Reliability evaluation method of natural gas pipeline network, electronic equipment and storage medium

Abstract

The invention discloses a reliability evaluation method of a natural gas pipeline network, electronic equipment and a storage medium, relates to the technical field of oil and gas pipelines, and can comprehensively analyze various pipeline network factors and optimize a reliability evaluation result. The method comprises the steps of determining operation state data of a natural gas pipeline network in a target time period based on operation state data of each gas transmission unit in the natural gas pipeline network in the target time period; determining the actual gas supply amount of the natural gas pipeline network in the target time period based on the gas supply amount calculation model and the operation state data of the natural gas pipeline network in the target time period; decision parameters in the air supply amount calculation model comprise pipeline flow, node pressure and pipeline pipe storage; the constraint condition of the air supply amount calculation model comprises at least one of the following items: flow constraint, pressure constraint, pipe network hydraulic constraint and pipe network pipe storage constraint; and determining the gas supply reliability of the natural gas pipeline network based on the gas consumption demand of the user in the target time period and the actual gas supply amount of the natural gas pipeline network in the target time period.

Description

Technical Field

[0001] The present application relates to the technical field of oil and gas pipelines, and particularly to a method for evaluating the reliability of a natural gas pipeline network, an electronic device, and a storage medium. Background Art

[0002] The natural gas pipeline network is a key infrastructure connecting the production, transportation, and consumption links of natural gas, and is widely used in fields such as urban gas supply and industrial fuel transportation. With the development of the economic society, the construction scale of the natural gas pipeline network has been continuously expanding, and its reliability has become the focus of attention of the industry and the public. Improving the reliability of the natural gas pipeline network not only helps to ensure the safe and stable energy supply, but also can reduce the risk of accidents and protect the safety of people's lives and property.

[0003] In the prior art, for the reliability evaluation method of the natural gas pipeline network, the evaluation factors are relatively simple, it is difficult to adapt to the reliability of the natural gas pipeline network under different operating conditions, and the evaluation effect is not good. Summary of the Invention

[0004] The embodiments of the present application provide a method for evaluating the reliability of a natural gas pipeline network, an electronic device, and a storage medium, which can comprehensively analyze complex natural gas pipeline network factors and optimize the evaluation effect of reliability evaluation.

[0005] To achieve the above object, the present application adopts the following technical solutions:

[0006] In a first aspect, a method for evaluating the reliability of a natural gas pipeline network is provided, and the method includes: determining the operation state data of the natural gas pipeline network in a target time period based on the operation state data of each gas transmission unit in the natural gas pipeline network in the target time period; determining the actual gas supply volume of the natural gas pipeline network in the target time period based on the gas supply volume calculation model and the operation state data of the natural gas pipeline network in the target time period; the decision parameters in the gas supply volume calculation model include pipeline flow, node pressure, and pipeline inventory; the constraint conditions of the gas supply volume calculation model include at least one of the following: flow constraint, pressure constraint, pipeline network hydraulic constraint, and pipeline network inventory constraint; determining the gas supply reliability of the natural gas pipeline network based on the gas consumption demand of the user in the target time period and the actual gas supply volume of the natural gas pipeline network in the target time period.

[0007] The reliability evaluation method for natural gas pipeline networks provided by this application determines the operating state data of the entire natural gas pipeline network during a target time period based on the operating state data of each gas transmission unit in the natural gas pipeline network during the target time period. Then, using a gas supply calculation model with pipeline flow rate, node pressure, and pipeline inventory as decision parameters, combined with the pipeline operating state data, it calculates the actual gas supply of the natural gas pipeline network during the target time period. Finally, by comparing the gas demand of users during the target time period with the actual gas supply of the pipeline, it determines the gas supply reliability of the natural gas pipeline network. This method calculates the actual gas supply of the natural gas pipeline network by comprehensively considering complex natural gas pipeline network conditions (pipeline flow rate, node pressure, and pipeline inventory), improves the calculation accuracy of the actual gas supply, provides more accurate data support for determining the reliability of the natural gas pipeline network, and thus can optimize the reliability evaluation results.

[0008] In some embodiments, the operating state data of each gas transmission unit in the natural gas pipeline network during the target time period includes: the operating states that occur in each pipeline during the target time period, the moments when each operating state occurs, and the duration of each operating state; the operating state data of the natural gas pipeline network during the target time period includes: all the operating states that occur in the natural gas pipeline network during the target time period, the moments when each operating state occurs, and the duration of each operating state.

[0009] In some embodiments, the natural gas pipeline network includes multiple gas transmission units. Before determining the operating state data of the natural gas pipeline network during the target time period based on the operating state data of each gas transmission unit in the natural gas pipeline network during the target time period, the method further includes: for each gas transmission unit of the natural gas pipeline network, using a state transition simulation algorithm, based on the failure rate and repair rate of each gas transmission unit, to determine the operating state data of each gas transmission unit during the target time period.

[0010] In some embodiments, the failure rate of the gas transmission unit is determined based on the load rate of the gas transmission unit and the functional relationship between the load rate and the pipe section failure rate; the functional relationship between the load rate and the pipe section failure rate is used to indicate a positive correlation between the load rate and the pipe section failure rate; wherein, the load rate is determined based on the flow rate of the current working condition of the gas transmission unit and the designed gas transmission volume of the gas transmission unit.

[0011] In some embodiments, the types of gas transmission units include at least one of the following: gas transmission pipeline sections, compressor stations; the compressor stations are provided with compressor units.

[0012] In some embodiments, determining the gas supply reliability of the natural gas pipeline network based on the gas demand of users during the target time period and the actual gas supply of the natural gas pipeline network during the target time period includes: using the Monte Carlo simulation algorithm, based on the gas demand of users during the target time period and the actual gas supply of the natural gas pipeline network during the target time period, to calculate the reliability index of the natural gas pipeline network, and the reliability index is used to reflect the gas supply reliability of the natural gas pipeline network.

[0013] In some embodiments, the gas supply reliability of the natural gas pipeline network includes at least one of the following: the gas supply reliability of the entire natural gas pipeline network, and the gas supply reliability of the user demand nodes in the natural gas pipeline network.

[0014] In some embodiments, the gas consumption demand is determined based on the gas consumption characteristics of users, the fluctuation characteristics of user demands, and a demand prediction model; wherein, the demand prediction model includes at least one of the following: a time series model, a support vector machine model, and a long short-term memory artificial neural network (LSTM) model.

