CN108333943B - On-line optimization method of crude oil blending based on incremental mode - Google Patents

On-line optimization method of crude oil blending based on incremental mode Download PDF

Info

Publication number
CN108333943B
CN108333943B CN201810162826.6A CN201810162826A CN108333943B CN 108333943 B CN108333943 B CN 108333943B CN 201810162826 A CN201810162826 A CN 201810162826A CN 108333943 B CN108333943 B CN 108333943B
Authority
CN
China
Prior art keywords
blending
formula
component
attribute
increment
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201810162826.6A
Other languages
Chinese (zh)
Other versions
CN108333943A (en
Inventor
钱锋
钟伟民
何仁初
杜文莉
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
East China University of Science and Technology
Original Assignee
East China University of Science and Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by East China University of Science and Technology filed Critical East China University of Science and Technology
Priority to CN201810162826.6A priority Critical patent/CN108333943B/en
Publication of CN108333943A publication Critical patent/CN108333943A/en
Application granted granted Critical
Publication of CN108333943B publication Critical patent/CN108333943B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Computation (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Production Of Liquid Hydrocarbon Mixture For Refining Petroleum (AREA)

Abstract

本发明公开了基于增量模式的原油调合在线优化方法，包括调合任务参数初始化，设置优化周期、各属性优化方式与目标函数权重，按照预定优化周期获取各调合组分属性数据与累积调合质量属性积，更新调合头属性增量、组分配方增量、组分流量增量上下限约束，求取当前优化周期各调合组分的最优配方，并送至调合控制系统执行。该方法针对炼油企业原油调合生产过程，以调合原油属性合格与调合成本最低为优化目标，可同时实现原油属性向上限优化与向下限优化，按照一定优化周期计算组分最优配方，并将优化结果送至调合控制系统执行，保证调合原油属性质量满足常减压装置要求的同时兼顾经济最优，从而实现调合过程实时优化，提高炼油企业经济效益。

Figure 201810162826

The invention discloses an on-line optimization method for crude oil blending based on an incremental mode. Blending quality attribute product, update blending head attribute increment, component formula increment, component flow increment upper and lower limit constraints, obtain the optimal formula of each blending component in the current optimization cycle, and send it to the blending control System executes. This method is aimed at the crude oil blending production process of oil refining enterprises, and takes the qualified properties of blended crude oil and the lowest blending cost as the optimization goals, and can realize the optimization of crude oil properties to the upper limit and the lower limit at the same time, and calculate the optimal formula of components according to a certain optimization period. The optimization results are sent to the blending control system for execution to ensure that the properties and quality of the blended crude oil meet the requirements of the atmospheric and vacuum unit while taking into account the economical optimization, so as to realize the real-time optimization of the blending process and improve the economic benefits of the refining enterprise.

Figure 201810162826

Description

基于增量模式的原油调合在线优化方法On-line optimization method of crude oil blending based on incremental mode

技术领域technical field

本发明涉及炼油企业原油加工领域，尤其是原油调合的优化方法，是一种基于增量模式的原油调合在线优化方法。The invention relates to the field of crude oil processing in oil refining enterprises, in particular to an optimization method for crude oil blending, which is an on-line optimization method for crude oil blending based on an incremental mode.

背景技术Background technique

为满足常减压装置和下游装置对原料质量的要求与炼油企业的经济效益，原油调合中必然要采用相应的优化技术。在原油调合实际工业中，炼油企业大多采用手工计算或离线优化技术获得各调合组分的初始配方，并在整个调合过程中保持配方不变，然而当组分油的属性在一定范围内产生波动时，如果仍然采用调合方案给出的初始配方会造成调合后原油属性波动大，常减压装置运行不稳，影响到炼油企业的正常生产任务与经济效益。In order to meet the raw material quality requirements of atmospheric and vacuum units and downstream units and the economic benefits of oil refining enterprises, corresponding optimization techniques must be adopted in crude oil blending. In the actual crude oil blending industry, most refineries use manual calculation or offline optimization technology to obtain the initial formula of each blending component, and keep the formula unchanged throughout the blending process. However, when the properties of the component oils are within a certain range When internal fluctuations occur, if the initial formula given by the blending plan is still used, the properties of the crude oil after blending will fluctuate greatly, and the operation of the atmospheric and vacuum units will be unstable, which will affect the normal production tasks and economic benefits of the oil refining enterprise.

传统的优化方法其结果一般为绝对量，在离线应用中影响不大，但对于在线应用，由于过程容易受到各种干扰的影响，优化结果也会发生较大的变化，如果采用绝对量结果，即使是当前工况下最优值，仍然会因为调整步幅过大而容易导致控制不平稳、生产过程波动大。The results of traditional optimization methods are generally absolute quantities, which have little effect in offline applications. However, for online applications, since the process is easily affected by various disturbances, the optimization results will also change greatly. Even if it is the optimal value under the current working conditions, it is still easy to cause unstable control and large fluctuations in the production process because the adjustment step is too large.

发明内容SUMMARY OF THE INVENTION

本发明针对炼油企业原油调合生产中采用手工计算配方或离线优化配方无法适应实际生产过程中组分属性波动等情况，导致调合产品质量不合格、效益较低的问题，提出一种基于增量模式的原油调合在线优化方法。在满足一系列约束的前提下，以调合原油属性合格与调合成本最低为优化目标，同时可实现原油属性向上限优化与向下限优化，最后将所得优化配方送至相应控制器，避免实际生产中组分属性波动引起的原油不合格，从而满足常减压装置和下游装置对原料质量的要求，并提高企业经济效益。Aiming at the problems that manual calculation formula or off-line optimized formula cannot adapt to the fluctuation of component attributes in the actual production process in the crude oil blending production of oil refining enterprises, resulting in unqualified quality and low benefit of blended products, the invention proposes a method based on increasing On-line optimization method for crude oil blending in quantitative mode. On the premise of satisfying a series of constraints, the optimization goal is to have qualified properties of blended crude oil and the lowest blending cost, and at the same time, it can realize the optimization of crude oil properties to the upper limit and the lower limit, and finally send the obtained optimized formula to the corresponding controller to avoid actual The crude oil caused by the fluctuation of component attributes in production is unqualified, so as to meet the requirements of atmospheric and vacuum units and downstream units on the quality of raw materials, and improve the economic benefits of the enterprise.

本发明的基于增量模式的原油调合在线优化方法包括以下步骤：The on-line optimization method for crude oil blending based on the incremental mode of the present invention comprises the following steps:

首先，进行调合任务参数初始化；First, initialize the parameters of the blending task;

其次，设置优化周期、各属性优化方式与目标函数权重；Second, set the optimization period, the optimization method of each attribute and the weight of the objective function;

再次，按照预定优化周期获取各调合组分属性数据与累积调合质量属性积，更新调合头属性增量、组分配方增量、组分流量增量上下限约束；Thirdly, obtain the attribute data of each blending component and the cumulative blending quality attribute product according to the predetermined optimization cycle, and update the upper and lower limit constraints of the blending head attribute increment, the component formula increment, and the component flow increment increment;

最后，求取当前优化周期各调合组分的最优配方，并送至调合控制系统执行。Finally, the optimal formula of each blending component in the current optimization cycle is obtained and sent to the blending control system for execution.

在一个或多个实施方案中，所述初始化包括：设置目标调合质量、调合原油各属性指标上下限、各调合组分油初始配方、配方上下限、最大配方变化步长、流量上下限以及价格因子。In one or more embodiments, the initialization includes: setting the target blending quality, the upper and lower limits of each attribute index of the blended crude oil, the initial formula of each blended component oil, the upper and lower limits of the formula, the maximum formula change step size, and the upper and lower flow rates. Lower bound and price factor.

在一个或多个实施方案中，所述优化方式包括调合原油属性满足上下限范围、向上限优化与向下限优化，同时兼顾调合成本最低。In one or more embodiments, the optimization method includes that the properties of the blended crude oil satisfy the upper and lower limits, optimization toward the upper limit, and optimization toward the lower limit, while taking into account the lowest blending cost.

在一个或多个实施方案中，所述原油属性包括密度、硫含量、酸值和渣油收率。In one or more embodiments, the crude oil properties include density, sulfur content, acid number, and residue yield.

