CN104611000B - Dispatch control method is criticized in a kind of production improving Large Scale Ethylene Cracking Furnace operating efficiency - Google Patents
Dispatch control method is criticized in a kind of production improving Large Scale Ethylene Cracking Furnace operating efficiency Download PDFInfo
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- 238000004519 manufacturing process Methods 0.000 title claims abstract description 498
- 238000005336 cracking Methods 0.000 title claims abstract description 440
- VGGSQFUCUMXWEO-UHFFFAOYSA-N Ethene Chemical compound C=C VGGSQFUCUMXWEO-UHFFFAOYSA-N 0.000 title claims abstract description 99
- 239000005977 Ethylene Substances 0.000 title claims abstract description 99
- 238000000034 method Methods 0.000 title claims abstract description 43
- 239000002994 raw material Substances 0.000 claims abstract description 159
- 239000000571 coke Substances 0.000 claims abstract description 53
- 238000004140 cleaning Methods 0.000 claims abstract description 36
- 238000009826 distribution Methods 0.000 claims abstract description 29
- 239000000463 material Substances 0.000 claims abstract description 23
- 238000005235 decoking Methods 0.000 claims description 58
- 238000004939 coking Methods 0.000 claims description 25
- 238000010923 batch production Methods 0.000 claims description 17
- 238000000197 pyrolysis Methods 0.000 claims description 17
- 230000000704 physical effect Effects 0.000 claims description 12
- 238000012163 sequencing technique Methods 0.000 claims description 10
- 238000005265 energy consumption Methods 0.000 claims description 9
- 238000010924 continuous production Methods 0.000 claims description 7
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- 238000004886 process control Methods 0.000 claims description 4
- 230000002040 relaxant effect Effects 0.000 claims description 4
- 238000005516 engineering process Methods 0.000 claims description 3
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- 238000010206 sensitivity analysis Methods 0.000 claims description 3
- 230000033764 rhythmic process Effects 0.000 abstract description 4
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- 239000000047 product Substances 0.000 description 38
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- 238000005457 optimization Methods 0.000 description 10
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- 239000007858 starting material Substances 0.000 description 6
- 238000004422 calculation algorithm Methods 0.000 description 5
- ATUOYWHBWRKTHZ-UHFFFAOYSA-N Propane Chemical compound CCC ATUOYWHBWRKTHZ-UHFFFAOYSA-N 0.000 description 4
- QQONPFPTGQHPMA-UHFFFAOYSA-N propylene Natural products CC=C QQONPFPTGQHPMA-UHFFFAOYSA-N 0.000 description 4
- 125000004805 propylene group Chemical group [H]C([H])([H])C([H])([*:1])C([H])([H])[*:2] 0.000 description 4
- 238000000354 decomposition reaction Methods 0.000 description 3
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- IJDNQMDRQITEOD-UHFFFAOYSA-N n-butane Chemical compound CCCC IJDNQMDRQITEOD-UHFFFAOYSA-N 0.000 description 2
- OFBQJSOFQDEBGM-UHFFFAOYSA-N n-pentane Natural products CCCCC OFBQJSOFQDEBGM-UHFFFAOYSA-N 0.000 description 2
- 239000001294 propane Substances 0.000 description 2
- VYZAMTAEIAYCRO-UHFFFAOYSA-N Chromium Chemical compound [Cr] VYZAMTAEIAYCRO-UHFFFAOYSA-N 0.000 description 1
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000009529 body temperature measurement Methods 0.000 description 1
- 239000004566 building material Substances 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000012668 chain scission Methods 0.000 description 1
- 238000001311 chemical methods and process Methods 0.000 description 1
- 229910052804 chromium Inorganic materials 0.000 description 1
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- -1 ethylene, propylene, butadiene Chemical class 0.000 description 1
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention provides a kind of production improving Large Scale Ethylene Cracking Furnace operating efficiency and criticize dispatch control method, comprising: set up cracking of ethylene work production database; Gather the physical parameter of the material of cracking of ethylene industry spot, real-time working condition data and market, stock and cost data; Set up and go up cracking of ethylene operation and always produce the production that net profit is target to maximize the production program phase and criticize scheduling controlling model; Solve and revise and produce batch scheduling controlling model; Revised production be criticized scheduling controlling scheme transmission to Secondary process Controlling System.The production batch length of main each pyrolyzer of Decision Control of the present invention, coke cleaning rhythm, the distribution of each raw material between pyrolyzer and material balance, realize improving pyrolyzer production operation efficiency, the coordination of multiple pyrolyzer coke cleaning operation and batch Optimizing manufacture, reach cracking operation net profit and maximize target.
Description
Technical Field
The invention belongs to the technical field of chemical process industry, and particularly relates to a production batch scheduling control method for improving the operation efficiency of a large ethylene cracking furnace.
Background
The ethylene industry is the core of the petrochemical industry; ethylene is also a basic raw material of three major synthetic materials and fine chemical products, is one of the chemical products with the largest yield in the world, and the product accounts for more than 70% of petrochemical products. Ethylene production has been used worldwide as one of the important indicators for the development of petrochemical in one country. In the period of 'eleven five', the ethylene industry in China develops rapidly, and the total ethylene yield in China reaches 1531 ten thousand tons/year by the end of 2011, so that the ethylene production system becomes the second major ethylene production country next to the United states in the world. Due to the rapid development of building materials, household electrical appliances and automobile industries in China, the monomer ethylene in China can basically realize self-sufficiency in the coming years, the gap of the consumption of equivalent ethylene is still large, and the ethylene industry in China still has certain development potential.
The whole process of ethylene production belongs to the continuous and multistage co-product production process, and has no intermediate storage tank. Various cracking feedstocks such as propane fractions, butane fractions, reformed liquefied gases (main components are propane and butane), reformed topped oils (C5 hydrocarbons), straight run naphtha and non-condensable gases (C2, C3), crude propylene. Various products including ethylene, propylene, butadiene are produced simultaneously. The main production stages of the whole process are divided into cracking, cooling, compressing and separating, and the process flow of the ethylene production is shown in figure 1. Wherein the cracking stage completes the main chain scission chemical reaction, determines the final yield of main products (ethylene and propylene) to a great extent and is completed by a large-scale parallel cracking furnace. The cracking reaction takes place in the cracking tube with coking. As the coke layer builds up, heat transfer and cracked gas flow will be blocked, resulting in a decrease in ethylene yield. In order to ensure the utilization rate of raw materials and the yield of ethylene, reduce fuel consumption and ensure the safe operation of the cracking furnace, the device is required to be periodically shut down and decoking. The continuous and safe production of the parallel cracking furnace needs to consider a plurality of factors such as the supply amount of raw materials, the production and decoking time of the cracking furnace, the yield of products (ethylene and propylene), energy consumption indexes, equipment safety and the like.