[0015] In a second aspect, the present application provides a reliability evaluation device for a natural gas pipeline network, which can implement the reliability evaluation method for the natural gas pipeline network provided in the first aspect above. The reliability evaluation device for this pipeline network includes an analysis module.

[0016] The analysis module is configured to determine the operating state data of the natural gas pipeline network in a target time period based on the operating state data of each gas transmission unit in the natural gas pipeline network in the target time period.

[0017] The analysis module is further configured to determine the actual gas supply volume of the natural gas pipeline network in the target time period based on a gas supply volume calculation model and the operating state data of the natural gas pipeline network in the target time period; the decision parameters in the gas supply volume calculation model include pipeline flow rate, node pressure, and pipeline inventory; the constraint conditions of the gas supply volume calculation model include at least one of the following: flow constraint, pressure constraint, pipeline network hydraulic constraint, and pipeline network inventory constraint.

[0018] The analysis module is further configured to determine the gas supply reliability of the natural gas pipeline network based on the gas consumption demand of users in the target time period and the actual gas supply volume of the natural gas pipeline network in the target time period.

[0019] In a possible implementation manner, the operating state data of each gas transmission unit in the natural gas pipeline network in the target time period includes: the operating states that occur in each pipeline in the target time period, the moments when each operating state occurs, and the duration of each operating state; the operating state data of the natural gas pipeline network in the target time period includes: all the operating states that occur in the natural gas pipeline network in the target time period, the moments when each operating state occurs, and the duration of each operating state.

[0020] In a possible implementation manner, the natural gas pipeline network includes multiple gas transmission units. Before determining the operating state data of the natural gas pipeline network in the target time period based on the operating state data of each gas transmission unit in the natural gas pipeline network, the analysis module is further configured to, for each gas transmission unit of the natural gas pipeline network, use a state transition simulation algorithm to determine the operating state data of each gas transmission unit in the target time period according to each gas transmission unit, failure rate, and repair rate.

[0021] A possible implementation is that the failure rate of the gas transmission unit is determined based on the load rate of the gas transmission unit and the functional relationship between the load rate and the pipe section failure rate; the functional relationship between the load rate and the pipe section failure rate is used to indicate a positive correlation between the load rate and the pipe section failure rate; wherein, the load rate is determined based on the flow rate of the current operating condition of the gas transmission unit and the designed gas transmission volume of the gas transmission unit.

[0022] A possible implementation is that the types of the gas transmission units include at least one of the following: gas transmission pipelines, compressor stations; the compressor stations are provided with compressor units.

[0023] A possible implementation is that the analysis module is specifically configured to use the Monte Carlo simulation algorithm to calculate the reliability index of the natural gas pipeline network based on the gas consumption demand of the user within the target time period and the actual gas supply volume of the natural gas pipeline network within the target time period, and the reliability index is used to reflect the gas supply reliability of the natural gas pipeline network.

[0024] A possible implementation is that the gas supply reliability of the natural gas pipeline network includes at least one of the following: the gas supply reliability of the entire natural gas pipeline network, the gas supply reliability of the user demand nodes in the natural gas pipeline network.

[0025] In a third aspect, the present application provides an electronic device, which includes: a processor and a memory; the memory stores instructions executable by the processor; when the processor is configured to execute the instructions, the electronic device implements the method of the first aspect above.

[0026] In a fourth aspect, the present application provides a computer-readable storage medium, which includes: computer software instructions; when the computer software instructions run in an electronic device, the electronic device implements the method of the first aspect above.

[0027] In a fifth aspect, the present application provides a computer program product, which includes a computer program; when the computer program runs in an electronic device, the electronic device implements the method of the first aspect above.

[0028] For the beneficial effects of the second to fifth aspects above, reference may be made to the corresponding descriptions of the first aspect, and details are not repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0030] Figure 1Schematic flowchart of a reliability evaluation method for a natural gas pipeline network provided by an embodiment of the present application;

[0031] Figure 2 Schematic flowchart of another reliability evaluation method for a natural gas pipeline network provided by an embodiment of the present application;

[0032] Figure 3 Schematic flowchart of yet another reliability evaluation method for a natural gas pipeline network provided by an embodiment of the present application;

[0033] Figure 4 Schematic flowchart of yet another reliability evaluation method for a natural gas pipeline network provided by an embodiment of the present application;

[0034] Figure 5 Schematic structural diagram of a reliability evaluation device for a natural gas pipeline network provided by an embodiment of the present application;

[0035] Figure 6 Schematic structural diagram of an electronic device provided by the present application. Detailed implementation manners

[0036] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0037] In the description of the present application, it should be understood that the orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", "front", "rear", "inner", "outer", etc. is the orientation or relative positional relationship based on the orientation shown in the accompanying drawings, and is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation to the present application. Without special instructions, in the case of satisfying the relative positional relationship shown in the accompanying drawings, the above-described orientation description can be flexibly set during the actual application process.

[0038] The terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present application, unless otherwise stated, the meaning of "a plurality" is two or more.

[0039] In the description of this application, it should be noted that unless otherwise clearly specified and limited, the terms "installed", "connected", "linked", and "communicated" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection. It can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0040] In the embodiments of this application, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, article or device. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the presence of additional identical elements in the process, article or device comprising such element.

[0041] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or having more advantages than other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present relevant concepts in a specific manner.

[0042] In the description of this specification, specific features, structures, materials or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0043] The reliability assessment of natural gas pipeline networks is an important process to ensure the safe, stable and efficient operation of natural gas pipeline networks. In the prior art, the reliability assessment methods of natural gas pipeline networks mostly obtain the gas supply capacity of natural gas pipeline networks by analyzing historical data to evaluate their reliability. However, this method does not analyze different influencing factors and is difficult to adapt to complex and changeable application scenarios, resulting in poor reliability evaluation effects.

[0044] In view of the above technical problems, the present application proposes a reliability evaluation method for a natural gas pipeline network. The idea of this method is as follows: Based on the operation status data of each gas transmission unit in the natural gas pipeline network during the target time period, determine the operation status data of the natural gas pipeline network during the target time period; Based on the gas supply calculation model and the operation status data of the natural gas pipeline network during the target time period, determine the actual gas supply of the natural gas pipeline network during the target time period; The decision parameters in the gas supply calculation model include pipeline flow, node pressure, and pipeline inventory / gas supply calculation model constraints include at least one of the following: flow constraint, pressure constraint, pipeline network hydraulic constraint, pipeline network inventory constraint; Based on the gas consumption demand of users during the target time period and the actual gas supply of the natural gas pipeline network during the target time period, determine the gas supply reliability of the natural gas pipeline network. This method can comprehensively analyze various natural gas pipeline network factors and optimize the reliability evaluation results.

