阅读说明：本技术 考虑平均结焦量与原料负荷的乙烯裂解炉炉群调度方法 (Ethylene cracking furnace group scheduling method considering average coking amount and raw material load ) 是由 朱群雄 叶玮 贺彦林 徐圆 张洋 于 2020-11-25 设计创作，主要内容包括：本发明公开了一种考虑平均结焦量与原料负荷的乙烯裂解炉炉群调度方法,包括：获取不同裂解原料投放进不同炉型裂解炉中的平均结焦量与乙烯产品量,获得调度模型的目标函数,建立约束条件,构造MINLP模型,使用DICOPT求解器对MINLP模型进行优化求解。本发明综合考虑乙烯生产中产率随时间衰减的特性,兼顾裂解原料负荷的变化,为每个裂解炉规划调度时间范围内的批次、批处理时间、清焦顺序以及批次原料进料量的最佳安排。此外,本发明可以在清焦阶段减少污染物的排放,在牺牲少量利润的代价下,获取更加可观的环境效益,为乙烯工厂的节能减排、优化排产提供了理论依据。(The invention discloses an ethylene cracking furnace group scheduling method considering average coking amount and raw material load, which comprises the following steps: the method comprises the steps of obtaining average coking amount and ethylene product amount of different cracking raw materials fed into different furnace type cracking furnaces, obtaining a target function of a scheduling model, establishing constraint conditions, constructing an MINLP model, and performing optimization solution on the MINLP model by using a DICOPT solver. The invention comprehensively considers the characteristic of yield attenuation along with time in ethylene production, considers the change of cracking raw material load, and plans and dispatches the optimal arrangement of batch, batch processing time, decoking sequence and batch raw material feeding quantity in the time range for each cracking furnace. In addition, the method can reduce the emission of pollutants in the decoking stage, obtain more considerable environmental benefits at the cost of sacrificing a small amount of profits, and provide a theoretical basis for energy conservation, emission reduction and optimized production scheduling of the ethylene plant.)

1. An ethylene cracking furnace group scheduling method considering average coking amount and raw material load is characterized by comprising the following steps:

obtaining the average coking amount and the ethylene product amount of different cracking raw materials put into different furnace type cracking furnaces;

obtaining an objective function of a scheduling model according to the average coking amount and the ethylene product amount, wherein the objective function is used for minimizing the average coking amount of unit ethylene production, and the expression of the objective function is as follows:

wherein, F_i,j,kAs the rate of feed of the raw materials,denotes ethylene when feedstock i is cracked in cracking furnace j during batch operationYield model of the yield dynamic over time, a_i,j、b_i,jAnd c_i,jIs a fitting parameter of the yield model;

establishing constraint conditions, wherein the constraint conditions comprise a raw material balance constraint, a time constraint, an integer constraint, an asynchronous decoking constraint, a variable upper and lower limit constraint and an additional constraint;

considering the load change of the cracking raw material, obtaining ethylene yield models under different load levels through simulation, wherein the load of the cracking raw material is adjusted and optimized within a feeding range only when the operation condition changes and is kept unchanged in a single scheduling period;

forming an MINLP model for the furnace group scheduling according to the objective function, the constraint condition and the ethylene yield model;

and (3) carrying out optimization solution on the MINLP model by using a DICOPT solver, and respectively processing the MILP problem and the NLP problem by using a sub solver CPLEX and a sub solver CONOPT.

2. The ethylene cracking furnace cluster scheduling method considering average coke amount and raw material load as claimed in claim 1, wherein the ethylene yield model is a function relationship of time and load, and the expression of the ethylene yield model is as follows:

a_i,j(D_i,j)＝pma_i,j×F_i,j+pna_i,j (2)

b_i,j(D_i,j)＝pmb_i,j×F_i,j+pnb_i,j (3)

c_ij(D_ij)＝pmc_ij×F_ij+pnc_ij (4)

3. the ethylene cracking furnace cluster scheduling method considering the average coking amount and the raw material load as claimed in claim 1, wherein the expression of the raw material balance constraint is as follows:

G_i≤(Dup_i-Dlo_i)H (9)

Flo_i，jgy_i，j，k≤F_i，j，k≤Fup_i，jgy_i，j，k (10)

the total feeding amount of all cracking furnaces is in the range of raw material supply, the consumption of the feeding material i in the time range H is scheduled, Gi represents the excess of the feeding material i exceeding the lower limit, the feeding amount of the cracking raw material is adjusted in the preset range, y_i,j,kIs a binary logical variable, the feed amount F of the cracking feedstock if the feed i is not allocated to the kth batch production run of the jth furnace_i,j,kIs 0.