Domestic ethylene raw materials are mainly heavy raw materials such as naphtha and are short in raw material supply. The heavy raw material has the disadvantages of low yield, easy coking and the like. In order to ensure the ethylene yield and maximize the utilization rate of raw materials, a production mode with relatively constant product yield is usually adopted, namely, the temperature of a hearth is continuously increased, and the cracking temperature is ensured. The decoking time of the cracking furnace is determined by measuring the temperature outside the device on line at regular time. Because the cracking process is complex, the coking rates of different raw materials are different, the coke layer is unevenly distributed along the tube wall, the resources of coke cleaning equipment are limited, the coke cleaning rhythm of the production field is disordered due to the coke cleaning strategy formulated by experience and temperature measurement methods, the coke cleaning condition is often too early or too late, and the too early coke cleaning brings unnecessary coke cleaning cost, and the production capacity is reduced; the delayed decoking causes the blockage of the furnace tube, and the furnace tube needs to be replaced when the production is stopped, generally, the furnace tube is replaced by a group, the replacement cost is high, and time and labor are needed. How to control the production and decoking time of the cracking furnace, reasonably distributing decoking resources and optimally controlling fuel energy consumption indexes and furnace tube replacement amount so as to improve the cracking operation efficiency, save energy and reduce production cost is a key technical problem to be solved urgently in an ethylene cracking production field.
The foreign literature "JainV, Grossmann IE. cyclic scheduling of continuous outsparale-process with subsequent performance, AIChEjournal,1998,44(7): 1623-. Production patterns are usually aperiodic with insufficient raw materials; changes in the production operating environment will result in non-portability of the control methodology. Therefore, it is necessary to redesign a new control optimization strategy suitable for the ethylene production process conditions in China.
The Chinese patent 'complete set optimization control method of ethylene cracking furnace' (application number: 2012100555951) is to establish a single cracking furnace process reaction model from the viewpoint of cracking reaction process, and is used for controlling reaction depth and energy consumption, optimizing reaction process parameters and controlling outlet temperature. The patent only considers the dynamic cracking process modeling of a single device and a cracking period, the operation optimization control and implementation are realized, the control variables are the dilution ratio and the furnace tube outlet temperature parameter, and the aim is that the cracking operation energy consumption is minimum.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a production batch scheduling control method for improving the operation efficiency of a large ethylene cracking furnace.
The technical scheme of the invention is as follows:
a production batch scheduling control method for improving the operation efficiency of a large ethylene cracking furnace comprises the following steps:
step 1: establishing an ethylene cracking operation production database, wherein data in the database comprises physical property parameters, working condition data and decoking equipment parameters of materials in ethylene cracking production;
the physical parameters of the material comprise coking rate data and average yield of ethylene cracking products;
the working condition data comprises: the flow rate of the raw material in the cracking furnace, the product yield of each cracking furnace, the average coking rate of each cracking furnace, the upper limit and the lower limit of continuous cracking cycles of different cracking furnaces, the average decoking cycle and fuel energy consumption index of each cracking furnace, and the upper limit of accumulated thickness of a coke layer;
market, inventory and cost data include: safe stock of various raw materials, raw material supply rate, product market demand rate, unit raw material market price, product market price, cracking furnace production, equipment depreciation cost and decoking cost;
the decoking equipment parameters comprise average decoking time and decoking capacity;
step 2: collecting physical property parameters, real-time working condition data, market, inventory and cost data of materials in an ethylene cracking industrial field, and selecting the physical property parameters, the real-time working condition data, the market, the inventory and the cost data of the materials which are closest to each other from an ethylene cracking operation production database;
and step 3: establishing a production batch scheduling control model aiming at maximizing the net profit of the total production of the ethylene cracking operation in a production planning period;
defining a continuous production cycle of the cracking furnace as a production batch;
the decision variables of the model comprise discrete decision variables and continuous decision variables;
discrete decision variables include: distributing cracking raw materials in cracking batches of the cracking furnace, and sequentially cleaning coke of each cracking furnace in each production batch;
the continuous decision variables include: the continuous cracking time of the cracking raw materials in each production batch of the cracking furnace, the average inventory of the cracking raw materials at the end of each production batch in the production process, the production time of each production batch of the cracking furnace and the production starting time of each production batch of the cracking furnace;
the input of the model comprises physical property parameters, real-time working condition data and market, inventory and cost data of the closest materials selected from an ethylene cracking operation production database;
the total production net profit of the cracking operation on the production planning period is that the total income of the product is subtracted by the total cost of raw materials, production cost, inventory cost and decoking cost;
the constraint conditions of the production batch scheduling control model comprise cracking raw material inventory balance constraint, process operation constraint, safe production constraint and product requirement constraint;
the constraint conditions of the production batch scheduling control model are as follows:
a pyrolysis feed inventory balance constraint, i.e., the difference between pyrolysis feed inventory of adjacent production batches equals the supply minus the process;
process operating constraints include: (1) the types of the cracking raw materials in each production batch do not exceed the total number of the cracking raw materials, namely the production of one cracking raw material in one production batch of a certain cracking furnace is continuous; (2) all kinds of cracking raw materials are produced in a production planning period, and at least one production batch is produced; (3) the coke cleaning operation of the cracking furnaces is restricted, namely the parallel cracking furnaces sequentially carry out coke cleaning operation; (4) and (3) restricting the production time: if the cracking raw materials are distributed to a certain production batch of a certain cracking furnace for production, the continuous production time meets the upper limit and the lower limit of the continuous cracking cycle of different cracking furnaces; (5) the production time of a certain production batch of a cracking furnace is the sum of the production times of all cracking raw materials; (6) the production time of the production batch of the cracking furnace meets the upper limit constraint of batch production time; (7) time constraints between adjacent production batches of the same cracking furnace: in two adjacent production batches of the same cracking furnace, the sum of the end time of the previous production batch and the decoking time is less than the start time of the next production batch; (8) starting time constraints and ending time constraints of production batches of all cracking furnaces; (9) coke cleaning cannot be simultaneously carried out among different cracking furnaces;
safety production constraint, namely the thickness limit of the accumulated coke layer of each cracking furnace;
product demand constraints, i.e. the individual ethylene cracking product yield requirements.
