Gas supply distribution method and device of natural gas pipeline network system and storage medium

Abstract

The invention provides a natural gas pipeline network system gas supply distribution method and device and a storage medium, and relates to the technical field of natural gas pipeline network safety conveying. According to the method, the SPS physical simulation model of the natural gas pipeline network is established based on the feasibility, the system gas shortage in the failure time is determined by simulating the model, the gas supply reliability index of the pipeline network system is reasonably distributed to each unit in the system, and the augmentation target function is reconstructed through the unit reliability optimization target and the penalty function, so that the reliability of the system is improved. The gas supply reliability distribution value of the natural gas pipeline network system is obtained through the new augmentation objective function, a scientific basis is provided for reliability enhancement, and therefore the supply safety of the natural gas pipeline network is guaranteed.

Description

Technical Field

[0001] The present invention mainly relates to the technical field of safe transportation of natural gas pipeline networks, and in particular to a gas supply distribution method, device and storage medium of a natural gas pipeline network system. Background Art

[0002] At present, the natural gas pipeline network is the only means of large-scale natural gas transportation and the link between resources and markets. With the increasing consumption of natural gas, the scale of my country's natural gas pipeline network has continued to expand, forming a natural gas pipeline network pattern that runs across the east and west, across the north and south, and connects the inside and outside. However, the redundancy of my country's natural gas pipeline network is low. Once a failure occurs, it will seriously threaten the supply security and put forward higher requirements for the reliable operation of the natural gas pipeline network. Carrying out the reliability management of natural gas pipeline network is crucial to ensure the safety of natural gas supply. At present, certain theoretical and technical achievements have been made in the calculation methods of gas supply reliability of complex natural gas pipeline network units and systems, but the existing natural gas pipeline network management method system does not take into account multiple factors. The optimization theory and method research after the evaluation of the gas supply reliability of the natural gas pipeline network system is not mature enough, resulting in unsatisfactory gas supply distribution effect. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a gas supply distribution method, device and storage medium for a natural gas pipeline network system in view of the deficiencies in the prior art.

[0004] On the one hand, the technical solution of the present invention to solve the above technical problem is as follows: a gas supply distribution method for a natural gas pipeline network system, comprising the following steps:

[0005] S1. Import multiple preset influencing factors, calculate the score of each influencing factor, and calculate the feasibility of each influencing factor based on the score of each influencing factor;

[0006] S2. Establish a natural gas pipeline network SPS physical simulation model based on the feasibility of various influencing factors, the topological information of the natural gas pipeline network system, and the information of multiple pipe section units and multiple natural gas stations in the natural gas pipeline network topology;

[0007] S3. According to the gas source information and distribution point information of the natural gas pipeline network system, the SPS physical simulation model of the natural gas pipeline network is simulated;

[0008] S4. Perform SPS non-steady-state simulation on the SPS physical simulation model of the simulated natural gas pipeline network according to the statistical data of unit failure time, and determine the gas shortage of the system within the failure time of each pipe section unit;

[0009] S5. Score the amount of gas shortage in the system during each failure time to obtain a total severity score, and determine the consequence importance coefficient of each pipe section unit based on the total severity score;

[0010] S6. Determine the unreliability of each pipe section unit according to the consequence importance coefficient of each pipe section unit, and obtain the reliability according to the unreliability;

[0011] S7, establishing a unit cost function model according to the reliability, and determining a gas supply reliability optimization allocation objective function and constraint conditions according to the unit cost function model, constructing an augmented objective function according to the gas supply reliability optimization allocation objective function and constraint conditions, constructing a penalty function, and reconstructing the augmented objective function through the penalty function to obtain a new augmented objective function;

[0012] S8. Solve the new augmented objective function through the particle swarm algorithm to obtain the gas supply reliability distribution value of the natural gas pipeline network system.

[0013] The beneficial effects of the present invention are as follows: a physical simulation model of the natural gas pipeline network SPS is established based on feasibility, the amount of gas shortage in the system within the failure time is determined by simulating the model, the gas supply reliability index of the pipeline network system is reasonably distributed to each unit in the system, and an augmented objective function is established through the unit reliability optimization target. The gas supply reliability distribution value of the natural gas pipeline network system is obtained through the augmented objective function, which provides a scientific basis for reliability enhancement, thereby ensuring the safety of natural gas pipeline network supply.