在一个或多个实施方案中，调合原油属性优化为属性合格、向上限优化与向下限优化，即对于第j种属性的优化方式权重wj，当wj>0则第j种属性向下限优化，wj<0则第j种属性向上限优化，wj＝0则第j种满足属性上下限约束。In one or more embodiments, the properties of the blended crude oil are optimized into qualified properties, optimization toward the upper limit, and optimization toward the lower limit, that is, the weight w j of the optimization method for the j-th property, when w j >0, the j-th property is toward the lower limit. Lower limit optimization, w j < 0, the jth attribute is optimized to the upper limit, w j =0, the jth attribute satisfies the upper and lower limit constraints of the attribute.

在一个或多个实施方案中，调合后原油属性满足式(3)，In one or more embodiments, the properties of the crude oil after blending satisfy equation (3),

Figure GDA0002897778020000021
Figure GDA0002897778020000021

其中，

Figure GDA0002897778020000022
和
Figure GDA0002897778020000023
表示调合原油第j种属性指标上下限，Proj表示调合原油第j种属性；当属性合格时则
Figure GDA0002897778020000024
向下限优化时则Proj趋近于
Figure GDA0002897778020000025
当向上限优化时则Proj趋近于
Figure GDA0002897778020000026
in,
Figure GDA0002897778020000022
and
Figure GDA0002897778020000023
Indicates the upper and lower limits of the jth property index of blended crude oil, and Pro j represents the jth property of blended crude oil; when the properties are qualified, the
Figure GDA0002897778020000024
When the lower bound is optimized, Pro j approaches
Figure GDA0002897778020000025
When optimizing towards the upper limit, then Pro j approaches
Figure GDA0002897778020000026

在一个或多个实施方案中，所述方法以调合原油属性合格与成本最低作为目标，原油属性满足上下限范围和/或向上限优化和/或向下限优化，将调合组分配方优化转换为调合组分配方增量优化，对于第k个优化周期，采用式(1)与式(2)计算得到各调合组分配方的最优增量与当前最优配方：In one or more embodiments, the method aims to blend the crude oil with qualified properties and the lowest cost, the crude oil properties meet the upper and lower limits and/or are optimized toward the upper limit and/or the lower limit is optimized, and the formulation of the blending components is optimized. Converted to the incremental optimization of blending component recipes, for the kth optimization cycle, formulas (1) and (2) are used to calculate the optimal increment of each blending component recipe and the current optimal formula:

Figure GDA0002897778020000031
Figure GDA0002897778020000031

ri(k+1)＝ri(k)+Δri,i＝1...n (2)r i (k+1)=r i (k)+Δr i , i=1...n (2)

其中，i(i＝1,2,…,n)表示调合组分个数；j(j＝1,2,…,m)表示调合组分的原油属性个数；wp表示成本最小权值；Pricei表示第i种调合组分的价格因子；wj表示第j种属性的优化方式权重；Prozi,j表示第i种调合组分的第j种属性值；Δri Hi与Δri Lo分别表示第i种调合组分的配方增量上下限；

Figure GDA0002897778020000032
与
Figure GDA0002897778020000033
分别表示为调合头第j种属性指标增量的上下限；ΔFi Hi与ΔFi Lo分别表示为第i种组分流量增量的上下限；Δri表示第i种组分油的配方增量；ri(k+1)与ri(k)分别表示第k+1周期(下一周期)与第k周期(当前周期)时第i种组分油的配方。Among them, i(i=1,2,...,n) represents the number of blending components; j(j=1,2,...,m) represents the number of crude oil properties of the blending components; w p represents the minimum cost Weight; Price i represents the price factor of the i-th blending component; w j represents the optimization method weight of the j-th property; Proz i,j represents the j-th property value of the i-th blending component; Δr i Hi and Δr i Lo represent the upper and lower limits of the formula increment of the i-th blending component, respectively;
Figure GDA0002897778020000032
and
Figure GDA0002897778020000033
respectively represent the upper and lower limits of the j-th property index increment of the blending head; ΔF i Hi and ΔF i Lo represent the upper and lower limits of the i-th component flow increment, respectively; Δr i represents the formula of the i-th component oil Increment; ri ( k +1) and ri (k) represent the formula of the i -th component oil in the k+1th cycle (next cycle) and the kth cycle (current cycle), respectively.

在一个或多个实施方案中，采用式(4)与式(5)计算优化调合质量，即调合头的指标范围，In one or more embodiments, formulas (4) and (5) are used to calculate the optimal blending quality, that is, the index range of the blending head,

Figure GDA0002897778020000034
Figure GDA0002897778020000034

Figure GDA0002897778020000035
Figure GDA0002897778020000035

其中，

Figure GDA0002897778020000036
和
Figure GDA0002897778020000037
分别表示为使全罐原油属性指标上下限满足规定的范围而优化调合质量的属性指标应满足的指标上下限，即调合头第j种属性指标的上限和下限；VProTol表示累积调合质量属性积；VProHeel表示罐底油质量属性积；VolH表示罐底质量；VolS表示调合总质量；VolT表示已调合质量。in,
Figure GDA0002897778020000036
and
Figure GDA0002897778020000037
Respectively represent the upper and lower limits of the attribute index to optimize the blending quality in order to make the upper and lower limits of the crude oil attribute index of the whole tank meet the specified range, that is, the upper and lower limits of the jth attribute index of the blending head; VPro Tol represents the cumulative blending Mass property product; VPro Heel represents the quality property product of the tank bottom oil; VolH represents the tank bottom mass; VolS represents the total blended mass; VolT represents the blended quality.

在一个或多个实施方案中，采用式(6)与式(7)计算得到当前调合头属性增量的允许变化范围，In one or more embodiments, formula (6) and formula (7) are used to calculate the allowable variation range of the current blending head attribute increment,

Figure GDA0002897778020000041
Figure GDA0002897778020000041

Figure GDA0002897778020000042
Figure GDA0002897778020000042

其中，Protj(k)表示当前调合头第j种测量属性；

Figure GDA0002897778020000043
与
Figure GDA0002897778020000044
分别表示调合头第j种属性指标增量的上下限。Among them, Prot j (k) represents the jth measurement property of the current blending head;
Figure GDA0002897778020000043
and
Figure GDA0002897778020000044
Respectively represent the upper and lower limits of the jth attribute index increment of the blending head.

在一个或多个实施方案中，采用式(8)与式(9)计算得到当前时刻配方增量的允许变化范围，In one or more embodiments, formula (8) and formula (9) are used to calculate the allowable variation range of the recipe increment at the current moment,

Figure GDA0002897778020000045
Figure GDA0002897778020000045

Figure GDA0002897778020000046
Figure GDA0002897778020000046

其中，ri Hi和ri Lo分别表示第i种调合组分的配方上下限；rStepi Hi和rStepi Lo分别表示第i种调合组分的最大、最小配方变化步长；Δri Hi与Δri Lo分别表示第i种调合组分的配方增量上下限。Among them, r i Hi and r i Lo represent the upper and lower limits of the formula of the ith blending component, respectively; rStep i Hi and rStep i Lo represent the maximum and minimum formula change steps of the ith blending component, respectively; Δr i Hi and Δr i Lo represent the upper and lower limits of the formula increment of the i-th blending component, respectively.

在一个或多个实施方案中，采用式(10)与式(11)计算得到当前时刻流量增量的允许变化范围，In one or more embodiments, the allowable variation range of the flow rate increment at the current moment is calculated by using formula (10) and formula (11),

ΔFi Hi＝Fi Hi-Ft·ri(k) (10)ΔF i Hi =Fi Hi -F t ·r i ( k) (10)

ΔFi Lo＝Fi Lo-Ft·ri(k) (11)ΔF i Lo =Fi Lo -F t ·r i ( k) (11)

其中，ri(k)表示当前第i种组分油的配方；Fi Hi和Fi Lo分别表示第i种组分油的流量上下限；Ft表示调合头基准流量；ΔFi Hi与ΔFi Lo分别表示第i种调合组分的流量增量上下限。Among them, ri (k) represents the current formula of the ith component oil; F i Hi and F i Lo represent the upper and lower flow limits of the ith component oil, respectively; F t represents the reference flow of the blending head; ΔF i Hi and ΔF i Lo represent the upper and lower limits of the flow increment of the i-th blending component, respectively.

