examples in the literature were used to validate the method. In both cases, the strategy presented was able to attain solutions with better total annual costs than those from the literature (15.8 and 11.5% lower). Solutions found with the present approach presented a greater degree of heat integration than those from the literature: more heat recovery units are present with considerably greater total heat duty (about twice greater in example 1, for instance).

In a growing energy consumption world, energy efficiency has become mandatory. In this context, the design of heat exchanger networks (HEN) is of crucial importance, but most of the approaches to HEN design consider only shell and tube (S&T) heat exchangers with a perfect counter current heat transfer. However, the 1-2 heat exchanger, (one shell pass, and two tubes pass), is likely the most common in the chemical industry. In this work, we present a two steps sequential algorithm that allows the design of HEN to capture the main details of the heat exchangers (number of tubes pass, number of shells, logarithmic mean correction factors) that influence the cost estimation. The first stage is based on an extended transportation model. It uses the concept of temperature intervals and considers the possibility of heat transfer between the hot and cold streams inside those intervals. Then, it is possible the a priori calculation of the logarithmic mean temperature difference between matches, the efficiency factor, and the number of shells in series, maintaining the area linear in the model. The second step uses a superstructure with all the possible alternatives in which the heat exchangers predicted by the first stage model can exchange heat to design the final heat exchanger network.