Natural gas pipeline network scheduling method, device and system based on integer linear programming and storage medium

Abstract

The invention discloses a natural gas pipeline network scheduling method, device and system based on integer linear programming and a storage medium, which take the maximum yield of a natural gas pipeline network system as a target function and consider constraint conditions such as pipeline strength, operation parameters of a booster station, a dehydration station and a purification plant, and hydrogen sulfide content. And establishing a mathematical model for operation optimization of the natural gas pipeline network, and solving the optimal scheduling method by adopting a method based on integer linear programming. Therefore, the maximum productivity of a natural gas pipe network system is exerted, economic benefits are increased, and the utilization rate of a pipe network is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of natural gas surface engineering, and particularly relates to a natural gas pipeline network scheduling method, device, system and storage medium based on integer linear programming. Background Art

[0002] During the operation of a natural gas raw material pipeline network, in order to maximize production, as many gas wells as possible need to be opened. However, in practice, several gas wells are connected to dehydration stations and booster stations, and several dehydration stations are connected to purification plants, with constraints that prevent all gas wells in the pipeline network from being opened simultaneously. These constraints include the maximum processing capacity constraint of the dehydration station, the sulfur concentration constraint, the minimum processing capacity constraint and the maximum processing capacity constraint of the booster station. If the minimum processing capacity constraint cannot be met, the gas wells connected to that booster station need to be completely shut down, as well as the minimum processing capacity constraint and the maximum processing capacity constraint of the purification plant. In an actual production environment, scheduling by manually opening and closing wells has two problems: low efficiency and difficulty in achieving an optimal solution.

[0003] The patent "Multi-objective Optimization Scheduling Method for Natural Gas Pipeline Network Based on MQPSO" (Publication No.: CN110232481A) establishes a natural gas pipeline network model based on the distribution of nodes, pipeline segments and compressors in the natural gas pipeline network, treats operation data such as data flow as variables, sets initial values and generates an initial population, and then uses the MQPSO algorithm to solve the multi-objective optimization scheduling problem of the pipeline network to obtain the optimized values of the flow distribution of each node and the operating parameters of the compressor, and can quickly obtain an optimal solution set with uniform distribution, and uses the obtained decision parameters to guide production scheduling. However, this technology does not consider the capacity constraints of dehydration stations, booster stations and purification plants during the operation of the raw material pipeline network. In actual operation, natural gas produced from gas wells will pass through dehydration stations, booster stations and purification plants, and each station will have maximum and minimum processing constraints and H2S concentration constraints, which seriously affect the scheduling results in actual production. Therefore, it is very important to combine the pipeline network with the actual situation and consider the processing conditions of each station.

[0004] Patent "A Gas Volume Scheduling Method for Natural Gas Pipeline Networks" (Publication No.: CN109064033A) determines the gas storage capacity of the pipeline itself and creates a relationship curve between the pipeline transportation volume and the gas storage capacity; calculates the peak shaving demand of users based on the 24-hour gas usage plan of each user; arranges according to the pipeline network structure market. This technology can balance the gas volume scheduling relationship among the gas supply capacity of the gas source, the peak shaving gas demand of users, and the gas transportation capacity of the pipeline network. This technology balances the gas volume scheduling relationship among the gas supply capacity of the gas source, the peak shaving gas demand of users, and the gas transportation capacity of the pipeline network. However, this technology does not consider the constraint conditions in dehydration stations, booster stations, and purification plants either. As a result, during the scheduling process, while the pipeline network requirements are met, the constraint conditions of dehydration stations, booster stations, and purification plants are not satisfied, causing the machines to malfunction and resulting in abnormal pipeline network scheduling situations.