[0014] On the other hand, another technical solution of the present invention to solve the above technical problem is as follows: a gas supply distribution device for a natural gas pipeline network system, comprising:

[0015] A feasibility calculation module is used to import multiple preset influencing factors, calculate the score of each influencing factor, and calculate the feasibility of each influencing factor based on the score of each influencing factor;

[0016] The simulation model building module is used to build a natural gas pipeline network SPS physical simulation model based on the feasibility of various influencing factors, the topological information of the natural gas pipeline network system, and the information of multiple pipe section units and multiple natural gas stations in the natural gas pipeline network topology;

[0017] The simulation module is used to simulate the SPS physical simulation model of the natural gas pipeline network according to the gas source information and distribution point information of the natural gas pipeline network system;

[0018] The non-steady-state simulation module is used to perform SPS non-steady-state simulation on the SPS physical simulation model of the simulated natural gas pipeline network according to the statistical data of unit failure time, and determine the system gas shortage within the failure time of each pipe section unit;

[0019] An importance coefficient determination module is used to score the system gas shortage volume within each failure time to obtain a total severity score value, and determine the consequence importance coefficient of each pipe section unit based on the total severity score value;

[0020] A reliability determination module is used to determine the unreliability of each pipe section unit according to the consequence importance coefficient of each pipe section unit, and obtain the reliability according to the unreliability;

[0021] An augmented objective function construction module is used to establish a unit cost function model according to the reliability, and determine the gas supply reliability optimization allocation objective function and constraint conditions according to the unit cost function model, construct an augmented objective function according to the gas supply reliability optimization allocation objective function and constraint conditions, construct a penalty function, and reconstruct the augmented objective function through the penalty function to obtain a new augmented objective function;

[0022] The distribution value solving module is used to solve the new augmented objective function through the particle swarm algorithm to obtain the distribution value of the gas supply reliability of the natural gas pipeline network system.

[0023] On the other hand, another technical solution of the present invention to solve the above-mentioned technical problem is as follows: a gas supply distribution device for a natural gas pipeline network system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor; when the processor executes the computer program, the gas supply distribution method for the natural gas pipeline network system as described above is implemented.

[0024] On the other hand, another technical solution of the present invention to solve the above technical problem is as follows: a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the gas supply distribution method of the natural gas pipeline system as described above is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A schematic flow chart of a gas supply distribution method for a natural gas pipeline network system provided in an embodiment of the present invention;

[0026] Figure 2 A module block diagram of a gas supply distribution device for a natural gas pipeline network system provided by an embodiment of the present invention;

[0027] Figure 3 A topological diagram of a natural gas pipeline system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0029] At present, the natural gas pipeline network is the only means of large-scale natural gas transportation and the link between resources and markets. With the increasing consumption of natural gas, the scale of my country's natural gas pipeline network has continued to expand, forming a natural gas pipeline network pattern that runs across the east and west, across the north and south, and connects the inside and outside. However, the redundancy of my country's natural gas pipeline network is low. Once a failure occurs, it will seriously threaten the supply security and put forward higher requirements for the reliable operation of the natural gas pipeline network. Carrying out the reliability management of natural gas pipeline network is crucial to ensure the safety of natural gas supply. At present, certain theoretical and technical achievements have been made in the calculation methods of gas supply reliability of complex natural gas pipeline network units and systems, but a complete natural gas pipeline network reliability management method system has not yet been established, and the research on the optimization theory and method after the evaluation of the gas supply reliability of the natural gas pipeline network system is not mature enough.

[0030] To address this issue, current reliability allocation is the process of allocating system reliability indicators to each unit within the system according to certain allocation principles and methods. It can provide scientific advice for unit reliability and is a key link in reliability management.

[0031] Existing reliability allocation methods are divided into two categories: unconstrained and constrained. Unconstrained allocation methods determine the allocation weight and reliability allocation value of units according to their importance by evaluating the many factors that affect the reliability of the unit, including equal allocation method, proportional allocation method, comprehensive factor weighting method, hierarchical analysis method, etc. Constrained allocation methods mainly include Lagrange multiplier algorithm, direct search method, dynamic programming method, etc., which require that the reliability of the system be maximized under the existing resource conditions, or that the target values ​​such as cost, volume and weight be minimized under the conditions of achieving the specified reliability index, which largely depends on the accuracy of the system reliability optimization model.

[0032] Most of the existing reliability allocation studies allocate the reliability of the system structure, mainly focusing on the pipeline structure such as single pipelines and equipment as the research object. The impact of the unit on the system gas supply is not considered in the allocation process, and the correlation between the unit structure and the gas supply function of the complex pipeline system is lacking. For the natural gas pipeline system, especially the complex system containing multiple sub-units (such as natural gas pipelines, compressors, etc.), it is urgent to allocate the reliability of the system to complete the gas supply task, establish the correlation model between the unit and the system gas supply reliability index, and use the optimization method to more accurately and reasonably allocate the system reliability target value to the various units that make up the system, so as to facilitate on-site implementation and management.

