炼油企业全厂多周期生产计划优化研究

将生产过程和公用工程作为一个整体,建立全厂的多周期生产计划模型。全厂生产计划模型在传统的生产计划模型基础上细化了装置的能耗模型和集成了公用工程优化操作模型,实现了生产过程系统与公用工程的同时优化,避免了传统方法将生产过程系统与公用工程分割开来进行优化的缺陷。本文以中国北方某大型炼油企业为例,验证了模型的有效性。     

炼油企业生产计划与重点装置工艺条件集成优化

传统的生产计划优化由于不考虑过程装置的操作优化,从而无法保证企业生产计划层与过程操作层的全局最优.为了在获得炼油企业最优生产计划的同时,确保计划优化中重点装置的操作条件可以实现,本文建立了集成装置工艺条件的炼油企业生产计划优化模型.该模型引入常减压装置侧线产品切割点温度、催化裂化装置转化率等过程工艺条件,基于物料质量平衡、产品质量指标约束等关系,进行厂级生产计划建模与求解,确定可达的装置操作条件.应用案例中重点通过与传统常减压装置侧线收率固定的生产计划方案比较,证明在满足可达的操作条件下,集成装置工艺条件操作范围的生产计划优化模型,可以实现更高的全厂利润与更优的装置收率分布,同时优化结果对炼厂实际生产更具有指导意义.     

受流股分流限制的石化工艺装置换热网络分析

石化工艺装置在工艺和流程优化的基础上,通过夹点分析可以确定换热网络的最小热、冷公用工程量;同时,为增加装置热能回收利用效率,通常利用夹点之下的余热生产相应压力等级的蒸汽。但是,在工程实践中,由于石化装置冷物流的分流限制,导致夹点之上的热量并不能全部用于加热冷物流,不可避免的引起热量穿越夹点换热。基于夹点技术,建立流股受分流约束的换热网络混合整数线性规划模型。将建立的模型应用于某延迟焦化装置,通过模型求解,获取不可避免的穿越夹点的换热量,指出在夹点附近处冷、热流股的合理匹配方案,并对比分析受流股分流限制和不受流股分流限制的冷、热公用工程,结果表明建立的模型能够为石化工艺装置换热网络设计或改造提供技术支持。     

一个直实化工厂蒸汽网络系统的建模与优化

对蒸汽网络系统进行建模与优化,可以在系统配置和操作条件满足公用工程要求的前提下,以最小产汽量为目标,实现化工厂的节能运行.本文利用在一个真实化工厂现场调研得到的实际数据,对该化工厂的蒸汽网络系统进行建模,得到LP(线性规划)和MINLP(混合整数非线性规划)模型,用线性规划算法和改进文化差分算法分别对模型进行求解,并与现场实时数据和LINGO计算结果进行对比.计算结果显示,MINLP模型更好的描述了该蒸汽网络系统,并达到了可观的优化效果,可在满足生产需求的条件下,减小锅炉产汽量和放空量,达到降低成本、提高经济效益的效果.     

一个真实化工厂蒸汽网络系统的建模与优化

对蒸汽网络系统进行建模与优化,可以在系统配置和操作条件满足公用工程要求的前提下,以最小产汽量为目标,实现化工厂的节能运行。本文利用在一个真实化工厂现场调研得到的实际数据,对该化工厂的蒸汽网络系统进行建模,得到LP(线性规划)和MINLP(混合整数非线性规划)模型,用线性规划算法和改进文化差分算法分别对模型进行求解,并与现场实时数据和LINGO计算结果进行对比。计算结果显示,MINLP模型更好的描述了该蒸汽网络系统,并达到了可观的优化效果,可在满足生产需求的条件下,减小锅炉产汽量和放空量,达到降低成本、提高经济效益的效果。     

基于分析的乙烯装置蒸汽系统操作优化

针对乙烯装置蒸汽系统的操作参数优化问题,从系统能效视角提出了一种基于分析的优化方法。在建立蒸汽供应和转换设备模型的基础上,依据蒸汽系统的结构建立了各级蒸汽的平衡模型和约束方程。基于Aspen Plus流程模拟软件建立了乙烯过程的流程模拟系统,建立了可计算蒸汽和动力需求的非线性黑箱模型。通过集成蒸汽平衡模型、设备模型和流程模拟黑箱模型,以蒸汽系统能效最大为优化目标,采用两步计算方法,可得到蒸汽系统内各设备的最优操作条件。乙烯装置的实例分析验证了该方法的有效性。     