[0045] The reliability evaluation method for a natural gas pipeline network provided by the embodiments of the present application can be executed by an electronic device.

[0046] Exemplarily, the electronic device can be a server. For example, a single server, or a server cluster composed of multiple servers. In some embodiments, the server cluster can also be a distributed cluster.

[0047] Exemplarily, the electronic device can be a terminal device. For example, a mobile phone, a tablet computer, a desktop type, a laptop, a handheld computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, and a cellular phone, a personal digital assistant (PDA), an augmented reality (AR) / virtual reality (VR) device, etc. The embodiments of the present application do not impose special restrictions on the specific form of the terminal device.

[0048] The following will introduce in detail the reliability evaluation method for a natural gas pipeline network provided by the present application with reference to the accompanying drawings.

[0049] Figure 1 It is a schematic flowchart of a reliability evaluation method for a natural gas pipeline network provided by an embodiment of the present application, as Figure 1 shown, the method includes:

[0050] S100. Based on the operation status data of each gas transmission unit in the natural gas pipeline network during the target time period, determine the operation status data of the natural gas pipeline network during the target time period.

[0051] In some embodiments, the operating status data of each gas transmission unit in the natural gas pipeline network during the target time period includes: the operating statuses that occur for each gas transmission unit during the target time period, the moments when each operating status occurs, and the duration of each operating status.

[0052] In some embodiments, the operating status data of the natural gas pipeline network during the target time period includes: all the operating statuses that occur in the natural gas pipeline network during the target time period, the moments when each operating status occurs, and the duration of each operating status.

[0053] S200. Based on the gas supply calculation model and the operating status data of the natural gas pipeline network during the target time period, determine the actual gas supply of the natural gas pipeline network during the target time period.

[0054] In some embodiments, the decision parameters in the gas supply calculation model include pipeline flow rate, node pressure, and pipeline inventory.

[0055] In some embodiments, the constraint conditions of the gas supply calculation model include at least one of the following: flow constraint, pressure constraint, pipeline network hydraulic constraint, and pipeline network inventory constraint.

[0056] In some embodiments, a gas supply calculation model is constructed based on a directed weighted graph. The natural gas pipeline network system is represented by the directed weighted graph, and then the actual gas supply of the natural gas pipeline network system is calculated. The specific implementation process is described in detail later and will not be elaborated here.

[0057] S300. Based on the gas consumption demand of users during the target time period and the actual gas supply of the natural gas pipeline network during the target time period, determine the gas supply reliability of the natural gas pipeline network.

[0058] In some embodiments, the Monte Carlo simulation algorithm is used to calculate the reliability index of the natural gas pipeline network based on the gas consumption demand of users during the target time period and the actual gas supply of the natural gas pipeline network during the target time period. Among them, the reliability index is used to reflect the gas supply reliability of the natural gas pipeline network.

[0059] It should be noted that the Monte Carlo simulation algorithm is a calculation method based on probability and statistical methods. It simulates the target process by repeating random sampling and using random numbers or pseudo-random numbers to obtain the probability distribution and mathematical expectation of a complex process.

[0060] It is understandable that the reliability evaluation method for the natural gas pipeline network provided by this application determines the operation status data of the entire natural gas pipeline network during the target time period based on the operation status data of each gas transmission unit in the natural gas pipeline network. Then, using a gas supply calculation model with pipeline flow rate, node pressure, and pipeline inventory as decision parameters and flow constraints, pressure constraints, pipeline network hydraulic constraints, and pipeline network inventory constraints as constraint conditions, combined with the pipeline operation status data, the actual gas supply of the natural gas pipeline network during the target time period is calculated. Finally, by comparing the gas consumption demand of users during the target time period with the actual gas supply of the pipeline, the gas supply reliability of the natural gas pipeline network is determined. This method calculates the actual gas supply of the natural gas pipeline network by comprehensively considering the complex conditions of the natural gas pipeline network, improving the calculation accuracy, and thus optimizing the reliability evaluation results.

[0061] In some embodiments, the gas supply reliability of the natural gas pipeline network includes at least one of the following: the gas supply reliability of the entire natural gas pipeline network, the gas supply reliability of the user demand nodes in the natural gas pipeline network.

[0062] Furthermore, the reliability index of the natural gas pipeline network includes at least one of the following: the reliability index of the entire natural gas pipeline network, the reliability index of the user demand nodes in the natural gas pipeline network.

[0063] Exemplarily, using the Monte Carlo simulation algorithm to calculate the reliability index of the entire natural gas pipeline network satisfies the following formula:

[0064]

[0065] Using the Monte Carlo simulation algorithm to calculate the reliability index of the user demand nodes in the natural gas pipeline network satisfies the following formula:

[0066]

[0067] Wherein, the superscript i is the i-th Monte Carlo simulation; N is the number of Monte Carlo simulations; the subscript j is the j-th demand node in the natural gas pipeline network; M is the total number of demand nodes; is the gas supply obtained by the j-th demand node in the i-th Monte Carlo simulation on the t-th day; D j (t) is the demand of the j-th demand node on the t-th day.

[0068] In some embodiments, the gas consumption demand is determined based on the gas consumption characteristics of users, the fluctuation characteristics of user demands, and the demand prediction model.

[0069] In some embodiments, the demand prediction model includes at least one of the following: time series model, support vector machine model, long short-term memory artificial neural network (LSTM) model.

[0070] In some embodiments, by obtaining user gas consumption behavior data, a demand prediction model is trained based on the user gas consumption behavior data, and then the gas consumption demand of the user is predicted based on the trained demand prediction model.

[0071] In some embodiments, due to the different data processing capabilities of different models, a suitable model is selected according to the volatility index of the user gas consumption behavior.

[0072] Among them, the volatility index of the user gas consumption represents the magnitude of the volatility of the user gas consumption over time and can be calculated based on the gas consumption data of the user.

[0073] Exemplarily, the applicable ranges of the above various demand prediction models are shown in Table 1.

[0074] Table 1

[0075]

[0076]

[0077] In some embodiments, the non-linear influencing factor is a non-linear influencing factor that affects the volatility index.

[0078] Exemplarily, the non-linear influencing factors include climate factors, holiday factors, market economy factors, etc.

