CN103472722B - For control method and the system of petrochemical industry - Google Patents

Abstract

The invention discloses a kind of control method for petrochemical industry and system, for solve in existing control method and system adopt manually provide control control that parameter causes not accurately, resource distribution optimizes not and designs. Described control method comprises: gather or receive the at the appointed time manufacturing parameter of interior processing of oil plant; Simulation charging, time processing that crude(oil)unit is corresponding, secondary operations, product oil that secondary operations device is corresponding be in harmonious proportion and the constraints of shipment under, adopt linear or non-linear optimizing to solve described manufacturing parameter, control parameter thereby generate; According to the instruction of described control parameter formation control; According to the production procedure of described control instruction control oil plant processing, there is reaction fast, control the advantages such as accurate, be conducive to the resource distribution of raw material and equipment, to reduce production costs and to improve productivity effect.

Description

Control method and system for petrochemical industry

Technical Field

The invention relates to the technical field of petrochemical industry, in particular to a control method and a control system for petrochemical industry.

Background

The control parameters used by the oil refinery to control petrochemical processing are manually derived from actual production parameters. Manual derivation strongly depends on the experience of the designated staff, the level of business, and the job status. And petrochemical production relates to various raw materials, and processing steps are complicated, and manual analysis and calculation often not only has insufficient calculation accuracy and precision, but also cannot obtain optimized control parameters, often causes the problems of low processing efficiency, raw material waste, overstocked or lacking inventory, and finally causes the increase of production cost.

Disclosure of Invention

Technical problem to be solved

The technical problem to be solved by the invention is as follows: how to provide a control method and a control system for the petrochemical industry to reduce the difficulty of control parameter manufacture, optimize the control parameters to ensure that the production is smoother, reduce the production cost and improve the production efficiency.

(II) technical scheme

In order to solve the above problems, the control method for petrochemical industry of the present invention comprises:

collecting or receiving production parameters processed by an oil refinery within a specified time;

under the constraint conditions of simulating feeding, primary processing corresponding to a crude oil distillation device, secondary processing corresponding to a secondary processing device, blending of finished oil and shipment, solving the production parameters by linear or nonlinear optimization so as to generate control parameters;

forming a control instruction according to the control parameter;

and controlling the production flow of the processing of the oil refinery according to the control instruction.

Further, the air conditioner is provided with a fan,

and simulating secondary processing corresponding to the secondary processing device by adopting the following formula:

$\frac{\underset{l}{\mathrm{\Σ}}{F}_{l,d}\×Q_l+{\mathrm{INV}}_d^{p-1}\×Q_d^{p-1}}{\underset{l}{\mathrm{\Σ}}{F}_{l,d}+{\mathrm{INV}}_d^{p-1}}=Q_d,$

Q_dmin≤Q_d≤Q_dmax，

$\underset{e}{\mathrm{\Σ}}{F}_{m,e}=\underset{d}{\mathrm{\Σ}}{F}_d\×(W_{d,m}+\underset{Q_d}{\mathrm{\Σ}}\mathrm{\Δ}{Q}_d\×\mathrm{\Δ}{W}_{Q_d,d,m}+\underset{T_d}{\mathrm{\Σ}}\mathrm{\Δ}{T}_d\×\mathrm{\Δ}{W}_{T_d,d,m})+({\mathrm{INV}}_m^{p-1}-{\mathrm{INV}}_m^p),$

$\frac{\underset{d}{\mathrm{\Σ}}{F}_d\×W_{d,m}\×(Q_{d,m}+\underset{Q_d}{\mathrm{\Σ}}\mathrm{\Δ}{Q}_d\×\mathrm{\Δ}{Q}_{Q_d,d,m}+\underset{T_d}{\mathrm{\Σ}}\mathrm{\Δ}{T}_d\×\mathrm{\Δ}{Q}_{T_d,d,m})+{\mathrm{INV}}_m^{p-1}\×Q_m^{p-1}}{\underset{d}{\mathrm{\Σ}}{F}_d\×W_{d,m}+{\mathrm{INV}}_m^{p-1}}=Q_m,$

wherein Q is_lIs the value of the property of the feed l, F_l，dIs the flow rate of feed l under secondary processing scheme d,is the initial inventory of mixed feed for secondary processing scheme d,is a property value, Q, of the initial inventory_dIs the quality value of the mixed feed of the secondary processing scheme d, Q_dminIs the minimum value, Q, allowed to be reached by the feed properties of the secondary processing scheme d_dmaxIs the maximum value that the feed properties of the secondary processing scheme d allow to reach;

F_dis the feed rate of the secondary processing scheme d, W_d，mIs the yield of the secondary discharge m of the secondary processing scheme d, F_m，eThe processing scheme e downstream of the secondary processing scheme d consumes the amount of secondary discharge m,is the stock quantity of the secondary discharge m at the initial production,is the stock quantity, Delta Q, of the secondary discharge m at the end of production_dIs Q_dThe difference value from the base value is,is Q_dW per unit deviation from the base value_d，mCorrection value of, Δ T_dIs a processing parameter T under a secondary processing scheme d_dThe difference value from the base value is,for the machining parameter T_dW per unit deviation from the base value_d，mThe correction value of (1);

Q_d，mis the value of the property of the secondary discharge m,is the property value of the initial inventory of the secondary discharge m,is Q_dQ per unit deviation from the base value_d，mThe correction value of (a) is determined,for the machining parameter T_dQ per unit deviation from the base value_d，mCorrection value of (1), Q_mRepresents the properties of the secondary discharge m;

the processing scheme e comprises the following steps: a secondary processing scheme d, a blending scheme o and a delivery scheme;

said Q_l Q_dmin、Q_dmax、W_d，m、 Q_d，m Andthe production parameters processed by the oil refinery within a specified time are collected or received;

the control parameters obtained by the above calculation include F_l，d、Q_d、F_d、F_m，e、ΔQ_d、ΔT_dAnd Q_m。

Further, the simulation of the primary processing corresponding to the crude oil distillation unit is carried out by adopting the following formula:

$\frac{\underset{i}{\mathrm{\Σ}}{F}_{i,b}\×Q_i}{\underset{i}{\mathrm{\Σ}}{F}_{i,b}}=Q_b,$

Q_bmin≤Q_b≤Q_bmax，

$\underset{c}{\mathrm{\Σ}}{F}_{u,c}=\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{F}_{i,b}\×W_{i,b,u}+({\mathrm{INV}}_u^{p-1}-{\mathrm{INV}}_u^p),$

$\frac{\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{F}_{i,b}\×W_{i,b,u}\×Q_{i,b,u}+{\mathrm{INV}}_u^{p-1}\×Q_u^{p-1}}{(\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{F}_{i,b}\×W_{i,b,u}+{\mathrm{INV}}_u^{p-1})}=Q_u,$

$C_{\mathrm{ATM},\mathrm{TR}\min }\≤\underset{b\∈\mathrm{TRB}}{\mathrm{\Σ}}\underset{i}{\mathrm{\Σ}}{F}_{i,b}\≤C_{\mathrm{ATM},\mathrm{TR}\max },$

$C_{\mathrm{VTM},\mathrm{TR}\min }\≤\underset{b\∈\mathrm{TRB}}{\mathrm{\Σ}}\underset{i}{\mathrm{\Σ}}{F}_{i,b}*V_{i,b}\≤C_{\mathrm{VTM},\mathrm{TR}\max },$

wherein Q is_iIs the property value of crude oil i, F_i，bIs the consumption of crude oil i in the distillation scheme b, Q_bIs the property value, Q, of the mixed feed of all crude oils under distillation processing scheme b_bminIs the minimum value, Q, allowed to be reached by the feed properties under distillation processing scheme b_bmaxIs a distillation processing scheme, the maximum value that is allowed to be reached by the feed properties;

W_i，b，uis the yield of crude oil i in the distillation output u of the distillation process variant b, F_u，cIs the consumption of the distillate u in a downstream processing scheme c of the distillation processing scheme b,is the inventory of the distillation discharge u at the initial production,is the inventory of the distillation discharge u at the end of production;

Q_i，b，uis the property value of crude i in the distillate output u of the distillation process variant b,is the initial stock property value, Q, of the distillate discharge u_uIs the property value of the distillation output u;

TR is a crude unit, ATM is an atmospheric tower in a crude unit, TRB is a set of processing schemes corresponding to a crude unit, C_ATM，TRminIs the minimum constraint value, C, of the atmospheric tower processing load in TR_ATM，TRmaxIs a processing load of a normal pressure tower in TRMaximum constraint value of the load;

VTM is the vacuum column in the crude unit TR, V_i，bIs the yield of atmospheric residue from crude oil i in distillation scheme b, C_VTM，TRminIs the minimum constraint value of the processing load of the vacuum tower in TR, C_VTM，TRmaxIs the maximum constraint value of the processing load of the vacuum tower in the TR;

the processing scheme c comprises the following steps: a secondary processing scheme d, a blending scheme o and a delivery scheme.

Said Q_i、Q_bmin、Q_bmax、W_i，b，u、Q_i，b，u C_ATM，TRmin、C_ATM，TRmax、C_VTM，TRmin、C_VTM，TRmaxAnd V_i，bThe production parameters processed by the oil refinery within a specified time are collected or received;

the control parameters obtained by the above calculation include F_i，b、Q_b、F_u，c、And Q_u。

Further, the control parameters are solved by adopting a distributed recursive algorithm.