物料平衡在惠州炼化的构建与应用

通过构建物料平衡系统,惠州炼化实现了单装置和全厂物料每日高精度平衡,使全厂和各装置投入、产出和公用工程消耗以报表的形式实时展现,为生产管理人员和统计人员提供了准确的信息。惠州炼化在物料平衡的基础上融入了价格管理体系,创建出经济核算模型,对各装置和全厂进行成本利润日测算,强化了生产组织和操作调整的针对性,能够对市场变化及时做出反应。     

基于生产计划模型制定乙烯原料优化方案

将乙烯原料优化与企业生产计划优化相结合,既能保证乙烯生产企业的原料供给,又有利于提升石化企业的整体经济效益,实现了炼化一体化的目标.本文通过建立裂解产物收率模型预测乙烯裂解过程产物收率,并将其与图形化石化工业模拟系统(GIOPIMS)相集成,替换原有模拟系统中乙烯热裂解收率的固定经验值,建立起了与乙烯原料优化相结合的生产计划模型,并通过求解得到了最佳的排产方案.实例表明,集成后的系统不仅能够准确给出乙烯原料优化方案,优化了原料选择和配置,提高了企业经济效益,同时使生产计划模型更加符合实际情况.得到的优化方案效果更好.     

炼化企业生产数据集成应用平台的设计与实现

智能炼厂建设的核心是对生产过程的智能管控,建立生产计划优化模型和各类装置的模拟优化模型是其中的重要内容。这些模型的建立和应用涉及到企业多个应用系统中的大量数据,收集、整合各类数据是智能优化工作中重要而繁琐的工作,针对某炼化企业智能优化工作的需求,开发了生产数据集成应用平台。数据集成应用平台的开发采用了先进的B/S技术、数据库技术,通过定时对各类生产数据进行采集整理,生成完善的模型支撑数据库,实现了各类装置数据的快速、方便查询;所具有的数据处理功能多层次展示数据变化趋势,方便用户筛选有效数据;数据应用模版的建立,提高了优化模型建模的便利性和建模数据的可靠性。数据集成应用平台运行稳定,界面友好,效率高,系统响应速度小于15秒,为计划优化模型和过程模拟优化模型的建模及应用提供了及时、准确的数据支撑,为进一步的企业生产优化和智能炼厂建设奠定了数据基础。     

炼油企业全厂生产计划系统设计与开发

采用面向对象方法,使用统一建模语言进行炼油企业生产计划系统的需求分析和系统设计。首先描述了生产计划系统的功能需求,包括数据管理、模型管理、模型发生器和过程分析等,并且采用序列图初步分析了系统核心功能生产计划的实现过程。在此基础上,进行系统的数据模型设计,包括公用数据模型,装置数据模型和物流数据模型。上述数据模型描述了炼油企业生产流程的静态结构和生产计划活动的信息。最后开发了软件OpTechPlan,并且在中国北方某炼油企业得到了初步的应用。     

Plantwide optimization via real-time optimization with persistent parameter adaptation

Determining the optimization scope is a major issue whenever implementing Real-time Optimization (RTO). Ideally, the optimization problem should encompass the whole plant and not a single unit, which represents only a local subset of the problem. However, if the standard RTO method, the two-step approach (TS), is applied to the entire plant, the whole system needs to be at steady-state (SS) in order to initiate the optimization cycle. This condition is rarely found in practice. One alternative is to apply Real-time Optimization with Persistent Parameter Adaptation (ROPA). ROPA is an RTO variant that integrates online estimators to the standard TS framework and avoids the need of waiting for steady-state to trigger the optimization cycle. However, the problem shifts to obtaining a dynamic model of the entire plant, which can be challenging and time consuming. This paper proposes a variant of ROPA, named asynchronous ROPA (asROPA), where the plant-wide model is partitioned into submodels and, depending on their characteristics, their parameters are updated using either online or steady-state estimators. Consequently, it is not necessary to obtain a dynamic model for the whole process. This asynchronous updating strategy allows the plant-wide model to be up-to-date to the process and the plant-wide optimization can be scheduled at any arbitrary time. The new strategy is applied to a case study consisting of a system whose model can be partitioned into a separation and a reaction submodel. The plant-wide results indicate that asROPA reacts much faster to the disturbances in comparison to the TS approach, improving the overall economic performance and is able to drive the system to the plant-wide optimum. Additionally, a strategy for partitioning the process and choosing the estimation strategy for each partition is proposed.     