本发明还提供一种计算机设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其中，所述处理器执行所述程序时实现以下步骤：采用式(1)与式(2)计算得到各调合组分配方的最优增量与当前最优配方：The present invention also provides a computer device, comprising a memory, a processor, and a computer program stored on the memory and running on the processor, wherein the processor implements the following steps when executing the program: using formula (1) Calculated with formula (2) to obtain the optimal increment and current optimal formulation of each blending component formula:

Figure GDA0002897778020000051
Figure GDA0002897778020000051

ri(k+1)＝ri(k)+Δri,i＝1...n (2)r i (k+1)=r i (k)+Δr i , i=1...n (2)

其中，i(i＝1,2,…,n)表示调合组分个数；j(j＝1,2,…,m)表示调合组分的原油属性个数；wp表示成本最小权值；Pricei表示第i种调合组分的价格因子；wj表示第j种属性的优化方式权重；Prozi,j表示第i种调合组分的第j种属性值；Δri Hi与Δri Lo分别表示第i种调合组分的配方增量上下限；

Figure GDA0002897778020000052
与
Figure GDA0002897778020000053
分别表示为调合头第j种属性指标增量的上下限；ΔFi Hi与ΔFi Lo分别表示为第i种组分流量增量的上下限；Δri表示第i种组分油的配方增量；ri(k+1)与ri(k)分别表示第k+1周期(下一周期)与第k周期(当前周期)时第i种组分油的配方。Among them, i(i=1,2,...,n) represents the number of blending components; j(j=1,2,...,m) represents the number of crude oil properties of the blending components; w p represents the minimum cost Weight; Price i represents the price factor of the i-th blending component; w j represents the optimization method weight of the j-th property; Proz i,j represents the j-th property value of the i-th blending component; Δr i Hi and Δr i Lo represent the upper and lower limits of the formula increment of the i-th blending component, respectively;
Figure GDA0002897778020000052
and
Figure GDA0002897778020000053
respectively represent the upper and lower limits of the j-th property index increment of the blending head; ΔF i Hi and ΔF i Lo represent the upper and lower limits of the i-th component flow increment, respectively; Δr i represents the formula of the i-th component oil Increment; ri ( k +1) and ri (k) represent the formula of the i -th component oil in the k+1th cycle (next cycle) and the kth cycle (current cycle), respectively.

在一个或多个实施方案中，所述处理器执行所述程序时还实现以下步骤：根据本文所述的公式(4)到(11)计算得到调合头第j种属性指标的上下限、调合头第j种属性指标增量的上下限、第i种调合组分的配方增量上下限和第i种调合组分的流量增量上下限。In one or more embodiments, the processor further implements the following steps when executing the program: calculating the upper and lower limits of the j-th property index of the blending head according to formulas (4) to (11) described herein, The upper and lower limits of the jth attribute index increment of the blending head, the upper and lower limits of the formula increment of the ith blending component, and the upper and lower limits of the flow increment of the ith blending component.

本发明还提供一种计算机可读存储介质，其上存有计算机程序，该程序被处理器执行时实现本文所述的各计算步骤。The present invention also provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, implements the computing steps described herein.

附图说明Description of drawings

图1是原油管道调合在线优化控制系统结构。Figure 1 is the structure of the crude oil pipeline blending online optimization control system.

图2是原油调合在线优化方法流程图。Figure 2 is a flow chart of the crude oil blending online optimization method.

具体实施方式Detailed ways

本发明公开了一种基于增量模式的原油调合在线优化方法，针对炼油企业原油调合生产过程，以调合原油属性合格与调合成本最低为优化目标，在满足一系列约束的前提下，按照一定优化周期计算组分最优配方，并将优化结果送至调合控制系统执行，保证调合原油属性质量满足常减压装置要求的同时兼顾经济最优，从而实现调合过程实时优化，提高炼油企业经济效益。The invention discloses an on-line optimization method for crude oil blending based on an incremental mode. Aiming at the crude oil blending production process of a refinery enterprise, the optimization objectives are that the properties of the blended crude oil are qualified and the blending cost is the lowest. On the premise of satisfying a series of constraints , calculate the optimal formula of the components according to a certain optimization cycle, and send the optimization results to the blending control system for execution to ensure that the properties and quality of the blended crude oil meet the requirements of the atmospheric and vacuum unit while taking into account the economic optimization, so as to realize the real-time optimization of the blending process , improve the economic efficiency of oil refining enterprises.

本发明基于增量模式的原油调合的在线优化方法首先进行调合任务参数初始化。调合任务参数包括但不限于目标调合质量、调合原油各属性指标上下限、各调合组分油初始配方、配方上下限、最大配方变化步长、流量上下限以及价格因子等。原油属性包括本领域所周知的各种原油属性，例如密度、硫含量、酸值与渣油收率等。The on-line optimization method for crude oil blending based on the incremental mode of the present invention firstly initializes the parameters of the blending task. The parameters of the blending task include but are not limited to the target blending quality, the upper and lower limits of each attribute index of the blended crude oil, the initial formula of each blending component oil, the upper and lower limits of the formula, the maximum formula change step, the upper and lower limits of the flow rate, and the price factor, etc. Crude oil properties include various crude oil properties known in the art, such as density, sulfur content, acid number, and residue yield, among others.

因此，调合任务参数初始化可包括设置调合总质量VolS，确定罐底油质量VolH、已调合质量VolT和调合头基准流量等。包括调合原油各属性指标的上下限、配方上下限、最大配方变化步长、流量上下限以及价格因子等可根据实际的设备、生产情况和期望的油品予以确定。例如，在某些实施方案中，调合头基准流量可设在100～500吨/小时的范围内；密度下限为0.881g/ml，上限为0.911g/ml；硫含量上限为0％，上限为2.05％；酸值下限为0mgKOH/g，上限为0.75mgKOH/g；渣油收率下限为25％，上限为30％；各调合组分最大配方变化步长上限为5％，下限-5％。Therefore, the initialization of the parameters of the blending task may include setting the total blending mass VolS, determining the bottom oil quality VolH, the blended quality VolT, and the reference flow rate of the blending head, etc. Including the upper and lower limits of each attribute index of the blended crude oil, the upper and lower limits of the formula, the maximum formula change step, the upper and lower limits of the flow rate, and the price factor, etc., can be determined according to the actual equipment, production conditions and expected oil products. For example, in certain embodiments, the blending head base flow rate can be set in the range of 100-500 tons/hour; the lower limit of density is 0.881g/ml, the upper limit is 0.911g/ml; the upper limit of sulfur content is 0%, the upper limit The lower limit of acid value is 0mgKOH/g, the upper limit is 0.75mgKOH/g; the lower limit of residual oil yield is 25%, and the upper limit is 30%; the upper limit of the maximum formula change step size of each blending component is 5%, the lower limit - 5%.

然后设置优化周期、各属性优化方式与目标函数权重。优化周期任何合适的时间段，例如1～120min。优化方式包括：保持在约束范围内(即保持在上下限范围内)、向上限优化以及向下限优化。可根据实际需要确定各属性的优化方式。例如，在某些实施方案中，密度的优化方式为保持在约束范围内即可，硫含量的优化方式为向下限优化，酸值的优化方式为向下限优化，渣油收率的优化方式为向上限优化。目标函数的权重通常根据优化方式而变。例如，针对调合原油属性优化可实现属性合格、向上限优化与向下限优化，对于第j种属性的优化方式权重wj，当wj>0则第j种属性向下限优化，wj<0则第j种属性向上限优化，wj＝0则第j种满足属性上下限约束即可。Then set the optimization period, the optimization method of each attribute and the weight of the objective function. The optimization cycle is any suitable time period, eg, 1 to 120 min. The optimization methods include: keeping within the constraint range (that is, keeping within the upper and lower bounds), optimizing to the upper limit, and optimizing to the lower limit. The optimization method of each attribute can be determined according to actual needs. For example, in some embodiments, the optimization method for density can be kept within the constraints, the optimization method for sulfur content is lower bound optimization, the optimization method for acid value is lower bound optimization, and the optimization method for residual oil yield is Optimize towards the upper limit. The weight of the objective function usually varies according to the optimization method. For example, for the attribute optimization of blended crude oil, the attributes can be qualified, optimized to the upper limit and optimized to the lower limit. For the optimization method weight w j of the jth attribute, when w j > 0, the jth attribute is optimized to the lower limit, w j < 0 means that the jth attribute is optimized towards the upper limit, and w j =0 means that the jth type satisfies the upper and lower limit constraints of the attribute.

再次，获取各调合组分属性和罐内累积。可采用常规的方法检测各调合组分的各属性，如密度、硫含量、酸值和渣油收率。通常，罐内的初始累积为0吨。通常，可按照预定优化周期获取各调合组分属性数据与累积调合质量属性积，并更新调合头属性增量、组分配方增量、组分流量增量上下限约束。此步骤可采用下式(4)－(11)实现这些计算。Again, get individual blend component properties and in-tank accumulation. The properties of each blending component, such as density, sulfur content, acid number and residue yield, can be tested using conventional methods. Typically, the initial accumulation in the tank is 0 tons. Usually, the attribute data of each blending component and the cumulative blending quality attribute product can be obtained according to a predetermined optimization cycle, and the blending head attribute increment, the component formula increment, and the upper and lower limit constraints of the component flow increment can be updated. This step can implement these calculations using the following equations (4)-(11).

