基于粒子群算法的高炉热风炉煤气消耗优化方法研究

高炉煤气管网压力与流量具有不稳定性,导致煤气存在严重放散损失。该研究基于粒子群算法进行高炉热风炉煤气消耗优化。首先,基于高炉热风炉煤气消耗量的预测结果,建立一个以煤气产消平衡和煤气放散量最小为目标的高炉热风炉煤气消耗优化模型;其次,引入粒子群算法求解模型,获得最佳优化方案。实验结果表明,经设计方法优化后的高炉热风炉煤气放散量基本为0,证实了该方法可以有效降低煤气消耗。     

基于PSA-SVRM模型的钢铁企业副产煤气消耗量预测

针对钢铁企业副产煤气消耗量经验模型难以对其进行精确预测的问题,通过分析副产煤气消耗用户及其特点,按不同用户利用支持向量机对副产煤气消耗量进行分类,依托Powell算法、模拟退火法和支持向量回归机各自的性质及特点,构建了副产煤气消耗量预测模型,并依托企业实际数据对模型进行验证. 结果表明,对烧结、炼钢、连铸3个主工序60个步长的测试分类准确率分别为94.8%, 94.9%和100%,模型预测的相对平均误差分别为2.5%, 2.8%和2.1%,表明模型适用于副产煤气消耗量预测. Wilcoxon符号秩检验验证了模型的有效性.     

炼油厂两级物料平衡的数据校正方法

提出一种分两级进行物料平衡的数据校正策略。第一步,利用测量精度较高的进厂、出厂、库存计量数据进行进销存平衡数据校正;第二步,利用第一步的计算结果作为约束进行装置投入、产出和油品移动层的数据校正,该方法提高了对于显著误差的处理能力。通过一个工程数据的仿真实例验证了该方法的有效性。     

HIsmelt工艺静态模型研究

基于物料平衡、能量平衡建立了对HIsmelt工艺进行计算分析的静态模型.模型能够通过设定输入工艺操作参数,计算并预测原料和熔剂消耗、渣量及成分和产生煤气量及成分等重要参数,并能对原料、铁水成分和其他参数改变引起的变化进行计算.重点分析了产生煤气的氧化度、温度、预还原度与煤耗、氧耗及煤气量之间的关系.     

Hlsmelt工艺静态模型研究

基于物料平衡、能量平衡建立了对Hlsmelt工艺进行计算分析的静态模型.模型能够通过设定输入工艺操作参数,计算并预测原料和熔剂消耗、渣量及成分和产生煤气量及成分等重要参数,并能对原料、铁水成分和其他参数改变引起的变化进行计算.重点分析了产生煤气的氧化度、温度、预还原度与煤耗、氧耗及煤气量之间的关系.     

化工过程的数据校正和参数估计(Ⅱ)

三、复杂化工系统的过程数据校正和参数估计问题 1.问题的提出 复杂化工系统是指由许多化工单元设备按某种流程组成的一种化工过程。在进行过程分析和开发时,必须要有一套可靠的物料平衡和热量平衡数据,其中有些数据可以直接测出,有些就要通过已测数据和物料平衡、热量平衡与化学反应计量方程估算出。就是直接测量的数据也需进行校正。     

RBF神经网络预测焦化企业煤气产量

对焦炉的发生和消耗特性进行分析,找出影响煤气产量的主要影响因素,并建立径向基函数（RBF）神经网络模型进行预测,实验表明：RBF模型具有较强的非线性逼近能力,能较真实地反映煤气产量和影响因素之间的非线性关系,预测效果要优于BP神经网络模型。     