[0005] Patent "Method and Device for Determining the Operating Scheme of a Natural Gas Pipeline Network" (Publication No.: CN109754109A) determines a method and device for determining the operating scheme of a natural gas pipeline network. The method includes: obtaining the topological structure composed of N components in the pipeline network, as well as the static parameters and boundary constraint conditions of each of the N components; dividing the pipeline network into M pipeline chains according to this topological structure, and determining the constraint conditions between adjacent pipeline chains among the M pipeline chains based on the boundary constraint conditions of the N components; respectively determining multiple pipeline chain operating schemes for each pipeline chain based on the static parameters and boundary constraint conditions of at least one component included in each pipeline chain through the dynamic programming method; and then, based on the multiple pipeline chain operating schemes of each pipeline chain and the constraint conditions between adjacent pipeline chains, determining the optimal energy consumption of the pipeline network and the optimal operating scheme of each pipeline chain when the energy consumption of the pipeline network is optimal in a linearized processing manner through a mixed-integer linear programming model, so as to determine the operating scheme of the pipeline network when the energy consumption of the pipeline network is optimal. Taking the optimal energy consumption of the pipeline network as the objective function to be solved, regarding the pipeline network topological structure as N components, dividing it into M pipeline chains, and using the boundary elm conditions of the N components as the constraint conditions of the mixed-integer linear programming. Using this technology, the optimal energy consumption of the pipeline network may cause changes in the overall pipeline flow direction and gas well switch adjustment due to very small energy consumption optimization in pipeline network scheduling, and the production cannot reach the optimal level. Secondly, the constraint conditions of hydrogen sulfide in dehydration devices and purification devices are not considered in the scheduling process of this technology, the factor of pipeline flow direction change is not considered, and the daily well shut-off priority factor of the overall pipeline network scheduling is not combined, such as the gas well switch factors caused by high-sulfur gas wells, process level, or production factors.

[0006] In summary, the current scheduling of natural gas pipeline networks is a hot spot and a difficult point in operation. Although there are already relevant technical solutions, they all have problems such as imperfect functions, limited application scenarios, and insufficient consideration of actual conditions. Therefore, it is urgent to design a practical and effective new pipeline network scheduling scheme for these problems. Summary of the Invention

[0007] To maximize the production capacity of the natural gas pipeline network, increase economic benefits and improve the utilization rate of the pipeline network, a mathematical model for optimizing the operation of the natural gas pipeline network is established with the maximum output of the natural gas pipeline network as the objective function, while considering constraints such as pipeline strength, booster stations, dehydration stations, operating parameters of purification plants, and hydrogen sulfide content. An optimal scheduling method is solved using an integer linear programming-based approach.

[0008] The present invention provides a calculation scheme for the operation scheduling of a natural gas raw material pipeline network. By scheduling the production output and switching states of production gas wells, the processing capacity and hydrogen sulfide concentration indicators of booster devices, dehydration devices, and purification devices in the natural gas raw material pipeline network are satisfied, thereby achieving the optimization of the transportation pipeline and maximizing the production output of the raw material gas.

[0009] In view of the problems in the prior art, the present invention proposes a natural gas pipeline network scheduling method based on integer linear programming, which can complete gas well scheduling more quickly.

[0010] To achieve the above object of the present invention, the present invention provides a natural gas pipeline network scheduling method based on integer linear programming, including:

[0011] S1. Extract and organize relevant single-well scheduling variables according to the natural gas raw material pipeline network diagram;

[0012] S2. Model it as an integer linear programming problem according to the constraints of dehydration stations, booster stations, and purification plants;

[0013] S3. Solve the integer linear programming problem.

[0014] For further improvement, the step S1 includes: extracting the single-well variables to be scheduled in the natural gas raw material pipeline network diagram. According to the natural gas raw material pipeline network diagram, a gas field contains several gas wells, and optimization variables are set in sequence: x 1 , x 2 , …, x m , where m represents that there are m gas wells to be scheduled, and the value of each optimization variable is 0 or 1.