4. The ethylene cracking furnace bank scheduling method considering the average coking amount and the raw material load as claimed in claim 3, wherein the expression of the time constraint is as follows:

setting the continuous processing time of the feed material i within a preset minimum value and a preset maximum value, wherein if the feed material i is not distributed to the kth batch production operation of the jth furnace, the processing time is 0;

Ts_j,kstarting time of cracking batch for all cracking furnaces, Te_j,kFor the end time of the cracking batch of all cracking furnaces, the cracking start time point of the current batch is equal to the cracking end time point of the previous batch plus the furnace shutdown decoking time between two batches, the end time point of the current batch is equal to the starting time point of the current batch plus the batch processing time, the start time of the first batch of all cracking furnaces is 0, if the batch processing start time point is greater than the dispatching time range H, the start time Ts is equal to the dispatching time range H_j,kEqual to 0;

introducing a binary variable y_i,j,kA binary variable y representing whether said feed i is assigned to a kth batch production run of a jth furnace if said cracking feedstock has been assigned_i,j,k1, if the cracking feedstock has not been distributed, a binary variable y_i,j,k0, if the kth lot has no production run, the start and end times of the kth lot are the same.

5. The ethylene cracking furnace bank scheduling method considering the average coking amount and the raw material load as claimed in claim 4, wherein the expression of the integer constraint is as follows:

the first batch of all cracking furnaces is always used for cracking feeding materials, each batch can only crack one feeding material at most, all types of raw materials are processed at least once in the whole scheduling time range, the previous batch and the next batch are sequentially used in the whole scheduling process, and if a certain batch of the cracking furnaces is not used, the subsequent batch of the cracking furnaces cannot be used.

6. The ethylene cracking furnace cluster scheduling method considering average coke amount and raw material load as claimed in claim 5, wherein the expression of the asynchronous decoking constraint is as follows:

the time intervals for decoking different cracking furnaces are forbidden to have overlapping portions, and the non-synchronous decoking constraint is described using a time difference between two starting points and a time difference between two end points, the product of the time difference between the two starting points and the time difference between the two end points being less than or equal to 0.

7. The method for scheduling the furnace group of the ethylene cracking furnace considering the average coking amount and the raw material load as claimed in claim 6, wherein the expression of the constraint of the upper and lower limits of the variable is as follows:

Tp_i,j,k≥0,G_i≥0,y_i,j,k∈{0,1}，H＞0 (22)

the start time Ts_j,kIs 0, the end time Te_j,kThe scheduling time range H is greater than 0, the binary logic variable y_i,j,kIs 0 or 1, and the other variables are not less than 0.

8. The ethylene cracking furnace cluster scheduling method considering the average coke amount and the raw material load as claimed in claim 7, wherein the additional constraint is expressed as follows:

the additional constraint is the daily average profit for each scheduling scheme.

Technical Field

The invention relates to the technical field of ethylene production, in particular to a method for scheduling an ethylene cracking furnace group by considering average coking amount and raw material load.

Background

Ethylene is the most important organic compound in the petrochemical/chemical industry, and its yield greatly exceeds that of other petrochemicals. A wide range of ethylene derivatives play an extremely important role in the daily life of people, such as ethylene oxide, vinyl acetate, ethylene dichloride, high/low density polyethylene, and the like. Steam thermal cracking is the first operating section of an ethylene plant and largely determines the yield of downstream products and the energy consumption of the overall plant. Today, ethylene plants are encouraged to diversify feedstock combinations as profit margins get more and more tightened and feedstock markets fluctuate, and to increase their operational flexibility in the face of raw material uncertainty.