具体而言，通常，在原油罐内原油的属性满足线性叠加原理，利用优化调合质量的属性补偿已调合质量和罐底油的属性偏差，使整个成品罐属性合格。因此，可根据全罐原油属性指标要求，采用式(4)与式(5)计算优化调合质量，即调合头的指标范围，Specifically, usually, the properties of crude oil in the crude oil tank satisfy the linear superposition principle, and the properties of the optimized blending quality are used to compensate for the property deviation of the blended quality and the bottom oil, so that the properties of the entire finished product tank are qualified. Therefore, formulas (4) and (5) can be used to calculate and optimize the blending quality, that is, the index range of the blending head, according to the requirements of the crude oil property index of the whole tank.

Figure GDA0002897778020000071
Figure GDA0002897778020000071

Figure GDA0002897778020000072
Figure GDA0002897778020000072

其中，

Figure GDA0002897778020000073
和
Figure GDA0002897778020000074
表示为使全罐原油属性指标上下限满足规定的范围，优化调合质量的属性指标应满足的指标上下限，即调合头第j种属性指标的上限和下限；VProTol表示累积调合质量属性积；VProHeel表示罐底油质量属性积；VolH表示罐底质量；VolS表示调合总质量；VolT表示已调合质量。in,
Figure GDA0002897778020000073
and
Figure GDA0002897778020000074
Indicates the upper and lower limits of the attribute index to optimize the blending quality in order to make the upper and lower limits of the crude oil attribute index of the whole tank meet the specified range, that is, the upper and lower limits of the jth attribute index of the blending head; VPro Tol represents the cumulative blending quality Attribute product; VPro Heel represents the quality property product of the tank bottom oil; VolH represents the tank bottom quality; VolS represents the total blended mass; VolT represents the blended quality.

可根据调合头指标和当前调合头属性测量值，采用式(6)与式(7)计算得到当前调合头属性增量的允许变化范围，According to the adjustment head index and the current adjustment head attribute measurement value, the allowable variation range of the current adjustment head attribute increment can be calculated by formula (6) and formula (7),

Figure GDA0002897778020000075
Figure GDA0002897778020000075

Figure GDA0002897778020000076
Figure GDA0002897778020000076

其中，Protj(k)表示当前调合头第j种测量属性；

Figure GDA0002897778020000077
与
Figure GDA0002897778020000078
分别表示调合头第j种属性指标增量的上下限。Among them, Prot j (k) represents the jth measurement property of the current blending head;
Figure GDA0002897778020000077
and
Figure GDA0002897778020000078
Respectively represent the upper and lower limits of the jth attribute index increment of the blending head.

可根据组分油配方上下限、当前组分油配方以及最大配方变化步长，采用式(8)与式(9)计算得到当前时刻配方增量的允许变化范围，The allowable variation range of the formula increment at the current moment can be calculated by formula (8) and formula (9) according to the upper and lower limits of the composition oil formula, the current composition oil formula and the maximum formula change step size,

Figure GDA0002897778020000079
Figure GDA0002897778020000079

Figure GDA0002897778020000081
Figure GDA0002897778020000081

其中，ri Hi和ri Lo分别表示第i种组分油的配方上下限；rStepi Hi和rStepi Lo分别表示第i种组分油的最大、最小配方变化步长；Δri Hi与Δri Lo分别表示第i种调合组分的配方增量上下限。Among them, ri Hi and ri Lo represent the upper and lower limits of the formula of the ith component oil, respectively; rStep i Hi and rStep i Lo represent the maximum and minimum formula change steps of the ith component oil, respectively; Δr i Hi and Δr i Lo represents the upper and lower limits of the formula increment of the i-th blending component, respectively.

可根据组分油流量上下限、当前组分油配方，采用式(10)与式(11)计算得到当前时刻流量增量的允许变化范围，According to the upper and lower limits of the component oil flow rate and the current component oil formula, formulas (10) and (11) can be used to calculate the allowable variation range of the flow rate increment at the current moment,

ΔFi Hi＝Fi Hi-Ft·ri(k) (10)ΔF i Hi =Fi Hi -F t ·r i ( k) (10)

ΔFi Lo＝Fi Lo-Ft·ri(k) (11)ΔF i Lo =Fi Lo -F t ·r i ( k) (11)

其中，ri(k)表示当前第i种组分油的配方；Fi Hi和Fi Lo分别表示第i种组分油的流量上下限；Ft表示调合头基准流量；ΔFi Hi与ΔFi Lo分别表示第i种调合组分的流量增量上下限。Among them, ri (k) represents the current formula of the ith component oil; F i Hi and F i Lo represent the upper and lower flow limits of the ith component oil, respectively; F t represents the reference flow of the blending head; ΔF i Hi and ΔF i Lo represent the upper and lower limits of the flow increment of the i-th blending component, respectively.

最后是计算当前优化周期各调合组分的最优配方与当前最优配方，并送至调合控制系统执行。可采用下式(1)和(2)计算得到各调合组分配方的最优增量与当前最优配方：Finally, the optimal formula and the current optimal formula of each blending component in the current optimization cycle are calculated, and sent to the blending control system for execution. The following formulas (1) and (2) can be used to calculate the optimal increment and current optimal formulation of each blending component formula:

Figure GDA0002897778020000082
Figure GDA0002897778020000082

ri(k+1)＝ri(k)+Δri,i＝1...n (2)r i (k+1)=r i (k)+Δr i , i=1...n (2)

其中，i(i＝1,2,…,n)表示调合组分个数；j(j＝1,2,…,m)表示调合组分的原油属性个数；wp表示成本最小权值；Pricei表示第i种调合组分的价格因子；wj表示第j种属性的优化方式权重；Prozi,j表示第i种调合组分的第j种属性值；Δri Hi与Δri Lo分别表示第i种调合组分的配方增量上下限；

Figure GDA0002897778020000091
与
Figure GDA0002897778020000092
分别表示为调合头第j种属性指标增量的上下限；ΔFi Hi与ΔFi Lo分别表示为第i种组分流量增量的上下限；Δri表示第i种组分油的配方增量；ri(k+1)与ri(k)分别表示第k+1周期(下一周期)与第k周期(当前周期)时第i种组分油的配方。Among them, i(i=1,2,...,n) represents the number of blending components; j(j=1,2,...,m) represents the number of crude oil properties of the blending components; w p represents the minimum cost Weight; Price i represents the price factor of the i-th blending component; w j represents the optimization method weight of the j-th property; Proz i,j represents the j-th property value of the i-th blending component; Δr i Hi and Δr i Lo represent the upper and lower limits of the formula increment of the i-th blending component, respectively;
Figure GDA0002897778020000091
and
Figure GDA0002897778020000092
respectively represent the upper and lower limits of the j-th property index increment of the blending head; ΔF i Hi and ΔF i Lo represent the upper and lower limits of the i-th component flow increment, respectively; Δr i represents the formula of the i-th component oil Increment; ri ( k +1) and ri (k) represent the formula of the i -th component oil in the k+1th cycle (next cycle) and the kth cycle (current cycle), respectively.

在某些实施方案中，本发明是以调合原油属性合格与成本最低两者为目标，实现原油属性向上限优化与向下限优化，利用上述式(1)和(2)将参调组分配方优化转换为参调组分配方增量优化。In some embodiments, the present invention aims at blending both qualified crude oil properties and the lowest cost, so as to achieve the upper limit optimization and lower limit optimization of crude oil properties. The formula optimization is converted into the incremental optimization of the parameter adjustment component formula.