[0015] For further improvement, the step S2 includes: according to the constraints of the dehydration station, a dehydration station is connected to several gas wells, and these gas wells need to meet two constraints: the maximum processing capacity and the sulfur concentration; let the kth dehydration station start from the nth gas well and include t gas wells, then the maximum processing capacity constraint is:

[0016] 0 ≤ x n o n + x n+1 o n+1 + … + x n+t-1 o n+t-1 ≤ T k

[0017] Among them, T k is the maximum processing capacity of the dehydration station, and the sulfur concentration constraint is:

[0018]

[0019] p n is the sulfur concentration of the nth gas well, and P k is the maximum sulfur concentration limit of the kth dehydration station; actually, the above formula is not a linear constraint, so it needs to be converted to:

[0020] x n o n (p n -P k ) + x n+1 o n+1 (p n+1 -P n+1 ) + … + x n+t-1 o n+t-1 (p n+t-1 -P n+t-1 ) ≤ 0

[0021] For the booster station constraint, assume that the kth booster station starts from the lth gas well and includes z gas wells. The booster station requires that the processing capacities of the z gas wells must have a maximum and a minimum. If it is lower than the minimum, all gas wells need to be shut down, then the constraint is:

[0022]

[0023] Among them represents the minimum processing capacity of the kth booster station, represents the maximum processing capacity of the kth booster station; for the purification plant constraint, assume that the kth purification plant starts from the hth booster station and includes j booster stations. The purification plant requires that the processing capacities of the j purification plants must have a maximum and a minimum, then the constraint is:

[0024]

[0025] Among them represents the minimum processing capacity of the kth purification plant, represents the maximum processing capacity of the kth purification plant; Considering the constraints of the dehydration station, booster station, and purification plant at the same time, with the goal of maximizing the single-well production, so the objective problem and constraints are:

[0026] For further improvement, step S3 includes: solving a linear programming problem without integer constraints, that is:

[0027]

[0028] If the linear problem has no solution, and at this time the original integer linear programming problem also has no solution, then stop;

[0029] If the linear problem has an optimal solution and meets the integer conditions of the original integer programming problem, then the optimal solution of the linear problem is the optimal solution of the original problem, and stop;

[0030] If the linear problem has an optimal solution but does not meet the integer conditions of the original problem, denote its objective function value as f 0 , first start from x 1 , take x 1 = 0, and obtain the objective function value as f 1 , take x 1 = 1, and obtain the objective function value as f 2 , and so on. If x n is an integer, then skip it. Finally, traverse to x m , and obtain f v , v ≤ 2m; among f 0 , f 1 , …, f v , in the subset f b , f b+1 , …, f b+u , the corresponding solution sets x 1 , x 2 , …, x m all satisfy the constraint conditions of the original integer linear programming problem, then the solution corresponding to the maximum value of this subset is the optimal solution.

[0031] The present invention also relates to a natural gas pipeline network scheduling device based on integer linear programming. The device includes: a collection module for extracting and organizing relevant single - well scheduling variables according to the natural gas raw material pipeline network diagram; a modeling module for constructing an integer linear programming problem solving model according to the dehydration station constraints, booster station constraints, and purification plant constraints; and a planning module for solving the integer linear programming problem to obtain the optimal solution.

[0032] The present invention also relates to a natural gas pipeline network scheduling system based on integer linear programming. The system includes: a memory configured to store instructions; and a processor configured to call the instructions from the memory and be able to implement the above - mentioned natural gas pipeline network scheduling method based on integer linear programming when executing the instructions. Further, the system includes a plurality of scheduling terminals; the processor communicates with the plurality of scheduling terminals.

[0033] The present invention also includes a computer - readable storage medium storing computer - executable instructions, and when the computer - executable instructions are executed by a processor, the above - mentioned natural gas pipeline network scheduling method based on integer linear programming is implemented.

