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首页> 外文期刊>Journal of Cleaner Production >Dynamic modelling, identification and preliminary control analysis of an amine-based post-combustion CO2 capture pilot plant
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Dynamic modelling, identification and preliminary control analysis of an amine-based post-combustion CO2 capture pilot plant

机译:基于胺的燃烧后二氧化碳捕集中试装置的动态建模,识别和初步控制分析

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Solvent-based post combustion CO2 capture (PCC) is considered as a mature technology for dealing with CO2 emissions from fossil-fired power plants. In this study, a mathematical black box model is developed to analyse the dynamic responses of a PCC pilot plant. The model identification reported the dynamics of variables of the key units in the plant, the absorber, rich/lean heat exchanger and desorber. Pilot plant dynamic data were used to develop a data-driven model for each unit operation. Individual models were integrated to produce a simplified 4 x 3 PCC process model of the PCC plant. The fastest dynamic with a time constant ranging from 2 to 3 min featured in the relationship between power plant flue gas flow rate and CO2 concentration in the absorber off gas. Whereas, the slowest response with a process time constant between 9 and 27 min occurred in CO2 concentration at the top of the stripper due to changes in reboiler heat duty. Preliminary control analysis using relative gain array (RGA) analysis suggested that carbon capture efficiency, CC (%), and energy performance, EP (MJ per kg of CO2 captured), can be controlled by manipulating the lean solvent flow rate and reboiler heat duty, respectively. The proposed control structure was tested and tracked CC and EP random set point step changes in the range between 7 -25 h and 4-5 h respectively. This study contributes to understanding transient variable behaviours in PCC plants; concurrent with current industrial requirements for controllability and flexible operation of PCC plants, in response to the dynamics of power plant load, electricity and carbon prices. (C) 2015 Elsevier Ltd. All rights reserved.
机译:基于溶剂的燃烧后CO2捕集(PCC)被认为是处理化石发电厂CO2排放的成熟技术。在这项研究中,开发了一个数学黑匣子模型来分析PCC中试工厂的动态响应。模型识别报告了工厂中关键单元,吸收器,富/贫热交换器和解吸器的变量动态。中试工厂动态数据用于为每个单元操作开发数据驱动的模型。集成了各个模型,以生成PCC工厂的简化4 x 3 PCC工艺模型。电厂烟道气流速与吸收塔尾气中CO2浓度之间的关系具有最快的动态变化,时间常数介于2到3分钟之间。然而,由于再沸器热负荷的变化,汽提塔顶部的CO2浓度出现了最慢的响应,过程时间常数在9至27分钟之间。使用相对增益阵列(RGA)分析的初步控制分析表明,可以通过控制稀溶剂流速和再沸器热负荷来控制碳捕集效率CC(%)和能源性能EP(MJ / kg捕集的二氧化碳) , 分别。测试了所提出的控制结构,并跟踪了CC和EP随机设定点阶跃变化(分别在7 -25小时和4-5小时之间)。这项研究有助于理解PCC工厂中的瞬态变量行为。响应当前工业对PCC电厂的可控性和灵活运行的要求,以响应电厂负荷,电力和碳价的动态变化。 (C)2015 Elsevier Ltd.保留所有权利。

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