And 4, step 4: solving the production batch scheduling control model to obtain the distribution of cracking raw materials in cracking batches of the cracking furnace, the decoking sequence of each cracking furnace in each production batch, the continuous cracking time of each production batch of the cracking raw materials in the cracking furnace, the average inventory of the cracking raw materials at the end of each production batch in the production process, the production time of each production batch of the cracking furnace and the production starting time of each production batch of the cracking furnace, wherein the decision variables form a production batch scheduling control scheme;
and 5: setting a raw material supply rate, a raw material average coking rate and a fluctuation range limited by the thickness of a cracking furnace coke layer by using a sensitivity analysis technology, and correcting a production batch scheduling control scheme;
step 6: and transmitting the modified production batch scheduling control scheme to a secondary process control system to complete scheduling control of the ethylene cracking production batch.
The step 4 is carried out according to the following specific steps:
step 4.1: according to the ethylene cracking coking rate data and the average yield of ethylene cracking products, a group of cracking raw material distribution and decoking sequencing schemes are given, wherein the schemes comprise the distribution of cracking raw materials in cracking batches of a cracking furnace and the decoking sequence of the cracking furnace of each production batch, namely a group of discrete decision variables are given;
step 4.2: solving a continuous cracking time optimal solution of the corresponding cracking raw materials in each production batch of the cracking furnace, an average stock quantity optimal solution of the cracking raw materials at the end of each production batch in the production process, a production time optimal solution of each production batch of the cracking furnace and a production time starting optimal solution of each production batch of the cracking furnace according to the discrete decision variables;
step 4.2.1: giving the initial production time of each batch of each cracking furnace, and calculating the average inventory of the cracking raw materials at the end of each production batch in the production process;
step 4.2.2: determining a searching feasible step length according to the given initial production time of each production batch of each cracking furnace and the safety stock, and searching to obtain the new production time of each production batch of each cracking furnace and the average stock of each production batch of cracking raw materials in the production process by taking the fastest net profit increasing direction as a searching direction;
step 4.2.3: if the net profit is less than the set threshold value in the fastest growing direction, stopping searching, and obtaining a production batch scheduling control scheme by using the average inventory at the end of each production batch production time and each production batch production time of each pyrolysis furnace and the average inventory at the end of each production batch production time and each production batch production time under the condition of a given pyrolysis raw material distribution and decoking sequencing scheme in the production process of the pyrolysis raw materials, wherein the total production net profit of the ethylene cracking operation in the production plan period corresponding to the scheme is the lower bound value of the total production net profit of the cracking operation in the production plan period; otherwise, go to step 4.2.2, continue searching;
step 4.3: constructing an approximate linear operation scheduling problem, namely a mixed integer programming problem, based on the production batch scheduling control scheme obtained in the step 4.2.3, and obtaining a plurality of production batch scheduling approximate control schemes by solving the problem;
the approximate linear operation scheduling problem is to decide the distribution of the cracking raw materials in the cracking batch of the cracking furnace and the coke cleaning sequence of each batch of the cracking furnace, the continuous cracking time of each batch of the cracking raw materials in the cracking furnace, the average stock of each production batch of the cracking raw materials in the production process, the production time of each batch of the cracking furnace and the production starting time of each batch of the cracking furnace; the objective function value of the approximate linear job scheduling problem is the upper bound of the objective function value of the production batch scheduling control scheme;
step 4.3.1: taking all decision variables as continuous variables, relaxing the approximate linear operation scheduling problem into a linear programming problem, solving the linear programming problem by using a simplex method to obtain an initial relaxed production batch scheduling control scheme, wherein the total production net profit of the ethylene cracking operation in the production plan period corresponding to the scheme is the upper bound of the total production net profit of the ethylene cracking operation in the production plan period;
step 4.3.2: aiming at the distribution of cracking raw materials on cracking batches of a cracking furnace and the variable values of the decoking sequence of each batch of the cracking furnace in the initial slack production batch scheduling control scheme, selecting one of decision variables which is not taken as an integer to carry out upper branching and lower branching of the variable values, namely respectively adding disjoint rounding constraint inequalities to obtain 2 new linear programming problems;
step 4.3.3: constructing a mixed integer rounding cut plane according to the current production batch scheduling control scheme, adding the mixed integer rounding cut plane into 2 linear programming problems in the step 4.3.2, respectively solving by utilizing a simplex method to obtain 2 new relaxed production batch scheduling control schemes, simultaneously updating an upper bound value of the total production net profit of the cracking operation in a production plan period, if a discrete decision variable of the solved relaxed production batch scheduling control scheme meets an integration condition, obtaining a production batch scheduling approximate control scheme, simultaneously obtaining a target value lower bound of an approximate linear operation scheduling problem, and terminating when all linear programming problems are solved; otherwise, returning to the step 4.3.2;
step 4.3.4: obtaining a plurality of production batch scheduling approximate control schemes including the optimal solution and the total production net profit of the cracking operation in the production plan period, and updating the upper bound value of the objective function of the production batch scheduling control schemes;
step 4.4: distributing cracking raw materials in a cracking furnace cracking production batch and cleaning coke sequence of each production batch in a plurality of production batch scheduling approximate control schemes, substituting the cracking raw materials into a production batch scheduling control model to obtain a plurality of sub-problems with given discrete decision variables, and solving the sub-problems in parallel by using the step 4.2 to obtain a plurality of feasible or infeasible production batch scheduling control schemes and simultaneously obtain a lower bound value of the total production net profit of the ethylene cracking operation in a production plan period, namely the lower bound of the total production net profit of the ethylene cracking operation in the best production plan period is not less than the total production net profit;
step 4.5: if the target value of the currently obtained feasible production batch scheduling control scheme is larger than the target function value of the control scheme obtained by previous iteration, judging whether an iteration termination condition is met, namely: if the net profit of the total production of the ethylene cracking operation in the production plan period of the approximate control scheme for the production batch scheduling is smaller than the net profit of the total production of the ethylene cracking operation in the production plan period of the current feasible production batch scheduling control scheme in the step 4.4, or the relative difference between the net profit and the total production of the ethylene cracking operation in the production plan period of the current feasible production batch scheduling control scheme is in an allowable range, the iteration is terminated, and the feasible production batch scheduling control scheme obtained in the step 4.4 is the best production batch scheduling control scheme; otherwise go to step 4.3.
Has the advantages that:
the invention provides a production batch scheduling control method for improving the operation efficiency of a large-scale ethylene cracking furnace aiming at the characteristics of production modes of ethylene plants. The implementation of the method scientifically arranges the cracking operation tasks and the decoking rhythm of each cracking production batch of each cracking furnace, maximizes the raw material yield, controls the energy consumption index of the cracking process, optimizes the decoking resource utilization, meets the requirements of final products, ensures the production safety, the service life of equipment and the stability of material flow of the whole production flow. Meanwhile, the online data correction achieves the purpose of closed-loop real-time optimization control of the production operation flow, the effective implementation of a control scheme is guaranteed, and the intellectualization of the production process is promoted.