[0034] In summary, due to the adoption of the above technical solution, compared with the prior art, the present invention extracts and arranges relevant single-well scheduling variables according to the natural gas raw material pipeline network diagram, models the constraints as an integer linear programming problem, and converts the original objective problem and constraints into a linear programming problem to obtain an optimal gas well scheduling plan. The present invention can complete the scheduling of the natural gas raw material pipeline network in a short time through the method of natural gas raw material pipeline network scheduling based on integer linear programming, and use the switching conditions obtained by the integer linear programming method to improve the efficiency and accuracy of pipeline network scheduling, thereby ensuring the maximization of production. BRIEF DESCRIPTION OF THE DRAWINGS:

[0035] Figure 1 It is a flowchart of the model of the natural gas pipeline network scheduling method based on integer linear programming in an embodiment of the present invention.

[0036] Figure 2 It is the pipeline network diagram applied in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0038] In this application, the term "including", "comprising" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, article or device including a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "including a..." does not exclude the presence of additional identical elements in the process, method, article or device including the element.

[0039] In order to perform optimal gas scheduling, effectively improve the scheduling efficiency, and maximize the gas well production, this application provides a natural gas pipeline network scheduling method based on integer linear programming, which performs gas well scheduling in a timely manner, improves the scheduling efficiency, and reduces time and labor costs.

[0040] To ensure the timely completion of gas well scheduling, after obtaining the gas well data, it is necessary to solve the gas well scheduling result that meets the constraint conditions according to the integer linear programming model. The following example is given, and the specific steps include the following contents:

[0041] Refer to the attached Figure 1 , which shows the integer linear programming flowchart in the embodiment of the invention, including the following steps:

[0042] Step S101, start.

[0043] Step S102, input the natural gas pipeline network diagram as Figure 2 shown, which contains several structural elements such as gas wells (1 - 11), booster stations (1 - 4), dehydration stations (1 - 3), gas gathering stations, purification plants, one - way pipelines, two - way pipelines, etc. Figure 2

[0044] Step S103, extract and organize relevant single - well scheduling variables according to the natural gas pipeline network diagram. A gas field contains several gas wells. Optimized variables x 1 , x 2 , …, x m are set in sequence.

[0045] Among them, x m represents the on - off state of the m - th gas well, and the value of each optimized variable is 0 or 1.

[0046] Step S104, model it as an integer linear programming problem according to the constraints of dehydration stations, booster stations, and purification plants:

[0047] Specify the following constraint conditions according to the pipeline network operation variables:

[0048] 1) Gas well production and H 2 S concentration

[0049]

[0050] Gas wells 2, 7, 8, and 11 are high - sulfur gas wells (hydrogen sulfide concentration is greater than 30 g / m 3 ³), but the production of gas well 7 is 54435 m 3 ³. Therefore, in order to ensure the optimization of production, when the constraint conditions of downstream purification plants, dehydration stations, and booster stations are not met, the priority of well - shutting sequence is gas well 2, gas well 8, gas well 11, and gas well 7 should try to maintain the production state.

[0051] 2) Booster station throughput constraint

[0052]

[0053] This constraint condition means that within a certain range of throughput of the booster device, it can operate normally. If it is lower than the minimum throughput, the booster device cannot operate, and if it is higher than the maximum throughput, it exceeds the processing range of the booster device.

[0054] 3) Dehydration station throughput and H 2 S concentration constraint

[0055] ​

[0056] There are certain restrictions on the dehydration volume, hydrogen sulfide concentration, etc. according to the relevant constraints of the dehydration device.

[0057] 4) Constraints on the treatment capacity of the purification plant and the H 2 S concentration

[0058]

[0059] The purification plant is the final transportation node of the raw gas. There are the above restrictions on the maximum treatment capacity and the hydrogen sulfide treatment capacity of the desulfurization device in this process link.

[0060] 5) Constraints related to the raw gas pipeline

[0061]

[0062] Since relevant factors such as the length, diameter, material, and wall thickness of the raw gas pipeline have a certain impact on its gas transmission volume, there is a certain daily gas transmission volume limit for each pipe section. Here, only the transmission volume constraint of the main pipeline is considered. Similarly, the transmission volume constraints of all raw gas pipelines can also be considered.

