Optimization of Advanced Dual Refrigerant Expansion Cycle for Liquefaction

Minki Kim, S. Ryu, Jongchul Lee, Donghun Lee, Mungyu Kim, Hyunki Park, Hyobin Kim, Kihwan Lee, Taeyun Kim
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Abstract

This paper shows the sequential search algorithm that makes it possible to find the optimum operating conditions of Advanced Dual Refrigerant Expansion Cycle that is used for LNG liquefaction process. The operating conditions are key parameters in determining the overall liquefaction efficiency of system, so it is the core process to find out these optimized key parameters in LNG industries. The steps of this method are as follows. 1) Defining input variables based on understanding of liquefaction cycle and thermodynamics. 2) Setting simulation to apply the sequential search algorithm. 3) Searching sequentially several local optimum points between the upper and lower limits of several input variables considering minimum/average efficiencies and the number of points satisfied with minimum approach 4) Repeat step 3) with narrower ranges and step sizes of each input variable based on previous results. 5) Get the global (final) optimum point considering final results and realistic operation. The operating conditions of Advanced Dual Refrigerant Expansion Cycle are eventually optimized with the best overall liquefaction efficiency of system by using the sequential search method. It is directly related to economical effect in terms of the high production rate against supply power, small size of equipment and the associated pipe lines, simple system layout and so on. During searching, several local optimum points of the operating conditions can be recorded in order to compare the liquefaction efficiencies at each of points by using this method. It serves as the objective evidence to understand trends of the efficiencies calculated from variable inputs. In addition, this method can provide a variety of selecting the main equipment such as compressor, expander, heat exchanger and so on because it is possible to identify several local optimum points have similar efficiencies. This new sequential search method can be applied for the optimization of existing other gas expansion liquefaction cycles and the mixed refrigerant (MR) LNG liquefaction cycles by making adjustments to input variables e.g. MR compositions can be available input variables as well in case of MR cycles.
先进双制冷剂液化膨胀循环优化
本文给出了一种序贯搜索算法,该算法可以找到用于LNG液化过程的先进双制冷剂膨胀循环的最佳运行条件。操作条件是决定系统整体液化效率的关键参数,因此找出这些优化的关键参数是液化天然气工业的核心过程。该方法的步骤如下。1)基于对液化循环和热力学的理解,定义输入变量。2)设置仿真应用顺序搜索算法。3)考虑最小/平均效率和满足最小方法的点数,在多个输入变量的上下限之间依次搜索多个局部最优点。4)根据之前的结果,缩小每个输入变量的范围和步长,重复步骤3)。5)考虑最终结果和实际操作,求全局(最终)最优点。采用序贯搜索法,最终优化了先进双制冷剂膨胀循环的工况,使系统整体液化效率达到最佳。对供电功率的生产率高、设备及配套管线体积小、系统布置简单等直接关系到经济效益。在搜索过程中,可以记录几个局部工况的最优点,以便比较每个点的液化效率。它可以作为客观证据来理解从可变投入计算的效率的趋势。此外,这种方法可以提供多种选择的主要设备,如压缩机、膨胀机、换热器等,因为它有可能确定几个局部最优点具有相似的效率。这种新的顺序搜索方法可以应用于现有的其他气体膨胀液化循环和混合制冷剂(MR)液化循环的优化,通过调整输入变量,例如MR成分也可以作为MR循环的可用输入变量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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