The invention relates to an online optimization energy-saving control method for cracking operation when insufficient raw material supply is considered for a plurality of parallel cracking furnaces and a cracking production period, which mainly decides and controls the length of a production batch of each cracking furnace, the decoking rhythm, the distribution of each raw material among the cracking furnaces and the material balance, realizes the improvement of the production efficiency of the cracking furnaces, the coordination of the decoking operation of the plurality of cracking furnaces and the optimization of batch production, has energy consumption indexes in a reasonable range, and achieves the goal of maximizing the net profit of the cracking operation.
Drawings
FIG. 1 is a schematic flow diagram of an ethylene production process;
FIG. 2 is a flow chart of a production batch scheduling control method for improving the operating efficiency of a large ethylene cracking furnace according to an embodiment of the present invention;
FIG. 3 is a flow diagram of a process for solving a production batch scheduling control model in accordance with an embodiment of the present invention;
FIG. 4 is an optimal production lot scheduling control scheme in accordance with an embodiment of the present invention;
FIG. 5 is a graph showing the variation of the ethylene feedstock inventory according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings.
A production batch scheduling control method for improving the operation efficiency of a large ethylene cracking furnace is shown in figure 2 and comprises the following steps:
step 1: establishing an ethylene cracking operation production database, wherein data in the database comprises physical property parameters, working condition data and decoking equipment parameters of materials in ethylene cracking production;
the physical parameters of the material comprise coking rate data and average yield of ethylene cracking products;
the working condition data comprises: the flow rate of the raw material in the cracking furnace, the product yield of each cracking furnace, the average coking rate of each cracking furnace, the upper limit and the lower limit of continuous cracking cycles of different cracking furnaces, the average decoking cycle and fuel energy consumption index of each cracking furnace, and the upper limit of accumulated thickness of a coke layer;
market, inventory and cost data include: safe stock of various raw materials, raw material supply rate, product market demand rate, unit raw material market price, product market price, cracking furnace production, equipment depreciation cost and decoking cost;
the decoking equipment parameters comprise average decoking time and decoking capacity;
the average yield of each raw material in each cracking furnace is shown in table 1; the coking rate is shown in Table 2; the feed flow rates in the cracking furnace are shown in Table 3. The cost parameters of unit production and equipment depreciation are 2.1,1.9,1.9 and 1.7 yuan/ton; the upper limit of the cumulative thickness of the coke layer is 2.5,2.4,2.6 and 2.5; the average coke cleaning time is 1,2,4 and 2 days respectively; the decoking cost parameter was 4670.0,5100,4550,5200 yuan/day. Two main products: ethylene and propylene (prices 7500 and 7800 yuan/ton, respectively; average demand rate 240 and 75 tons/day). The safety stock of the raw materials is 500,500,600,600,600,400 tons respectively; the average supply rate is 105,125,115,125,120,100 tons/day respectively; the price is 3800,3500,3200,3000,2500,3200 yuan/ton. The cost parameters α ═ 1.7 and β ═ 3.1 were obtained by data fitting. The upper and lower limits of the continuous cracking cycle are 28 and 10 days, respectively, as determined by the furnace operating conditions.
TABLE 16 product yield statistics of feedstocks in 4 cracking furnaces
TABLE 26 coking Rate of feedstocks in 4 cracking furnaces
Starting materials 1 | Raw material 2 | Raw material 3 | Raw material 4 | Starting Material 5 | Starting Material 6 | |
Cracking furnace 1 | 0.080 | 0.090 | 0.110 | 0.070 | 0.060 | 0.081 |
Cracking furnace 2 | 0.070 | 0.100 | 0.120 | 0.060 | 0.070 | 0.120 |
Cracking furnace 3 | 0.075 | 0.095 | 0.115 | 0.065 | 0.065 | 0.075 |
Cracking furnace 4 | 0.077 | 0.11 | 0.100 | 0.067 | 0.071 | 0.100 |
TABLE 36 flow rates of feedstock in 4 cracking furnaces
Starting materials 1 | Raw material 2 | Raw material 3 | Raw material 4 | Starting Material 5 | Starting Material 6 | |
Cracking furnace 1 | 180 | 180 | 170 | 200 | 195 | 170 |
Cracking furnace 2 | 190 | 190 | 180 | 210 | 190 | 180 |
Cracking furnace 3 | 160 | 150 | 140 | 170 | 140 | 140 |
Cracking furnace 4 | 170 | 160 | 150 | 190 | 160 | 150 |
Step 2: collecting physical property parameters, real-time working condition data, market, inventory and cost data of materials in an ethylene cracking industrial field, and selecting the physical property parameters, the real-time working condition data, the market, the inventory and the cost data of the materials which are closest to each other from an ethylene cracking operation production database;
in the present embodiment, the initial stocks of raw materials are 1000,950,1200,1100,1050,800 tons, respectively; the production planning period is 120 days. In this embodiment, the current parameters need not be modified because the production operating environment is not changed significantly.
And step 3: establishing a production batch scheduling control model aiming at maximizing the net profit of the total production of the ethylene cracking operation in a production planning period;
wherein I is 1, …, I represents the cracking raw material type; j is 1, …, J, representing the cracking furnace number; k is 1, …, K, representing a production lot; l ═ 1, …, L indicates the final product category; plRepresents the price of the product; c. CijlRepresents the product yield; fijRepresenting the feed cracking flow rate; ps isijkRepresenting the continuous cracking time of each batch of the cracking raw material in the cracking furnace; cr (chromium) componentiThe unit cost of raw materials is expressed; cviThe unit stock cost of the raw materials is expressed; i isikRepresents the average inventory of the cracking raw material at the end of each production batch in the production process; cpjRepresenting the cost of the cracking furnace production and equipment depreciation; ccjThe cost of coke cleaning; rijIndicating the coking rate of the feedstock, α and β indicating non-linear exponential parameters of the production operation and the decoking costs.
The decision variables of the model comprise discrete decision variables and continuous decision variables;
discrete decision variables include: distribution x of cracking raw material in cracking batch of cracking furnaceijkCoke cleaning sequence z of each cracking furnace for each production batchjj'k;
The continuous decision variables include: continuous cracking time ps of cracking raw material in each production batch of cracking furnaceijkAverage inventory level I of cracking raw materials at the end of each production batch in the production processikProduction time p of each production batch of cracking furnacejkAnd the start time ts of each production batch of the cracking furnacejk;
The input of the model comprises physical property parameters, real-time working condition data and market, inventory and cost data of the closest materials selected from an ethylene cracking operation production database;
defining a continuous production time period of the cracking furnace as a production batch;
the total production net profit of the cracking operation on the production planning period is that the total income of the product is subtracted by the total cost of raw materials, production cost, inventory cost and decoking cost;
the constraint conditions of the production batch scheduling control model comprise cracking raw material inventory balance constraint, process operation constraint, safe production constraint and product requirement constraint;
the constraint conditions of the production batch scheduling control model are as follows:
a pyrolysis feed inventory balance constraint, i.e., the difference between pyrolysis feed inventory of adjacent production batches equals the supply minus the process;
wherein, IikInventory of pyrolysis feed stock, I, representing production Lot ki,k-1Representing production batch k-1Inventory of cracking feed, SfiRepresents the average supply rate of the raw material; p is a radical ofjkRepresenting the production time of each batch of the cracking furnace.