With the current increasingly strict background of energy conservation and emission reduction and low carbon environmental protection in the industrial production of ethylene in China, the method needs to pay particular attention to how to effectively reduce the pollutant emission of an ethylene plant, and the reduction of the coking amount of a cracking furnace can radically meet the environmental protection requirement. Therefore, improvements and optimizations for the furnace cluster system of the cracking furnace have been proposed. Since most of the previous research focuses on the operation optimization of a single cracking furnace, in the actual industry, a plurality of cracking furnaces are used for producing ethylene products in parallel. Therefore, raw material scheduling is required for the production of the cracking furnace group, so as to achieve the corresponding optimization target.

Disclosure of Invention

In order to solve the limitations and defects of the prior art, the invention provides an ethylene cracking furnace group scheduling method considering the average coking amount and the raw material load, which comprises the following steps:

obtaining the average coking amount and the ethylene product amount of different cracking raw materials put into different furnace type cracking furnaces;

obtaining an objective function of a scheduling model according to the average coking amount and the ethylene product amount, wherein the objective function is used for minimizing the average coking amount of unit ethylene production, and the expression of the objective function is as follows:

wherein, F_i,j,kAs the rate of feed of the raw materials,a yield model showing the dynamic variation of the ethylene yield over time during the cracking of feed i in cracking furnace j during batch operation, a_i,j、b_i,jAnd c_i,jIs a fitting parameter of the yield model;

establishing constraint conditions, wherein the constraint conditions comprise a raw material balance constraint, a time constraint, an integer constraint, an asynchronous decoking constraint, a variable upper and lower limit constraint and an additional constraint;

considering the load change of the cracking raw material, obtaining ethylene yield models under different load levels through simulation, wherein the load of the cracking raw material is adjusted and optimized within a feeding range only when the operation condition changes and is kept unchanged in a single scheduling period;

forming an MINLP model for the furnace group scheduling according to the objective function, the constraint condition and the ethylene yield model;

and (3) carrying out optimization solution on the MINLP model by using a DICOPT solver, and respectively processing the MILP problem and the NLP problem by using a sub solver CPLEX and a sub solver CONOPT.

Optionally, the ethylene yield model is a function of time and load, and the expression of the ethylene yield model is as follows:

a_i,j(D_i,j)＝pma_i,j×F_i,j+pna_i,j (2)

b_i,j(D_i,j)＝pmb_i,j×F_i,j+pnb_i,j (3)

c_ij(D_ij)＝pmc_ij×F_ij+pnc_ij (4)

optionally, the expression of the material balance constraint is as follows:

G_i≤(Dup_i-Dlo_i)H (9)

Flo_i，jgy_i，j，k≤F_i，j，k≤Fup_i，jgy_i，j，k (10)

the total feeding amount of all cracking furnaces is in the range of raw material supply, the consumption of the feeding material i in the time range H is scheduled, Gi represents the excess of the feeding material i exceeding the lower limit, the feeding amount of the cracking raw material is adjusted in the preset range, y_i,j,kIs a binary logical variable, the feed amount F of the cracking feedstock if the feed i is not allocated to the kth batch production run of the jth furnace_i,j,kIs 0.

Optionally, the expression of the time constraint is as follows:

setting the continuous processing time of the feed material i within a preset minimum value and a preset maximum value, wherein if the feed material i is not distributed to the kth batch production operation of the jth furnace, the processing time is 0;

Ts_j,kstarting time of cracking batch for all cracking furnaces, Te_j,kFor the end time of the cracking batch of all cracking furnaces, the cracking start time point of the current batch is equal to the cracking end time point of the previous batch plus the furnace shutdown decoking time between two batches, the end time point of the current batch is equal to the starting time point of the current batch plus the batch processing time, the start time of the first batch of all cracking furnaces is 0, if the batch processing start time point is greater than the dispatching time range H, the start time Ts is equal to the dispatching time range H_j,kEqual to 0;

introducing a binary variable y_i,j,kA binary variable y representing whether said feed i is assigned to a kth batch production run of a jth furnace if said cracking feedstock has been assigned_i,j,k1, if the cracking feedstock has not been distributed, a binary variable y_i,j,k0, if the kth lot has no production run, the start and end times of the kth lot are the same.