Further, when the control parameters are solved by adopting a distribution recursion algorithm, the property value Q of the distillation discharge u_uInitial value Q of_u0Solving by the following formula:

$Q_{u0}=\frac{\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{W}_{i,b,u}\×Q_{i,b,u}+Q_u^{p-1}}{(\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{W}_{i,b,u}+1)};$

Q_uis in the value range of $[\min \left(Q_{i,b,u,}{Q}_u^{p-1}\right),\max \left(Q_{i,b,u}{Q}_u^{p-1}\right)].$

Further, when the control parameters are solved by adopting a distributed recursive algorithm, the property Q of the secondary discharge m_mInitial value Q of_m0Solving by the following formula:

$Q_{m0}=\frac{\underset{d}{\mathrm{\Σ}}{W}_{d,m}\×Q_{d,m}+Q_m^{p-1}}{\underset{d}{\mathrm{\Σ}}{W}_{d,m}+1}$

Q_min the range of $[\min \left(Q_{d,m,}{Q}_m^{p-1}\right),\max \left(Q_{d,m,}{Q}_m^{p-1}\right)].$

Further, when the control parameters are solved by adopting a distribution recursion algorithm, counting the destination number dd for each material subjected to property recursion calculation, wherein the destination number dd excludes processing schemes with constraint quantity of 0, and for processing schemes without constraint quantity of 0, the initial value of the error distribution coefficient is l/dd, and for processing schemes with constraint quantity of 0, the initial value of the error distribution coefficient is 0.

Further, generating the control parameter specifically includes:

determining whether the fluctuation of the collected or received production parameter within a specified time is greater than a threshold,

if the time is greater than the preset time, dividing the appointed time into at least two time units according to the time sequence, and calculating the control parameters according to the production parameters in each time unit;

when time units are divided, all the fluctuation of the production parameters in each time unit is not more than a threshold value; and the fluctuation of at least one production parameter in two adjacent time units is larger than the threshold value.

In order to solve the problems, the control system for the petrochemical industry comprises a production parameter acquisition device, a control parameter generation device, a control instruction generation device and a controller;

the acquisition device acquires or receives production parameters processed by the oil refinery within a specified time;

the control parameter generating device is used for solving the production parameters by linear or nonlinear optimization under the constraint conditions of simulating feeding, primary processing corresponding to the crude oil distilling device, secondary processing corresponding to the secondary processing device, finished oil blending and shipment, so as to generate control parameters;

the control instruction generating device receives the control parameters and forms control instructions according to the control parameters;

and the controller is used for receiving and controlling the production flow processed by the oil refinery according to the control instruction.

Further, the air conditioner is provided with a fan,

the control parameter generating device is used for simulating secondary processing corresponding to the secondary processing device and adopting the following formula:

$\frac{\underset{l}{\mathrm{\Σ}}{F}_{l,d}\×Q_l+{\mathrm{INV}}_d^{p-1}\×Q_d^{p-1}}{\underset{l}{\mathrm{\Σ}}{F}_{l,d}+{\mathrm{INV}}_d^{p-1}}=Q_d,$

Q_dmin≤Q_d≤Q_dmax，

$\underset{e}{\mathrm{\Σ}}{F}_{m,e}=\underset{d}{\mathrm{\Σ}}{F}_d\×(W_{d,m}+\underset{Q_d}{\mathrm{\Σ}}\mathrm{\Δ}{Q}_d\×\mathrm{\Δ}{W}_{Q_d,d,m}+\underset{T_d}{\mathrm{\Σ}}\mathrm{\Δ}{T}_d\×\mathrm{\Δ}{W}_{T_d,d,m})+({\mathrm{INV}}_m^{p-1}-{\mathrm{INV}}_m^p),$

$\frac{\underset{d}{\mathrm{\Σ}}{F}_d\×W_{d,m}\×(Q_{d,m}+\underset{Q_d}{\mathrm{\Σ}}\mathrm{\Δ}{Q}_d\×\mathrm{\Δ}{Q}_{Q_d,d,m}+\underset{T_d}{\mathrm{\Σ}}\mathrm{\Δ}{T}_d\×\mathrm{\Δ}{Q}_{T_d,d,m})+{\mathrm{INV}}_m^{p-1}\×Q_m^{p-1}}{\underset{d}{\mathrm{\Σ}}{F}_d\×W_{d,m}+{\mathrm{INV}}_m^{p-1}}=Q_m,$

wherein Q is_lIs the value of the property of the feed l, F_l，dIs the flow rate of feed l under secondary processing scheme d,is the initial inventory of mixed feed for secondary processing scheme d,is a property value, Q, of the initial inventory_dIs the quality value of the mixed feed of the secondary processing scheme d, Q_dminIs the minimum value, Q, allowed to be reached by the feed properties of the secondary processing scheme d_dmaxIs the maximum value that the feed properties of the secondary processing scheme d allow to reach;

F_dis the feed rate of the secondary processing scheme d, W_d，mIs the yield of the secondary discharge m of the secondary processing scheme d, F_m，eThe processing scheme e downstream of the secondary processing scheme d consumes the amount of secondary discharge m,is the stock quantity of the secondary discharge m at the initial production,is the stock quantity of the secondary discharge m at the end of production, △ Q_dIs Q_dThe difference value from the base value is,is Q_dW per unit deviation from the base value_d，mCorrection value of (8), (△ T)_dIs a processing parameter T under a secondary processing scheme d_dThe difference value from the base value is,for the machining parameter T_dW per unit deviation from the base value_d，mThe correction value of (1);

Q_d，mis the value of the property of the secondary discharge m,is the property value of the initial inventory of the secondary discharge m,is Q_dQ per unit deviation from the base value_d，mThe correction value of (a) is determined,for the machining parameter T_dQ per unit deviation from the base value_d，mCorrection value of (1), Q_mRepresents the properties of the secondary discharge m;

the processing scheme e comprises the following steps: a secondary processing scheme d, a blending scheme o and a delivery scheme;

said Q_l Q_dmin、Q_dmax、W_d，m、 Q_d，m Andthe production parameters processed by the oil refinery within a specified time are collected or received;

the control parameters obtained by the above calculation include F_l，d、Q_d、F_d、F_m，e、△Q_d、△T_dAnd Q_m。

Further, the air conditioner is provided with a fan,

the control parameter generating device simulates the primary processing corresponding to the crude oil distillation device and adopts the following formula:

$\frac{\underset{i}{\mathrm{\Σ}}{F}_{i,b}\×Q_i}{\underset{i}{\mathrm{\Σ}}{F}_{i,b}}=Q_b,$

Q_bmin≤Q_b≤Q_bmax，

$\underset{c}{\mathrm{\Σ}}{F}_{u,c}=\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{F}_{i,b}\×W_{i,b,u}+({\mathrm{INV}}_u^{p-1}-{\mathrm{INV}}_u^p),$

$\frac{\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{F}_{i,b}\×W_{i,b,u}\×Q_{i,b,u}+{\mathrm{INV}}_u^{p-1}\×Q_u^{p-1}}{(\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{F}_{i,b}\×W_{i,b,u}+{\mathrm{INV}}_u^{p-1})}=Q_u,$

$C_{\mathrm{ATM},\mathrm{TR}\min }\≤\underset{b\∈\mathrm{TRB}}{\mathrm{\Σ}}\underset{i}{\mathrm{\Σ}}{F}_{i,b}\≤C_{\mathrm{ATM},\mathrm{TR}\max },$

$C_{\mathrm{VTM},\mathrm{TR}\min }\≤\underset{b\∈\mathrm{TRB}}{\mathrm{\Σ}}\underset{i}{\mathrm{\Σ}}{F}_{i,b}*V_{i,b}\≤C_{\mathrm{VTM},\mathrm{TR}\max },$

wherein Q is_iIs the property value of crude oil i, F_i，bIs the consumption of crude oil i in the distillation scheme b, Q_bIs the property value, Q, of the mixed feed of all crude oils under distillation processing scheme b_bminIs the minimum value, Q, allowed to be reached by the feed properties under distillation processing scheme b_bmaxIs the maximum allowable feed properties under distillation processing scheme b;

W_i，b，uis the yield of crude oil i in the distillation output u of the distillation process variant b, F_u，cIs the consumption of the distillate u in a downstream processing scheme c of the distillation processing scheme b,is the inventory of the distillation discharge u at the initial production,is the inventory of the distillation discharge u at the end of production;

Q_i，b，uis the property value of crude i in the distillate output u of the distillation process variant b,is the initial stock property value, Q, of the distillate discharge u_uIs the property value of the distillation output u;

TR is a crude unit, ATM is an atmospheric tower in a crude unit, TRB is a set of processing schemes corresponding to a crude unit, C_ATM，TRminIs the minimum constraint value, C, of the atmospheric tower processing load in TR_ATM，TRmaxIs the maximum constraint value of the processing load of the normal pressure tower in TR；

VTM is the vacuum column in the crude unit TR, V_i，bIs the yield of atmospheric residue from crude oil i in distillation scheme b, C_VTM，TRminIs the minimum constraint value of the processing load of the vacuum tower in TR, C_VTM，TRmaxIs the maximum constraint value of the processing load of the vacuum tower in the TR;

the processing scheme c comprises the following steps: a secondary processing scheme d, a blending scheme o and a delivery scheme.