调合后原油属性满足式(3)，The properties of the crude oil after blending satisfy equation (3),

Figure GDA0002897778020000093
Figure GDA0002897778020000093

其中，

Figure GDA0002897778020000094
和
Figure GDA0002897778020000095
表示调合原油第j种属性指标上下限，Proj表示调合原油第j种属性。因此，当属性合格时则
Figure GDA0002897778020000096
即可，向下限优化时则Proj趋近于
Figure GDA0002897778020000097
当向上限优化时则Proj趋近于
Figure GDA0002897778020000098
in,
Figure GDA0002897778020000094
and
Figure GDA0002897778020000095
Indicates the upper and lower limits of the jth property index of blended crude oil, and Pro j represents the jth property of blended crude oil. Therefore, when the attribute is qualified then
Figure GDA0002897778020000096
That is, when the lower bound is optimized, Pro j approaches
Figure GDA0002897778020000097
When optimizing towards the upper limit, then Pro j approaches
Figure GDA0002897778020000098

可采用本领域常规的通讯接口将当前最优配方送至调合控制系统执行。之后等待下一优化周期，并判断本次调合是否完成，若到达优化周期且本次调合未完成，则重新获取各调合组分属性和罐内累积，并进行其之后的步骤，直至完成调合。The current optimal formula can be sent to the blending control system for execution by using a conventional communication interface in the art. Then wait for the next optimization cycle, and judge whether the blending is completed. If the optimization cycle is reached and the blending is not completed, the properties of each blending component and the accumulation in the tank are re-acquired, and the subsequent steps are performed until Completion of blending.

本发明中，调合头基准流量是指调合头按调度要求设定的总调合流量，各组分原油流量之和等于调合头基准流量。In the present invention, the reference flow of the blending head refers to the total blending flow set by the blending head according to scheduling requirements, and the sum of the crude oil flow of each component is equal to the reference flow of the blending head.

在某些实施方案中，本发明还提供一种计算机设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其中，所述处理器执行所述程序时实现以下步骤：In certain embodiments, the present invention also provides a computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor, when executing the program, implements the following step:

采用式(4)与式(5)计算优化调合质量，即调合头的指标范围，Formulas (4) and (5) are used to calculate the optimal blending quality, that is, the index range of the blending head,

Figure GDA0002897778020000099
Figure GDA0002897778020000099

Figure GDA00028977780200000910
Figure GDA00028977780200000910

其中，

Figure GDA0002897778020000101
和
Figure GDA0002897778020000102
表示为使全罐原油属性指标上下限满足规定的范围，优化调合质量的属性指标应满足的指标上下限，即调合头第j种属性指标的上限和下限；VProTol表示累积调合质量属性积；VProHeel表示罐底油质量属性积；VolH表示罐底质量；VolS表示调合总质量；VolT表示已调合质量；in,
Figure GDA0002897778020000101
and
Figure GDA0002897778020000102
Indicates the upper and lower limits of the attribute index to optimize the blending quality in order to make the upper and lower limits of the crude oil attribute index of the whole tank meet the specified range, that is, the upper and lower limits of the jth attribute index of the blending head; VPro Tol represents the cumulative blending quality Attribute product; VPro Heel represents the quality attribute product of the tank bottom oil; VolH represents the tank bottom quality; VolS represents the total blended mass; VolT represents the blended quality;

采用式(6)与式(7)计算得到当前调合头属性增量的允许变化范围，The allowable variation range of the attribute increment of the current blending head is calculated by formula (6) and formula (7),

Figure GDA0002897778020000103
Figure GDA0002897778020000103

Figure GDA0002897778020000104
Figure GDA0002897778020000104

其中，Protj(k)表示当前调合头第j种测量属性；

Figure GDA0002897778020000105
与
Figure GDA0002897778020000106
分别表示调合头第j种属性指标增量的上下限；Among them, Prot j (k) represents the jth measurement property of the current blending head;
Figure GDA0002897778020000105
and
Figure GDA0002897778020000106
Respectively represent the upper and lower limits of the jth attribute index increment of the blending head;

采用式(8)与式(9)计算得到当前时刻配方增量的允许变化范围，Using formula (8) and formula (9) to calculate the allowable variation range of the recipe increment at the current moment,

Figure GDA0002897778020000107
Figure GDA0002897778020000107

Figure GDA0002897778020000108
Figure GDA0002897778020000108

其中，ri Hi和ri Lo分别表示第i种组分油的配方上下限；rStepi Hi和rStepi Lo分别表示第i种组分油的最大、最小配方变化步长；Δri Hi与Δri Lo分别表示第i种调合组分的配方增量上下限；Among them, ri Hi and ri Lo represent the upper and lower limits of the formula of the ith component oil, respectively; rStep i Hi and rStep i Lo represent the maximum and minimum formula change steps of the ith component oil, respectively; Δr i Hi and Δr i Lo represents the upper and lower limits of the formula increment of the i-th blending component, respectively;

采用式(10)与式(11)计算得到当前时刻流量增量的允许变化范围，Using formula (10) and formula (11) to calculate the allowable variation range of flow increment at the current moment,

ΔFi Hi＝Fi Hi-Ft·ri(k) (10)ΔF i Hi =Fi Hi -F t ·r i ( k) (10)

ΔFi Lo＝Fi Lo-Ft·ri(k) (11)ΔF i Lo =Fi Lo -F t ·r i ( k) (11)

其中，ri(k)表示当前第i种组分油的配方；Fi Hi和Fi Lo分别表示第i种组分油的流量上下限；Ft表示调合头基准流量；ΔFi Hi与ΔFi Lo分别表示第i种调合组分的流量增量上下限；和Among them, ri (k) represents the current formula of the ith component oil; F i Hi and F i Lo represent the upper and lower flow limits of the ith component oil, respectively; F t represents the reference flow of the blending head; ΔF i Hi and ΔF i Lo represent the upper and lower limits of the flow increment of the i-th blending component, respectively; and

采用下式(1)和(2)计算得到各调合组分配方的最优增量与当前最优配方：The following formulas (1) and (2) are used to calculate the optimal increment and current optimal formulation of each blending component formula:

Figure GDA0002897778020000111
Figure GDA0002897778020000111

ri(k+1)＝ri(k)+Δri,i＝1...n (2)r i (k+1)=r i (k)+Δr i , i=1...n (2)

其中，i(i＝1,2,…,n)表示调合组分个数；j(j＝1,2,…,m)表示调合组分的原油属性个数；wp表示成本最小权值；Pricei表示第i种调合组分的价格因子；wj表示第j种属性的优化方式权重；Prozi,j表示第i种调合组分的第j种属性值；Δri Hi与Δri Lo分别表示第i种调合组分的配方增量上下限；

Figure GDA0002897778020000112
与
Figure GDA0002897778020000113
分别表示为调合头第j种属性指标增量的上下限；ΔFi Hi与ΔFi Lo分别表示为第i种组分流量增量的上下限；Δri表示第i种组分油的配方增量；ri(k+1)与ri(k)分别表示第k+1周期(下一周期)与第k周期(当前周期)时第i种组分油的配方。Among them, i(i=1,2,...,n) represents the number of blending components; j(j=1,2,...,m) represents the number of crude oil properties of the blending components; w p represents the minimum cost Weight; Price i represents the price factor of the i-th blending component; w j represents the optimization method weight of the j-th property; Proz i,j represents the j-th property value of the i-th blending component; Δr i Hi and Δr i Lo represent the upper and lower limits of the formula increment of the i-th blending component, respectively;
Figure GDA0002897778020000112
and
Figure GDA0002897778020000113
respectively represent the upper and lower limits of the j-th property index increment of the blending head; ΔF i Hi and ΔF i Lo represent the upper and lower limits of the i-th component flow increment, respectively; Δr i represents the formula of the i-th component oil Increment; ri ( k +1) and ri (k) represent the formula of the i -th component oil in the k+1th cycle (next cycle) and the kth cycle (current cycle), respectively.

在某些实施方案中，本发明还提供一种计算机可读存储介质，其上存有计算机程序，该程序被处理器执行时实现本文所述的各计算步骤。具体而言，该程序被处理器执行时可依据式(1)与式(2)计算得到各调合组分配方的最优增量与当前最优配方：In certain embodiments, the present invention also provides a computer-readable storage medium having stored thereon a computer program that, when executed by a processor, implements the computing steps described herein. Specifically, when the program is executed by the processor, the optimal increment and current optimal formulation of each blending component formula can be calculated according to formula (1) and formula (2):

Figure GDA0002897778020000121
Figure GDA0002897778020000121

ri(k+1)＝ri(k)+Δri,i＝1...n (2)r i (k+1)=r i (k)+Δr i , i=1...n (2)

其中，i(i＝1,2,…,n)表示调合组分个数；j(j＝1,2,…,m)表示调合组分的原油属性个数；wp表示成本最小权值；Pricei表示第i种调合组分的价格因子；wj表示第j种属性的优化方式权重；Prozi,j表示第i种调合组分的第j种属性值；Δri Hi与Δri Lo分别表示第i种调合组分的配方增量上下限；

Figure GDA0002897778020000122
与
Figure GDA0002897778020000123
分别表示为调合头第j种属性指标增量的上下限；ΔFi Hi与ΔFi Lo分别表示为第i种组分流量增量的上下限；Δri表示第i种组分油的配方增量；ri(k+1)与ri(k)分别表示第k+1周期(下一周期)与第k周期(当前周期)时第i种组分油的配方。Among them, i(i=1,2,...,n) represents the number of blending components; j(j=1,2,...,m) represents the number of crude oil properties of the blending components; w p represents the minimum cost Weight; Price i represents the price factor of the i-th blending component; w j represents the optimization method weight of the j-th property; Proz i,j represents the j-th property value of the i-th blending component; Δr i Hi and Δr i Lo represent the upper and lower limits of the formula increment of the i-th blending component, respectively;
Figure GDA0002897778020000122
and
Figure GDA0002897778020000123
respectively represent the upper and lower limits of the j-th property index increment of the blending head; ΔF i Hi and ΔF i Lo represent the upper and lower limits of the i-th component flow increment, respectively; Δr i represents the formula of the i-th component oil Increment; ri ( k +1) and ri (k) represent the formula of the i -th component oil in the k+1th cycle (next cycle) and the kth cycle (current cycle), respectively.