[0033] In view of the problems that the impact of the unit on the system gas supply is not considered in the above-mentioned natural gas distribution process, and the correlation between the unit structure and the gas supply function of the complex pipeline system is lacking, the present invention provides a natural gas pipeline system gas supply distribution method and device, which can determine the unit reliability optimization target and determine the weak gas supply units of the natural gas pipeline system, providing a scientific basis for reliability enhancement, thereby ensuring the safety of the natural gas pipeline supply.

[0034] like Figure 1 As shown, an embodiment of the present invention provides a gas supply distribution method for a natural gas pipeline network system, comprising the following steps:

[0035] S1. Import multiple preset influencing factors, calculate the score of each influencing factor, and calculate the feasibility of each influencing factor based on the score of each influencing factor;

[0036] S2. Establish a natural gas pipeline network SPS physical simulation model based on the feasibility of various influencing factors, the topological information of the natural gas pipeline network system, and the information of multiple pipe section units and multiple natural gas stations in the natural gas pipeline network topology;

[0037] S3. According to the gas source information and distribution point information of the natural gas pipeline network system, the SPS physical simulation model of the natural gas pipeline network is simulated;

[0038] S4. Perform SPS non-steady-state simulation on the SPS physical simulation model of the simulated natural gas pipeline network according to the statistical data of unit failure time, and determine the gas shortage of the system within the failure time of each pipe section unit;

[0039] S5. Score the amount of gas shortage in the system during each failure time to obtain a total severity score, and determine the consequence importance coefficient of each pipe section unit based on the total severity score;

[0040] S6. Determine the unreliability of each pipe section unit according to the consequence importance coefficient of each pipe section unit, and obtain the reliability according to the unreliability;

[0041] S7, establishing a unit cost function model according to the reliability, and determining a gas supply reliability optimization allocation objective function and constraint conditions according to the unit cost function model, constructing an augmented objective function according to the gas supply reliability optimization allocation objective function and constraint conditions, constructing a penalty function, and reconstructing the augmented objective function through the penalty function to obtain a new augmented objective function;

[0042] S8. Solve the new augmented objective function through the particle swarm algorithm to obtain the gas supply reliability distribution value of the natural gas pipeline network system.

[0043] In the above embodiment, a physical simulation model of the natural gas pipeline network SPS is established based on the feasibility, the gas shortage of the system within the failure time is determined by simulating the model, and the gas supply reliability index of the pipeline network system is reasonably allocated to each unit in the system. The augmented objective function is established through the unit reliability optimization target, and the gas supply reliability distribution value of the natural gas pipeline network system is obtained through the augmented objective function, which provides a scientific basis for reliability enhancement, thereby ensuring the safety of natural gas pipeline supply.

[0044] Preferably, in S1, a plurality of preset influencing factors are imported, and the scores of the influencing factors are calculated, and the feasibility of the influencing factors is calculated based on the scores of the influencing factors, including:

[0045] Importing multiple preset influencing factors, including structural complexity, technical maturity, maintenance difficulty, and environmental complexity;

[0046] The score of each influencing factor is calculated based on the scoring formula, which is:

[0047]

[0048] Among them, C w1 is the score value of the structural complexity influencing factor of the i-th unit, w1 is the weight of the structural complexity influencing factor, E w3 is the score value of the factors affecting the difficulty of emergency repair of the ith unit, w3 is the weight of the factors affecting the difficulty of emergency repair, T w2 is the score value of the technology maturity influencing factor of the i-th unit, w2 is the weight of the technology maturity influencing factor, M w4 is the score value of the environmental complexity influencing factor of the i-th unit, and w4 is the weight of the environmental complexity influencing factor;

[0049] Based on the feasibility formula, the scores of each influencing factor are calculated to obtain the feasibility of each influencing factor f i , the feasibility formula is:

[0050]

[0051] In the above embodiment, the unit weight factor is determined according to the predetermined natural gas pipeline network gas supply reliability influencing factors; and the objective function is established according to the preset reliability threshold of the natural gas pipeline network system.

[0052] Generally speaking, the influencing factors include: structural complexity, technical maturity, maintenance difficulty, environmental complexity, supply importance, and consequence severity. The scores of structural complexity, technical maturity, maintenance difficulty, and environmental complexity are selected to determine the unit feasibility f i .