[0079] It can be understood that by selecting a suitable model according to the volatility index of the user gas consumption behavior, for users with low volatility, a relatively simple model can be used to meet the requirements, reducing unnecessary computational overhead, while for users with complex requirements, a more powerful model is used to ensure the prediction accuracy, achieving reasonable utilization of resources.

[0080] In some embodiments, as Figure 2 shown, before the above S100, the pipeline reliability evaluation method provided by the present application further includes:

[0081] S400. For each gas transmission unit of the natural gas pipeline network, by using a state transition simulation algorithm, according to the historical failure data, failure rate and repair rate of each gas transmission unit, the operation state data of each gas transmission unit in the target time period is determined.

[0082] Among them, the types of gas transmission units include at least one of the following: gas transmission pipeline segments, compressor stations. Among them, at least one compressor unit is provided in the compressor station.

[0083] In some embodiments, the state transition simulation algorithm obtains the operation state data of the gas transmission unit in the target time period by adopting a two-stage method.

[0084] The first stage: Determine the moment of the transfer of the operating state of the natural gas pipeline network.

[0085] In some embodiments, the state of the unit includes a normal state and a failure state.

[0086] Exemplarily, the operating state of the natural gas pipeline network is expressed by the following formula:

[0087]

[0088] where k(t) represents the state of the natural gas pipeline network at time t, n p is the number of gas transmission pipeline segments in the natural gas pipeline network, k p,i (t) is the state of the i-th gas transmission pipeline segment, k p,i (t) = 1 indicates that the gas transmission pipeline segment is in a normal state, k p,i (t) = 0 indicates that the gas transmission pipeline segment is in a failure state; n c is the number of compressor stations in the natural gas pipeline network, k c,j (t) is the state of the j-th compressor station at time t, k c,j (t) is determined based on the number of compressor units operating normally in the j-th compressor station.

[0089] Then, under the condition that the natural gas pipeline network is in state k at time t, the rate of the next state transfer of the natural gas pipeline network satisfies the following formula:

[0090]

[0091] where λ i (k p,i (t)) is the state transfer rate of the i-th gas transmission unit and satisfies the following formula:

[0092] λ i (k p,i (t)) = k p,i (t) · λ p,i + (1 - k p,i (t)) · μ p,i

[0093] λ p,i is the failure rate of the i-th gas transmission unit, μ p,i is the repair rate of the i-th gas transmission unit; λ j (k c,j (t)) is the state transfer rate of the j-th compressor station and satisfies the following formula:

[0094] λ j (k c,j (t)) = k c,j (t) · λ c + (nc j - kp,i (t))·μ c

[0095] Among them, nc j is the number of compressor units in the j-th compressor station.

[0096] Next, construct a pseudo-random number R between (0-1) 1 , and determine the moment t' of the next state transition of the natural gas pipeline network. The calculation of t' satisfies the following formula:

[0097]

[0098] Second stage: Determine the gas transmission unit where the state transition occurs and the state of the gas transmission unit where the state transition occurs.

[0099] In some embodiments, it is assumed that the natural gas pipeline network includes a total of n p +n c gas transmission units. The first n p (including n p ) gas transmission units are gas pipelines, and the gas transmission units from n p +1 to n p +n c are compressor stations.

[0100] In some embodiments, randomly draw a random number R between (0,1) 2 ,

[0101] When R 2 satisfies the following formula:

[0102]

[0103] , it is determined that the state transition occurs in the gas pipeline;

[0104] When R 2 satisfies the following formula:

[0105]

[0106] , it is determined that the state transition occurs in the compressor station.

[0107] Next, determine the serial number of the gas transmission unit where the state transition occurs.

[0108] In some embodiments, the serial number of the gas pipeline where the state transition occurs is calculated to satisfy the following formula:

[0109]

[0110] Among them, m is the serial number of the gas pipeline where the state transition occurs.

[0111] Among them, it is assumed that the state of the m-th gas pipeline segment at time t is k p,m (t), and the state at time t' is k p,m (t'). Then, when the gas pipeline segment is in the normal state at time t (i.e., k p,m (t) = 1), it will transfer to the failure state next time (i.e., k p,m (t) = 0); when the gas pipeline segment is in the failure state at time t (i.e., k p,n (t') = 0), it will transfer to the normal state next time (i.e., k p,n (t') = 1).

[0112] In some embodiments, the state of the compressor station is based on the number of units operating normally in the compressor station.

[0113] In some embodiments, when it is determined that the gas transmission unit with a state transition is a compressor station, the unit number of the compressor unit with a state transition is further confirmed, and the following formula is calculated:

[0114]

[0115] Among them, m is the unit number of the compressor unit with a state transition.

[0116] In some embodiments, after determining the unit number of the compressor unit with a state transition, a pseudo-random number between (0 - 1) is randomly sampled to determine the state of the compressor station after the state transition.

[0117] Exemplarily, it is assumed that the state of the m-th compressor station after the state transition is k c,m (t'), then k c,m (t') satisfies the following formula:

[0118]

[0119] Furthermore, through the above two-stage state transition simulation algorithm, the state transition time of the natural gas pipeline network, the gas transmission unit with a state transition at this time, and the operating state data of the gas transmission unit after the state transition are determined. Then, the operating state data of the gas transmission unit after the state transition at the state transition time is substituted into the above operating state formula of the natural gas pipeline network, and the operating state data of the natural gas pipeline network after the state transition at the state transition time is obtained.

[0120] In some embodiments, the above state transition simulation is repeated based on the target time period, and finally the operating state data of the natural gas pipeline network in the target time period is obtained.

[0121] It can be understood that the state transition simulation algorithm can effectively improve the accuracy and efficiency of simulation by accurately calculating the state transition moment, flexibly identifying the state transition unit, dynamically updating the state, and repeating the simulation within the target time period, truly reflecting the dynamic changes of the natural gas pipeline network during operation, and providing more accurate data support for evaluating the reliability of the pipeline network.

[0122] In some embodiments, the failure rate and repair rate of the compressor units in the compressor station are determined by collecting the historical failure data of the compressor units and using probability statistics methods.

[0123] In some embodiments, the repair rate of the gas transmission pipeline section is determined by collecting the historical failure data of the gas transmission pipeline section and performing probability statistics methods on the historical failure data.