在一个或多个实施方案中，该程序被处理器执行时还实现以下步骤：根据本文所述的公式(4)到(11)计算得到调合头第j种属性指标的上下限、调合头第j种属性指标增量的上下限、第i种调合组分的配方增量上下限和第i种调合组分的流量增量上下限。In one or more embodiments, when the program is executed by the processor, the following steps are further implemented: calculating the upper and lower limits of the j-th attribute index of the blending head according to the formulas (4) to (11) described herein, the blending The upper and lower limits of the first jth attribute index increment, the upper and lower limits of the formula increment of the ith blending component, and the upper and lower limits of the flow increment of the ith blending component.

本发明基于增量模式的原油调合的在线优化方法在调合过程中按照一定优化周期计算组分最优配方，并将优化结果送至调合控制系统执行，保证调合原油属性质量满足常减压装置要求的同时兼顾经济最优，从而实现调合过程实时优化，提高炼油企业经济效益。The on-line optimization method for crude oil blending based on the incremental mode of the present invention calculates the optimal formula of components according to a certain optimization period during the blending process, and sends the optimization results to the blending control system for execution, so as to ensure that the properties and quality of the blended crude oil meet the normal requirements. The requirements of the decompression device are taken into account at the same time as the economic optimization, so as to realize the real-time optimization of the blending process and improve the economic benefits of the oil refining enterprise.

下面结合附图与实施算例对本发明做进一步说明，但本发明不限于此实施例。The present invention will be further described below with reference to the accompanying drawings and embodiments, but the present invention is not limited to this embodiment.

本实施例的原油调合过程有3个原油组分罐。调合过程依照批次进行，每批次调合一定总量，当前批次调合完成之后再进行下一批次调合。本算例在以本发明技术方案为前提进行实施。The crude oil blending process in this embodiment has three crude oil component tanks. The blending process is carried out in batches, each batch blends a certain amount, and the next batch is blended after the current batch is blended. This example is implemented on the premise of the technical solution of the present invention.

如图1所示，本原油调合系统包括：调合优化系统、调合控制系统、在线分析系统与现场设备及仪表。现场设备及仪表包括调合组分罐、调合泵、流量计、控制阀、调合头静态混合器与原油罐。调合优化系统将组分配方送至调合控制系统，从而实现现场设备的控制。As shown in Figure 1, the crude oil blending system includes: a blending optimization system, a blending control system, an online analysis system, and field equipment and instruments. Field equipment and instruments include blending component tanks, blending pumps, flow meters, control valves, blending head static mixers and crude oil tanks. The blending optimization system sends the component formula to the blending control system, so as to realize the control of the field equipment.

如图2所示，原油调合优化系统的工作流程主要包括以下步骤：As shown in Figure 2, the workflow of the crude oil blending optimization system mainly includes the following steps:

步骤一：调合任务参数初始化。Step 1: Initialize the parameters of the blending task.

结合具体算例，假设本次调合总质量VolS＝9000t，罐底油质量VolH＝0t，已调合质量VolT＝0t，调合头基准流量Ft＝300t/h。Combined with a specific example, it is assumed that the total mass of this blending VolS=9000t, the quality of the tank bottom oil VolH=0t, the blended mass VolT =0t, and the reference flow rate of the blending head Ft=300t/h.

调合原油各属性指标上下限设置。假设选择四种原油属性参与优化，即密度、硫含量、酸值与渣油收率。其中，Set the upper and lower limits of each attribute index of blended crude oil. It is assumed that four crude oil properties are selected to participate in the optimization, namely density, sulfur content, acid value and residual oil yield. in,

密度下限

Figure GDA0002897778020000131
密度上限
Figure GDA0002897778020000132
lower density limit
Figure GDA0002897778020000131
Density cap
Figure GDA0002897778020000132

硫含量下限

Figure GDA0002897778020000133
硫含量上限
Figure GDA0002897778020000134
Lower limit of sulfur content
Figure GDA0002897778020000133
Upper limit of sulfur content
Figure GDA0002897778020000134

酸值下限

Figure GDA0002897778020000135
酸值上限
Figure GDA0002897778020000136
Acid value lower limit
Figure GDA0002897778020000135
Upper limit of acid value
Figure GDA0002897778020000136

渣油收率下限

Figure GDA0002897778020000137
渣油收率上限
Figure GDA0002897778020000138
Residual oil yield lower limit
Figure GDA0002897778020000137
Residue yield upper limit
Figure GDA0002897778020000138

各调合组分油初始配方设置。假设组分1初始配方r1(0)＝20％，组分2初始配方r2(0)＝35％，组分3初始配方r3(0)＝45％。The initial formula setting of each blending component oil. Assume that Component 1 initial formulation r 1 (0)=20%, Component 2 initial formulation r 2 (0)=35%, and Component 3 initial formulation r 3 (0)=45%.

各调合组分油最大配方变化步长设置，假设

Figure GDA0002897778020000139
The maximum formula change step size setting for each blending component oil, assuming
Figure GDA0002897778020000139

各调合组分油配方上下限设置。假设组分1配方下限r1 Lo＝12％，配方上限r1 Hi＝30％；组分2配方下限

Figure GDA00028977780200001310
配方上限
Figure GDA00028977780200001311
组分3配方下限
Figure GDA00028977780200001312
配方上限
Figure GDA00028977780200001313
The upper and lower limits of the oil formula of each blending component are set. Assuming that the lower formula limit of component 1 r 1 Lo = 12%, the upper limit of the formula r 1 Hi = 30%; the lower formula limit of component 2
Figure GDA00028977780200001310
Recipe cap
Figure GDA00028977780200001311
Component 3 formulation lower limit
Figure GDA00028977780200001312
Recipe cap
Figure GDA00028977780200001313

各调合组分油流量上下限设置。假设组分1流量下限F1 Lo＝0t/h，配方上限F1 Hi＝180t/h；组分2配方下限

Figure GDA00028977780200001314
配方上限
Figure GDA00028977780200001315
组分3配方下限
Figure GDA00028977780200001316
配方上限
Figure GDA00028977780200001317
The upper and lower limits of the oil flow of each blending component are set. Assume that the lower limit of flow rate of component 1 is F 1 Lo =0t/h, the upper limit of formula F 1 Hi =180t/h; the lower limit of formula of component 2
Figure GDA00028977780200001314
Recipe cap
Figure GDA00028977780200001315
Component 3 formulation lower limit
Figure GDA00028977780200001316
Recipe cap
Figure GDA00028977780200001317

各调合组分油价格因子与成本最小权值设置。假设组分1价格为Price1＝4300rmb/t，组分2价格为

Figure GDA00028977780200001318
组分3价格为
Figure GDA00028977780200001319
The oil price factor and cost minimum weight setting of each blending component. Assuming that the price of component 1 is Price 1 =4300rmb/t, the price of component 2 is
Figure GDA00028977780200001318
Component 3 is priced at
Figure GDA00028977780200001319

步骤二：设置优化周期、优化方式与目标函数权重。Step 2: Set the optimization period, optimization method and objective function weight.

