Abstract
Abstract Recent growth in world-wide consumption of natural gas highlights its immense importance as a source of primary energy. Liquefied natural gas (LNG) is the most economic way to transport natural gas over long distances. Main Cryogenic Heat Exchanger (MCHE) is a very critical equipment in an energy intensive LNG plant. To that end, modeling MCHE is the inevitable first step in the optimization of LNG plant operation. In this paper, we develop a model that is designed to simulate and predict the performance of an existing MCHE without knowing its physical details. The concept of superstructure representation is employed to derive an equivalent 2-stream heat exchanger network. The objective is to address the rating of an existing MCHE or the prediction of its performance rather than finding the area for a design or minimizing the cost. We use a mixed-integer nonlinear programming (MINLP) approach to select the best network that describes an existing MCHE. An example case is also presented to assess the ability of our model in predicting the performance of a MCHE.
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