[0124] In some embodiments, the failure rate of the gas transmission pipeline section is determined based on the load rate of the gas transmission pipeline section and the functional relationship between the load rate and the failure rate of the gas transmission pipeline section. Among them, the functional relationship between the load rate and the failure rate of the pipeline section is used to indicate that the load rate is positively correlated with the failure rate of the pipeline section.

[0125] In some embodiments, the load rate is determined based on the flow rate of the current operating condition of the gas transmission unit and the designed gas transmission volume of the gas transmission unit.

[0126] In some embodiments, taking corrosion failure as the main failure type of the gas transmission pipeline section, the functional relationship between the load rate and the failure rate of the gas transmission pipeline section is determined

[0127] As Figure 3 shown, the process of determining the functional relationship between the load rate and the failure rate of the gas transmission pipeline section is as follows:

[0128] S501. Obtain the basic information of the gas transmission pipeline section.

[0129] In some embodiments, the basic information of the gas transmission pipeline section includes the design pressure, design flow rate, pipeline diameter, pipeline wall thickness, etc. of the gas transmission pipeline section.

[0130] S502. Establish a corrosion defect limit state equation and calculate the failure probability of each corrosion defect.

[0131] In some embodiments, the corrosion limit state equation recommended in the ASME B31G standard is used for modeling.

[0132] Exemplarily, the limit state equation of the corrosion defect satisfies the following formula:

[0133] g = P b -P

[0134] Among them, P b represents the failure pressure, P represents the pipeline operating pressure, and P b satisfies the following formula:

[0135]

[0136] Among them, M is the coefficient of expansion; σ flow is the flow stress, with the unit of MPa; d is the depth of the corrosion defect, with the unit of nm; L is the length of the corrosion defect, with the unit of mm; D is the outer diameter of the pipeline, with the unit of mm; t is the wall thickness of the pipeline, with the unit of mm.

[0137] Among them, the calculation of the coefficient of expansion M satisfies the following formula:

[0138]

[0139] Furthermore, when g > 0, it indicates that the defect is normal; otherwise, the defect fails.

[0140] S503. Determine the failure probability of the corrosion defect based on the load rate of the gas transmission pipeline section.

[0141] Among them, the calculation of the load rate satisfies the following formula:

[0142]

[0143] Among them, Q d is the designed gas transmission volume of the gas transmission pipeline section, and Q is the actual gas transmission volume of the gas transmission pipeline section.

[0144] In some embodiments, in order to consider the influence of the load rate on the failure probability, for each gas transmission pipeline section, assuming that its end pressure is the lowest pressure of 3 MPa, and the pipeline gas transmission volume takes 500,000 m³ / day as the step, calculate the compliance rate from zero gas transmission volume to the designed gas transmission volume, and calculate the starting pressure of the gas transmission pipeline section at different gas transmission volumes (i.e., different load rates) through the Weymouth formula. Then, take the starting pressure of the gas transmission pipeline section at different gas transmission volumes (i.e., different load rates) as the input parameter P in the above limit state equation, so as to obtain the failure probability of each corrosion defect under different load rate conditions.

[0145] S504. Determine the reliability of the gas transmission pipeline section based on the failure probability of the corrosion defect.

[0146] In some embodiments, the reliability of the corrosion defect satisfies the following formula:

[0147]

[0148] Among them, is the failure probability of the nth corrosion defect, is the reliability of the nth corrosion defect.

[0149] In some embodiments, based on the load factor in S503, for the N corrosion defects existing in a single gas pipeline segment under each load factor condition, the first-order second-moment method is used for solution to calculate the reliability of each corrosion defect of the gas pipeline segment.

[0150] In some embodiments, it is assumed that the correlation of the corrosion defects of the gas pipeline segment is 1, that is, the reliability of the gas pipeline segment is equal to the minimum value of the reliabilities of all corrosion defects. The reliability of the gas transmission unit satisfies the following formula:

[0151]

[0152] Wherein, represents the reliability of the nth corrosion defect of the gas pipeline segment, represents the reliability of the gas pipeline segment only considering the corrosion defects.

[0153] In some implementations, according to historical data statistics, corrosion failures account for two-thirds of the total failure types. Therefore, the reliability R of the gas pipeline segment can be obtained pipeline satisfies the following formula:

[0154]

[0155] S505. Determine the functional relationship between the failure rate and the load factor of the gas pipeline segment.

[0156] In some embodiments, by looping through steps S501 - S504, a corresponding relationship between a set of load factors of a single gas pipeline segment and the reliability of the gas pipeline segment is obtained. This corresponding relationship is expressed as the following formula:

[0157]

[0158] Wherein, r is the load factor, r 0 = 0%, r M = 100%.

[0159] Furthermore, according to the relationship formula between the reliability of the gas transmission unit and the failure rate, the failure rate of the gas transmission unit under each load factor is determined.

[0160] The relationship between the reliability of the gas transmission unit and the failure rate of the gas transmission unit satisfies the following formula:

[0161] R = e -λt

[0162] Wherein, R represents the reliability of the gas pipeline segment; λ represents the failure rate of the gas pipeline segment, with the unit of 1 / year; t represents time, with the unit of year.

[0163] Based on the relationship formula between the reliability of the gas transmission unit and the failure rate of the gas transmission unit, a corresponding relationship between a set of load factors of the gas transmission unit and the failure rate of the gas transmission unit is obtained. This corresponding relationship is expressed as the following formula:

[0164]

[0165] Next, based on the data of the corresponding relationship between the load rate of the above gas transmission unit and the failure rate of the gas transmission unit, exponential function fitting is performed to obtain the functional relationship between the failure rate and the load rate of the gas pipeline section.

[0166] Exemplarily, the process of determining the functional relationship between the failure rate and the load rate of all gas pipeline sections in the natural gas pipeline network is introduced below through a complete embodiment. As Figure 4 shown, first, the gas pipeline sections are divided according to the compressor stations in the natural gas pipeline network (the number of false pipeline sections is Z). Then, all gas pipeline sections are assigned labels (the label is represented by i, and the initial label i = 1). Then, parameters such as the end pressure, design flow rate, pipeline diameter, pipeline wall thickness, etc. of the gas pipeline section with label i = 1 are input, as well as corrosion parameters such as the number of corrosion defects, depth, length, growth rate, etc. of this gas pipeline section. Then, with M load rate numbers and the initial load rate label j = 1, enter the loop. The loop process includes: input the end pressure, obtain the flow rate according to the load rate, and calculate the starting pressure by the Weymouth formula. Then, with the number of corrosion defects being N and the initial corrosion defect label k = 1, enter the loop. Substitute the data of each corrosion defect of this gas pipeline section into the corrosion limit state equation, calculate the failure probability of each defect, obtain the reliability of each corrosion defect, then take the minimum value of the reliabilities of all corrosion defects, and calculate the reliability of this gas pipeline section according to the formula. After completing the calculation of the reliabilities of the gas pipeline sections for all M load rates, obtain the failure rate of the gas pipeline section according to the relationship formula between reliability and failure rate, and obtain the functional relationship between the load rate and the failure rate of the gas pipeline section through fitting. Finally, for all a total of Z gas pipeline sections, determine the functional relationships between the load rates and the failure rates of all Z gas pipeline sections according to the above process.