复杂生产流程协同优化与智能控制

我国流程行业原料来源复杂,如何优化调控工艺指标使复杂生产流程适应原料波动,是保障产品质量、降低物耗能耗的关键.本文结合全流程、工序、反应器等不同生产层级的工艺特点,系统研究复杂生产流程协同优化和智能控制方法.针对全流程多工序关联的特点,提出了操作模式优化方法和操作模式动态匹配的全流程多工序协同优化方法;针对单元工序多反应器级联的特点,分析了工序内不同反应器的物质转化效率差异,提出了反应器指标梯度协同优化方法;针对反应器多反应共存、工况多变的特点,研究了基于完备状态空间的动态特性描述框架,建立了竞争-促进反应体系机理模型,提出了工况全覆盖的模型参数自主辨识方法和基于分工况智能综合调节的反应器操作参数精细化调控方法.通过锌冶炼智能工厂建设案例阐述了所提方法在提高工艺原料适应能力、生产效率、质量稳定性等方面的成效.最后,结合我国流程行业智能化发展现状和需求,分析了需进一步研究的问题.     

Data-based multiple-model prediction of the production rate for hematite ore beneficiation process

The prediction of the production rate of the hematite ore beneficiation process is important to plant-wide optimization. This paper presents a data-based multi-model approach to predict the production rate with multiple operating modes. The inputs of the predictive model are the performance indices of each unit process, and the output is the global production index (the production rate) of the hematite ore beneficiation process. The multiple models are developed by integrating the fuzzy clustering algorithm and machine learning algorithm. A global model, Takagi–Sugeno–Kang fuzzy model, and multiple neural network model were compared using the data obtained from a practical industrial process, and the effectiveness of the proposed algorithm was proven.     

面向全流程优化的选矿过程仿真系统研发

选矿过程的物流是各环节有机联系的纽带,进行选矿物流仿真实验研究对实现优化操作与优化控制生产具有重要的意义。面向选矿过程生产全流程的优化,为了对选矿全流程的物流与生产过程进行仿真,研究选矿过程各个单元的操作与控制对生产全流程指标的影响,建立了基于物料平衡和金属守恒原理的选矿过程物流模拟数学模型总体框架;设计开发了选矿过程物流仿真系统,包括实验软硬件平台结构、功能及其对控制与优化系统的通讯接口。该系统主要侧重其物流的仿真,及其操作与控制对选矿全流程指标(即金属回收率、精矿品位和产量等)的影响,从而为全流程优化的研究提供依据。在所开发的平台上开展了仿真实验研究,实验结果验证了所研发实验平台的有效性。     

Data-based adaptive online prediction model for plant-wide production indices

A data-based adaptive online prediction model is proposed for plant-wide production indices based on support vector regression, a general method which we customized specifically to model very large data sets that are generated dynamically and periodically. The proposed model can update its parameters online according to the statistical properties of the training samples. Further, in order to improve the prediction precision, each sample is weighted with a dynamic penalty factor that considers the effect of each sample on the prediction model accuracy. Moreover, a customized procedure is introduced to handle large training sets. After having been convincingly evaluated on benchmark data, effectiveness and performance of our approach for plant-wide production indices is demonstrated using industrial data from an operating ore dressing plant over a range of scale in training data set size. The higher accuracy and shorter computation times than existing methods suggest that it may prove advantageous in actual application to dynamic production processes.     

镁砂熔炼过程全厂电能分配实时多目标优化方法研究

镁砂熔炼过程具有多工况、群炉并行生产、高能耗等特点.在全厂供电容量约束下,为了最大化能源使用效率,需要根据全厂每台炉子的工况变化实时分配电能,实现全厂镁砂单位能耗与平均品位的多目标优化. 本文基于最小二乘支持向量机技术建立了镁砂熔炼过程全厂电能分配优化模型.根据不同工况下降低镁炉供电量对镁砂熔炼过程的影响程度,提出了基于工况优先级的电能分配策略.根据主熔工况下镁砂产量与品位指标函数的特性分析,推导出 主熔工况下电能分配模型决策变量维数缩减的条件. 为了提高多目标优化算法的运行效率,设计了一种快速非支配解集构造方法,用来提高传统多目标粒子群优化算法的寻优效率. 基于标准测试问题与现场实际例子对所提出的方法进行了检验.基于现场例子的实验结果证明所提出的方法能够避免工厂出现的用电超容量情况,并且提高了全厂用电效率.     

石化企业生产计划与能量系统集成研究

应用并行工程方法对生产计划与能量系统的集成进行了分析,提出了用于确定业务流程和信息流的业务过程模型,明确了系统的并行特性,采用并行工程方法建立了并行业务过程模型,并确定了用于数据建模的数据流,从而为集成效据库管理和集成软件系统的开发奠定了基础。     

Appraising production targets through agent-based Petri net simulation of material handling systems in open pit mines

In a mining operation, significant differences between production targets in the planning stage and actual production quantities are a common issue. These differences can be related to heterogeneity of quality of ore within orebody, availability, and reliability of mining equipment, design-related problems of mining activities, and external factors. One way to understand the feasibility of targeted production rates is to simulate the activities. In this paper, an agent-based Petri net simulation model is proposed to check whether production targets are feasible, and the extent to control head grade in mineral processing. The model evaluates different realizations under the uncertain operation environment. Moreover, the fuel consumption of haul trucks is tracked in the proposed model. A case study was carried out to evaluate the proposed approach in an open pit mine. The research outcomes showed that this approach could assist in capacity installation, mineral processing design, and fuel tracking in mining operations.     

Joint production,inspection and maintenance control policies for deteriorating system under quality constraint

This paper studies the integration of production, sampling inspection and age-based maintenance planning for an unreliable production system subject to gradual deterioration. The deterioration process of the production unit has a twofold effect on its reliability and product quality. To mitigate the effects of such deterioration, an age-based major maintenance can be conducted, which denotes a perfect repair that restores the production unit to initial conditions. The quality control is performed through a sampling plan that inspects a fraction of the parts produced. The problem further considers that the optimal decision must be determined under a constraint on the outgoing quality required by the final customer. In this domain, standard sampling procedures are applicable only to production process that are statistically stable and under control. Nevertheless, such sampling plans disregard the interaction with production management and maintenance issues and they do not consider the effects of deterioration. In this paper a new joint control policy considering the interactions between production-quality and maintenance is proposed. A stochastic mathematical model is developed through specialized optimization techniques to solve such quality constrained problem. Numerical examples are provided to illustrate the usefulness of the proposed approach and to study the interactions between production-quality and maintenance strategies. An extensive sensitivity analysis and a comparative study are conducted to illustrate the effectiveness of the obtained joint control policy.     

Knowledge intensive Petri net framework for concurrent intelligent design of automatic assembly systems

The integration of design and planning of flexible assembly system has been recognized as a tool for achieving efficient assembly in a production environment that demands assembly with a high degree of flexibility. This paper proposes a concurrent intelligent approach and framework for the design of robotic flexible assembly systems. The principle of the proposed approach is based on the knowledge Petri net formalisms, incorporating Petri nets with more general problem-solving strategies in AI using knowledge-based system techniques. The complex assembly systems are modeled and analyzed by adopting a formal representation of the system dynamic behaviors through knowledge Petri net modeling from the specifications and the analysis of those models. A template is first defined for a knowledge Petri net model, and then the models for assembly system individuals are established in the form of instances of the template. The design of assembly systems is implemented through a knowledge Petri net-based function–behavior–structure model. The research results show that the proposed knowledge Petri net approach is applicable for design, simulation, analysis and evaluation, and even layout optimization of the flexible assembly system in an integrated intelligent environment. The integration of assembly design and planning process can help reduce the development time of assembly systems.