Optionally, the expression of the integer constraint is as follows:

the first batch of all cracking furnaces is always used for cracking feeding materials, each batch can only crack one feeding material at most, all types of raw materials are processed at least once in the whole scheduling time range, the previous batch and the next batch are sequentially used in the whole scheduling process, and if a certain batch of the cracking furnaces is not used, the subsequent batch of the cracking furnaces cannot be used.

Optionally, the expression of the asynchronous decoking constraint is as follows:

the time intervals for decoking different cracking furnaces are forbidden to have overlapping portions, and the non-synchronous decoking constraint is described using a time difference between two starting points and a time difference between two end points, the product of the time difference between the two starting points and the time difference between the two end points being less than or equal to 0.

Optionally, the expression of the variable upper and lower limit constraints is as follows:

Tp_i,j,k≥0,G_i≥0,y_i,j,k∈{0,1}，H＞0 (22)

the start time Ts_j,kIs 0, the end time Te_j,kThe scheduling time range H is greater than 0, the binary logic variable y_i,j,kIs 0 or 1, and the other variables are not less than 0.

Optionally, the expression of the additional constraint is as follows:

the additional constraint is the daily average profit for each scheduling scheme.

The invention has the following beneficial effects:

the invention considers the actual production process of the cracking furnace, abandons the assumption that all batches of a certain raw material entering the cracking furnace in the original model have equal time, introduces binary variables to indicate whether the raw material enters the kth batch of the cracking furnace for cracking, and better accords with the actual production condition. Meanwhile, the feeding load of each raw material to each cracking furnace and the combination of the raw materials put into each cracking furnace can be better optimized by considering the load change condition of the cracking furnaces. The invention also fully considers the production characteristics of non-synchronous decoking in the ethylene production process, thereby ensuring the normal and steady operation of scheduling. The invention can effectively simulate the ethylene chemical industry furnace group scheduling production and effectively improve the environmental benefit, thereby effectively coping with the current increasingly serious environmental pollution and playing a reference and guidance role in the actual production.

Drawings

Fig. 1 is a schematic scheduling diagram of a furnace group scheduling model of a cracking furnace according to an embodiment of the present invention.

FIG. 2a is a schematic diagram of ethylene cracking yield over time according to one embodiment of the present invention.

FIG. 2b is another schematic diagram of ethylene cracking yield over time according to the first embodiment of the present invention.

FIG. 3a is a graph showing the variation of coke amount with time according to an embodiment of the present invention.

FIG. 3b is another graph of coke amount as a function of run time for an embodiment of the present invention.

FIG. 3c is a graph showing another trend of coke amount as a function of operating time according to an embodiment of the present invention.

Fig. 4a is a schematic diagram of a basic model scheduling scheme according to an embodiment of the present invention.

Fig. 4b is another schematic diagram of the basic model scheduling scheme according to the first embodiment of the present invention.

Fig. 4c is a schematic diagram of a basic model scheduling scheme according to an embodiment of the present invention.

Fig. 5a is a schematic diagram of an improved model scheduling scheme according to an embodiment of the present invention.

Fig. 5b is another schematic diagram of an improved model scheduling scheme according to an embodiment of the present invention.

Fig. 5c is a schematic diagram of an improved model scheduling scheme according to an embodiment of the present invention.

Detailed Description

In order to make the technical scheme of the present invention better understood by those skilled in the art, the method for scheduling the furnace group of the ethylene cracking furnace considering the average coking amount and the raw material load provided by the present invention is described in detail below with reference to the accompanying drawings.

Example one

The purpose of this embodiment is: the average coking amount of unit ethylene products is taken as an objective function, the change of raw material load is considered, an improved ethylene cracking furnace group scheduling model is constructed, a reliable and efficient furnace group scheduling solution is provided after solving, and technical support and technical reference are provided for ethylene enterprises to improve production efficiency and reduce environmental pollution. In this embodiment, the average coking amount of unit ethylene product is minimized as an objective function, corresponding constraint conditions are established through the actual ethylene production process, the change of raw material load is considered, the furnace group scheduling problem is modeled, and the established model is optimized and solved.