Said Q_i、Q_bmin、Q_bmax、W_i，b，u、Q_i，b，u、C_ATM，TRmin、C_ATM，TRmax、C_VTM，TRmin、C_VTM，TRmaxAnd V_i，bThe production parameters processed by the oil refinery within a specified time are collected or received;

the control parameters obtained by the above calculation include F_i，b、Q_b、F_u，c、And Q_u。

Further, the control parameter generating device solves the control parameters by adopting a distributed recursive algorithm.

Further, when the control parameter generating device adopts a distributed recursive algorithm to solve the control parameters, the property value Q of the distillation discharge material u_uInitial value Q of_u0Solving by the following formula:

$Q_{u0}=\frac{\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{W}_{i,b,u}\×Q_{i,b,u}+Q_u^{p-1}}{(\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{W}_{i,b,u}+1)};$

Q_uis in the value range of $[\min \left(Q_{i,b,u,}{Q}_u^{p-1}\right),\max \left(Q_{i,b,u,}{Q}_u^{p-1}\right)].$

Further, when the control parameter generating device adopts a distributed recursive algorithm to solve the control parameters, the property Q of the secondary discharge m_mInitial value Q of_m0Solving by the following formula:

$Q_{m0}=\frac{\underset{d}{\mathrm{\Σ}}{W}_{d,m}\×Q_{d,m}+Q_m^{p-1}}{\underset{d}{\mathrm{\Σ}}{W}_{d,m}+1}$

Q_min the range of $[\min \left(Q_{d,m,}{Q}_m^{p-1}\right),\max \left(Q_{d,m,}{Q}_m^{p-1}\right)].$

Further, when the control parameter generating device adopts a distribution recursion algorithm to solve the control parameters, counting a destination number dd for each material subjected to property recursion calculation, wherein the destination number dd excludes a processing scheme with a constraint quantity of 0, and for a processing scheme without a constraint quantity of 0, an initial value of an error distribution coefficient is 1/dd, and for a processing scheme with a constraint quantity of 0, an initial value of the error distribution coefficient is 0.

Further, the control parameter generating device is specifically configured to:

determining whether the fluctuation of the collected or received production parameter within a specified time is greater than a threshold,

if the time is greater than the preset time, dividing the appointed time into at least two time units according to the time sequence, and calculating the control parameters according to the production parameters in each time unit;

when time units are divided, all the production parameters in each time unit are enabled to be not larger than a threshold value in a fluctuation mode; and the fluctuation of at least one production parameter in two adjacent time units is larger than the threshold value.

The control method and the system for the petrochemical industry have the beneficial effects that:

firstly, the method comprises the following steps: the control method and the control system for the petrochemical industry solve the production parameters by adopting linear or nonlinear optimization through the computer under the constraint conditions of simulating feeding, primary processing corresponding to a crude oil distillation device, secondary processing corresponding to a secondary processing device, finished oil blending and shipment so as to generate the control parameters, replace manual derivation, have the advantage of quicker and more accurate calculation, reduce errors formed by manual derivation and have the phenomenon of high raw material waste or defective rate, thereby having the advantage of reducing the production cost;

secondly, the method comprises the following steps: the production parameters are solved by a computer through linear or nonlinear optimization to generate control parameters, the optimized control parameters are obtained, and the control parameters are used for controlling production, so that the advantages of improving the production efficiency, improving the utilization rate of materials and reducing the production cost are achieved.

Thirdly, the method comprises the following steps: the invention relates to a control method and a control system for petrochemical industry, which comprehensively consider the parameters of material properties, flow, temperature, pressure, duration and the like in processing under the constraint conditions of simulating feeding, primary processing corresponding to a crude oil distillation device, secondary processing corresponding to a secondary processing device, finished oil blending and shipment, and dynamically simulate and track the change of each parameter in a specified time, so that the simulation of actual production is closer to the reality, the control of production by control parameters obtained by multi-cycle optimization is more reasonable, the control is optimized again, the production is optimized again, and the invention has the advantages of improving efficiency, reducing cost and the like.

Drawings

FIG. 1 is a flow chart of a control method for the petrochemical industry according to an embodiment of the invention;

FIG. 2 is a block diagram of a control system for the petrochemical industry according to an embodiment of the present invention;

fig. 3 is a second structural diagram of a control system for petrochemical industry according to an embodiment of the present invention.

Detailed Description

The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.

Example 1

As shown in fig. 1, the control method for the petrochemical industry of the present embodiment includes:

step S1: collecting or receiving production parameters processed by an oil refinery within a specified time;

step S2: under the constraint conditions of simulating feeding, primary processing corresponding to a crude oil distillation device, secondary processing corresponding to a secondary processing device, blending of finished oil and shipment, solving the production parameters by linear or nonlinear optimization so as to generate control parameters;

step S3: forming a control instruction according to the control parameter;

step S4: and controlling the production flow of the processing of the oil refinery according to the control instruction.

Refining in petrochemical processing refers to refining petroleum, which is a production process for producing fuel oil such as kerosene, gasoline, diesel oil, heavy oil, paraffin and the like and industrial lubricating oil from petroleum by a physical separation or chemical conversion method. Raw materials involved in petrochemical processing comprise crude oil with different properties and components, catalysts and promoters for various reactions, and the related equipment is also in various types and quantities. In this embodiment, the feeding, discharging and intermediate processing processes of the materials of the main processing equipment of the oil refinery are simulated by the extracted constraint conditions, and the control parameters are calculated by the computer equipment. In the conventional control method, control parameters related to the input, output, processing of materials and the connection of materials between processing devices are derived manually according to personal experience. Due to the fact that the related materials are various, the related processing steps, reactions and processes are complex, a reasonable control parameter with the optimal resource configuration is difficult to obtain through manual derivation, various errors caused by human factors are caused during specific control processing, raw material waste, equipment idling or excessive load on part of processing equipment on a production line occurs, and the production efficiency is low and the processing cost is high due to the fact that part of equipment is in a standby state, the quality of produced products is unqualified or unnecessarily high. In the control method described in this embodiment, the corresponding models of feeding, crude oil distillation, secondary processing, finished oil blending, and shipment are abstracted into models that can be calculated, so that the calculation is more accurate, the factors considered are comprehensive and comprehensive, and the computer and other devices solve the models instead of solving the models manually, thereby simply solving the limitations of manual errors and the like caused by the manual derivation. Therefore, when the control method is used for monitoring the oil refinery, the control is more accurate; the oil refinery carries out production according to the control method, the production efficiency is high, the waste is small, the quality of the finished product is good, and the production cost is greatly reduced.

Wherein, the crude oil distillation refers to a process of separating crude oil according to different boiling points; the secondary processing refers to refining the semi-finished product subjected to crude oil distillation separation again; the finished product oil blending refers to a manufacturing process of mixing various finished products according to preset proportion and properties to form required articles by taking the finished products after secondary processing as objects.

Example 2

The control method for petrochemical processing comprises the following steps

Step 1: collecting or receiving production parameters processed by an oil refinery within a specified time;

step 2: under the constraint conditions of simulating feeding, primary processing corresponding to a crude oil distillation device, secondary processing corresponding to a secondary processing device, blending of finished oil and shipment, solving the production parameters by linear or nonlinear optimization so as to generate control parameters;

and step 3: forming a control instruction according to the control parameter;

and 4, step 4: and controlling the production flow of the processing of the oil refinery according to the control instruction.

And simulating the secondary processing corresponding to the secondary processing device by adopting the following formula:

$\frac{\underset{l}{\mathrm{\Σ}}{F}_{l,d}\×Q_l+{\mathrm{INV}}_d^{p-1}\×Q_d^{p-1}}{\underset{l}{\mathrm{\Σ}}{F}_{l,d}+{\mathrm{INV}}_d^{p-1}}=Q_d,$

Q_dmin≤Q_d≤Q_dmax，

$\underset{e}{\mathrm{\Σ}}{F}_{m,e}=\underset{d}{\mathrm{\Σ}}{F}_d\×(W_{d,m}+\underset{Q_d}{\mathrm{\Σ}}\mathrm{\Δ}{Q}_d\×\mathrm{\Δ}{W}_{Q_d,d,m}+\underset{T_d}{\mathrm{\Σ}}\mathrm{\Δ}{T}_d\×\mathrm{\Δ}{W}_{T_d,d,m})+({\mathrm{INV}}_m^{p-1}-{\mathrm{INV}}_m^p),$

$\frac{\underset{d}{\mathrm{\Σ}}{F}_d\×W_{d,m}\×(Q_{d,m}+\underset{Q_d}{\mathrm{\Σ}}\mathrm{\Δ}{Q}_d\×\mathrm{\Δ}{Q}_{Q_d,d,m}+\underset{T_d}{\mathrm{\Σ}}\mathrm{\Δ}{T}_d\×\mathrm{\Δ}{Q}_{T_d,d,m})+{\mathrm{INV}}_m^{p-1}\×Q_m^{p-1}}{\underset{d}{\mathrm{\Σ}}{F}_d\×W_{d,m}+{\mathrm{INV}}_m^{p-1}}=Q_m,$

wherein Q is_lIs the value of the property of the feed l, F_l，dIs the flow rate of feed l under secondary processing scheme d,is the initial inventory of mixed feed for secondary processing scheme d,is a property value, Q, of the initial inventory_dIs the quality value of the mixed feed of the secondary processing scheme d, Q_dminIs the minimum value, Q, allowed to be reached by the feed properties of the secondary processing scheme d_dmaxIs the maximum value that the feed properties of the secondary processing scheme d allow to reach;