石化企业物料平衡的多层次数据校正方法

针对石化企业多层次物料平衡需求,提出了一种多层次数据校正方法和分层物料平衡策略。首先介绍了物料平衡的工程背景,从测量条件、数据转换和平衡流程等角度分析了企业物料平衡存在的问题和传统方法的不足。基于石化企业装置层、调度层、统计层的多层次物流管理模型,提出了多层次数据校正方法,并给出了统一的数学描述。该方法进一步引入层间约束关系作为某一层次的校正约束方程,增加了测量数据的冗余性。对于多层次数据校正的不一致性问题,提出以下策略:先进行工厂统计平衡,校正储罐收付量,再完成调度平衡,求出装置间的互供量,最后进行分装置平衡,完成全厂装置层物料平衡。该方法提高了数据校正结果的精度,降低了求解规模。仿真研究实例说明了方法的有效性。     

试论城市煤气建设初期的供气平衡问题及对策

我国新发展的城市煤气工程，一般都是采用边施工边供气的方法，这就出现了在初供气阶段的供需不平衡。笔者从气源生产及使用平衡，选择好工业与民用气比例，负荷预测和产供调度、规划设计等几个要点入手，探索最初供气阶段条件下的气源生产，并使之达到供气平衡。既保证煤气用户的正常用气，又使煤气公司同时兼顾社会效益和经济效益。     

合成氨厂生产气温压自补偿流量测量系统

本文介绍了一种能对合成氨厂半水煤气、变换气,弛放气等生产气进行准确计量的温度、压力自动补偿流量测量系统,监导出了DDZ-Ⅲ型仪表构成此系统时各单元仪表的转换系数及整个系统的输出电流与被测气体流量的运算关系式。     

一种新的测量数据校正方法—两步法

测量数据中所含的测量误差是影响化工过程监控质量的重要因素之一。本文提出一种新的测量数据校正方法—两步法,用于将难以求解的非线性校正问题转化为线性校正的问题,从而使得数据校正过程大为简化。文中还导出了两步法应用于反应器测量数据校正的公式。     

一种混杂系统数据校正新方法

对于既包含连续生产过程又包含离散事件的混杂系统,尤其是对于带有生产方案切换的实际生产过程,通过在物料平衡模型中引入随机调度方程,从而构造出包含随机调度方程参数变量θ的新型协调模型,然后利用一种不确定模型的协调算法对此模型进行求解,最后,通过仿真研究证实了该方法的有效性和鲁棒性.     

制碱工业生产过程的建模与仿真

针对60万吨的纯碱生产流程,建立了包括石灰石煅烧、盐水制备、盐水氨化和碳化、重碱煅烧以及蒸氨等过程基于物料平衡和能量平衡产率模型,以典型操作单元为例给出了建模细节说明,并利用工厂实际运行数据对模型的参数进行了拟合。提出了针对该模型的数据校正和MINLP优化目标函数。基于上述模型对纯碱的生产过程进行各种生产条件下制碱过程的物流和能耗的实际状态的仿真,与生产数据进行了对比,验证了模型的有效性。该模型是对制碱过程进行数据校正和过程优化的基础。     

Estimation of nitrous oxide emissions (GHG) from wastewater treatment plants using closed-loop mass balance and data reconciliation

The amount of greenhouse gases (GHG), especially, nitrous oxide (N₂O) emitted from wastewater treatment plants (WWTP) using data reconciliation and closed-loop mass balance was estimated. This study is based on a flowbased emission estimation approach which depends on the accuracy of the measurement data. To reduce the (random) measurement error, data reconciliation was used to enhance the accuracy of the flow measurements. After performing data reconciliation, N₂O emission was estimated with more precision by using the closed-loop mass balance. The results in both pilot-scale and full-scale plants show that the suggested method can easily obtain the precise flow measurement for GHG emission, which in turn, results in the accurate estimation of the N₂O amounts emitted from WWTP. Moreover, it is shown that the estimated flowrate values can be used as a software sensor, which can replace the faulty sensors and can validate the existing field measurements.     

