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作 者:苗准 王鑫磊[1] 张蕾[1] Miao Zhun;Wang Xinlei;Zhang Lei(SINOPEC Research Institute of Petroleum Processing,Beijing 100083)
机构地区:[1]中国石化石油化工科学研究院,北京100083
出 处:《石油炼制与化工》2022年第5期83-87,共5页Petroleum Processing and Petrochemicals
基 金:国家重点研发计划资助项目(2017YFB0306501)。
摘 要:生产装置运行数据是现代炼化企业来源最广、跨度最长、规模最大的数据,充分处理好、利用好生产大数据,对优化生产、提质增效、建设智慧炼油厂具有重大意义.介绍了专门为处理智慧炼油厂生产数据设计的通用标准流程软件包SmartPec及其在催化重整数据处理上的应用.SmartPec通过数据预处理与分类建模,将催化重整装置广义线性模型的均方误差减小了76.9%、神经网络模型的均方误差减小了88.3%,准确识别出影响重整芳烃收率的4个关键要素,并提供了重整芳烃收率最大化方案.结果表明,SmartPec可大幅提高催化重整与炼油厂各类装置数据建模预测准确性,适用范围广,通用性强;可用于探测多类样本间差异特征,应用方式灵活,稳定性强;可用于多种优化任务,简单易用,方便快捷.The production data is the data with the widest source,longest-span,and largest-scale in modern refineries.It is of great significance for optimizing production,improving quality and efficiency,and building smart refinery to fully handle and make good use of production big data.The general standard process software package SmartPec was specially designed for processing the production data of the smart refinery,and its application in catalytic reforming data processing were introduced.The mean square error of the generalized linear model was reduced by 76.9%and the mean square error of the neural network model was reduced by 88.3%by data pre-processing and categorical modeling.Four key factors affecting the yield of reforming aromatics were identified accurately,and the scheme of maximizing the yield of reforming aromatics was provided.The results show that SmartPec can greatly improve the accuracy of data modeling and prediction of catalytic reforming and various units in refinery plants,with a wide range of applications and strong versatility;it can be used to detect differential features between multiple types of samples,with flexible application mode and strong stability;it can be used for a variety of optimization tasks,easy to use,convenient and fast.
关 键 词:智慧炼油厂 大数据 催化重整 数据处理 分析流程 软件包
分 类 号:TE96[石油与天然气工程—石油机械设备]
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