[0053] The above embodiment can determine the weight factors of multiple influencing factors and obtain the feasibility of each influencing factor. i ,According to the influence degree of the above four influencing factors on the system gas supply reliability, a judgment matrix is ​​established to determine the weights of the four influencing factors.

[0054] Preferably, in S5, the amount of system gas shortage within each failure time is scored to obtain a total severity score, and the consequence importance coefficient of each pipe section unit is determined based on the total severity score, including:

[0055] Score the amount of gas shortage in the system at each failure time, and sum up each score value to get the total severity score value Q i ;

[0056] According to the consequence importance formula, the total severity score Q i Calculate and obtain the consequence importance coefficient w of each pipe section unit i , the consequence importance formula is:

[0057]

[0058] In the above embodiment, the consequence importance coefficient of each pipe section unit is determined by the scoring of the system gas shortage within each failure time, and the influence of the unit on the system gas supply can be considered in the allocation process.

[0059] Preferably, in S6, the unreliability of each pipe section unit is determined according to the consequence importance coefficient of each pipe section unit, and the reliability is obtained according to the unreliability, including:

[0060] Based on the Markov process and the consequence importance coefficient of each pipe section unit, the failure shutdown state probability of the pipe section unit is constructed:

[0061]

[0062] The compressor station unit failure shutdown state probability is constructed by the pipeline unit failure shutdown state probability:

[0063]

[0064] Among them, λ p is the failure rate of the pipe section unit, L is the length of the pipe section unit, μ p is the maintenance rate of the pipe section unit, λ C is the compressor unit failure rate, μ p is the compressor unit maintenance rate, e is a constant;

[0065] Integrate the probability of the compressor station unit failure shutdown state to obtain the unreliability of each pipe section unit;

[0066] The reliability is calculated based on the sum of the unreliability and the reliability being equal to 1.

[0067] In the above embodiment, the reliability target value of the system can be more accurately and reasonably allocated to each unit constituting the system, so as to facilitate on-site implementation and management.

[0068] Preferably, in S7, a unit cost function model is established according to the reliability, and a gas supply reliability optimization allocation objective function and constraint conditions are determined according to the unit cost function model, including:

[0069] Assuming the theoretical shortest maintenance time as the maximum reliability of each pipe section unit, and assuming the longest acceptable maintenance time as the minimum reliability of each pipe section unit, the unit cost function model is established based on the maximum reliability and the minimum reliability as follows:

[0070]

[0071] Based on the unit cost function model, the objective function and constraints for optimizing gas supply reliability are determined as follows:

[0072]

[0073] Among them, C is the cost, f i is the feasibility, 0 <f i <1, G i To ensure the importance of supply, w i is the severity of the consequence, R i,min is the minimum reliability, R i,max For maximum reliability, R i Assign a value to the gas supply reliability, R s is the system gas supply reliability, Q i,缺 Q is the system gas shortage, j,需 is the system user demand, R obj is the target reliability of the system.

[0074] Specifically, the maximum reliability of each unit is determined according to the theoretical shortest maintenance time; and the minimum reliability of the unit is determined according to the longest acceptable maintenance time.

[0075] Preferably, in S7, an augmented objective function is constructed according to the gas supply reliability optimization allocation objective function and constraint conditions, including:

[0076] The penalty term is determined according to the objective function and the constraints, and the augmented objective function is obtained through the penalty term:

[0077]

[0078] Preferably, in S7, constructing a penalty function, and reconstructing the augmented objective function by using the penalty function to obtain a new augmented objective function includes:

[0079] The penalty function is constructed by the exterior point method, and the augmented objective function is reconstructed based on the penalty function to obtain a new augmented objective function:

[0080]

[0081] In the above embodiment, a correlation model between the unit and the system gas supply reliability index is established, and an optimization method is used to more accurately and reasonably distribute the system reliability target value to each unit constituting the system, so as to facilitate on-site implementation and management.

[0082] like Figure 2 As shown, the present invention also provides a gas supply distribution device for a natural gas pipeline network system, comprising:

[0083] A feasibility calculation module is used to import multiple preset influencing factors, calculate the score of each influencing factor, and calculate the feasibility of each influencing factor based on the score of each influencing factor;

[0084] The simulation model building module is used to build a natural gas pipeline network SPS physical simulation model based on the feasibility of various influencing factors, the topological information of the natural gas pipeline network system, and the information of multiple pipe section units and multiple natural gas stations in the natural gas pipeline network topology;

[0085] The simulation module is used to simulate the SPS physical simulation model of the natural gas pipeline network according to the gas source information and distribution point information of the natural gas pipeline network system;

