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首页> 外文期刊>Journal of natural gas science and engineering >Optimization of mixed refrigerant systems in low temperature applications by means of group method of data handling (GMDH)
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Optimization of mixed refrigerant systems in low temperature applications by means of group method of data handling (GMDH)

机译：通过分组数据处理（GMDH）优化低温应用中的混合制冷剂系统

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Over the past decades, increasing attention has been paid to optimal design and operation of energy intensive industries. In this paper, a multi-hybrid model with high estimation capability has been applied for prediction of optimum consumed power. Consumed power is the most important factor for cascade refrigeration systems in which efficient estimation of this factor in various operating conditions is essential. The purpose of this paper is to present a new multi-hybrid Model in which six input variables consist of methane, ethane, propane, and nitrogen components composition along with suction and discharge pressures have been employed in order to estimate and predict the optimal consumed power. Having replaced by pure ethylene cycle in the olefin plant of the Tabriz Petrochemical Complex, the one and two stage-cascade cycles are modeled continuously by the proposed model. A hybrid group method of data handling (GMDH) along with linking between Aspen HYSYS and MATLAB software, optimized with Genetic algorithm (GA), is herein proposed to obtain efficient polynomial correlation to estimate optimal consumed power for these two cascade cycles. Results show that the proposed multi-hybrid model is superior to non-linear programming techniques for obtaining the optimum consumed power of cascade refrigeration cycles and finding the values of optimizing variables. (C) 2015 Elsevier B.V. All rights reserved.
机译：在过去的几十年中，人们越来越关注能源密集型产业的优化设计和运营。在本文中，具有高估计能力的多混合模型已经被用于预测最佳消耗功率。消耗功率是级联制冷系统的最重要因素，在该系统中，必须有效估算各种运行条件下的该因素。本文的目的是提出一个新的多混合模型，其中六个输入变量由甲烷，乙烷，丙烷和氮组分组成以及吸气和排气压力组成，用于估计和预测最佳消耗功率。在大不里士石油化工总厂的烯烃工厂中，用纯乙烯循环代替后，通过所提出的模型对一个和两个级联循环进行了连续建模。本文提出了一种混合数据处理组方法（GMDH），以及经过遗传算法（GA）优化的Aspen HYSYS和MATLAB软件之间的链接，以获取有效的多项式相关性，以估算这两个级联循环的最佳功耗。结果表明，所提出的多混合模型在获得级联制冷循环的最佳消耗功率并找到优化变量的值方面优于非线性编程技术。 （C）2015 Elsevier B.V.保留所有权利。

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