This paper presents an alternative model to deal with the problem of optimal energy consumption minimization of non-isothermal systems with variable inlet and outlet temperatures.The model is based on an implicit temperature ordering and the "transshipment model"proposed by . It is supplemented with a set of logical relationships related to the relative position of the inlet temperatures of process streams and the dynamic temperature intervals. In the extreme situation of fixed inlet and outlet temperatures, the model reduces to the "transshipment model". Several examples with fixed and variable temperatures are presented to illustrate the model's performance.

ABSTRACT

HighlightsA new modeling framework that exploits the synergistic combination of commercial process simulators and GDP models Our methodology allows to include easily logical relationships among alternativesThe proposed tool uses a logic based Outer Approximation algorithmThe methodology is applied to the synthesis of a methanol plant where different alternatives AbstractThe optimization of chemical processes where the flowsheet topology is not kept fixed is a challenging discrete-continuous optimization problem. Usually, this task has been performed through equation based models. This approach presents several problems, as tedious and complicated component properties estimation or the handling of huge problems (with thousands of equations and variables). We propose a GDP approach as an alternative to the MINLP models coupled with a flowsheet program. The novelty of this approach relies on using a commercial modular process simulator where the superstructure is drawn directly on the graphical use interface of the simulator. This methodology takes advantage of modular process simulators (specially tailored numerical methods, reliability, and robustness) and the flexibility of the GDP formulation for the modeling and solution. The optimization tool proposed is successfully applied

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