Equilibrium equation for the first production lot of cracking feedstock inventory equilibrium constraints:
in order to ensure the continuity of production, the inventory of cracking raw materials is required to be larger than the safety inventory in the production process.
Wherein, I0iIndicates initial inventory, IsiIndicating a safety stock.
Process operating constraints include: (1) the types of the cracking raw materials in each production batch do not exceed the total number of the cracking raw materials, namely the production of one cracking raw material in one production batch of a certain cracking furnace is continuous; (2) all kinds of cracking raw materials are produced in a production planning period, and at least one production batch is produced; (3) the coke cleaning operation of the cracking furnaces is restricted, namely the parallel cracking furnaces sequentially carry out coke cleaning operation; (4) and (3) restricting the production time: if the cracking raw materials are distributed to a certain production batch of a certain cracking furnace for production, the continuous production time meets the upper limit and the lower limit of the continuous cracking cycle of different cracking furnaces; (5) the production time of a certain production batch of a cracking furnace is the sum of the production times of all cracking raw materials; (6) the production time of the production batch of the cracking furnace meets the upper limit constraint of batch production time; (7) time constraints between adjacent production batches of the same cracking furnace: in two adjacent production batches of the same cracking furnace, the sum of the end time of the previous production batch and the decoking time is less than the start time of the next production batch; (8) starting time constraints and ending time constraints of production batches of all cracking furnaces; (9) coke cleaning cannot be simultaneously carried out among different cracking furnaces;
(1) the type of cracking material in each production batch does not exceed the total number of cracking materials, i.e. the production of a cracking material in a production batch of a certain cracking furnace is continuous:
wherein x isijkThe variable is 0 and 1, and represents the distribution of the cracking raw material in the cracking batch of the cracking furnace.
(2) All kinds of cracking raw materials are produced in a production planning period, and at least one production batch is produced; preventing the accumulation of certain cracking feedstocks, resulting in an excess inventory:
(3) and (3) coke cleaning operation restriction of the cracking furnace, namely coke cleaning operation is sequentially carried out on the parallel cracking furnaces:
wherein z isjj'kThe variable is 0 and 1, and represents the decoking sequence of each batch of the cracking furnace.
(4) And (3) restricting the production time: if the cracking raw material is distributed to a certain production batch of a certain cracking furnace for production, the continuous production time meets the upper limit and the lower limit of the continuous cracking cycle of different cracking furnaces:
wherein,andrespectively representing the upper limit and the lower limit of the time for which the cracking furnace continuously cracks one raw material.
(5) The production time of a certain production batch of a cracking furnace is the sum of the production times of all cracking raw materials:
wherein p isjkRepresenting the production time of each batch of the cracking furnace.
(6) The production time of the production batch of the cracking furnace meets the upper limit constraint of the batch production time:
(7) time constraints between adjacent production batches of the same cracking furnace: in two adjacent production batches of the same cracking furnace, the end time and the decoking time of the previous production batch are less than the start time of the next production batch:
wherein, tsjkRepresents the starting production time of each batch of the cracking furnace; tau isjThe decoking time of each cracking furnace is shown.
(8) Production batch start time constraints and end time constraints for all furnaces:
wherein the parameter H represents the entire production schedule length.
(9) Coke cleaning cannot be simultaneously carried out between different cracking furnaces:
in consideration of the fact that coke cleaning equipment is unique in general, coke cleaning cannot be carried out simultaneously among different cracking furnaces.
Safety production constraint, namely the limitation of the thickness of the accumulated coke layer of each cracking furnace:
wherein R isijRepresents the coking rate, TH, of the feedstock i in the cracking furnace jjIndicating the focal layer thickness limit.
Product demand constraints, namely the requirements for the yield of each ethylene cracking product:
wherein Q islRepresenting the average demand rate for the product.
xijk,zjj'kIs 0,1 integer variable, psijk,tsjk,pjk,IikIs a non-negative continuous variable.
The production batch scheduling control model is a complex mixed integer nonlinear programming (MINLP) model, which comprises discrete decision variables (distribution x of cracking raw material in cracking furnace cracking batch)ijkCoke cleaning sequence z of each cracking furnace for each production batchjj'k) Continuous decision variable (continuous cracking time ps of cracking raw material in each production batch of cracking furnaceijkAverage inventory level I of cracking raw materials at the end of each production batch in the production processikProduction time p of each production batch of cracking furnacejkAnd the start time ts of each production batch of the cracking furnacejk) And a non-linear objective function (to maximize the overall production net profit of the ethylene cracking operation on the production schedule). Solving by using existing solving techniquesThe solution has the conditions that the algorithm convergence is slow, or a better feasible scheme cannot be found, and the like, so that a new decomposition optimization algorithm is designed for solving the complex problems with actual problem scale, namely solving the production batch scheduling control model.
And 4, step 4: solving the production batch scheduling control model to obtain the distribution of cracking raw materials in cracking batches of the cracking furnace, the decoking sequence of each cracking furnace in each production batch, the continuous cracking time of each production batch of the cracking raw materials in the cracking furnace, the average inventory of the cracking raw materials at the end of each production batch in the production process, the production time of each production batch of the cracking furnace and the production starting time of each production batch of the cracking furnace, wherein the decision variables form a production batch scheduling control scheme;
the framework of the new decomposition optimization algorithm is to decompose the production batch scheduling control problem into two problems: firstly, when the cracking raw material distribution and decoking sequencing scheme is determined, the composition, length and inventory of a production batch are decided, and the problem is defined as a nonlinear programming subproblem of production batch scheduling control; and secondly, the approximate linear operation scheduling problem is obtained through a cracking raw material distribution and decoking sequencing scheme in the linear production batch scheduling control and is defined as a mixed integer linear programming approximate problem of the production batch scheduling control. By solving the subproblems, a feasible production batch scheduling control scheme and a lower bound of the optimal objective function value of the production batch scheduling control model can be obtained (when the subproblems are not feasible, the corresponding splitting raw material distribution and coke cleaning sequencing scheme is ignored); by solving the approximate problem, a plurality of new cracking raw material distribution and decoking sequencing schemes and the upper bound of the optimal objective function value of the production batch scheduling control model can be obtained, and a plurality of sub-problems are obtained by fixing the corresponding decision variables. And iteratively and alternately solving the two problems until a production batch scheduling control scheme which cannot be improved is obtained. The relaxation problem is defined as follows: for a sub-problem or an approximate problem, a new optimization problem is obtained by relaxing the constraint of a part of variables, such as a rounding requirement constraint, and the new optimization problem is called as a relaxation problem of production batch scheduling control. Solving the relaxation problem can obtain the upper bound value of the objective function corresponding to the production batch scheduling control.
