Abstract
AbstractWith liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data‐driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large‐scale industrial chemical systems.
Highlights
Large scale production of liquefied natural gas (LNG) typically involves the use of complex and energy-intensive cascade refrigeration cycles
Achieving global surrogate model accuracy is not the goal in this methodology and creating a perfect global approximation may bring about original issues that we wish to address such as computational expense and extreme nonlinearity
The optimization of processes implemented within process simulators is a considered task, to ensure success many moving parts were combined in this work
Summary
Large scale production of liquefied natural gas (LNG) typically involves the use of complex and energy-intensive cascade refrigeration cycles. In terms of its configuration, the precooling cycle in the CryoMan Cascade configuration utilizes a “heavy” mixed refrigerant that comprises of ethane, propane and n-butane, to cool down the natural gas stream and the refrigerant stream from the liquefaction cycle. This heavy refrigerant provides cooling, in a series of two multistream heat exchangers (MSHEs), at two evaporating pressures (low pressure (LP) heavy refrigerant and high pressure (HP) heavy refrigerant). The original HYSYS code for the CryoMan cascade rigorous model can be shared upon request
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