基于工业大数据的天然气净化过程能耗控制方法  

Energy Consumption Control Method of Natural Gas Purification Process Based on Industrial Big Data

作　　者：胡景梅 厉建祥 杨国栋 Hu Jingmei;Li Jianxiang;Yang Guodong(SINOPEC Research Institute of Safety Engineering Co.,Ltd.,Shandong,Qingdao,266104)

机构地区：[1]中石化安全工程研究院有限公司,山东青岛266104 [2]中石化管理体系认证(青岛)有限公司,山东青岛266071

出　　处：《安全、健康和环境》2025年第2期26-36,共11页Safety Health & Environment

基　　金：中国石化科技部科研项目(R24038),中国石化HSE管理体系要求与“三基”工作要求基层落实方法。

摘　　要：高含硫天然气净化过程的能耗约占整个天然气开发过程总能耗的80%以上,节能潜力巨大。通过深入研究高含硫天然气净化过程能耗现状、特点及能量消耗规律,完成净化装置能耗分析与优化;采集关键操作参数和能耗物耗的历史运行数据,利用神经网络建立装置关键操作参数和装置能耗之间的关系预测模型;利用智能优化算法结合神经网络关系预测模型,求取不同处理工况下装置的最优能耗值,并作为基准能耗,此时的关键操作参数优化结果为该处理工况下的基准工况。分析净化装置的能源消耗特性,建立净化装置的组合开启及负荷优化分配模型,并利用智能优化算法进行求解,找到不同处理量下能耗最低时的装置开启组合方案及对应的开启装置负荷优化分配结果;建立公用工程能耗模型,通过历史运行数据分析确定模型参数,并利用智能优化算法进行优化求解,找到能耗最低时的公用工程匹配生产方案。指导净化装置与公用工程载能工质消耗量的协同优化,有效实现能源高效综合利用。The energy consumption of high-sulfur natural gas purification process accounts for more than 80%of the total energy consumption of the whole natural gas development process,and the energy saving potential is huge.The energy consumption analysis and optimization of the purification equipment were completed by deeply studying the current situation,characteristics and energy consumption law of the purification process of high sulfur natural gas.The historical operation data of key operating parameters and energy consumption were collected,and the relationship prediction model between key operating parameters and energy consumption was established by using neural network.Intelligent optimization algorithm combined with neural network relationship prediction model was used to obtain the optimal energy consumption of the device under different treatment conditions as the benchmark energy consumption,and the optimization results of key operating parameters were the benchmark conditions under the treatment conditions.The energy consumption characteristics of the purification unit were analyzed,the model of combined opening and load optimization distribution of the purification unit was established,and the intelligent optimization algorithm was used to solve it,and the device opening combination scheme with the lowest energy consumption and the corresponding load optimization distribution results of the opening unit were found under different processing volumes of the whole plant.The energy consumption model of public projects was established,the model parameters were determined through the analysis of historical operation data,and the intelligent optimization algorithm was used to optimize the solution,and the matching production scheme of public projects with the lowest energy consumption was found.This study will guide the collaborative optimization of the consumption of energy-carrying working medium between the purification device and the public project,and effectively realize the efficient and comprehensive utiliza

关 键 词：天然气净化 大数据 公用工程 能源综合利用 预测 

分 类 号：TE64[石油与天然气工程—油气加工工程]