F_dis the feed rate of the secondary processing scheme d, W_d，mIs the yield of the secondary discharge m of the secondary processing scheme d, F_m，eThe processing scheme e downstream of the secondary processing scheme d consumes the amount of secondary discharge m,is the stock quantity of the secondary discharge m at the initial production,is the stock quantity of the secondary discharge m at the end of production, △ Q_dIs Q_dThe difference value from the base value is,is Q_dW per unit deviation from the base value_d，mCorrection value of (8), (△ T)_dIs a processing parameter T under a secondary processing scheme d_dThe difference value from the base value is,for the machining parameter T_dW per unit deviation from the base value_d，mThe correction value of (1);

Q_d，mis the value of the property of the secondary discharge m,is the property value of the initial inventory of the secondary discharge m,is Q_dQ per unit deviation from the base value_d，mThe correction value of (a) is determined,for the machining parameter T_dQ per unit deviation from the base value_d，mCorrection value of (1), Q_mRepresents the properties of the secondary discharge m;

the processing scheme e comprises the following steps: a secondary processing scheme d, a blending scheme o and a delivery scheme;

said Q_l Q_dmin、Q_dmax、W_d，m、 Q_d，m Andthe production parameters processed by the oil refinery within a specified time are collected or received;

the control parameters obtained by the above calculation include F_i，d、Q_d、Q_d、F_m，e、△Q_d、△T_dAnd Q_m。

The constraint conditions for simulating the secondary processing may be various, and this embodiment provides a constraint condition for specifically, preferably simulating the secondary processing with respect to embodiment 1. The constraint condition formed by the formula fully considers the property of the material (such as parameter Q)_l) Also introduces Q_d、ΔQ_dAndand (5) the parameters are equal, and the control parameters are corrected when the material properties deviate from the basic values. The concrete steps are as follows: wherein Δ Q_dFeed Property Q for scheme d_dDeviation from the base value q_dDifference of (1), i.e. Δ Q_d=Q_d-q_d；Is of nature Q_dPer deviation from the base value q_dYield per unit hour W_d，mThe correction value of (2).I.e. the sum of the corrected values for the m yield of the material when all the properties of the feed deviate from their basic values. Due to the fact that the deviation of the material property from the reference value is fully considered, the simulation production process flow is closer to the actual situation and more reasonable, the obtained control parameters are more reasonable, and therefore when production is controlled, the production flow is smoother, the property of the produced product meets the requirements, and production is optimized again.

Example 3

In this embodiment, on the basis of embodiment 2, a set of constraint conditions for optimizing and simulating the primary processing is further provided, which are specifically as follows:

and simulating the corresponding primary processing of the crude oil distillation device by adopting the following formula:

$\frac{\underset{i}{\mathrm{\Σ}}{F}_{i,b}\×Q_i}{\underset{i}{\mathrm{\Σ}}{F}_{i,b}}=Q_b,$

Q_bmin≤Q_b≤Q_bmax，

$\underset{c}{\mathrm{\Σ}}{F}_{u,c}=\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{F}_{i,b}\×W_{i,b,u}+({\mathrm{INV}}_u^{p-1}-{\mathrm{INV}}_u^p),$

$\frac{\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{F}_{i,b}\×W_{i,b,u}\×Q_{i,b,u}+{\mathrm{INV}}_u^{p-1}\×Q_u^{p-1}}{(\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{F}_{i,b}\×W_{i,b,u}+{\mathrm{INV}}_u^{p-1})}=Q_u,$

$C_{\mathrm{ATM},\mathrm{TR}\min }\≤\underset{b\∈\mathrm{TRB}}{\mathrm{\Σ}}\underset{i}{\mathrm{\Σ}}{F}_{i,b}\≤C_{\mathrm{ATM},\mathrm{TR}\max },$

$C_{\mathrm{VTM},\mathrm{TR}\min }\≤\underset{b\∈\mathrm{TRB}}{\mathrm{\Σ}}\underset{i}{\mathrm{\Σ}}{F}_{i,b}*V_{i,b}\≤C_{\mathrm{VTM},\mathrm{TR}\max ,}$

wherein Q is_iIs the property value of crude oil i, F_i，bIs the consumption of crude oil i in the distillation scheme b, Q_bIs the property value, Q, of the mixed feed of all crude oils under distillation processing scheme b_bminIs that the feed properties under distillation processing scheme b allowTo minimum value, Q_bmaxIs the maximum allowable feed properties under distillation processing scheme b;

W_i，b，uis the yield of crude oil i in the distillation output u of the distillation process variant b, F_u，cIs the consumption of the distillate u in a downstream processing scheme c of the distillation processing scheme b,is the inventory of the distillation discharge u at the initial production,is the inventory of the distillation discharge u at the end of production;

Q_i，b，uis the property value of crude i in the distillate output u of the distillation process variant b,is the initial stock property value, Q, of the distillate discharge u_uIs the property value of the distillation output u;

TR is a crude unit, ATM is an atmospheric tower in a crude unit, TRB is a set of processing schemes corresponding to a crude unit, C_ATM，TRminIs the minimum constraint value, C, of the atmospheric tower processing load in TR_ATM，TRmaxIs the maximum constraint value of the normal pressure tower processing load in TR;

VTM is the vacuum column in the crude unit TR, V_i，bIs the yield of atmospheric residue from crude oil i in distillation scheme b, C_VTM，TRminIs the minimum constraint value of the processing load of the vacuum tower in TR, C_VTM，TRmaxIs the maximum constraint value of the processing load of the vacuum tower in the TR;

the processing scheme c comprises the following steps: a secondary processing scheme d, a blending scheme o and a delivery scheme.

Said Q_i、Q_bmin、Q_bmax、W_i，b，u、Q_i，b，u、C_ATM，TRmin、C_ATM，TRmax、C_VTM，TRmin、C_VTM，TRmaxAnd V_i，bThe production parameters processed by the oil refinery within a specified time are collected or received;

the control parameters obtained by the above calculation include F_i，b、Q_b、F_u，c、And Q_u。

The constraint conditions in the embodiment simulate a plurality of processing flows of a crude oil distillation device in an oil refinery, the processing flows are linearly superposed together, a constraint condition which only concerns feeding, feeding control, discharging, and the relation between the properties and the flow of the feeding and the discharging is defined, and the actual situation of production is accurately and fully reflected, so that the production control parameters are more favorable for optimization control.

In a specific implementation process, a plurality of calculation methods may be adopted to calculate the control parameters, and in this embodiment, a distributed recursive algorithm is preferentially adopted to solve the control parameters. In the embodiment, the nonlinear problem is linearized through a distributed recursive algorithm, and then optimized values of a plurality of solutions are obtained through optimization solution, so that the obtained control parameters are also optimized parameters, and further, the production is optimized.

Example 4

In the control method for petrochemical processing according to this embodiment, based on embodiment 3, when the control parameter is solved by using a distributed recursive algorithm, the property value Q of the distilled material u is obtained_uInitial value Q of_u0Solving by the following formula:

$Q_{u0}=\frac{\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{W}_{i,b,u}\×Q_{i,b,u}+Q_u^{p-1}}{(\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{W}_{i,b,u}+1)};$

Q_uis in the value range of $[\min (Q_{i,b,u},Q_u^{p-1}),\max (Q_{i,b,u},Q_u^{p-1})].$

Further, when the control parameters are solved by adopting a distributed recursive algorithm, the property Q of the secondary discharge m_mInitial value Q of_m0Solving by the following formula:

$Q_{m0}=\frac{\underset{d}{\mathrm{\Σ}}{W}_{d,m}\×Q_{d,m}+Q_m^{p-1}}{\underset{d}{\mathrm{\Σ}}{W}_{d,m}+1}$

Q_min the range of $[\min \left(Q_{d,m,}{Q}_m^{p-1}\right),\max \left(Q_{d,m,}{Q}_m^{p-1}\right)].$

Above Q_u、Q_mThe value range can be set according to the actual condition of the material, and the result convergence is improved conveniently by setting the value range, so that the calculated amount is reduced. Specifically, for example, where there are multiple processing schemes (e.g., diesel scheme and gasoline scheme, etc.) for catalytic cracking in one of the secondary processing units that produce gasoline, an initial guess for a property (e.g., sulfur content) of the gasoline produced by that unit can be expressed as the above equation. Wherein d represents a processing scheme, W_d，mRepresents the yield of gasoline produced in processing scheme d, Q_d，mIndicating the properties of the gasoline produced under processing scheme d,indicating the nature of the initial inventory of gasoline. Property Q of gasoline produced under each scheme_d，mAnd in the nature of stockThe maximum and minimum values correspond to maximum and minimum limits, respectively.