[0167] In some embodiments, by performing the above steps S501 - S505 for each gas pipeline section, the functional relationship between the failure rate and the load rate of each gas pipeline section can be obtained.

[0168] In some embodiments, based on the functional relationship between the failure rate and the load rate of each gas pipeline section and the load rate of each gas pipeline section, the failure rate of each gas pipeline section is calculated.

[0169] Exemplarily, the failure rate of the gas pipeline section can be expressed as λ p,i , and the repair rate of the gas pipeline section can be expressed as μ p,i , where i represents the i-th gas pipeline section.

[0170] The specific implementation manner of calculating the actual gas supply volume of the natural gas pipeline network within the target time period based on the directed weighted graph is introduced below.

[0171] Exemplarily, the directed weighted graph of the natural gas pipeline network can be expressed as:

[0172] G = (V, E)

[0173] where V represents the set of all nodes, and E represents the set of all gas transmission units.

[0174] In some embodiments, in the set of all nodes V, the node set is further split into: an uploading node set, a compressor station node set, a transfer supply node set, and a downloading node set. The descriptions of various types of nodes are shown in Table 2 below.

[0175] Table 2

[0176]

[0177] In some embodiments, since the compressor station nodes are involved in gas boosting, in the directed weighted graph representing the natural gas pipeline network system, the compressor stations are set as two nodes, that is, one compressor station has two nodes, and the two nodes of the compressor station are connected by a virtual pipeline.

[0178] In some embodiments, using the directed weighted graph of the natural gas pipeline network, based on the operation status data of the natural gas pipeline network in the target time period, the actual gas supply volume of the natural gas pipeline network in the target time period is calculated by combining the genetic algorithm, the particle swarm algorithm, the branch and bound method, and the interior point method.

[0179] In some embodiments, the maximum gas supply volume supplied by the natural gas pipeline network to each downloading node in the target time period is used as the actual gas supply volume of the natural gas pipeline network in the target time period.

[0180] Exemplarily, the objective function for calculating the maximum gas supply volume supplied by the natural gas pipeline network to each downloading node in the target time period satisfies the following formula:

[0181]

[0182] where T is the target time period, with the unit of day; t is the moment, with the unit of day; U is the set of downloading nodes; S i (t) represents the gas volume supplied to downloading node i at moment t, with the unit of Nm 3 / day.

[0183] In some embodiments, the constraint conditions satisfied by the calculation based on the directed weighted graph include: flow constraint, pressure constraint, pipeline hydraulic constraint, and pipeline storage constraint.

[0184] The following provides a detailed introduction to various types of constraint conditions.

[0185] 1. Flow constraint.

[0186] In a natural gas pipeline network, for any node, the sum of the gas flow rates flowing into the node is equal to the sum of the flow rates flowing out of the node.

[0187] Exemplarily, the flow rate constraint condition satisfies the following formula:

[0188]

[0189] Wherein, represents the flow rate from node i to j at time t, with the unit of Nm 3 / day; represents the flow rate from node j to l at time t, with the unit of Nm 3 / day.

[0190] In some embodiments, for an upload node, there is only the gas flow rate flowing out of the node. Therefore, for any upload node, the flow rate constraint condition satisfies the following formula:

[0191]

[0192] Wherein, (s, j) represents the pipeline from upload node s to node j, represents the inflow rate of the pipeline from upload node s to node j at time t, with the unit of Nm 3 / day; S s (t) is the supply capacity of upload node s, with the unit of Nm 3 / day.

[0193] In some embodiments, for a download node, there is only the gas flow rate flowing into the node. Therefore, for any demand node, the flow rate constraint condition satisfies the following formula:

[0194]

[0195] Wherein, (j, d) is the pipeline from node j to download node d, represents the outflow rate of the pipeline from node j to download node d at time t, with the unit of Nm 3 / day; S d (t) is the gas supply obtained by the d-th download node on the t-th day, with the unit of Nm 3 / day.

[0196] In some embodiments, for a gas pipeline section, assuming that all gas pipeline sections have bidirectional transportation capabilities, at a certain moment, a single gas pipeline section only has one gas flow direction, that is:

[0197]

[0198]

[0199] Among them, F (i,j) (t) and F (j,i) (t) respectively represent the 0-1 type auxiliary decision variables with positive and negative flow directions of the natural gas pipeline network with the control start node as i and the end node as j at time t.

[0200] In some embodiments, since the gas transmission flow of the natural gas pipeline network is restricted by the designed throughput of the pipeline, the flow constraint condition satisfies the following formula:

[0201]

[0202] Among them, represents the designed throughput of pipeline (i,j), with the unit of Nm 3 / day.

[0203] In some embodiments, when the pipeline between node i and node j fails, When a compressor unit fails at a compressor station, the pipeline transportation capacity between the two nodes of the compressor station decreases, and simulation software can be used for measurement.

[0204] 2. Pressure constraint.

[0205] In some embodiments, except for the compressor station nodes where there are two pressures before and after gas pressurization, each of the other nodes has only one pressure.

[0206] Therefore, for non-compressor station nodes, their node pressures need to satisfy the following formula:

[0207]

[0208] Among them, P i (t) represents the pressure of node i at time t, with the unit of MPa; represents the lowest set pressure of node i, with the unit of MPa; represents the highest set pressure of node i, with the unit of MPa.

[0209] For compressor station nodes, two nodes can be used to represent, and the two nodes are connected by a virtual pipeline (i,j). Assuming that for the c-th compressor station, its two nodes before and after are respectively represented as and Then the pressure constraint condition satisfies the following formula:

[0210]

[0211] Among them, P c,lower and P c,upper are respectively the upstream inlet pressure limit and downstream outlet pressure limit of the c-th compressor station, with the unit of MPa, ε cThe station pressure ratio of the compressor station at time t is (t).