The advantage of the new decomposition algorithm is that multiple feasible solutions are obtained through one iteration to speed up the convergence of the whole algorithm.
As shown in fig. 3, step 4 is performed according to the following specific steps:
step 4.1: according to the ethylene cracking coking rate data and the average yield of ethylene cracking products, a group of cracking raw material distribution and decoking sequencing schemes are given, wherein the schemes comprise the distribution of cracking raw materials in cracking batches of a cracking furnace and the decoking sequence of the cracking furnace of each production batch, namely a group of discrete decision variables are given;
step 4.2: solving a continuous cracking time optimal solution of the corresponding cracking raw materials in each production batch of the cracking furnace, an average stock quantity optimal solution of the cracking raw materials at the end of each production batch in the production process, a production time optimal solution of each production batch of the cracking furnace and a production time starting optimal solution of each production batch of the cracking furnace according to the discrete decision variables;
step 4.2.1: giving the initial production time of each batch of each cracking furnace, and calculating the average inventory of the cracking raw materials at the end of each production batch in the production process;
step 4.2.2: determining a searching feasible step length according to the given initial production time of each production batch of each cracking furnace and the safety stock, and searching to obtain the new production time of each production batch of each cracking furnace and the average stock of each production batch of cracking raw materials in the production process by taking the fastest net profit increasing direction as a searching direction;
step 4.2.3: if the net profit is less than the set threshold value in the fastest growing direction, stopping searching, and obtaining a production batch scheduling control scheme by using the average inventory at the end of each production batch production time and each production batch production time of each pyrolysis furnace and the average inventory at the end of each production batch production time and each production batch production time under the condition of a given pyrolysis raw material distribution and decoking sequencing scheme in the production process of the pyrolysis raw materials, wherein the total production net profit of the ethylene cracking operation in the production plan period corresponding to the scheme is the lower bound value of the total production net profit of the cracking operation in the production plan period; otherwise, go to step 4.2.2, continue searching;
step 4.3: constructing an approximate linear operation scheduling problem, namely a mixed integer programming problem, based on the production batch scheduling control scheme obtained in the step 4.2.3, and obtaining a plurality of production batch scheduling approximate control schemes by solving the problem;
the approximate linear operation scheduling problem is to decide the distribution of the cracking raw materials in the cracking batch of the cracking furnace and the coke cleaning sequence of each batch of the cracking furnace, the continuous cracking time of each batch of the cracking raw materials in the cracking furnace, the average stock of each production batch of the cracking raw materials in the production process, the production time of each batch of the cracking furnace and the production starting time of each batch of the cracking furnace; the objective function value of the approximate linear job scheduling problem is the upper bound of the objective function value of the production batch scheduling control scheme;
step 4.3.1: taking all decision variables as continuous variables, relaxing the approximate linear operation scheduling problem into a linear programming problem, solving the linear programming problem by using a simplex method to obtain an initial relaxed production batch scheduling control scheme, wherein the total production net profit of the ethylene cracking operation in the production plan period corresponding to the scheme is the upper bound of the total production net profit of the ethylene cracking operation in the production plan period;
step 4.3.2: aiming at the distribution of cracking raw materials on cracking batches of a cracking furnace and the variable values of the decoking sequence of each batch of the cracking furnace in the initial slack production batch scheduling control scheme, selecting one of decision variables which is not taken as an integer to carry out upper branching and lower branching of the variable values, namely respectively adding disjoint rounding constraint inequalities to obtain 2 new linear programming problems;
step 4.3.3: constructing a mixed integer rounding cut plane according to the current production batch scheduling control scheme, adding the mixed integer rounding cut plane into 2 linear programming problems in the step 4.3.2, respectively solving by utilizing a simplex method to obtain 2 new relaxed production batch scheduling control schemes, simultaneously updating an upper bound value of the total production net profit of the cracking operation in a production plan period, if a discrete decision variable of the solved relaxed production batch scheduling control scheme meets an integration condition, obtaining a production batch scheduling approximate control scheme, simultaneously obtaining a target value lower bound of an approximate linear operation scheduling problem, and stopping when all linear programming problems are solved; otherwise, returning to the step 4.3.2;
step 4.3.4: obtaining a plurality of production batch scheduling approximate control schemes including the optimal solution and the total production net profit of the cracking operation in the production plan period, and updating the upper bound value of the objective function of the production batch scheduling control schemes;
step 4.4: distributing cracking raw materials in a cracking furnace cracking production batch and cleaning coke sequence of each production batch in a plurality of production batch scheduling approximate control schemes, substituting the cracking raw materials into a production batch scheduling control model to obtain a plurality of sub-problems with given discrete decision variables, and solving the sub-problems in parallel by using the step 4.2 to obtain a plurality of feasible or infeasible production batch scheduling control schemes and simultaneously obtain a lower bound value of the total production net profit of the ethylene cracking operation in a production plan period, namely the lower bound of the total production net profit of the ethylene cracking operation in the best production plan period is not less than the total production net profit;
step 4.5: if the target value of the currently obtained feasible production batch scheduling control scheme is larger than the target function value of the control scheme obtained by previous iteration, judging whether an iteration termination condition is met, namely: if the net profit of the total production of the ethylene cracking operation in the production plan period of the approximate control scheme for the production batch scheduling is smaller than the net profit of the total production of the ethylene cracking operation in the production plan period of the current feasible production batch scheduling control scheme in the step 4.4, or the relative difference between the net profit and the total production of the ethylene cracking operation in the production plan period of the current feasible production batch scheduling control scheme is in an allowable range, the iteration is terminated, and the feasible production batch scheduling control scheme obtained in the step 4.4 is the best production batch scheduling control scheme; otherwise go to step 4.3.