[0063] Combining the above various constraint conditions and the above description, the following calculation formula can be obtained:

[0064]

[0065] Among them, T k is the maximum treatment capacity of the k-th dehydration station, o n is the output of the n-th gas well, represents the minimum treatment capacity of the k-th purification plant, represents the maximum treatment capacity of the k-th purification plant, p n represents the sulfur concentration of the n-th gas well, o n is the output of the n-th gas well, P k represents the maximum sulfur concentration limit value of the k-th dehydration station. k represents the k-th dehydration station, n represents the n-th gas well, and t represents the number of gas wells included in a dehydration station. represents the minimum treatment capacity of the k-th booster station, represents the maximum treatment capacity of the k-th booster station.

[0066] Step S105, solve the linear programming problem without integer constraints according to the original target problem and constraints:

[0067]

[0068] Step S106, determine whether the linear problem has a solution. If there is a solution, proceed to step S107; otherwise, jump to step S111.

[0069] Step S107: Determine whether the integer condition of the original integer programming problem is met. If the condition is met, jump to Step S110; if not, proceed to Step S108;

[0070] Step S108: Set x 1 , x 2 , …, x m to 0 and 1 in sequence.

[0071] Step S109: Denote the objective function value as f 0 . First, starting from x 1 , take x 1 = 0 to obtain the objective function value f 1 , take x 1 = 1 to obtain the objective function value f 2 , and so on. If x n is an integer, skip it. Finally, traverse to x m to obtain f v , where v ≤ 2m; among f 0 , f 1 , …, f v , if the solution sets x b , x b+1 , …, x b+u corresponding to the subset f 1 , x 2 , …, x m all satisfy the constraint conditions of the original integer linear programming problem, then the solution corresponding to the maximum value of this subset is the optimal solution.

[0072] Step S110: Output the optimal solution.

[0073] Step S111: End.

[0074] The present invention also relates to a natural gas pipeline network scheduling device based on integer linear programming. The device includes: a collection module for extracting and organizing relevant single - well scheduling variables according to the natural gas raw material pipeline network diagram; a modeling module for constructing an integer linear programming problem solving model according to the dehydration station constraints, booster station constraints, and purification plant constraints; and a planning module for solving the integer linear programming problem to obtain the optimal solution.

[0075] The present invention also relates to a natural gas pipeline network scheduling system based on integer linear programming. The system includes: a memory configured to store instructions; and a processor configured to call the instructions from the memory and capable of implementing the above - mentioned natural gas pipeline network scheduling method based on integer linear programming when executing the instructions. Further, the system includes multiple scheduling terminals; the processor communicates with the multiple scheduling terminals.

[0076] The present invention further includes a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described natural gas pipeline network scheduling method based on integer linear programming.

[0077] According to the natural gas raw material pipeline network diagram, the present invention extracts and arranges relevant single-well scheduling variables, models them as an integer linear programming problem according to the constraints, and obtains the optimal gas well scheduling scheme by converting the original objective problem and constraints into a linear programming problem, so as to maximize the production.

[0078] Those of ordinary skill in the art can understand that the above embodiments are specific embodiments for implementing the present invention, and in practical applications, various changes can be made in form and details without departing from the spirit and scope of the present invention.

Claims

1. A natural gas pipeline network scheduling method based on integer linear programming, characterized in that, it includes the following steps: S1. Extract and organize relevant single-well scheduling variables according to the natural gas raw material pipeline network diagram; S2. Model it as an integer linear programming problem according to the dehydration station constraints, booster station constraints, and purification plant constraints; S3. Solve the integer linear programming problem to obtain the optimal solution.

2. The method according to claim 1, characterized in that, The step S1 includes: extracting the single - well variables to be scheduled in the natural - gas raw - material gas pipeline network diagram. According to the natural - gas raw - material gas pipeline network diagram, a gas field contains several gas wells, and optimization variables are set in sequence: x 1 , x 2 , …, x m , where m represents that there are m gas wells to be scheduled, and the value of each optimization variable is 0 or 1.