Further, when the control parameter is solved by using the distribution recursion algorithm, the going number dd is counted for each material subjected to the property recursion calculation, the going number dd excludes the processing plan in which the constraint amount is 0, and for the processing plan in which the constraint amount is not present, the initial value of the error distribution coefficient is 1/dd, and for the processing plan in which the constraint amount is 0, the initial value of the error distribution coefficient is 0. Specifically, for example, a certain discharge u of the crude oil distillation unit may flow to four processing flows of the secondary processing unit, and the four processing flows do not have the constraint that the processing amount is 0, so that the initial value of the error distribution coefficient introduced by the material u is 0.25 for the four sets of processing schemes.

Example 5

In this embodiment, a further improvement is made on the basis of embodiment 3 or embodiment 4, and the generation of the control parameter is detailed as follows:

determining whether the fluctuation of the collected or received production parameter within a specified time is greater than a threshold,

if the time is greater than the preset time, dividing the appointed time into at least two time units according to the time sequence, and calculating the control parameters according to the production parameters in each time unit;

when time units are divided, all the fluctuation of the production parameters in each time unit is not more than a threshold value; and the fluctuation of at least one production parameter in two adjacent time units is larger than the threshold value.

In the embodiment, the fluctuation of the received or collected production parameters in the designated time is judged, and when the production parameters fluctuate in the designated time range, the production parameters are sequentially divided into a plurality of time units according to the time sequence, so that the data in each unit do not fluctuate, and the data in each adjacent unit fluctuate, thereby constructing the optimization problem of multi-cycle optimization, conveniently generating control parameters aiming at each time period, and improving the control precision.

In addition, this embodiment still provides a constraint condition that simulation product oil mediation:

the method comprises the following specific steps: $Q_{o\min }\≤\frac{\underset{n}{\mathrm{\Σ}}{F}_{n,o}*Q_n}{\underset{n}{\mathrm{\Σ}}{F}_{n,o}}\≤Q_{o\max }$ … … type (A)

This equation characterizes the property constraints of the reconciliation scheme o. The product properties of the blending scheme are obtained by weighted averaging of the properties of the blending components. Wherein Q is_nIs the property value of the blending component n, F_n，oIs the flow rate at which component n is used for reconciliation,is a property value of the product. Q_ominAnd Q_omaxAre the minimum and maximum values allowed for the product properties.

In particular, if there is an interaction between two of the blend components, i.e., the physical properties of the mixture are not a linear weighted average of the physical properties of the components, but there are additional corrections based thereon, then equation (A), which characterizes the physical property constraints of the blended product, can be expressed as:

$Q_{o\min }\≤\frac{\underset{n}{\mathrm{\Σ}}{F}_{n,o}*Q_n+\underset{r,s\∈n}{\underset{r\≠s}{\mathrm{\Σ}}}{Y}_{\mathrm{rs}}*F_{s,o}}{\underset{n}{\mathrm{\Σ}}{f}_{n,o}}\≤Q_{o\max }$ … … type (B)

Wherein, Y_rsIs the interaction that occurs when blending components r and s are mixed.

$F_{n,o}=X_{n,o}*\underset{n}{\mathrm{\Σ}}{F}_{n,o}$ … … type (C)

Formula (C) is used to characterize the flow ratio of the blend components. Wherein,denotes the total amount of product, X_n，oThe proportion of blending component n in the total product is shown. The feeding n is one or more of raw material i, distillation scheme discharging u and secondary processing scheme discharging m.

Further, the relationship according to the stock amounts of the materials in examples 1 to 5 of the present invention may also satisfy the following constraints: ${\mathrm{INV}}_{z\min }^P\≤{\mathrm{INV}}_z^P\≤{\mathrm{INV}}_{z\max }^P$

wherein,is the inventory of material z at the end of production,andis the minimum and maximum allowed inventory of material z at the end of production.

The flow rate of all materials related in the embodiment of the invention can be volume flow rate or mass flow rate; the material concerned can be either volumetric or mass in nature. But the product of flow and property must be based on the same criteria, i.e. volume flow multiplied by volume-type property, or mass flow multiplied by mass-type property. When the standards are not in agreement, the conversion between the volume flow and the mass flow is as follows:

F_w，z=F_x，z*S_z

wherein, F_w，zIs the mass flow of the material z, F_v，zIs the volume flow of the material z, S_zIs the density (mass per unit volume) of the material z.

Flow F of material z involved in the above model_zThe following constraints may exist:

F_zmin≤F_z≤F_zmax

wherein, F_zminAnd F_zmaxAre the minimum and maximum constraint values for the z flow of the material.

In summary, embodiments 1 to 5 provide a method for realizing control of specific processes by simulating petrochemical processes and automatically generating control parameters by monitoring devices such as computers. The method has the advantages of accurate control, high production efficiency, low production cost and the like.

Example 6:

as shown in fig. 2, the control system for the petrochemical industry in this embodiment includes a production parameter collecting device 1, a control parameter generating device 2, a control instruction generating device 3, and a controller 4;

the acquisition device 1 acquires or receives production parameters processed by the oil refinery within a specified time;

the control parameter generating device 2 is used for solving the production parameters by linear or nonlinear optimization under the constraint conditions of simulating feeding, primary processing corresponding to a crude oil distillation device, secondary processing corresponding to a secondary processing device, finished oil blending and shipment, so as to generate control parameters;

the control instruction generating device 3 is used for receiving the control parameters and forming control instructions according to the control parameters;

and the controller 4 is used for receiving and controlling the production flow processed by the oil refinery according to the control instruction.

Control system of petrochemical industry in this embodiment, set up relatively traditional system control parameter generation device 2 can be by oneself according to the production parameter production control parameter who gathers or receive, and need not artifical manual derivation back input to it is intelligent higher, also swift more convenient for artifical manual derivation, the control parameter that forms simultaneously can more accurate control production, thereby be favorable to reducing the waste of raw materials in the production, the generation of inferior oil, improved production efficiency and reduced manufacturing cost.

Example 7:

the control system for the petrochemical industry in the embodiment comprises a production parameter acquisition device 1, a control parameter generation device 2, a control instruction generation device 3 and a controller 4;

the acquisition device 1 acquires or receives production parameters processed by the oil refinery within a specified time;

the control parameter generating device 2 is used for solving the production parameters by linear or nonlinear optimization under the constraint conditions of simulating feeding, primary processing corresponding to a crude oil distillation device, secondary processing corresponding to a secondary processing device, finished oil blending and shipment, so as to generate control parameters;

the control instruction generating device 3 is used for receiving the control parameters and forming control instructions according to the control parameters;

and the controller 4 is used for receiving and controlling the production flow processed by the oil refinery according to the control instruction.

Specifically, the control parameter generating device 3 is configured to simulate secondary processing corresponding to the secondary processing device by using the following formula:

$\frac{\underset{l}{\mathrm{\Σ}}{F}_{l,d}\×Q_l+{\mathrm{INV}}_d^{p-1}\×Q_d^{p-1}}{\underset{l}{\mathrm{\Σ}}{F}_{l,d}+{\mathrm{INV}}_d^{p-1}}=Q_d,$

Q_dmin≤Q_d≤Q_dmax，

$\underset{e}{\mathrm{\Σ}}{F}_{m,e}=\underset{d}{\mathrm{\Σ}}{F}_d\×(W_{d,m}+\underset{Q_d}{\mathrm{\Σ}}\mathrm{\Δ}{Q}_d\×\mathrm{\Δ}{W}_{Q_d,d,m}+\underset{T_d}{\mathrm{\Σ}}\mathrm{\Δ}{T}_d\×\mathrm{\Δ}{W}_{T_d,d,m})+({\mathrm{INV}}_m^{p-1}-{\mathrm{INV}}_m^p),$

$\frac{\underset{d}{\mathrm{\Σ}}{F}_d\×W_{d,m}\×(Q_{d,m}+\underset{Q_d}{\mathrm{\Σ}}\mathrm{\Δ}{Q}_d\×\mathrm{\Δ}{Q}_{Q_d,d,m}+\underset{T_d}{\mathrm{\Σ}}\mathrm{\Δ}{T}_d\×\mathrm{\Δ}{Q}_{T_d,d,m})+{\mathrm{INV}}_m^{p-1}\×Q_m^{p-1}}{\underset{d}{\mathrm{\Σ}}{F}_d\×W_{d,m}+{\mathrm{INV}}_m^{p-1}}=Q_m,$

wherein Q is_lIs the value of the property of the feed l, F_l，dIs the flow rate of feed l under secondary processing scheme d,is the initial inventory of mixed feed for secondary processing scheme d,is a property value, Q, of the initial inventory_dIs the quality value of the mixed feed of the secondary processing scheme d, Q_dminIs the minimum value allowed to be reached by the feed properties of the secondary processing scheme d，Q_dmaxIs the maximum value that the feed properties of the secondary processing scheme d allow to reach;

F_dis the feed rate of the secondary processing scheme d, W_d，mIs the yield of the secondary discharge m of the secondary processing scheme d, F_m，eThe processing scheme e downstream of the secondary processing scheme d consumes the amount of secondary discharge m,is the stock quantity of the secondary discharge m at the initial production,is the stock quantity, Delta Q, of the secondary discharge m at the end of production_dIs Q_dThe difference value from the base value is,is Q_dW per unit deviation from the base value_d，mCorrection value of, Δ T_dIs a processing parameter T under a secondary processing scheme d_dThe difference value from the base value is,for the machining parameter T_dW per unit deviation from the base value_d，mThe correction value of (1);