[0086] The non-steady-state simulation module is used to perform SPS non-steady-state simulation on the SPS physical simulation model of the simulated natural gas pipeline network according to the statistical data of unit failure time, and determine the system gas shortage within the failure time of each pipe section unit;

[0087] An importance coefficient determination module is used to score the system gas shortage volume within each failure time to obtain a total severity score value, and determine the consequence importance coefficient of each pipe section unit based on the total severity score value;

[0088] A reliability determination module is used to determine the unreliability of each pipe section unit according to the consequence importance coefficient of each pipe section unit, and obtain the reliability according to the unreliability;

[0089] An augmented objective function construction module is used to establish a unit cost function model according to the reliability, and determine the gas supply reliability optimization allocation objective function and constraint conditions according to the unit cost function model, construct an augmented objective function according to the gas supply reliability optimization allocation objective function and constraint conditions, construct a penalty function, and reconstruct the augmented objective function through the penalty function to obtain a new augmented objective function;

[0090] The distribution value solving module is used to solve the new augmented objective function through the particle swarm algorithm to obtain the distribution value of the gas supply reliability of the natural gas pipeline network system.

[0091] The following is an application example to illustrate the feasibility of the gas supply distribution method and device of the natural gas pipeline system.

[0092] Figure 3 This is a topological diagram of a natural gas pipeline system. Figure 3 As shown in the figure, the pipeline system consists of gas sources, pipeline sections, compressor stations, cut-off valves and distribution stations, including 19 pipeline sections, 6 compressor stations (green nodes), 2 gas sources, 17 demand points and 5 valve chambers. The total user demand is 57678×104m 3 .

[0093] The objective function and constraints for optimizing gas supply reliability are as follows:

[0094]

[0095] Among them, C is the cost, f i is the feasibility, 0 <f i <1, G i To ensure the importance of supply, w i is the severity of the consequence, R i,min is the minimum reliability, R i,max For maximum reliability, R i Assign a value to the gas supply reliability, R s is the system gas supply reliability, Q i,缺 Q is the system gas shortage, j,需 is the system user demand, R obj is the target reliability of the system.

[0096] The feasibility f is determined by using the weight factor i .

[0097] Four feasibility influencing factors are selected, namely structural complexity, technical maturity, maintenance and repair difficulty, and environmental complexity.

[0098] The judgment matrix constructed by comparing and scoring two factors is:

[0099]

[0100] The maximum weight root is found to be 4.11, and the normalized weight vector W = (0.49, 0.16, 0.17, 0.18).

[0101] A consistency test was performed and it was calculated that CR=0.04<0.1, which met the consistency test requirements.

[0102] The four feasibility influencing factors are scored separately.

[0103] The structural complexity scores of each unit are: 9, 5, 9, 5, 9, 5, 9, 5, 5, 9, 5, 5, 5, 5, 9, 5, 5, 5, 5, 5, 5, 5, 5, 5.

[0104] The technology maturity scores of each unit are: 7, 8, 7, 8, 7, 8, 8, 7, 8, 8, 8, 8, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8.

[0105] The environmental complexity scores of each unit are: 5, 7, 5, 7, 5, 6, 4, 6, 6, 4, 6, 5, 5, 5, 4, 5, 5, 5, 5, 4, 4, 3, 3, 4.

[0106] The maintenance and repair difficulty scores of each unit are: 5, 6, 5, 6, 5, 6, 5, 6, 5, 6, 7, 6, 6, 5, 6, 6, 7, 7, 7, 6, 6, 5, 5, 5.

[0107] According to the formula Get ratings for each unit.

[0108] according to Get the feasibility of each unit.

[0109] Determine the feasibility of each unit f i They are: 0.47, 0.63, 0.47, 0.63, 0.47, 0.65, 0.49, 0.65, 0.65, 0.49, 0.65, 0.68, 0.67, 0.67, 0.49, 0.67, 0.67, 0.68, 0.68, 0.69, 0.69, 0.70, 0.70, 0.67.

[0110] The gas shortage is normalized to obtain the importance of supply guarantee for each unit.

[0111] Determine the air shortage Q of each unit through SPS simulation i,缺They are: 8015, 8495, 309, 11371, 0, 14074, 0, 14967, 15357, 1633, 16057, 16271, 15557, 14682, 0, 15352, 14596, 14093, 12431, 7498, 0, 984, 3182, 1633, 899.

[0112] Normalization determines the supply importance of each unit G i They are: 5, 5, 1, 7, 1, 9, 1, 9, 9, 1, 10, 10, 10, 9, 1, 9, 9, 8, 5, 1, 1, 3, 2, 2.