3. The method according to claim 2, characterized in that, the step S2 includes: According to the dehydration station constraints, one dehydration station is connected to several gas wells, and these gas wells need to meet two constraints: the maximum processing capacity and the sulfur concentration; Let the k-th dehydration station start from the n-th gas well and include t gas wells, then the maximum processing capacity constraint is: 0 ≤ x n o n + x n+1 o n+1 + … + x n+t-1 o n+t-1 ≤ T k where T k is the maximum throughput of the dehydration station, and the sulfur concentration constraint is: p n is the sulfur concentration of the nth gas well, P k is the maximum sulfur concentration limit of the kth dehydration station; actually, the above formula is not a linear constraint, so it needs to be converted to: x n o n (p n -P k )+x n+1 o n+1 (p n+1 -P n+1 )+…+x n+t-1 o n+t-1 (p n+t-1 -P n+t-1 )≤0 4. The method according to claim 2, characterized in that, the step S2 includes: For the booster station constraints, let the k-th booster station start from the l-th gas well and include z gas wells. The booster station requires that the processing capacities of the z gas wells must have a maximum value and a minimum value. If it is lower than the minimum value, all gas wells need to be shut down, then the constraint is: y k = 0 or 1 wherein represents the minimum throughput of the k-th booster station, represents the maximum throughput of the k-th booster station.

5. The method according to claim 2, characterized in that, the step S2 includes: For the purification plant constraints, let the k-th purification plant start from the h-th booster station and include j booster stations. The purification plant requires that the processing capacities of the j purification plants must have a maximum value and a minimum value, then the constraint is: Among them represents the minimum processing capacity of the kth purification plant, represents the maximum processing capacity of the kth purification plant; at the same time, considering the constraints of dehydration stations, booster stations, and purification plants, with the goal of maximizing the single-well production, the target problem and constraints are as follows: max x 1 o 1 +x 2 o 2 +…+x m o m 6. The method according to claim 2, characterized in that, the step S3 includes: Solve the linear programming problem without integer constraints according to the original objective problem and constraints, max x 1 o 1 +x 2 o 2 +…+x m o m if the linear problem has no solution, and at this time the original integer linear programming problem also has no solution, then stop; if the linear problem has an optimal solution and meets the integer conditions of the original integer programming problem, then the optimal solution of the linear problem is the optimal solution of the original problem, and stop; If the linear problem has an optimal solution but does not meet the integer conditions of the original problem, denote its objective function value as f 0 , first start from x 1 , take x 1 = 0, and obtain the objective function value as f 1 , take x 1 = 1, and obtain the objective function value as f 2 , and so on. If x n is an integer, skip it. Finally, traverse to x m , and obtain f v , v ≤ 2m; among f 0 , f 1 , …, f v , the subset f b , f b+1 , …, f b+u 's corresponding solution sets x 1 , x 2 , …, x m all satisfy the constraint conditions of the original integer linear programming problem, then the solution corresponding to the maximum value of this subset is the optimal solution.

7. A natural gas pipeline network scheduling device based on integer linear programming, characterized in that, the device includes: An acquisition module, configured to extract and organize relevant single-well scheduling variables according to the natural gas raw material pipeline network diagram; A modeling module, configured to construct an integer linear programming problem solving model according to the dehydration station constraints, booster station constraints, and purification plant constraints; A planning module, configured to solve the integer linear programming problem to obtain the optimal solution.

8. A natural gas pipeline network scheduling system based on integer linear programming, characterized in that, the system includes: a memory configured to store instructions; and a processor configured to call the instructions from the memory and be able to implement the natural gas pipeline network scheduling method based on integer linear programming according to any one of claims 1 to 6 when executing the instructions.

9. The system according to claim 8, characterized in that, it includes: Multiple scheduling terminals; The processor according to claim 8 communicates with the multiple scheduling terminals.

10. A computer-readable storage medium storing computer-executable instructions, and when the computer-executable instructions are executed by a processor, the natural gas pipeline network scheduling method based on integer linear programming according to any one of claims 1 to 6 is implemented.

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