And 5: setting a raw material supply rate, a raw material average coking rate and a fluctuation range limited by the thickness of a cracking furnace coke layer by using a sensitivity analysis technology, and correcting a production batch scheduling control scheme;
the optimum net profit margin of 6.0216 million, the detailed operation scheme is shown in FIG. 4, and the inventory variation curve of the pyrolysis feedstock is shown in FIG. 5. The optimal cracking operation scheme obtained by analysis can show that the idle waiting time of the 4 cracking furnaces on the whole production prospect is zero, the cracking raw material operation distribution is reasonable, the stable and uninterrupted production flow is ensured, the balance of the raw material and the material balance of the raw material is ensured, and the requirements of all final products are met. The decoking time is selected ideally, the coking condition of the cracking furnace and the distribution of decoking resources are considered, and the safe production of equipment is ensured.
In consideration of the fluctuation of some data in practical calculation examples, the average feed rate of the raw material, the coking rate and the upper limit of the coke layer thickness were selected as objects for examining the data change, and the data change range is shown in Table 4. It is assumed here that there is only one case of data fluctuation objects per time. The net profit value, the average stock of raw materials and the product total amount are calculated by substituting the control model again and are shown in the table 5.
TABLE 4 production data fluctuation statistics
Example data Range | Raw material supply rate fluctuation | Fluctuation of coking rate of raw material | Limiting fluctuation of coke layer thickness |
Average rate of supply of raw material | [100,145] | [100,125] | [100,145] | [100,145] |
Coking rate of raw material | [0.06,0.12] | [0.06,0.12] | [0.06,0.10] | [0.06,0.12] |
Coke layer thickness limitation | [2.4,2.6] | [2.4,2.6] | [2.4,2.6] | [2.3,2.6] |
TABLE 5 variance statistics for profit, average stock of raw materials, and total product volume due to production data fluctuations
Target net profit (Yuan) | Average stock of raw materials (ton) | Total amount of final product (ton) | |
Example data | 60,216,489 | 1788.5 | 39,078 |
Raw material supply rate fluctuation | 55,467,625 | 977.3 | 38,188 |
Fluctuation of coking rate of raw material | 60,217,744 | 1786.7 | 39,057 |
Limiting fluctuation of coke layer thickness | 60,227,371 | 1775.1 | 39,081 |
The scheme after data fluctuation is analyzed, and the net profit of the production flow and the total production amount of products can be directly influenced when the average supply rate range of the raw materials is changed; while the variation in cracked feedstock coking rate and coke layer cumulative thickness limits here has almost negligible effect on net production profit and product inventory, the detailed scheme has large variation in all three data fluctuations. The practicability and effectiveness of the method can be checked again through a numerical test of data fluctuation.
Step 6: and transmitting the modified production batch scheduling control scheme to a secondary process control system to complete scheduling control of the ethylene cracking production batch.
Considering that the current supplied raw materials are relatively stable, the control scheme can be directly transmitted to a secondary process control system, and effective and safe optimized control on the cracking process flow is realized.
Claims (4)
1. A production batch scheduling control method for improving the operation efficiency of a large ethylene cracking furnace is characterized by comprising the following steps: the method comprises the following steps:
step 1: establishing an ethylene cracking operation production database, wherein data in the database comprises physical property parameters, working condition data, market, inventory and cost data and coke cleaning equipment parameters of materials in ethylene cracking production;
the physical parameters of the material comprise coking rate data and average yield of ethylene cracking products;
the working condition data comprises: the flow rate of the raw material in the cracking furnace, the product yield of each cracking furnace, the average coking rate of each cracking furnace, the upper limit and the lower limit of continuous cracking cycles of different cracking furnaces, the average decoking cycle and fuel energy consumption index of each cracking furnace, and the upper limit of accumulated thickness of a coke layer;
market, inventory and cost data include: safe stock of various raw materials, raw material supply rate, product market demand rate, unit raw material market price, product market price, cracking furnace production, equipment depreciation cost and decoking cost;
the decoking equipment parameters comprise average decoking time and decoking capacity;
step 2: collecting physical property parameters, real-time working condition data, market, inventory and cost data of materials in an ethylene cracking industrial field, and selecting the physical property parameters, the real-time working condition data, the market, the inventory and the cost data of the materials which are closest to each other from an ethylene cracking operation production database;
and step 3: establishing a production batch scheduling control model aiming at maximizing the net profit of the total production of the ethylene cracking operation in a production planning period;
defining a continuous production time period of the cracking furnace as a production batch;
the decision variables of the model comprise discrete decision variables and continuous decision variables;
discrete decision variables include: distributing cracking raw materials in cracking batches of the cracking furnace, and sequentially cleaning coke of each cracking furnace in each production batch;
the continuous decision variables include: the continuous cracking time of the cracking raw materials in each production batch of the cracking furnace, the average inventory of the cracking raw materials at the end of each production batch in the production process, the production time of each production batch of the cracking furnace and the production starting time of each production batch of the cracking furnace;
the input of the model comprises physical property parameters, real-time working condition data and market, inventory and cost data of the closest materials selected from an ethylene cracking operation production database;
the constraint conditions of the production batch scheduling control model comprise cracking raw material inventory balance constraint, process operation constraint, safe production constraint and product requirement constraint;
and 4, step 4: solving the production batch scheduling control model to obtain the distribution of cracking raw materials in cracking batches of the cracking furnace, the decoking sequence of each cracking furnace in each production batch, the continuous cracking time of each production batch of the cracking raw materials in the cracking furnace, the average inventory of the cracking raw materials at the end of each production batch in the production process, the production time of each production batch of the cracking furnace and the production starting time of each production batch of the cracking furnace, wherein the decision variables form a production batch scheduling control scheme;
and 5: setting a raw material supply rate, a raw material average coking rate and a fluctuation range limited by the thickness of a cracking furnace coke layer by using a sensitivity analysis technology, and correcting a production batch scheduling control scheme;
step 6: and transmitting the modified production batch scheduling control scheme to a secondary process control system to complete scheduling control of the ethylene cracking production batch.
2. The production batch scheduling control method for improving the operation efficiency of the large-scale ethylene cracking furnace according to claim 1, which is characterized in that: the constraint conditions of the production batch scheduling control model are as follows:
a pyrolysis feed inventory balance constraint, i.e., the difference between pyrolysis feed inventory of adjacent production batches equals the supply minus the process;
process operating constraints include: (1) the types of the cracking raw materials in each production batch do not exceed the total number of the cracking raw materials, namely the production of one cracking raw material in one production batch of a certain cracking furnace is continuous; (2) all kinds of cracking raw materials are produced in a production planning period, and at least one production batch is produced; (3) the coke cleaning operation of the cracking furnaces is restricted, namely the parallel cracking furnaces sequentially carry out coke cleaning operation; (4) and (3) restricting the production time: if the cracking raw materials are distributed to a certain production batch of a certain cracking furnace for production, the continuous production time meets the upper limit and the lower limit of the continuous cracking cycle of different cracking furnaces; (5) the production time of a certain production batch of a cracking furnace is the sum of the production times of all cracking raw materials; (6) the production time of the production batch of the cracking furnace meets the upper limit constraint of batch production time; (7) time constraints between adjacent production batches of the same cracking furnace: in two adjacent production batches of the same cracking furnace, the sum of the end time of the previous production batch and the decoking time is less than the start time of the next production batch; (8) starting time constraints and ending time constraints of production batches of all cracking furnaces; (9) coke cleaning cannot be simultaneously carried out among different cracking furnaces;
safety production constraint, namely the thickness limit of the accumulated coke layer of each cracking furnace;
product demand constraints, i.e. the individual ethylene cracking product yield requirements.