假设优化周期为5min，成本最小权值wp＝0.01；各属性优化方式设置如下：Assuming that the optimization period is 5 minutes, the minimum cost weight w p = 0.01; the optimization methods of each attribute are set as follows:

密度优化方式为保持约束范围内即可，权重w1＝0；硫含量优化方式为向下限优化，权重w2＝1；酸值优化方式为向下限优化，权重w3＝1；渣油收率，优化方式为向上限优化，权重w4＝-1。The density optimization method can be kept within the constraint range, and the weight w 1 =0; the sulfur content optimization method is the lower limit optimization, and the weight w 2 =1; the acid value optimization method is the lower limit optimization, and the weight w 3 =1; rate, the optimization method is to optimize toward the upper limit, and the weight w 4 =-1.

步骤三：按照预定优化周期获取各调合组分属性数据与累积调合质量属性积，更新调合头属性增量、组分配方增量、组分流量增量上下限约束。Step 3: Acquire the attribute data of each blending component and the cumulative blending quality attribute product according to a predetermined optimization period, and update the blending head attribute increment, component formula increment, and component flow increment upper and lower limit constraints.

由于本次调合启动时进行优化，原油罐内已调合量为0，因此累积调合质量属性积为0。Due to optimization at the start of this blending, the blended amount in the crude oil tank is 0, so the cumulative blending quality attribute product is 0.

假设各组分属性采集数据如下：It is assumed that the collected data of each component attribute is as follows:

组分1：密度0.8862g/ml，硫含量3.1％，酸值0.24mgKOH/g，渣油收率18％；Component 1: density 0.8862g/ml, sulfur content 3.1%, acid value 0.24mgKOH/g, residue yield 18%;

组分2：密度0.8693g/ml，硫含量2.48％，酸值0.22mgKOH/g，渣油收率32％；Component 2: density 0.8693g/ml, sulfur content 2.48%, acid value 0.22mgKOH/g, residue yield 32%;

组分3：密度0.8862g/ml，硫含量0.76％，酸值1.35mgKOH/g，渣油收率23％；Component 3: density 0.8862g/ml, sulfur content 0.76%, acid value 1.35mgKOH/g, residue yield 23%;

根据式(4)-(11)可计算出，According to formulas (4)-(11), it can be calculated,

调合头属性增量上下限：The upper and lower limits of the blending head attribute increment:

Figure GDA0002897778020000141
Figure GDA0002897778020000141

Figure GDA0002897778020000142
Figure GDA0002897778020000142

配方增量上下限：ΔrLo＝[-5,-5,-5]，ΔrHi＝[5,5,5]；Recipe increment upper and lower limits: Δr Lo =[-5,-5,-5], Δr Hi =[5,5,5];

流量增量上下限：ΔFLo＝[-60,-105,-135]，ΔFHi＝[120,95,35]。The upper and lower limits of flow increment: ΔF Lo =[-60,-105,-135], ΔF Hi =[120,95,35].

步骤四：计算最优配方增量与当前最优配方。Step 4: Calculate the optimal recipe increment and the current optimal recipe.

利用线性规划求解式(1)，得到最优配方增量Δr1＝-5％，Δr2＝5％，Δr3＝0％。Using linear programming to solve equation (1), the optimal formula increments Δr 1 =-5%, Δr 2 =5%, and Δr 3 =0% are obtained.

再利用式子(2)计算出当前最优配方r1(1)＝15％，r2(1)＝40％，r3(1)＝45％。Then, formula (2) is used to calculate the current optimal formula r 1 (1)=15%, r 2 (1)=40%, and r 3 (1)=45%.

步骤五：通过通讯接口将当前最优配方送至调合控制系统执行。Step 5: Send the current optimal formula to the blending control system for execution through the communication interface.

步骤六：等待下一优化周期，并判断本次调合是否完成，若到达优化周期且本次调合未完成，则返回步骤三。Step 6: Wait for the next optimization cycle, and determine whether the current blending is completed. If the optimization cycle is reached and the current blending is not completed, go back to step three.

本发明未涉及方法均与现有技术相同或可采用现有技术加以实现。None of the methods involved in the present invention are the same as the prior art or can be implemented by using the prior art.

Claims (13)

1. An online optimization method for crude oil blending based on an incremental mode is characterized by comprising the following steps:
firstly, initializing blending task parameters;
secondly, setting an optimization period, an optimization mode of each attribute and a weight of an objective function;
thirdly, acquiring the attribute data of each blending component and the accumulated blending quality attribute product according to a preset optimization period, and updating the attribute increment of the blending head, the component formula increment and the upper and lower limit constraints of the component flow increment;
finally, the optimal formula of each blending component in the current optimization period is obtained and sent to a blending control system for execution;
wherein, the optimized blending quality, namely the index range of the blending head, is calculated by adopting the formula (4) and the formula (5),
Figure FDA0002897778010000011
Figure FDA0002897778010000012
wherein,
Figure FDA0002897778010000013
and
Figure FDA0002897778010000014
respectively representing the upper limit and the lower limit of an index which is to be met by the property index for optimizing blending quality so that the upper limit and the lower limit of the property index of the whole tank crude oil meet the specified range, namely the upper limit and the lower limit of the jth property index of the blending head; VProTolRepresenting an accumulated blending quality attribute product; VProHeelRepresenting a product of quality properties of oil at the bottom of the tank; VolH represents the can bottom quality; VolS represents the total blended mass; VolT denotes the quality of the mix;
Figure FDA0002897778010000015
and
Figure FDA0002897778010000016
respectively representing the upper limit and the lower limit of the jth attribute index of the blended crude oil; VProTol,jA blending quality attribute product representing the accumulated jth attribute index; VProHeel,jRepresents the mass attribute product of the jth attribute index of the tank bottom oil.
2. The method of claim 1, wherein the blending task parameters include a target blending quality, upper and lower limits for each property index for the blended crude oil, an initial recipe for each blending component oil, upper and lower limits for the recipe, a maximum recipe change step size, upper and lower flow limits, and a price factor.
3. The method of claim 1, wherein the optimization comprises blending the crude oil properties to meet a range of upper and lower limits, optimization of the upper limit, and optimization of the lower limit while minimizing blending costs.
4. The method of claim 3 wherein the blended crude oil attribute is optimized for qualified attributes, upward optimization and downward optimization, i.e., optimization mode weight w for jth attributejWhen w isj>0 then j attribute is optimized towards lower bound, wj<0 then j attribute is optimized towards the upper limit, wjAnd if 0, the jth type satisfies the attribute upper and lower limit constraints.
5. The method of claim 3, wherein the crude oil properties include density, sulfur content, acid number, and residue yield.
6. The method of claim 1, wherein the allowable variation range of the current fitting head attribute increment is calculated by using the formula (6) and the formula (7),
Figure FDA0002897778010000021
Figure FDA0002897778010000022
wherein Protj(k) Representing the j measurement attribute of the current blending head;
Figure FDA0002897778010000023
and
Figure FDA0002897778010000024
respectively representing the upper limit and the lower limit of the jth attribute index increment of the blending head;
Figure FDA0002897778010000025
and
Figure FDA0002897778010000026
the upper limit and the lower limit of the property index of the crude oil in the whole tank are respectively expressed as the upper limit and the lower limit of the index which the property index of optimizing the blending quality needs to meet so that the upper limit and the lower limit of the property index of the crude oil in the whole tank meet the specified range, namely the upper limit and the lower limit of the jth property index of the blending head.
7. The method of claim 1, wherein the allowable variation range of the formula increment at the current time is calculated by using the formula (8) and the formula (9),
Figure FDA0002897778010000027
Figure FDA0002897778010000028
wherein r isi HiAnd ri LoRespectively representing the upper limit and the lower limit of the formula of the ith blending component;
Figure FDA0002897778010000029
and
Figure FDA00028977780100000210
respectively representing the maximum and minimum formula change step lengths of the ith blending component; Δ ri HiAnd Δ ri LoRespectively representing the upper limit and the lower limit of the formula increment of the ith blending component; r isi(k) The formulation of the i component oil at the k cycle is shown.
8. The method of claim 1, wherein the allowable variation range of the current time flow increment is calculated by using equations (10) and (11),
ΔFi Hi＝Fi Hi-Ft·ri(k) (10)
ΔFi Lo＝Fi Lo-Ft·ri(k) (11)
wherein r isi(k) Representing the formulation of the current component oil i; fi HiAnd Fi LoRespectively representing the upper and lower flow limits of the ith component oil; ftRepresenting a blending head reference flow; Δ Fi HiAnd Δ Fi LoRespectively representing the upper and lower limits of the flow increment of the ith blending component.
9. The method of claim 1, wherein for the kth optimization cycle, the optimal increment of each blending component formula and the current optimal formula are calculated using formula (1) and formula (2):
Figure FDA0002897778010000031
ri(k+1)＝ri(k)+Δri,i＝1...n (2)
wherein i (i ═ 1,2, …, n) represents the number of blending components; j (j is 1,2, …, m) represents the crude oil attribute number of the blending component; w is apRepresenting a cost minimum weight; priceiA price factor representing the ith blending component; w is ajRepresenting the optimization mode weight of the jth attribute; prozi,jA jth attribute value representing the ith blending component; Δ ri HiAnd Δ ri LoRespectively representing the upper limit and the lower limit of the formula increment of the ith blending component;
Figure FDA0002897778010000032
and
Figure FDA0002897778010000033
respectively representing the upper limit and the lower limit of the jth attribute index increment of the blending head; Δ Fi HiAnd Δ Fi LoRespectively expressed as the upper and lower limits of the ith component flow increment; Δ riRepresenting the formulation increment of the ith component oil; r isi(k +1) and ri(k) The formulas of the ith component oil in the k +1 th cycle and the kth cycle are respectively shown.
10. The method of claim 1, wherein the blended crude oil has properties that satisfy formula (3),
Figure FDA0002897778010000034
wherein,
Figure FDA0002897778010000041
and
Figure FDA0002897778010000042
indicates the upper and lower limits of the jth attribute index Pro of the blended crude oiljRepresenting the j attribute of the blended crude oil; when the attribute is qualified, then
Figure FDA0002897778010000043
Pro when optimizing to lower boundjApproach to
Figure FDA0002897778010000044
Pro when optimizing to the upper boundjApproach to
Figure FDA0002897778010000045
11. A computer readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the computing steps of any one of claims 1 to 10 or all of the computing steps of claims 1 to 10.
12. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of: calculating by adopting an equation (1) and an equation (2) to obtain the optimal increment of each blending component formula and the current optimal formula:
Figure FDA0002897778010000046
ri(k+1)＝ri(k)+Δri,i＝1...n (2)
wherein i (i ═ 1,2, …, n) represents the number of blending components; j (j is 1,2, …, m) represents the crude oil attribute number of the blending component; w is apRepresenting a cost minimum weight; priceiA price factor representing the ith blending component; w is ajOptimizer representing j-th attribute(ii) a formula weight; prozi,jA jth attribute value representing the ith blending component; Δ ri HiAnd Δ ri LoRespectively representing the upper limit and the lower limit of the formula increment of the ith blending component;
Figure FDA0002897778010000047
and
Figure FDA0002897778010000048
respectively representing the upper limit and the lower limit of the jth attribute index increment of the blending head; Δ Fi HiAnd Δ Fi LoRespectively expressed as the upper and lower limits of the ith component flow increment; Δ riRepresenting the formulation increment of the ith component oil; r isi(k +1) and ri(k) The formulas of the ith component oil in the k +1 th cycle and the kth cycle are respectively shown.
13. The computer device of claim 12, wherein the processor when executing the program further performs the steps of: the upper and lower limits of the jth attribute index of the blending head, the upper and lower limits of the jth attribute index increment of the blending head, the upper and lower limits of the formula increment of the ith blending component and the upper and lower limits of the flow increment of the ith blending component are calculated according to the formulas (4) to (11) of claims 1 to 8.
CN201810162826.6A 2018-02-26 2018-02-26 On-line optimization method of crude oil blending based on incremental mode Active CN108333943B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810162826.6A CN108333943B (en) 2018-02-26 2018-02-26 On-line optimization method of crude oil blending based on incremental mode