[0113] For the social consequence s1, the scores of each unit are: 6, 7, 8, 6, 9, 10, 9, 9, 8, 8, 7, 9, 9, 6, 6, 5, 7, 5, 6, 4, 8, 7, 8, 9, 10.

[0114] For the economic consequences s2, the scores of each unit are: 7, 7, 8, 8, 8, 8, 6, 10, 8, 6, 7, 8, 9, 5, 7, 4, 5, 5, 5, 7, 5, 6, 5, 10, 8.

[0115] according to Determine the total consequence severity score Q i They are: 6.48, 7, 8, 6.93, 8.48, 8.94, 7.35, 9.48, 8, 6.93, 7, 8.48, 9, 5.48, 6.48, 4.47, 5.92, 5, 5.48, 5.29, 6.32, 6.48, 6.32, 9.48, 8.94.

[0116] according to Determine the consequence importance coefficient w of each unit i They are: 0.04, 0.04, 0.05, 0.04, 0.05, 0.05, 0.04, 0.05, 0.05, 0.04, 0.05, 0.05, 0.03, 0.04, 0.03, 0.03, 0.03, 0.03, 0.04, 0.04, 0.05, 0.05.

[0117] The pipeline failure rate is 1.26×10 －4 times / (km·a), and the failure rate of the station is 5.1×10 －4 times / h, the maximum maintenance rate is 2 times / d, and the minimum maintenance rate is 0.33 times / d.

[0118] The probability of failure and shutdown of pipe section unit Probabilistic formula for failure and shutdown status of compressor station unit

[0119] The unreliability of each unit is obtained by integrating the state probability. According to the relationship of "reliability + unreliability = 1", the reliability of each unit can be obtained.

[0120] The unit lengths of the pipe sections are: 33.3, 228.376, 212.677, 86.589, 104.686, 56.01, 98.007, 20.235, 7.489, 66.94, 14.259, 46.915, 88.29, 29.717, 22.3, 29.5, 61, 114.6, and 11.

[0121] Determine the minimum reliability R of each unit i,min They are: 0.98108, 0.99996, 0.98108, 0.99978, 0.98108, 0.99980, 0.98108, 0.99992, 0.99990, 0.98108, 0.99994, 0.99991, 0.99998, 0.99999, 0.98108, 0.99994, 0.99998, 0.99995, 0.99992, 0.99997, 0.99998, 0.99997, 0.99994, 0.99989, 0.99999.

[0125] Determine the maximum reliability R of each unit i,max They are: 0.9939, 0.999994, 0.9939, 0.99996, 0.9939, 0.99996, 0.9939, 0.99998, 0.99998, 0.9939, 0.99999, 0.99998, 0.999996, 0.999998, 0.9939, 0.99999, 0.999997, 0.999992, 0.99998, 0.999995, 0.999996, 0.999995, 0.99999, 0.999998, 0.999998.

[0126] Determine the system target reliability R obj is 0.9997.

[0127] The penalty function method is combined with the particle swarm optimization algorithm to solve the constrained nonlinear programming problem.

[0128] Determine the system parameters, including: inertia factor w is 0.7, learning factor c 1 、c 2 Both are set to 0.5, the initial population size is 100, and the maximum number of iterations is 300.

[0129] According to the objective function and constraints, the penalty term is determined, and the augmented objective function is obtained as follows:

[0130]

[0131] The penalty function is constructed by the exterior point method, and the augmented objective function is reconstructed based on the penalty function to obtain a new augmented objective function:

[0132]

[0133] Initialize the particle swarm position and randomly generate the initial position and initial velocity of the particle swarm.

[0134] Calculate the fitness values ​​of all particles.

[0135] Determine the optimal position pbest experienced by the individual id and the best position gbest experienced by the group id .

[0136] According to the formula Update speed.

[0137] According to the formula Update location.

[0138] Boundary condition processing is performed to ensure that the updated particle position and velocity are within the upper and lower limits of the search space.

[0139] Calculate the new fitness value and compare the new fitness value with the optimal position pbest experienced by the individual id Compare the fitness values ​​of , if better, update pbest id .

[0140] All pbest id The best position gbest experienced by the particle population id .

[0141] Determine whether the accuracy of the result meets the requirement or whether the number of iterations reaches the maximum number. If so, stop the iteration; otherwise, calculate the fitness values ​​of all particles and iterate again to find the optimal solution.