Q_d，mis the value of the property of the secondary discharge m,is the property value of the initial inventory of the secondary discharge m,is Q_dQ per unit deviation from the base value_d，mThe correction value of (a) is determined,for the machining parameter T_dQ per unit deviation from the base value_d，mCorrection value of (1), Q_mIndicating secondary dischargeThe nature of m;

the processing scheme e comprises the following steps: a secondary processing scheme d, a blending scheme o and a delivery scheme;

said Q_l Q_dmin、Q_dmax、W_d，m、 Q_d，m Andthe production parameters processed by the oil refinery within a specified time are collected or received;

the control parameters obtained by the above calculation include F_l，d、Q_d、F_d、F_m，e、ΔQ_d、ΔT_dAnd Q_m。

The control parameter generating device 3 may specifically implement various constraints for simulating the secondary processing, and this embodiment provides a set of constraints for specifically and preferably simulating the secondary processing, compared to embodiment 1. The constraint condition formed by the formula fully considers the property of the material (such as parameter Q)_l) Also introduces Q_d、ΔQ_dAndand (5) the parameters are equal, and the control parameters are corrected when the material properties deviate from the basic values. The concrete steps are as follows: wherein Δ Q_dFeed Property Q for scheme d_dDeviation from the base value q_dDifference of (1), i.e. Δ Q_d=Q_d-q_d；Is of nature Q_dPer deviation from the base value q_dYield per unit hour W_d，mThe correction value of (2).The process is closer to the actual situation and more reasonable, and the obtained control parameters are more reasonable, so that the production process is smoother, the quality standard reaching rate of the produced product is higher, and the production is optimized again.

Example 8:

in this embodiment, based on the above embodiments 6 and 7, the control parameter generating device simulates the primary processing of the crude oil distillation apparatus by using the following formula:

$\frac{\underset{i}{\mathrm{\Σ}}{F}_{i,b}\×Q_i}{\underset{i}{\mathrm{\Σ}}{F}_{i,b}}=Q_b,$

Q_bmin≤Q_b≤Q_bmax，

$\underset{c}{\mathrm{\Σ}}{F}_{u,c}=\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{F}_{i,b}\×W_{i,b,u}+({\mathrm{INV}}_u^{p-1}-{\mathrm{INV}}_u^p),$

$\frac{\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{F}_{i,b}\×W_{i,b,u}{\×Q}_{i,b,u}+{\mathrm{INV}}_u^{p-1}\×Q_u^{p-1}}{(\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{F}_{i,b}\×W_{i,b,u}+{\mathrm{INV}}_u^{p-1})}=Q_u,$

$C_{\mathrm{ATM},\mathrm{TR}\min }\≤\underset{b\∈\mathrm{TRB}}{\mathrm{\Σ}}\underset{i}{\mathrm{\Σ}}{F}_{i,b}\≤C_{\mathrm{ATM},\mathrm{TR}\max ,}$

$C_{\mathrm{VTM},\mathrm{TR}\min }\≤\underset{b\∈\mathrm{TRB}}{\mathrm{\Σ}}\underset{i}{\mathrm{\Σ}}{F}_{i,b}*V_{i,b}\≤C_{\mathrm{VTM},\mathrm{TR}\max },$

wherein Q is_iIs the property value of crude oil i, F_i，bIs the consumption of crude oil i in the distillation scheme b, Q_bIs the property value, Q, of the mixed feed of all crude oils under distillation processing scheme b_bminIs the minimum value, Q, allowed to be reached by the feed properties under distillation processing scheme b_bmaxIs the maximum allowable feed properties under distillation processing scheme b;

W_i，b，uis the yield of crude oil i in the distillation output u of the distillation process variant b, F_u，cIs the consumption of the distillate u in a downstream processing scheme c of the distillation processing scheme b,is the inventory of the distillation discharge u at the initial production,is the inventory of the distillation discharge u at the end of production;

Q_i，b，uis the property value of crude i in the distillate output u of the distillation process variant b,is the initial stock property value, Q, of the distillate discharge u_uIs the property value of the distillation output u;

TR is a crude unit, ATM is an atmospheric tower in a crude unit, TRB is a set of processing schemes corresponding to a crude unit, C_ATM，TRminIs the minimum constraint value, C, of the atmospheric tower processing load in TR_ATM，TRmaxIs the maximum constraint value of the normal pressure tower processing load in TR;

VTM is the vacuum column in the crude unit TR, V_i，bIs the yield of atmospheric residue from crude oil i in distillation scheme b, C_VTM，TRminIs the minimum constraint value of the processing load of the vacuum tower in TR, C_VTM，TRmaxIs the maximum constraint value of the processing load of the vacuum tower in the TR;

the processing scheme c comprises the following steps: a secondary processing scheme d, a blending scheme o and a delivery scheme.

Said Q_i、Q_bmin、Q_bmax、W_i，b，u、Q_i，b，u、C_ATM，TRminC_ATM，TRmaxC_VTM，TRminC_VTM，TRmaxAnd V_i，bThe production parameters processed by the oil refinery within a specified time are collected or received;

the control parameters obtained by the above calculation include F_i，b、Q_b、F_u，c、And Q_u。

Example 9:

the control system for the petrochemical industry according to this embodiment is further configured, on the basis of the foregoing embodiment 6 to embodiment 8, that the control parameter generating device solves the control parameter by using a distributed recursive algorithm.

Further, when the control parameter generating device adopts a distributed recursive algorithm to solve the control parameters, the property value Q of the distillation discharge material u_uInitial value Q of_u0Solving by the following formula:

$Q_{u0}=\frac{\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{W}_{i,b,u}\×Q_{i,b,u}+Q_u^{p-1}}{\left(\underset{i}{\mathrm{\Σ}}\underset{b}{\mathrm{\Σ}}{W}_{i,b,u}+1\right)};$

Q_uis in the value range of $[\min (Q_{i,b,u},Q_u^{p-1}),\max (Q_{i,b,u},Q_u^{p-1})].$

Further, when the control parameter generating device adopts a distributed recursive algorithm to solve the control parameters, the property Q of the secondary discharge m_mInitial value Q of_m0Solving by the following formula:

$Q_{m0}=\frac{\underset{d}{\mathrm{\Σ}}{W}_{d,m}\×Q_{d,m}+Q_m^{p-1}}{\underset{d}{\mathrm{\Σ}}{W}_{d,m}+1}$

Q_min the range of $[\min (Q_{d,m},Q_m^{p-1}),\max (Q_{d,m},Q_m^{p-1})].$

Further, when the control parameter generating device adopts a distribution recursion algorithm to solve the control parameters, counting a destination number dd for each material subjected to property recursion calculation, wherein the destination number dd excludes a processing scheme with a constraint quantity of 0, and for a processing scheme without a constraint quantity of 0, an initial value of an error distribution coefficient is 1/dd, and for a processing scheme with a constraint quantity of 0, an initial value of the error distribution coefficient is 0.

Further, the control parameter generating device is specifically configured to:

determining whether the fluctuation of the collected or received production parameter within a specified time is greater than a threshold,

if the time is greater than the preset time, dividing the appointed time into at least two time units according to the time sequence, and calculating the control parameters according to the production parameters in each time unit;

when time units are divided, all the fluctuation of the production parameters in each time unit is not more than a threshold value; and the fluctuation of at least one production parameter in two adjacent time units is larger than the threshold value.

In summary, the control system for the petrochemical industry according to the embodiments 6 to 9 correspondingly completes the control method for the petrochemical industry according to the present invention.

In addition, another specific structure of the control system for the petrochemical industry is also provided as shown in fig. 3:

the control system for the petrochemical industry comprises at least one processor 7 (e.g., CPU), at least one interface 6 or other communication interface, a memory 5 and at least one communication bus 8 for enabling communication among the devices. The processor 7 is used to execute executable modules stored in the memory 5, such as: a computer program. The memory 5 may include a Random Access Memory (RAM), a Read Only Memory (ROM), and a non-volatile memory (non-volatile), for example: at least one disk storage. The communication connection between the system gateway and at least one other network element is realized through at least one network interface (which can be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network and the like can be used.

In some embodiments, the memory 5 stores a program that can be executed by the processor 7, the program operating to perform at least the following functions:

collecting or receiving production parameters processed by an oil refinery within a specified time;

under the constraint conditions of simulating feeding, primary processing corresponding to a crude oil distillation device, secondary processing corresponding to a secondary processing device, blending of finished oil and shipment, solving the production parameters by linear or nonlinear optimization so as to generate control parameters;

forming a control instruction according to the control parameter;

and controlling the production flow of the processing of the oil refinery according to the control instruction.

In a specific implementation, each implementation step includes a separate apparatus having the structure shown in fig. 3.

The base station maintenance device has the advantages of simple structure, simplicity and convenience in implementation and low hardware cost.

The above embodiments are only for illustrating the invention and are not to be construed as limiting the invention, and those skilled in the art can make various changes and modifications without departing from the spirit and scope of the invention, therefore, all equivalent technical solutions also belong to the scope of the invention, and the scope of the invention is defined by the claims.