3. The production batch scheduling control method for improving the operation efficiency of the large-scale ethylene cracking furnace according to claim 1, which is characterized in that: the step 4 is carried out according to the following specific steps:
step 4.1: according to the ethylene cracking coking rate data and the average yield of ethylene cracking products, a group of cracking raw material distribution and decoking sequencing schemes are given, wherein the schemes comprise the distribution of cracking raw materials in cracking batches of a cracking furnace and the decoking sequence of the cracking furnace of each production batch, namely a group of discrete decision variables are given;
step 4.2: solving a continuous cracking time optimal solution of the corresponding cracking raw materials in each production batch of the cracking furnace, an average stock quantity optimal solution of the cracking raw materials at the end of each production batch in the production process, a production time optimal solution of each production batch of the cracking furnace and a production time starting optimal solution of each production batch of the cracking furnace according to the discrete decision variables;
step 4.2.1: giving the initial production time of each batch of each cracking furnace, and calculating the average inventory of the cracking raw materials at the end of each production batch in the production process;
step 4.2.2: determining a searching feasible step length according to the given initial production time of each production batch of each cracking furnace and the safety stock, and searching to obtain the new production time of each production batch of each cracking furnace and the average stock of each production batch of cracking raw materials in the production process by taking the fastest net profit increasing direction as a searching direction;
step 4.2.3: if the net profit is less than the set threshold value in the fastest growing direction, stopping searching, and obtaining a production batch scheduling control scheme by using the average inventory at the end of each production batch production time and each production batch production time of each pyrolysis furnace and the average inventory at the end of each production batch production time and each production batch production time under the condition of a given pyrolysis raw material distribution and decoking sequencing scheme in the production process of the pyrolysis raw materials, wherein the total production net profit of the ethylene cracking operation in the production plan period corresponding to the scheme is the lower bound value of the total production net profit of the cracking operation in the production plan period; otherwise, go to step 4.2.2, continue searching;
step 4.3: constructing an approximate linear operation scheduling problem, namely a mixed integer programming problem, based on the production batch scheduling control scheme obtained in the step 4.2.3, and obtaining a plurality of production batch scheduling approximate control schemes by solving the problem;
the approximate linear operation scheduling problem is to decide the distribution of the cracking raw materials in the cracking furnace and the coke cleaning sequence of each batch of the cracking furnace, the continuous cracking time of each batch of the cracking raw materials in the cracking furnace, the average inventory of the cracking raw materials at the end of each production batch in the production process, the production time of each batch of the cracking furnace and the production starting time of each batch of the cracking furnace; the objective function value of the approximate linear job scheduling problem is the upper bound of the objective function value of the production batch scheduling control scheme;
step 4.3.1: taking all decision variables as continuous variables, relaxing the approximate linear operation scheduling problem into a linear programming problem, solving the linear programming problem by using a simplex method to obtain an initial production batch scheduling control scheme, wherein the total production net profit of the ethylene cracking operation in the production plan period corresponding to the scheme is the upper bound value of the total production net profit of the ethylene cracking operation in the production plan period;
step 4.3.2: aiming at the distribution of cracking raw materials on cracking batches of a cracking furnace and the variable values of the decoking sequence of each batch of the cracking furnace in the initial slack production batch scheduling control scheme, selecting one of decision variables which is not taken as an integer to carry out upper branching and lower branching of the variable values, namely respectively adding disjoint rounding constraint inequalities to obtain 2 new linear programming problems;
step 4.3.3: constructing a mixed integer rounding cut plane according to the current production batch scheduling control scheme, adding the mixed integer rounding cut plane into 2 linear programming problems in the step 4.3.2, respectively solving by utilizing a simplex method to obtain 2 new relaxed production batch scheduling control schemes, simultaneously updating an upper bound value of the total production net profit of the cracking operation in a production plan period, if a discrete decision variable of the solved relaxed production batch scheduling control scheme meets an integration condition, obtaining a production batch scheduling approximate control scheme, simultaneously obtaining a target value lower bound of an approximate linear operation scheduling problem, and stopping when all linear programming problems are solved; otherwise, returning to the step 4.3.2;
step 4.3.4: obtaining a plurality of production batch scheduling approximate control schemes including the optimal solution and the total production net profit of the cracking operation in the production plan period, and updating the upper bound value of the objective function of the production batch scheduling control schemes;
step 4.4: distributing cracking raw materials in a cracking furnace cracking production batch and cleaning coke sequence of each production batch in a plurality of production batch scheduling approximate control schemes, substituting the cracking raw materials into a production batch scheduling control model to obtain a plurality of sub-problems with given discrete decision variables, and solving the sub-problems in parallel by using the step 4.2 to obtain a plurality of feasible or infeasible production batch scheduling control schemes and simultaneously obtain a lower bound value of the total production net profit of the ethylene cracking operation in a production plan period, namely the lower bound of the total production net profit of the ethylene cracking operation in the best production plan period is not less than the total production net profit;
step 4.5: if the target value of the currently obtained feasible production batch scheduling control scheme is larger than the target function value of the control scheme obtained by previous iteration, judging whether an iteration termination condition is met, namely: if the net profit of the total production of the ethylene cracking operation in the production plan period of the approximate control scheme for the production batch scheduling is smaller than the net profit of the total production of the ethylene cracking operation in the production plan period of the current feasible production batch scheduling control scheme in the step 4.4, or the relative difference between the net profit and the total production of the ethylene cracking operation in the production plan period of the current feasible production batch scheduling control scheme is in an allowable range, the iteration is terminated, and the feasible production batch scheduling control scheme obtained in the step 4.4 is the best production batch scheduling control scheme; otherwise go to step 4.3.
4. The production batch scheduling control method for improving the operation efficiency of the large-scale ethylene cracking furnace according to claim 1, which is characterized in that: and the total production net profit of the cracking operation on the production planning period is the total income of the product minus the total cost of raw materials, production cost, inventory cost and decoking cost.
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