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810162826.6A CN108333943B (en) 2018-02-26 2018-02-26 On-line optimization method of crude oil blending based on incremental mode

Publications (2)

Publication Number Publication Date
CN108333943A CN108333943A (en) 2018-07-27
CN108333943B true CN108333943B (en) 2021-05-07

Family

ID=62930152

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810162826.6A Active CN108333943B (en) 2018-02-26 2018-02-26 On-line optimization method of crude oil blending based on incremental mode

Country Status (1)

Country Link
CN (1) CN108333943B (en)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109765788B (en) * 2019-03-29 2022-03-04 华东理工大学 An online optimization method for multi-objective crude oil blending
CN109994160B (en) * 2019-03-29 2023-08-15 华东理工大学 Calculation method of blending effect parameters of crude oil blending
CN109765789B (en) * 2019-03-29 2022-04-19 华东理工大学 Crude oil blending double-blending head coordination optimization method considering tank bottom oil property
CN116224776A (en) * 2022-11-03 2023-06-06 上海流程智造科技创新研究院有限公司 Constraint multi-objective-based gasoline blending online optimization method

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1627215A (en) * 2004-06-09 2005-06-15 北京中科诚毅科技发展有限公司 Online optimized method for blending oil products, and system of implementing the method
CN101694571A (en) * 2009-10-21 2010-04-14 华东理工大学 Gasoline online blending method
CN102643662A (en) * 2012-04-25 2012-08-22 南京富岛信息工程有限公司 Crude oil blending optimization method
CN103116274A (en) * 2013-02-01 2013-05-22 浙江大学 Track optimization method for switching cannular polypropylene production marks
CN104007658A (en) * 2014-06-13 2014-08-27 南京富岛信息工程有限公司 Gasoline online blending method with dual-circulation optimization
KR20150044983A (en) * 2013-10-15 2015-04-28 에스케이이노베이션 주식회사 Method and Apparatus for blending fractions

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1627215A (en) * 2004-06-09 2005-06-15 北京中科诚毅科技发展有限公司 Online optimized method for blending oil products, and system of implementing the method
CN101694571A (en) * 2009-10-21 2010-04-14 华东理工大学 Gasoline online blending method
CN102643662A (en) * 2012-04-25 2012-08-22 南京富岛信息工程有限公司 Crude oil blending optimization method
CN103116274A (en) * 2013-02-01 2013-05-22 浙江大学 Track optimization method for switching cannular polypropylene production marks
KR20150044983A (en) * 2013-10-15 2015-04-28 에스케이이노베이션 주식회사 Method and Apparatus for blending fractions
CN104007658A (en) * 2014-06-13 2014-08-27 南京富岛信息工程有限公司 Gasoline online blending method with dual-circulation optimization

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
基于寄生行为的双种群萤火虫算法及其在柴油调合中的应用;孔祥东 等;《华东理工大学学报（自然科学版）》;20170430;第43卷(第2期);第213-219页 *

Also Published As

Publication number Publication date
CN108333943A (en) 2018-07-27

Similar Documents

Publication Publication Date Title
CN108333943B (en) On-line optimization method of crude oil blending based on incremental mode
JP7554774B2 (en) Methods and means for optimizing biotechnological production - Patents.com
CN1023157C (en) Adaptive gain scheduling algorthm
CN109634105B (en) Crude oil dynamic blending method facing to processing scheme switching
CN110605178A (en) An intelligent control system and method for dense medium sorting process
WO2020199665A1 (en) Multi-target online optimization method for crude oil blending
US6816822B1 (en) System and method for dynamic modeling, parameter estimation and optimization for processes having operating targets
CN110945593A (en) Method for predicting the production of and modeling a process in a bioreactor
EP3698125A1 (en) In situ raman spectroscopy systems and methods for controlling process variables in cell cultures
CN108388966B (en) An optimization method of ore blending in sintering process based on improving profit
CN108733009B (en) An online optimization control method for oil blending with multi-layer architecture
KR20210144862A (en) Method of Calculation of Blending Effect Parameters of Crude Oil Blending
CN103365208A (en) Crude oil blending optimization method with deviation correction function of base oil property
CN113591362A (en) Clinker proportion optimization and regulation method based on big data intelligent control algorithm
Pauk et al. An all-in-one state-observer for protein refolding reactions using particle filters and delayed measurements
CN112686430B (en) Method for improving accuracy of product yield model of refining enterprise device
El-Anshasy et al. Evidence on the role of oil prices in Venezuela’s economic Performance: 1950-2001
US12217198B2 (en) Method and system for process schedule reconciliation using machine learning and algebraic model optimization
Ye et al. A personality-guided preference aggregator for ephemeral group recommendation
CN115600429B (en) Parameter estimation method of airborne self-adaptive model of aero-engine
CN107510089B (en) The method of accuracy of leaf feeding is improved in a kind of production of tobacco cutting
CN109870986A (en) An online control method for stirring reactor based on neural network and data-driven
WO2024092889A1 (en) Online gasoline blending optimization method based on constrained multiple objectives
CN109765789B (en) Crude oil blending double-blending head coordination optimization method considering tank bottom oil property
WO2025000614A1 (en) Method and system for online measurement of lye concentration

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant