硫回收装置炉膛BTEX连续排放在线软分析仪的研制

Satyadileep Dara, S. Ibrahim, A. Raj, I. Khan, Eisa Salem Al Jenaibi
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引用次数: 0

摘要

sru炉内苯、甲苯、乙苯、二甲苯(BTEX)的高温氧化是防止下游催化转化器克劳斯催化剂失活的有效解决方案。然而,由于市场上缺乏商用在线分析仪,现有的sru没有监测克劳斯炉BTEX排放的手段。这通常会导致炉内温度过高,高达1150°C,以确保BTEX的破坏。这样的高温增加了燃气消耗和CO排放,降低了硫的回收效率。为了获得炉膛出口BTEX的连续指示,建立了炉膛出口BTEX在线软测量模型来预测炉膛出口BTEX浓度。随后,该软传感器将在ADNOC气体处理的一个sru中实施。BTEX软传感器的开发是基于对BTEX氧化机理的理解,基于先前建立的详细且经过验证的动力学模型,构建了一个紧凑的炉内芳烃破坏动力学模型。采用Hysys/Sulsim软件对反应炉和催化转化器进行了动力学模型和速率参数模拟。BTEX软传感器已经在各种进料条件下(特别是在酸性气体进料中H2S、CO2和碳氢化合物的相对浓度不同的情况下)通过来自不同ADNOC气体处理SRU列车的工厂数据进行了验证,以确保其鲁棒性和多样化的预测准确性。该模型预测了反应炉在各种操作条件下的BTEX排放量,偏差不超过+/- 5ppm。它还可以在合理的误差范围内预测反应炉温度(偏差为+/- 5%)和反应炉出口的物质组成。目前,该模型正在作为在线软传感器部署在ADNO气体处理的一个sru中,它可以读取进料条件,预测BTEX出口浓度并将该值写入DCS。因此,工厂操作员可以连续监测BTEX出口浓度,并将其作为降低炉内燃气共烧速率的可靠依据,以达到最佳炉温,从而提供有效的BTEX破坏和低CO排放。在线软分析仪部署在SRU炉膛后,可以对SRU炉膛BTEX排放量进行连续、高精度的预测,这是目前大多数商用软件无法在工厂实验中实现的。该方法可用于寻求优化BTEX破坏的有利手段,以提高硫的回收率,同时减少硫回收装置的燃料气体消耗和碳足迹,以降低运行成本。
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Development of an Online Soft Analyzer for the Continuous Analysis of BTEX Emissions from the Furnace of Sulfur Recovery Units
The oxidation of Benzene, Toluene, Ethylbenzene, and Xylenes (BTEX) in the furnace of SRUs at high temperature is an effective solution to prevent Claus catalyst deactivation in the downstream catalytic converters. However, the existing SRUs do not have the means to monitor BTEX emissions from Claus furnace due to lack of commercial online analyzers in the market. This often leads to excessive temperatures up to 1150 °C in the furnace to ensure BTEX destruction. Such high temperatures increase fuel gas consumption and CO emission and reduce sulfur recovery efficiency. To obtain continuous BTEX indication at the furnace exit, an online BTEX soft sensor model is developed to predict BTEX concentration at furnace exit. Subsequently, this soft sensor will be implemented in one of the SRUs of ADNOC Gas Processing. The BTEX soft sensor has been developed by constructing a compact kinetic model for aromatics destruction in the furnace based on the understanding of BTEX oxidation mechanisms derived using a detailed and well validated kinetic model developed previously. The kinetic model, including its rate parameters were incorporated into Hysys/Sulsim software, where both the reaction furnace and catalytic converters were simulated. The BTEX soft sensor has been validated with plant data from different ADNOC Gas Processing SRU trains under a wide range of feed conditions (particularly, with varying relative concentrations of H2S, CO2, and hydrocarbons in acid gas feed) in order to ensure its robustness and versatile predictive accuracy. The model predicts BTEX emissions from the reaction furnace under a wide range of operating conditions in the furnace with deviation not exceeding +/- 5 ppm. It also predicts the reaction furnace temperature (with a deviation of +/- 5%) and species composition from the furnace exit within a reasonable error margin. Presently, the model is in the process of being deployed in one of the SRUs of ADNO Gas Processing as an online soft sensor, where it can read the feed conditions, predict the BTEX exit concentration and write this value to the DCS. Thus, plant operators can monitor BTEX exit concentration on continuous basis and use it as a reliable basis to lower fuel gas co-firing rate in the furnace to achieve optimum furnace temperature that provide efficient BTEX destruction and low CO emission. The online soft analyzer, when deployed in SRU, will continuously predict BTEX emission from SRU furnace with high accuracy, which cannot be done experimentally in the plant or reliably using most of the existing commercial software. This approach can be used to seek favorable means of optimizing BTEX destruction to enhance sulfur recovery, while decreasing fuel gas consumption and carbon footprint in sulfur recovery units to reduce operating cost.
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