[0212] 3. Pipeline hydraulic constraint.

[0213] In some embodiments, considering the pressures at both ends of the gas transmission pipeline and the flow rate of the pipeline section, the pipeline hydraulic constraint is determined based on the Weymouth formula, and the constraint conditions are as follows:

[0214]

[0215] where f is the hydraulic friction coefficient; Z is the compressibility factor; Δ* is the relative density; T is the pipeline transportation temperature, in K; L is the length of the pipeline between node i and node j, in km; D is the inner diameter of the pipeline, in m; C 0 is a constant; Q (i,j) represents the average value of the inlet and outlet flow rates, in Nm 3 / day.

[0216] 4. Pipeline inventory constraint.

[0217] In some embodiments, the pipeline inventory constraint includes the upper and lower limits of the pipeline inventory and the initial pipeline inventory constraint.

[0218] The pipeline inventory constraint satisfies the following formula:

[0219]

[0220] where G (i,j) (t) is the pipeline inventory between node i and node j at time t, in Nm 3 ; and are respectively the upper and lower limits of the pipeline inventory between node i and node j, in Nm 3 .

[0221] In some embodiments, the pipeline inventory at the current moment is equal to the pipeline inventory at the previous moment and is related to the pipeline inflow and outflow flow rates at the previous moment. The specific constraint conditions satisfy the following formula:

[0222]

[0223] It can be understood that the present application proposes a method for evaluating the reliability of a natural gas pipeline network. First, the operation state data of each unit in the natural gas pipeline network during the target time period is determined through a state transition simulation algorithm, including the operation state, occurrence time, and duration, so as to determine the operation state data of the entire natural gas pipeline network. Then, a gas supply calculation model that uses decision parameters such as pipeline flow rate, node pressure, and pipeline inventory, and takes flow rate constraints, pressure constraints, pipeline hydraulic constraints, and pipeline inventory constraints as constraint conditions, is combined with the operation state data to calculate the actual gas supply of the natural gas pipeline network during the target time period. Finally, through the Monte Carlo simulation algorithm, the gas demand of users during the target time period is compared with the actual gas supply of the pipeline to determine the gas supply reliability of the natural gas pipeline network. It can optimize the acquisition of pipeline operation state data and the accuracy of reliability evaluation.

[0224] It can be seen that the above mainly introduces the solution provided by the embodiments of the present application from the perspective of the method. To implement the above functions, the embodiments of the present application provide the corresponding hardware structure and / or software module for executing each function. Those skilled in the art should easily realize that, combining the modules and algorithm steps of each example described in the embodiments disclosed herein, the embodiments of the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraint conditions of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0225] The embodiments of the present application can divide the function modules of the reliability evaluation device for the pipeline according to the above method examples. For example, each function module can be divided corresponding to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of a software function module. Optionally, the division of modules in the embodiments of the present application is illustrative, and is only a logical function division. There can be other division methods in actual implementation.

[0226] Figure 5 It is a schematic structural diagram of a reliability evaluation device for a natural gas pipeline network provided by an embodiment of the present application, which can implement the reliability evaluation method for the natural gas pipeline network provided by the above method embodiment. As Figure 5 shown, the reliability evaluation device 600 for the natural gas pipeline network includes: an analysis module 601.

[0227] The analysis module 601 is configured to determine the operation state data of the natural gas pipeline network during the target time period based on the operation state data of each gas transmission unit in the natural gas pipeline network during the target time period;

[0228] The analysis module 601 is further configured to determine the actual gas supply volume of the natural gas pipeline network during the target time period based on the gas supply volume calculation model and the operation status data of the natural gas pipeline network during the target time period; the decision parameters in the gas supply volume calculation model include pipeline flow rate, node pressure, and pipeline inventory; the constraint conditions of the gas supply volume calculation model include at least one of the following: flow constraint, pressure constraint, pipeline network hydraulic constraint, and pipeline network inventory constraint;

[0229] The analysis module 601 is further configured to determine the gas supply reliability of the natural gas pipeline network based on the gas consumption demand of the user during the target time period and the actual gas supply volume of the natural gas pipeline network during the target time period.

[0230] A possible implementation manner is that the operation status data of each gas transmission unit in the natural gas pipeline network during the target time period includes: the operation status that appears in each pipeline during the target time period, the moment when each operation status appears, and the duration of each operation status; the operation status data of the natural gas pipeline network during the target time period includes: all operation statuses that appear in the natural gas pipeline network during the target time period, the moment when each operation status appears, and the duration of each operation status.

[0231] A possible implementation manner is that the natural gas pipeline network includes multiple gas transmission units. Before determining the operation status data of the natural gas pipeline network during the target time period based on the operation status data of each gas transmission unit in the natural gas pipeline network during the target time period, the analysis module 601 is further configured to, for each gas transmission unit of the natural gas pipeline network, use the state transition simulation algorithm to determine the operation status data of each gas transmission unit during the target time period according to the historical failure data, failure rate, and repair rate of each gas transmission unit.

[0232] A possible implementation manner is that the failure rate of the gas transmission unit is determined based on the load rate of the gas transmission unit and the functional relationship between the load rate and the pipe section failure rate; the functional relationship between the load rate and the pipe section failure rate is used to indicate that the load rate is positively correlated with the pipe section failure rate; wherein, the load rate is determined based on the flow rate of the current working condition of the gas transmission unit and the designed gas transmission volume of the gas transmission unit.

[0233] A possible implementation manner is that the types of gas transmission units include at least one of the following: gas transmission pipeline section, compressor station; the compressor station is provided with a compressor unit.

[0234] A possible implementation manner is that the analysis module 601 is specifically configured to use the Monte Carlo simulation algorithm to calculate the reliability index of the natural gas pipeline network based on the gas consumption demand of the user during the target time period and the actual gas supply volume of the natural gas pipeline network during the target time period, and the reliability index is used to reflect the gas supply reliability of the natural gas pipeline network.

[0235] A possible implementation, the gas supply reliability of the natural gas pipeline network includes at least one of the following: the gas supply reliability of the entire natural gas pipeline network, and the gas supply reliability of the user demand nodes in the natural gas pipeline network.

[0236] In the case where the functions of the above integrated module are implemented in the form of hardware, an embodiment of the present invention provides a possible structural schematic diagram of the electronic device involved in the above embodiment. As Figure 6 shown, the electronic device 900 includes: a processor 902, a communication interface 903, and a bus 904. Optionally, the electronic device 900 may further include a memory 901.