Claims (14)

1. A control method for the petrochemical industry, comprising:

collecting or receiving production parameters processed by an oil refinery within a specified time;

under the constraint conditions of simulating feeding, primary processing corresponding to a crude oil distillation device, secondary processing corresponding to a secondary processing device, blending of finished oil and shipment, solving the production parameters by linear or nonlinear optimization so as to generate control parameters;

forming a control instruction according to the control parameter;

controlling the production flow of the processing of the oil refinery according to the control instruction;

and simulating secondary processing corresponding to the secondary processing device by adopting the following formula:

$\frac{\underset{l}{\Σ}{F}_{l,d}\×Q_l+{\mathrm{INV}}_d^{p-1}\×Q_d^{p-1}}{\underset{l}{\Σ}{F}_{l,d}+{\mathrm{INV}}_d^{p-1}}=Q_d,$

Q_dmin≤Q_d≤Q_dmax，

$\underset{e}{\Σ}{F}_{m,e}=\underset{e}{\Σ}{F}_d\×\left(W_{d,m}+\underset{Q_d}{\Σ}{\mathrm{\ΔQ}}_d\×{\mathrm{\ΔW}}_{Q_d,d,m}+\underset{T_d}{\Σ}{\mathrm{\ΔT}}_d\×{\mathrm{\ΔW}}_{T_d,d,m}\right)+\left({\mathrm{INV}}_m^{p-1}-{\mathrm{INV}}_m^p\right),$

$\frac{\underset{d}{\Σ}{F}_d\×W_{d,m}\×(Q_{d,m}+\underset{Q_d}{\Σ}{\mathrm{\ΔQ}}_d\×{\mathrm{\ΔQ}}_{Q_d,d,m}+\underset{T_d}{\Σ}{\mathrm{\ΔT}}_d\×{\mathrm{\ΔQ}}_{T_d,d,m})+{\mathrm{INV}}_m^{p-1}\×Q_m^{p-1}}{\underset{d}{\Σ}{F}_d\×W_{d,m}+{\mathrm{INV}}_m^{p-1}}=Q_m,$

wherein Q is_lIs the value of the property of the feed l, F_l,dIs the flow rate of feed l under secondary processing scheme d,is the initial inventory of mixed feed for secondary processing scheme d,is a property value, Q, of the initial inventory_dIs the quality value of the mixed feed of the secondary processing scheme d, Q_dminIs the minimum value, Q, allowed to be reached by the feed properties of the secondary processing scheme d_dmaxIs the maximum value that the feed properties of the secondary processing scheme d allow to reach;

F_dis the feed rate of the secondary processing scheme d, W_d,mIs the yield of the secondary discharge m of the secondary processing scheme d, F_m,eThe processing scheme e downstream of the secondary processing scheme d consumes the amount of secondary discharge m,is the stock quantity of the secondary discharge m at the initial production,is the stock quantity, Delta Q, of the secondary discharge m at the end of production_dIs Q_dThe difference value from the base value is,is Q_dW per unit deviation from the base value_d,mCorrection value of, Δ T_dIs a processing parameter T under a secondary processing scheme d_dThe difference value from the base value is,for the machining parameter T_dW per unit deviation from the base value_d,mThe correction value of (1);

Q_d,mis the value of the property of the secondary discharge m,is the property value of the initial inventory of the secondary discharge m,is Q_dQ per unit deviation from the base value_d,mThe correction value of (a) is determined,for the machining parameter T_dQ per unit deviation from the base value_d,mCorrection value of (1), Q_mRepresents the properties of the secondary discharge m;

the processing scheme e comprises the following steps: a secondary processing scheme d, a blending scheme o and a delivery scheme;

said Q_l、Q_dmin、Q_dmax、W_d,m、 Q_d,m、Andthe production parameters processed by the oil refinery within a specified time are collected or received;

the control parameters obtained by the above calculation include F_l,d、Q_d、F_d、F_m,e、ΔQ_d、ΔT_dAnd Q_m。

2. The method of claim 1, wherein simulating the corresponding process of the crude unit is performed using the following equation:

$\frac{\underset{i}{\Σ}{F}_{i,b}\×Q_i}{\underset{i}{\Σ}{F}_{i,b}}=Q_b,$

Q_bmin≤Q_b≤Q_bmax，

$\underset{c}{\Σ}{F}_{u,c}=\underset{i}{\Σ}\underset{b}{\Σ}{F}_{i,b}\×W_{i,b,u}+({\mathrm{INV}}_u^{p-1}-{\mathrm{INV}}_u^p),$

$\frac{\underset{i}{\Σ}\underset{b}{\Σ}{F}_{i,b}\×W_{i,b,u}\×Q_{i,b,u}+{\mathrm{INV}}_u^{p-1}\×Q_u^{p-1}}{\left(\underset{i}{\Σ}\underset{b}{\Σ}{F}_{i,b}\×W_{i,b,u}+{\mathrm{INV}}_u^{p-1}\right)}=Q_u,$

$C_{ATM,TRmin}\≤\underset{b\∈TRB}{\Σ}\underset{i}{\Σ}{F}_{i,b}\≤C_{ATM,TRmax},$

$C_{VTM,TRmin}\≤\underset{b\∈TRB}{\Σ}\underset{i}{\Σ}{F}_{i,b}*V_{i,b}\≤C_{VTM,TRmax},$

wherein Q is_iIs the property value of crude oil i, F_i,bIs the consumption of crude oil i in the distillation scheme b, Q_bIs the property value, Q, of the mixed feed of all crude oils under distillation processing scheme b_bminIs the most permissible feed properties under distillation processing scheme bSmall value, Q_bmaxIs the maximum allowable feed properties under distillation processing scheme b;

W_i,b,uis the yield of crude oil i in the distillation output u of the distillation process variant b, F_u,cIs the consumption of the distillate u in a downstream processing scheme c of the distillation processing scheme b,is the inventory of the distillation discharge u at the initial production,is the inventory of the distillation discharge u at the end of production;

Q_i,b,uis the property value of crude i in the distillate output u of the distillation process variant b,is the initial stock property value, Q, of the distillate discharge u_uIs the property value of the distillation output u;

TR is a crude unit, ATM is an atmospheric tower in a crude unit, TRB is a set of processing schemes corresponding to a crude unit, C_ATM,TRminIs the minimum constraint value, C, of the atmospheric tower processing load in TR_ATM,TRmaxIs the maximum constraint value of the normal pressure tower processing load in TR;

VTM is the vacuum column in the crude unit TR, V_i,bIs the yield of atmospheric residue from crude oil i in distillation scheme b, C_VTM,TRminIs the minimum constraint value of the processing load of the vacuum tower in TR, C_VTM,TRmaxIs the maximum constraint value of the processing load of the vacuum tower in the TR;

the processing scheme c comprises the following steps: a secondary processing scheme d, a blending scheme o and a delivery scheme;

said Q_i、Q_bmin、Q_bmax、W_i,b,u、Q_i,b,u、C_ATM,TRmin、C_ATM,TRmax、C_VTM,TRmin、C_VTM,TRmaxAnd V_i,bThe production parameters processed by the oil refinery within a specified time are collected or received;

the control parameters obtained by the above calculation include F_i,b、Q_b、F_u,c、And Q_u。

3. The method of claim 2, wherein the control parameters are solved using a distributed recursive algorithm.

4. The method of claim 3, wherein the property value Q of the distillation output u when solving for the control parameter using a distributed recursive algorithm_uInitial value Q of_u0Solving by the following formula:

$Q_{u0}=\frac{\underset{i}{\Σ}\underset{b}{\Σ}{W}_{i,b,u}\×Q_{i,b,u}+Q_u^{p-1}}{(\underset{i}{\Σ}\underset{b}{\Σ}{W}_{i,b,u}+1)};$

Q_uis in the value range of

5. The method of claim 4, wherein the property Q of the secondary tap m when solving for the control parameter using a distributed recursive algorithm_mInitial value Q of_m0Solving by the following formula:

$Q_{m0}=\frac{\underset{d}{\Σ}{W}_{d,m}\×Q_{d,m}+Q_m^{p-1}}{\underset{d}{\Σ}{W}_{d,m}+1}$

Q_min the range of

6. The method according to claim 3, 4 or 5, characterized in that when solving the control parameters by using a distribution recursion algorithm, a going number dd is counted for each material subjected to property recursion calculation, the going number dd excludes a processing recipe in which a constraint amount of 0 is present, and an initial value of the error distribution coefficient is 1/dd for a processing recipe in which a constraint amount of 0 is not present and 0 for a processing recipe in which a constraint amount of 0 is present.

7. The method according to claim 3, 4 or 5, wherein generating the control parameter specifically comprises:

determining whether the fluctuation of the collected or received production parameter within a specified time is greater than a threshold,

if the time is greater than the preset time, dividing the appointed time into at least two time units according to the time sequence, and calculating the control parameters according to the production parameters in each time unit;

when the time units are divided, the fluctuation of all production parameters in the same time unit is not greater than a threshold value; and the fluctuation of at least one production parameter in two adjacent time units is larger than the threshold value.