The objective function provided by the present embodiment requires the introduction of the concept of average coke amount. In this example, the average coking amount avecook is defined as the mass of coke produced on the inner wall of the furnace tube every 1 ton of ethylene produced by the cracking furnace. The variable output is used herein to represent the total production of ethylene product in the cracker furnace system over the scheduled time period and the variable cofemass represents the total coke mass produced in the cracker furnace system over the scheduled time period. The fitting function relation of the coke amount of the furnace tube of the cracking furnace changing along with the time is obtained by simulation of COILSIM1D, wherein P₁、P₂、P₃、P₄Are all fitting parameters. In this embodiment, the ethylene yield of all batches of all cracking furnaces in the furnace group system of the cracking furnace is summed with the coking amount of the furnace tubes, so as to calculate the total average coking amount of the furnace group system, and further obtain the average coking amount.

The constraint conditions provided by the embodiment comprise a raw material balance constraint, a time constraint, an integer constraint, an asynchronous decoking constraint, a variable upper and lower limit constraint and an additional constraint. In the embodiment, the change of the raw material load is considered, and the feeding amount (raw material load) of the cracking raw material can be adjusted within a certain range according to the actual working condition. And obtaining ethylene yield models under different load levels through simulation, wherein the raw material load is adjusted and optimized within the feeding range only under the condition of changing the operation conditions and is kept unchanged in a scheduling period.

In this embodiment, a scheduling optimization model is established, and a basic MINLP mathematical model for furnace group scheduling of the cracking furnace is established by combining the objective function and the constraint variable. The model solution provided by this embodiment uses GAMS to solve, DICOPT is used as a solver for solving the MINLP problem, and sub-solvers CPLEX and CONOPT are used to process the MILP and NLP problems therein, respectively. The embodiment provides an ethylene cracking furnace group scheduling modeling method considering average coking amount and load change, which is used for optimizing a furnace group scheduling process, and can improve the accuracy of a model and obtain a better optimization result by improving the objective function and the constraint condition of the model. The embodiment can realize the acquisition of the scheduling scheme under the optimal target value, thereby playing the role of optimization and providing a guidance scheme.

The embodiment can be effectively applied to a parallel multi-feed and multi-product ethylene cracking furnace group scheduling system. Fig. 1 is a schematic scheduling diagram of a furnace group scheduling model of a cracking furnace according to an embodiment of the present invention. As shown in fig. 1. By optimal scheduling of the system, the average amount of coking per unit of product can be effectively reduced at the expense of a small amount of profit. This example presents a new MINLP model to consider the scheduling strategy for obtaining the maximum environmental benefit of the furnace system under the limit of exponential decay of product yield over time. FIG. 2a is a schematic diagram of ethylene cracking yield over time according to one embodiment of the present invention. FIG. 2b is another schematic diagram of ethylene cracking yield over time according to the first embodiment of the present invention. The ethylene yield versus time is shown in fig. 2a and 2 b.

The present embodiment gives the following information: upper and lower limits of the raw material load; product yield models of different cracking furnaces for cracking different raw materials; coke cleaning time of each cracking furnace when cracking different feeding materials; upper and lower limits of batch processing time; coke cleaning and disposal costs; a product price index; given schedulingA time range; a fitting function of the coking rate of the inner wall of each cracking furnace tube changing along with time. The information that can be determined by the best schedule includes: the number of batches allocated for each furnace; the type of feed processed in each batch operation; starting time point Ts of each batch of cracking operation_j,kAnd end time point Te_j,k(ii) a The specific decoking sequence of the whole furnace system.

In this embodiment, an objective function is established, where the objective function of the scheduling model is to minimize the average coking amount per unit ethylene product, and the expression is as follows:

this example allows for the consideration of the feedstock load variations, the ethylene yield as a function of time and load as follows:

a_i,j(D_i,j)＝pma_i,j×F_i,j+pna_i,j (2)

b_i,j(D_i,j)＝pmb_i,j×F_i,j+pnb_i,j (3)

c_ij(D_ij)＝pmc_ij×F_ij+pnc_ij (4)

in this embodiment, constraint conditions are established, where the constraint conditions include a raw material balance constraint, a time constraint, an integer constraint, an asynchronous decoking constraint, a variable upper and lower limit constraint, and an additional constraint.