Data reconciliation strategy with time registration for the evaporation process in alumina production

In real industrial production, many mass and heat transfer processes are influenced by high temperature, high pressure, and even strong acid or alkali conditions. In addition, some important variables cannot be measured and chemical compositions are analyzed offline with a long time delay, which leads to inaccurate measurements of the process data. In this paper, a layered data reconciliation (LDR) method based on time registration is proposed to improve the measurement accuracy and estimate unmeasured variables. Considering that the material cannot be tagged and tracked in process manufacturing, a temporal and spatial matching strategy for the process data is designed based on a time‐correlation analysis matrix which is determined to describe the correlation of each time sequence in the data matrix. Then, a layered data reconciliation model with time registration is developed by reconciling the mass balance layer and the heat balance layer separately and stepwise, and the model is solved by the state transition algorithm. Meanwhile, regular terms and engineer's knowledge are introduced into the data reconciliation model to solve the problem of insufficient redundancy. The industrial verification results from the actual industrial evaporation process indicate that the accuracy of measured values is improved by using the proposed reconciliation strategy.     

The application of nonlinear dynamic data reconciliation to plant data

We have extended a fairly comprehensive data reconciliation approach called nonlinear dynamic data reconciliation (NDDR) that was originally presented by Liebman et al. (1994, Comput. Chem. Engng, 16, 963–986). This approach is capable of reconciling data from both steady-state and dynamic processes as well as estimating parameters and unmeasured process variables. One recently added feature is the ability to detect measurement bias. Each of these features were developed and tested using computer simulation. In this paper we report the successful application of NDDR to reconcile actual plant data from an Exxon Chemicals process.     

CLOSED-LOOP DATA RECONCILIATION FOR THE CONTROL OF A BINARY DISTILLATION COLUMN

Data reconciliation is a procedure that makes use of process models along with process measurements to give more precise and consistent estimates for process variables. Data reconciliation has been traditionally used to provide a more representative set of data to calculate steady-state inventories and process yields. For dynamic systems, the use of data reconciliation is relatively nascent. This article examines the potential use of data reconciliation in closed-loop control as a filter to attenuate the noise in measurements of the controlled variables so that the controllers can access more accurate sets of data. Data reconciliation filters were implemented in simulations of a PID control system for a binary distillation column. Results showed that data reconciliation could efficiently reduce the propagation of measurement noise in control loops, so that the overall performance of the controller is enhanced.     

惠州炼油物料平衡设计与实现

物料平衡（Production Balance,PB）作为MES的一个重要模块,它利用数据校正技术,解决了流程工业企业物流数据中不准确,不一致,不完整等问题。它可以实现炼油生产物料一天一平衡功能,为生产统计人员、操作人员及管理人员提供实时的、正确的生产信息。     

CLOSED-LOOP DATA RECONCILIATION FOR THE CONTROL OF A BINARY DISTILLATION COLUMN

Data reconciliation is a procedure that makes use of process models along with process measurements to give more precise and consistent estimates for process variables. Data reconciliation has been traditionally used to provide a more representative set of data to calculate steady-state inventories and process yields. For dynamic systems, the use of data reconciliation is relatively nascent. This article examines the potential use of data reconciliation in closed-loop control as a filter to attenuate the noise in measurements of the controlled variables so that the controllers can access more accurate sets of data. Data reconciliation filters were implemented in simulations of a PID control system for a binary distillation column. Results showed that data reconciliation could efficiently reduce the propagation of measurement noise in control loops, so that the overall performance of the controller is enhanced.     

集成炼油企业生产与能量系统的生产计划优化

炼油企业通常由物料生产系统与能量系统组成。传统的企业生产计划优化通常以生产系统物流优化为主, 能量系统基于物料生产优化结果进行产能优化以满足企业级能源供需平衡。此种优化方法不仅压缩了企业整体优化空间并且降低了燃料油与瓦斯等中间产品的利用率。基于装置能耗模型与能源供需以及中间产品的产耗质量平衡关系, 建立炼油企业生产系统与能源系统的集成优化模型, 通过求解MINLP模型进而实现企业生产物流与能流的集成优化。案例实践表明, 相较于传统分步优化方法, 集成优化方法不仅有效降低了全厂的生产成本, 并且实现了生产的节能减排。