[0142] The optimized distribution values ​​of gas supply reliability of each unit are solved as follows: 0.98749, 0.999977, 0.98749, 0.99987, 0.98749, 0.99988, 0.98749, 0.99995, 0.99994, 0.98749, 0.999965, 0.999945, 0.999988, 0.999994, 0.98749, 0.999965, 0.9999885, 0.999971, 0.99995, 0.9999825, 0.999988, 0.9999825, 0.999965, 0.999935, 0.999994.

[0144] An embodiment of the present invention also provides a gas supply distribution device for a natural gas pipeline network system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the gas supply distribution method for the natural gas pipeline network system as described above is implemented.

[0145] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the gas supply distribution method of the natural gas pipeline network system as described above is implemented.

[0146] In some schemes, multiple embodiments of the present application can be combined, and the combined scheme can be implemented. Optionally, some operations in the process of each method embodiment are optionally combined, and / or the order of some operations is optionally changed. In addition, the execution order between the steps of each process is only exemplary and does not constitute a restriction on the execution order between the steps. There can also be other execution orders between the steps. It is not intended to indicate that the execution order is the only order in which these operations can be performed. A person of ordinary skill in the art will think of a variety of ways to reorder the operations described herein. In addition, it should be noted that the process details involved in a certain embodiment of this article are also applicable to other embodiments in a similar manner, or different embodiments can be used in combination.

[0147] In addition, some steps in the method embodiment may be equivalently replaced by other possible steps. Alternatively, some steps in the method embodiment may be optional and may be deleted in certain usage scenarios. Alternatively, other possible steps may be added to the method embodiment.

[0148] Furthermore, the various method embodiments may be implemented separately or in combination.

[0149] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0150] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A gas supply distribution method for a natural gas pipeline network system, characterized in that: The steps include: S1. Import multiple preset influencing factors, calculate the score of each influencing factor, and calculate the feasibility of each influencing factor based on the score of each influencing factor; S2. Establish a natural gas pipeline network SPS physical simulation model based on the feasibility of various influencing factors, the topological information of the natural gas pipeline network system, and the information of multiple pipe section units and multiple natural gas stations in the natural gas pipeline network topology; S3. According to the gas source information and distribution point information of the natural gas pipeline network system, the SPS physical simulation model of the natural gas pipeline network is simulated; S4. Perform SPS non-steady-state simulation on the SPS physical simulation model of the simulated natural gas pipeline network according to the statistical data of unit failure time, and determine the gas shortage of the system within the failure time of each pipe section unit; S5. Score the amount of gas shortage in the system during each failure time to obtain a total severity score, and determine the consequence importance coefficient of each pipe section unit based on the total severity score; S6. Determine the unreliability of each pipe section unit according to the consequence importance coefficient of each pipe section unit, and obtain the reliability according to the unreliability; S7, establishing a unit cost function model according to the reliability, and determining a gas supply reliability optimization allocation objective function and constraint conditions according to the unit cost function model, constructing an augmented objective function according to the gas supply reliability optimization allocation objective function and constraint conditions, constructing a penalty function, and reconstructing the augmented objective function through the penalty function to obtain a new augmented objective function; S8. Solve the new augmented objective function through the particle swarm algorithm to obtain the gas supply reliability distribution value of the natural gas pipeline network system.

2. The gas supply distribution method of the natural gas pipeline network system according to claim 1, characterized in that: In S1, a plurality of preset influencing factors are imported, and the scores of the influencing factors are calculated. The feasibility of each influencing factor is calculated based on the scores of each influencing factor, including: Importing multiple preset influencing factors, including structural complexity, technical maturity, maintenance difficulty, and environmental complexity; The score of each influencing factor is calculated based on the scoring formula, which is: Among them, C w1 is the score value of the structural complexity influencing factor of the i-th unit, w1 is the weight of the structural complexity influencing factor, E w3 is the score value of the factors affecting the difficulty of emergency repair of the ith unit, w3 is the weight of the factors affecting the difficulty of emergency repair, T w2 is the score value of the technology maturity influencing factor of the i-th unit, w2 is the weight of the technology maturity influencing factor, M w4 is the score value of the environmental complexity influencing factor of the i-th unit, and w4 is the weight of the environmental complexity influencing factor; Based on the feasibility formula, the scores of each influencing factor are calculated to obtain the feasibility of each influencing factor f i , the feasibility formula is:

3. The gas supply distribution method of the natural gas pipeline network system according to claim 1, characterized in that: In S5, the amount of gas shortage in the system during each failure time is scored to obtain a total severity score, and the consequence importance coefficient of each pipe section unit is determined based on the total severity score, including: Score the amount of gas shortage in the system at each failure time, and sum up each score value to get the total severity score value Q i ; According to the consequence importance formula, the total severity score Q i Calculate and obtain the consequence importance coefficient w of each pipe section unit i , the consequence importance formula is:

4. The gas supply distribution method of the natural gas pipeline network system according to claim 1, characterized in that: In S6, the unreliability of each pipe section unit is determined according to the consequence importance coefficient of each pipe section unit, and the reliability is obtained according to the unreliability, including: Based on the Markov process and the consequence importance coefficient of each pipe section unit, the failure shutdown state probability of the pipe section unit is constructed: The compressor station unit failure shutdown state probability is constructed by the pipeline unit failure shutdown state probability: Among them, λ p is the failure rate of the pipe section unit, L is the length of the pipe section unit, μ p is the maintenance rate of the pipe section unit, λ C is the compressor unit failure rate, μ p is the compressor unit maintenance rate, e is a constant; Integrate the probability of the compressor station unit failure shutdown state to obtain the unreliability of each pipe section unit; The reliability is calculated based on the sum of the unreliability and the reliability being equal to 1.

5. The gas supply distribution method of the natural gas pipeline network system according to claim 1, characterized in that: In S7, a unit cost function model is established according to the reliability, and a gas supply reliability optimization allocation objective function and constraint conditions are determined according to the unit cost function model, including: Assuming the theoretical shortest maintenance time as the maximum reliability of each pipe section unit, and assuming the longest acceptable maintenance time as the minimum reliability of each pipe section unit, the unit cost function model is established based on the maximum reliability and the minimum reliability as follows: Based on the unit cost function model, the objective function and constraints for optimizing gas supply reliability are determined as follows: Among them, C is the cost, f i is the feasibility, 0 <f i <1, G i To ensure the importance of supply, w i is the severity of the consequence, R i,min is the minimum reliability, R i,max For maximum reliability, R i Assign a value to the gas supply reliability, R s is the gas supply reliability of the system, Q i,缺 Q is the system gas shortage, j,需 is the system user demand, R obj is the target reliability of the system.

6. The gas supply distribution method of the natural gas pipeline network system according to claim 5, characterized in that: In S7, an augmented objective function is constructed according to the gas supply reliability optimization allocation objective function and constraint conditions, including: The penalty term is determined according to the objective function and the constraints, and the augmented objective function is obtained through the penalty term:

7. The gas supply distribution method of the natural gas pipeline network system according to claim 1, characterized in that: In S7, a penalty function is constructed, and the augmented objective function is reconstructed by the penalty function to obtain a new augmented objective function, including: The penalty function is constructed by the exterior point method, and the augmented objective function is reconstructed based on the penalty function to obtain a new augmented objective function:

8. A gas distribution device for a natural gas pipeline network system, characterized in that: include: A feasibility calculation module is used to import multiple preset influencing factors, calculate the score of each influencing factor, and calculate the feasibility of each influencing factor based on the score of each influencing factor; The simulation model building module is used to build a natural gas pipeline network SPS physical simulation model based on the feasibility of various influencing factors, the topological information of the natural gas pipeline network system, and the information of multiple pipe section units and multiple natural gas stations in the natural gas pipeline network topology; The simulation module is used to simulate the SPS physical simulation model of the natural gas pipeline network according to the gas source information and distribution point information of the natural gas pipeline network system; The non-steady-state simulation module is used to perform SPS non-steady-state simulation on the SPS physical simulation model of the simulated natural gas pipeline network according to the statistical data of unit failure time, and determine the system gas shortage within the failure time of each pipe section unit; An importance coefficient determination module is used to score the system gas shortage volume within each failure time to obtain a total severity score value, and determine the consequence importance coefficient of each pipe section unit based on the total severity score value; A reliability determination module is used to determine the unreliability of each pipe section unit according to the consequence importance coefficient of each pipe section unit, and obtain the reliability according to the unreliability; An augmented objective function construction module is used to establish a unit cost function model according to the reliability, and determine the gas supply reliability optimization allocation objective function and constraint conditions according to the unit cost function model, construct an augmented objective function according to the gas supply reliability optimization allocation objective function and constraint conditions, construct a penalty function, and reconstruct the augmented objective function through the penalty function to obtain a new augmented objective function; The distribution value solving module is used to solve the new augmented objective function through the particle swarm algorithm to obtain the distribution value of the gas supply reliability of the natural gas pipeline network system.

9. A gas distribution device for a natural gas pipeline network system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the gas supply distribution method of the natural gas pipeline network system according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the gas supply distribution method of a natural gas pipeline network system according to any one of claims 1 to 7 is implemented.

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