For feedstock balance constraints, the total feed rate for all cracking furnaces should be within the feedstock supply. The consumption of feed i within time range H is scheduled, where Gi represents the excess of feed i beyond the lower limit. In this embodiment, the feed rate (feedstock load) of the cracking feedstock can be adjusted within a certain range according to the actual conditions, y_i,j,kIs a binary logical variable if feed i is not assigned to furnace jIn the kth batch production run, the feed rate of cracking raw material F_i,j,kTo 0, the expression is as follows:

G_i≤(Dup_i-Dlo_i)H (9)

Flo_i，jgy_i，j，k≤F_i，j，k≤Fup_i，jgy_i，j，k (10)

for time constraints, the continuous processing time of feed i is within the minimum and maximum values practically allowed from a management and operational point of view. If feed i is not assigned to the kth batch production run of the jth furnace, then the processing time for that batch is 0. Define the start time Ts of the cracking batches of all the cracking furnaces_j,kAnd end time Te_j,k. The cracking starting time point of the current batch is equal to the cracking ending time point of the previous batch plus the furnace-out decoking time between two batches. The end time point of the current batch is equal to its start time point plus the batch processing time.

It is assumed that all the cracking units are clean at the beginning of the time frame and that the start time of the first batch of all the furnaces is 0. If the starting time point of the batch process is greater than the scheduling time range H, the batch process is not actually used, i.e. Tp_j,kEqual to 0. Introducing a binary variable y_i,j,kTo indicate whether feed i is assigned to the kth batch production run of the jth furnace. Binary variable y if the material is dispensed_i,j,kIs 1, otherwise, is 0. It is noted that the start and end times of a batch are arranged such that if the kth batch is not actually utilized, its start and end time points will be the same, as expressed below:

for integer constraints, in actual production, the first batch of all furnaces must always be used to crack the feed. For all furnaces, at most one feed can be cracked per batch. All types of raw materials must be processed at least once throughout the scheduling time. In the whole dispatching process, the former batch must be used before the latter batch is used. If a batch of a furnace is not used, subsequent batches of the furnace are not used, and the expression is as follows:

for the non-synchronized decoking constraint, there should be no overlap in the decoking intervals of the different furnaces, as shown in FIG. 1. The constraint can be described using the time difference between two start points and the time difference between two end points, the product between these two types of time differences should be less than or equal to 0. Note that this constraint cannot be applied to the last cleaning of each furnace, i.e. simultaneous decoking in the last production run of all the plants is feasible, the expression:

for variable upper and lower bound constraints, Ts_j,kAnd Te_j,kThe upper and lower limits of (A) are 0 and H, respectively; the scheduling time domain H should be greater than 0; binary variable y_i,j,kCan only take 0 or 1; other variables need not be less than 0, and the expression is as follows:

Tp_i,j,k≥0,G_i≥0,y_i,j,k∈{0,1}，H＞0 (22)

for the additional constraint, the daily average profit under each scheduling scheme is taken as the additional constraint of the scheduling model, and the expression is as follows:

through the steps, a new MINLP optimization model with formula (1) as an objective function and formulas (2) - (23) as constraints can be established. In order to highlight the effect of the present embodiment, the old basic model, which does not consider the change of the raw material load, is compared with the new model.

The case provided by the embodiment is derived from a certain ethylene factory in China, 3 types of cracking furnaces are researched, wherein the cracking furnaces are GK-VI type, GK-V type and GK-III type and are respectively represented by 1, 2 and 3; three cracking feedstocks, light Naphtha (NAP), Light Naphtha (LNAP) and Liquefied Petroleum Gas (LPG), were processed, each indicated at A, B, C. The scheduling time domain H is 200 days. The relevant parameters required in the scheduling model are shown in table 1:

TABLE 1 cracking furnace group System parameters values

FIG. 3a is a graph showing the variation of coke amount with time according to an embodiment of the present invention. FIG. 3b is another graph of coke amount as a function of run time for an embodiment of the present invention. FIG. 3c is a graph showing another trend of coke amount as a function of operating time according to an embodiment of the present invention. Wherein NAP is naphtha, LNAP is light naphtha, LPG is liquefied petroleum gas, GK-VI represents a GK-VI type cracking furnace, GK-V represents a GK-V type cracking furnace, and CBL-III represents a CBL-III type cracking furnace. Fig. 4a is a schematic diagram of a basic model scheduling scheme according to an embodiment of the present invention. Fig. 4b is another schematic diagram of the basic model scheduling scheme according to the first embodiment of the present invention. Fig. 4c is a schematic diagram of a basic model scheduling scheme according to an embodiment of the present invention. The raw material batch processing sequence is as follows: cracking furnace No. 1, A-B-C; the No. 2 cracking furnace is A-B-C; a cracking furnace No. 3 is A-B-C. Fig. 5a is a schematic diagram of an improved model scheduling scheme according to an embodiment of the present invention. Fig. 5b is another schematic diagram of an improved model scheduling scheme according to an embodiment of the present invention. Fig. 5c is a schematic diagram of an improved model scheduling scheme according to an embodiment of the present invention. The raw material batch processing sequence is as follows: the No. 1 cracking furnace is C-A-C-B; the No. 2 cracking furnace is B-C-A; the No. 3 cracking furnace is A-B-A-C.

As shown in fig. 4a, 4b, 4c, 5a, 5b, 5c, the basic model and the improved model are solved by GAMS, and the solver is DICOPT. The MINLP problem is decomposed into an MILP sub-problem and an NLP sub-problem, and the solution is completed through a CPLEX solver and a CONOPT solver respectively. The total cycle time was 200 days. The average coking amount of the basic model is 0.173kg/t ethylene, and the average daily profit is 735070 yuan/day. The average coke formation for the new improved model was 0.164kg/t ethylene and the average daily profit was 764890 yuan/day. The average daily profit and the average coke amount can be improved.

Comparison of the two models in the optimal scheduling optimization schemes of fig. 3a, fig. 3b, fig. 3c and fig. 4a, fig. 4b, fig. 4c can find that the modified model raw material processing sequence is greatly different from that before the modification. The actual production raw materials are not added in batches according to the specified sequence, and the processing time of different batches of the same raw material is not completely the same. Therefore, the arrangement of the raw material batches is more reasonable, and the average profit is improved to a certain extent compared with the original model.

The calculation results in table 2 show that the method for optimizing the scheduling and modeling of the furnace group of the cracking furnace considering the average coking amount can obtain higher coking amount reduction on the premise of sacrificing a small amount of profits, thereby achieving better environmental benefits. The invention fully considers the production characteristics of non-synchronous decoking in the ethylene production process, thereby ensuring the normal and steady operation of scheduling. The invention can effectively simulate the ethylene chemical industry furnace group scheduling production and effectively improve the environmental benefit, thereby effectively coping with the current increasingly serious environmental pollution and playing a reference and guidance role in the actual production.

TABLE 2 calculation results of old and New models

The embodiment provides an ethylene cracking furnace group scheduling method considering average coking amount and raw material load, which comprises the following steps: the method comprises the steps of obtaining average coking amount and ethylene product amount of different cracking raw materials fed into different furnace type cracking furnaces, obtaining a target function of a scheduling model, establishing constraint conditions, constructing an MINLP model, and performing optimization solution on the MINLP model by using a DICOPT solver. In this example, the optimal arrangement of the batch, the batch processing time, the decoking sequence and the batch raw material feeding amount within the scheduling time range for each cracking furnace is planned, taking into consideration the characteristic of the yield attenuation along with time in the ethylene production and considering the change of the cracking raw material load. In addition, the embodiment can reduce the emission of pollutants in the decoking stage, obtain more considerable environmental benefits at the cost of sacrificing a small amount of profits, and provide a theoretical basis for energy conservation, emission reduction and optimized production scheduling of the ethylene plant.

It will be understood that the above embodiments are merely exemplary embodiments taken to illustrate the principles of the present invention, which is not limited thereto. It will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the spirit and substance of the invention, and these modifications and improvements are also considered to be within the scope of the invention.