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Work and heat are the two predominant forms of energy in the process industry. Considerable savings can be achieved by synergizing the work and heat requirements of process streams. A generalized framework for integrating heat and work simultaneously is proposed based on a mixed‐integer nonlinear programing model for work‐heat exchange network synthesis. Starting with a set of streams with known flows, temperatures, and pressures, a network of single‐shaft‐turbine‐compressors with motors/generators, valves, heat exchangers, and utility heaters/coolers is synthesized for minimized total annualized cost. In contrast to existing works, (1) streams are not preclassified as hot/cold or high/low pressure, (2) pressure changes are allowed for streams with no net pressure change, (3) liquid‐vapor phase changes are allowed, and (4) phase‐based property correlations are used. Successful application of our approach to C3 splitting yields a nonintuitive configuration. Another application of an offshore natural gas liquefaction process is also studied. © 2018 American Institute of Chemical Engineers AIChE J, 64: 2472–2485, 2018

The existing mathematical programming-based methods for simultaneous heat exchanger network synthesis (HENS) have used either match-centric or stage-centric superstructures. Most works over the past four decades have primarily used various modifications of essentially two superstructures whose configurational limitations are well established. We revisit a novel, promising, but unsuccessful, exchanger-centric superstructure proposed by Huang and Karimi (Chem. Eng. Sci.201398231245). We modify the superstructure and the associated mixed-integer nonlinear programming formulation substantially, and develop an efficient algorithm for its solution. The superstructure simply assumes a pool of two-stream exchangers, to which hot and cold streams are assigned. Given a sufficiently large pool, it embeds all possible heat exchanger network (HEN) configurations (in contrast to previous superstructures) including repeated matches, cross flows, bypasses, etc., and allows multiple utilities. The novel HEN configurations obtained for three case studies and improvements in their total annual costs highlight the advantages of the proposed superstructure and model.

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Multistream heat exchangers (MHEXs) facilitate simultaneous heat exchange between multiple streams and are mainly used in energy-intensive cryogenic processes. Reducing the energy consumption of existing processes with MHEXs is important, but system-wide operational optimization necessitates that the heat-transfer parameters of the MHEXs are known. However, most MHEXs are practically black-boxes due to their proprietary designs and complex geometry. In this work, we present a procedure for the operational optimization of processes with MHEXs. Our procedure involves the development of a predictive model for MHEXs as the first step, followed by the illustration of operational optimization. We begin with the development of a data-driven nonlinear programming (NLP) model to synthesize an equivalent network of simple two-stream heat exchangers that best represents the operation of an MHEX. We then demonstrate our predictive modeling procedure on the main cryogenic heat exchanger (MCHE) from an existing natural gas liquefaction plant. Finally, we use the equivalent network of two-stream exchangers in the operational optimization of an example C3MR process.