[0237] The processor 902 can be used to implement or execute various exemplary logical blocks, modules, and circuits described in connection with the disclosure of the present application. The processor 902 can be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field-programmable gate array, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logical blocks, modules, and circuits described in connection with the disclosure of the present application. The processor 902 can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0238] The communication interface 903 is used to connect to other devices through a communication network. The communication network can be an Ethernet, a wireless access network, a wireless local area network (WLAN), etc.

[0239] The memory 901 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM), or other types of dynamic storage devices that can store information and instructions. It can also be an electrically erasable programmable read-only memory (EEPROM), a magnetic disk storage medium, or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0240] As a possible implementation, the memory 901 can exist independently of the processor 902. The memory 901 can be connected to the processor 902 through a bus 904 and is used to store instructions or program codes. When the processor 902 calls and executes the instructions or program codes stored in the memory 901, the reliability evaluation method for the natural gas pipeline network provided by the embodiments of the present invention can be implemented.

[0241] In another possible implementation, the memory 901 can also be integrated with the processor 902.

[0242] The bus 904 can be an extended industry standard architecture (EISA) bus or the like. The bus 904 can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 6 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0243] Through the description of the above embodiments, those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above division of each functional module is used as an example. In actual applications, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the service call device is divided into different functional modules to complete all or part of the functions described above.

[0244] The embodiments of the present application also provide a computer-readable storage medium. All or part of the processes in the above method embodiments can be instructed by computer program instructions to be completed by relevant hardware. The program can be stored in the above computer-readable storage medium. When the computer program instructions are executed on the computer, the computer is enabled to execute the reliability evaluation method for the natural gas pipeline network as described in any one of the above embodiments.

[0245] Exemplarily, the above computer-readable storage medium can include, but is not limited to: magnetic storage devices (such as hard disks, floppy disks or magnetic tapes, etc.), optical discs (such as compact discs (CDs), digital versatile discs (DVDs), etc.), smart cards and flash memory devices (such as erasable programmable read-only memories (EPROMs), cards, sticks or key drives, etc.). The various computer-readable storage media described in the present disclosure can represent one or more devices and / or other machine-readable storage media for storing information. The term "machine-readable storage medium" can include, but is not limited to, wireless channels and various other media that can store, contain, and / or carry instructions and / or data.

[0246] An embodiment of the present application also provides a computer program product. The computer program product includes a computer program. When the computer program product runs on a computer, it causes the computer to execute any one of the reliability evaluation methods for natural gas pipe networks provided in the above embodiments.

[0247] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A reliability evaluation method for a natural gas pipeline network, characterized in that: The method comprises: Determining the operating status data of the natural gas pipeline network in the target time period based on the operating status data of each gas transmission unit in the natural gas pipeline network in the target time period; Based on the gas supply volume calculation model and the operation status data of the natural gas pipeline network in the target time period, the actual gas supply volume of the natural gas pipeline network in the target time period is determined; the decision parameters in the gas supply volume calculation model include pipeline flow, node pressure and pipeline storage; the constraint conditions of the gas supply volume calculation model include at least one of the following: flow constraint, pressure constraint, pipeline network hydraulic constraint, pipeline network storage constraint; The gas supply reliability of the natural gas pipeline network is determined based on the gas demand of the user within the target time period and the actual gas supply of the natural gas pipeline network within the target time period.

2. The method according to claim 1, characterized in that The operating status data of each gas transmission unit in the natural gas pipeline network during the target time period includes: the operating status of each gas transmission unit during the target time period, the time when each operating status occurs, and the duration of each operating status; the operating status data of the natural gas pipeline network during the target time period includes: all operating statuses of the natural gas pipeline network during the target time period, the time when each operating status occurs, and the duration of each operating status.

3. The method according to claim 1, characterized in that The natural gas pipeline network includes a plurality of gas transmission units. Before determining the operating status data of the natural gas pipeline network in the target time period based on the operating status data of each gas transmission unit in the natural gas pipeline network in the target time period, the method further includes: For each gas transmission unit of the natural gas pipeline network, a state transition simulation algorithm is used to determine the operating state data of each gas transmission unit in the target time period according to the historical failure data, failure rate and maintenance rate of each gas transmission unit.

4. The method according to claim 3, characterized in that The failure rate of the gas transmission unit is determined based on the load rate of the gas transmission unit and the functional relationship between the load rate and the failure rate of the pipe section; The functional relationship between the load rate and the pipe section failure rate is used to indicate that the load rate is positively correlated with the pipe section failure rate; wherein the load rate is determined based on the flow rate of the current operating condition of the gas transmission unit and the designed transmission capacity of the gas transmission unit.

5. The method according to claim 1, characterized in that: The types of the gas transmission unit include at least one of the following: a gas transmission pipeline section, a gas compression station; the gas compression station is provided with a compressor unit.

6. The method according to claim 1, characterized in that The determining of the gas supply reliability of the natural gas pipeline network based on the gas demand of the user within the target time period and the actual gas supply of the natural gas pipeline network within the target time period includes: A Monte Carlo simulation algorithm is used to calculate the reliability index of the natural gas pipeline network based on the gas demand of the user during the target time period and the actual gas supply of the natural gas pipeline network during the target time period. The reliability index is used to reflect the gas supply reliability of the natural gas pipeline network.

7. The method according to claim 1, characterized in that The gas supply reliability of the natural gas pipeline network includes at least one of the following: The gas supply reliability of the entire natural gas pipeline network and the gas supply reliability of user demand nodes in the natural gas pipeline network.

8. The method according to claim 1, characterized in that: The gas demand is determined based on the user's gas usage characteristics, the fluctuation characteristics of the user's demand and a demand forecasting model; wherein the demand forecasting model includes at least one of the following: a time series model, a support vector machine model, and a long short-term memory artificial neural network LSTM model.

9. An electronic device, characterized in that: It comprises a processor and a memory, wherein the processor is coupled to the memory; the memory is used to store computer instructions, and the computer instructions are loaded and executed by the processor to enable the computer device to implement the reliability evaluation method of the natural gas pipeline network as described in any one of claims 1 to 8.

10. A computer storage medium, characterized in that: The computer storage medium includes computer execution instructions, and when the computer execution instructions are executed on a computer, the computer executes the reliability evaluation method for a natural gas pipeline network according to any one of claims 1 to 8.

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