8. A control system for petrochemical industry is characterized by comprising a production parameter acquisition device, a control parameter generation device, a control instruction generation device and a controller;

the acquisition device acquires or receives production parameters processed by the oil refinery within a specified time;

the control parameter generating device is used for solving the production parameters by linear or nonlinear optimization under the constraint conditions of simulating feeding, primary processing corresponding to the crude oil distilling device, secondary processing corresponding to the secondary processing device, finished oil blending and shipment, so as to generate control parameters;

the control instruction generating device receives the control parameters and forms control instructions according to the control parameters;

the controller is used for receiving and controlling the production flow processed by the oil refinery according to the control instruction;

the control parameter generating device is used for simulating secondary processing corresponding to the secondary processing device and adopting the following formula:

$\frac{\underset{l}{\Σ}{F}_{l,d}\×Q_l+{\mathrm{INV}}_d^{p-1}\×Q_d^{p-1}}{\underset{l}{\Σ}{F}_{l,d}+{\mathrm{INV}}_d^{p-1}}=Q_d,$

Q_dmin≤Q_d≤Q_dmax，

$\underset{e}{\Σ}{F}_{m,e}=\underset{d}{\Σ}{F}_d\×(W_{d,m}+\underset{Q_d}{\Σ}{\mathrm{\ΔQ}}_d\×{\mathrm{\ΔW}}_{Q_d,d,m}+\underset{T_d}{\Σ}{\mathrm{\ΔT}}_d\×{\mathrm{\ΔW}}_{T_d,d,m})+({\mathrm{INV}}_m^{p-1}-{\mathrm{INV}}_m^p),$

$\frac{\underset{d}{\Σ}{F}_d\×W_{d,m}\×(Q_{d,m}+\underset{Q_d}{\Σ}{\mathrm{\ΔQ}}_d\×{\mathrm{\ΔQ}}_{Q_d,d,m}+\underset{T_d}{\Σ}{\mathrm{\ΔT}}_d\×{\mathrm{\ΔQ}}_{T_d,d,m})+{\mathrm{INV}}_m^{p-1}\×Q_m^{p-1}}{\underset{d}{\Σ}{F}_d\×W_{d,m}+{\mathrm{INV}}_m^{p-1}}=Q_m,$

wherein Q is_lIs the value of the property of the feed l, F_l,dIs the flow rate of feed l under secondary processing scheme d,is the initial inventory of mixed feed for secondary processing scheme d,is a property value, Q, of the initial inventory_dIs the quality value of the mixed feed of the secondary processing scheme d, Q_dminIs that the feed properties of the secondary processing scheme d allowMinimum value reached, Q_dmaxIs the maximum value that the feed properties of the secondary processing scheme d allow to reach;

F_dis the feed rate of the secondary processing scheme d, W_d,mIs the yield of the secondary discharge m of the secondary processing scheme d, F_m,eThe processing scheme e downstream of the secondary processing scheme d consumes the amount of secondary discharge m,is the stock quantity of the secondary discharge m at the initial production,is the stock quantity, Delta Q, of the secondary discharge m at the end of production_dIs Q_dThe difference value from the base value is,is Q_dW per unit deviation from the base value_d,mCorrection value of, Δ T_dIs a processing parameter T under a secondary processing scheme d_dThe difference value from the base value is,for the machining parameter T_dW per unit deviation from the base value_d,mThe correction value of (1);

Q_d,mis the value of the property of the secondary discharge m,is the property value of the initial inventory of the secondary discharge m,is Q_dQ per unit deviation from the base value_d,mThe correction value of (a) is determined,for the machining parameter T_dQ per unit deviation from the base value_d,mCorrection value of (1), Q_mRepresents the properties of the secondary discharge m;

the processing scheme e comprises the following steps: a secondary processing scheme d, a blending scheme o and a delivery scheme;

said Q_l、Q_dmin、Q_dmax、W_d,m、 Q_d,m、Andthe production parameters processed by the oil refinery within a specified time are collected or received;

the control parameters obtained by the above calculation include F_l,d、Q_d、F_d、F_m,e、ΔQ_d、ΔT_dAnd Q_m。

9. The system of claim 8,

the control parameter generating device simulates the primary processing corresponding to the crude oil distillation device and adopts the following formula:

$\frac{\underset{i}{\Σ}{F}_{i,b}\×Q_i}{\underset{i}{\Σ}{F}_{i,b}}=Q_b$

Q_bmin≤Q_b≤Q_bmax，

$\underset{c}{\Σ}{F}_{u,c}=\underset{i}{\Σ}\underset{b}{\Σ}{F}_{i,b}\×W_{i,b,u}+({\mathrm{INV}}_u^{p-1}-{\mathrm{INV}}_u^p),$

$\frac{\underset{i}{\Σ}\underset{b}{\Σ}{F}_{i,b}\×W_{i,b,u}\×Q_{i,b,u}+{\mathrm{INV}}_u^{p-1}\×Q_u^{p-1}}{(\underset{i}{\Σ}\underset{b}{\Σ}{F}_{i,b}\×W_{i,b,u}+{\mathrm{INV}}_u^{p-1})}=Q_u,$

$C_{ATM,TRmin}\≤\underset{b\∈TRB}{\Σ}\underset{i}{\Σ}{F}_{i,b}\≤C_{ATM,TRmax},$

$C_{VTM,TR\min }\≤\underset{b\∈TRB}{\Σ}\underset{i}{\Σ}{F}_{i,b}*V_{i,b}\≤C_{VTM,TRmax},$

wherein Q is_iIs the property value of crude oil i, F_i,bIs the consumption of crude oil i in the distillation scheme b, Q_bIs the property value, Q, of the mixed feed of all crude oils under distillation processing scheme b_bminIs the minimum value, Q, allowed to be reached by the feed properties under distillation processing scheme b_bmaxIs the maximum allowable feed properties under distillation processing scheme b;

W_i,b,uis the yield of crude oil i in the distillation output u of the distillation process variant b, F_u,cIs the consumption of the distillate u in a downstream processing scheme c of the distillation processing scheme b,is the inventory of the distillation discharge u at the initial production,is the inventory of the distillation discharge u at the end of production;

Q_i,b,uis the property value of crude i in the distillate output u of the distillation process variant b,is the initial stock property value, Q, of the distillate discharge u_uIs the property value of the distillation output u;

TR is a crude unit, ATM is an atmospheric tower in a crude unit, TRB is a set of processing schemes corresponding to a crude unit, C_ATM,TRminIs the minimum constraint value, C, of the atmospheric tower processing load in TR_ATM,TRmaxIs the maximum constraint value of the normal pressure tower processing load in TR;

VTM is the vacuum column in the crude unit TR, V_i,bIs the yield of atmospheric residue from crude oil i in distillation scheme b, C_VTM,TRminIs the minimum constraint value of the processing load of the vacuum tower in TR, C_VTM,TRmaxIs the maximum constraint value of the processing load of the vacuum tower in the TR;

the processing scheme c comprises the following steps: a secondary processing scheme d, a blending scheme o and a delivery scheme;

said Q_i、Q_bmin、Q_bmax、W_i,b,u、Q_i,b,u、C_ATM,TRmin、C_ATM,TRmax、C_VTM,TRmin、C_VTM,TRmaxAnd V_i,bThe production parameters processed by the oil refinery within a specified time are collected or received;

the control parameters obtained by the above calculation include F_i,b、Q_b、F_u,c、And Q_u。

10. The system of claim 9, wherein the control parameter generating means solves the control parameters using a distributed recursive algorithm.

11. The system of claim 10, wherein the property value Q of the distillation output u is determined when the control parameter generating device solves the control parameter using a distributed recursive algorithm_uInitial value Q of_u0Solving by the following formula:

$Q_{u0}=\frac{\underset{i}{\Σ}\underset{b}{\Σ}{W}_{i,b,u}\×Q_{i,b,u}+Q_u^{p-1}}{(\underset{i}{\Σ}\underset{b}{\Σ}{W}_{i,b,u}+1)};$

Q_uis in the value range of

12. The system of claim 11, wherein the property Q of the secondary tap m is determined when the control parameter generating means solves the control parameter using a distributed recursive algorithm_mInitial value Q of_m0Solving by the following formula:

$Q_{m0}=\frac{\underset{d}{\Σ}{W}_{d,m}\×Q_{d,m}+Q_m^{p-1}}{\underset{d}{\Σ}{W}_{d,m}+1}$

Q_min the range of

13. The system according to claim 10, 11 or 12, wherein when the control parameter generation means solves the control parameters using a distribution recurrence algorithm, a going number dd excluding a processing recipe in which a constraint amount is 0 exists is counted for each material subjected to the property recurrence calculation, and an initial value of the error distribution coefficient is 1/dd for a processing recipe in which a constraint amount is 0 does not exist and is 0 for a processing recipe in which a constraint amount is 0.

14. The system according to claim 10, 11 or 12, wherein the control parameter generating means is specifically configured to:

determining whether the fluctuation of the collected or received production parameter within a specified time is greater than a threshold,

if the time is greater than the preset time, dividing the appointed time into at least two time units according to the time sequence, and calculating the control parameters according to the production parameters in each time unit;

when time units are divided, the fluctuation of all production parameters in the same time unit is not greater than a threshold value; and the fluctuation of at least one production parameter in two adjacent time units is larger than the threshold value.