Natural gas pipeline network multi-cycle supply and demand balance scheduling optimization method coupled with gas storage injection-production characteristics

Abstract

The invention provides a natural gas pipeline network multi-cycle supply and demand balance scheduling optimization method coupled with gas storage injection-production characteristics, which comprises the following steps: acquiring basic data of a target pipeline network, and establishing a natural gas pipeline network multi-cycle supply and demand balance scheduling optimization model target function coupled with the gas storage injection-production characteristics; constructing constraint conditions of the multi-cycle supply and demand balance scheduling optimization model of the natural gas pipeline network coupled with the injection-production characteristics of the gas storage; and solving the natural gas pipeline network multi-cycle supply and demand balance scheduling optimization model considering the injection-production characteristics of the coupled gas storage, and generating a pipeline network scheduling scheme and a gas storage injection-production scheme. The gas storage injection and production characteristics are coupled, the multi-cycle supply and demand balance optimization method for the natural gas pipeline network is provided, the comprehensive scheduling process of the natural gas pipeline network system containing the gas storage is fully researched by combining multi-cycle supply and demand fluctuation and gas storage injection and production peak regulation, and the operation cost of the gas storage system can be greatly reduced under the target of guaranteeing supply and demand balance; and the feasibility and economy of natural gas transportation and storage links are enhanced.

Description

Technical Field

[0001] The present invention relates to the field of gas storage ground pipeline layout optimization, and in particular to a natural gas pipeline network multi-period supply and demand balance scheduling optimization method coupled with gas storage injection and production characteristics. Background Art

[0002] From a global perspective, addressing climate change and promoting sustainable development have become urgent tasks. As a widely recognized high-clean energy source, natural gas will account for an increasing proportion in the energy structure. It is estimated that the annual natural gas consumption will reach about 375 billion cubic meters, accounting for 9% of the total primary energy consumption. With the growth of natural gas consumption, this trend makes the scientific and effective use of natural gas resources a core element in maintaining energy security.

[0003] In order to cope with the rising demand, pipelines, as the key link between gas sources and markets, have become the most economical way to achieve large-scale, long-distance transportation of natural gas. Gas storage, as an important peak-shaving facility in the pipeline network, can greatly improve the supply flexibility of the pipeline network and ensure the balance between supply and demand by injecting gas during low-demand periods and extracting gas during high-demand periods.

[0004] Gas storage injection and production peak regulation is a complex control process involving multiple cycles and multiple facilities. At present, there are problems in the optimization research of the natural gas pipeline network system of the gas storage, such as imperfect gas storage modeling and in-depth carbon emission optimization analysis, which makes it difficult to meet the actual requirements of the economic and low-carbon operation management of the gas storage. Therefore, it is necessary to finely model the gas storage system and optimize the comprehensive scheduling process of the natural gas pipeline network system containing the gas storage, so as to achieve the optimal operation state of the pipeline network and the gas storage. Summary of the invention

[0005] Based on the overall optimization strategy, the present invention proposes a multi-period supply and demand balance scheduling optimization method for the natural gas pipeline network coupled with the injection and production characteristics of the gas storage. By combining the multi-period supply and demand fluctuations and the injection and production peak regulation of the gas storage, the comprehensive scheduling process of the natural gas pipeline system containing the gas storage is fully studied. Under the goal of ensuring the supply and demand balance, the operating cost of the gas storage system can be greatly reduced, and the feasibility and economy of the natural gas transportation and storage links can be enhanced.

[0006] The present invention provides a multi-period supply and demand balance scheduling optimization method for a natural gas pipeline network coupled with the injection and production characteristics of a gas storage reservoir, the method comprising:

[0007] S1: Obtain the basic data of the target natural gas pipeline network;

[0008] S2: Establish the objective function of the multi-period supply and demand balance scheduling optimization model of the natural gas pipeline network coupled with the injection and production characteristics of the gas storage;

[0009] S3: Generate model constraints, and combine the objective function to establish a multi-period supply and demand balance scheduling optimization model for the natural gas pipeline network coupled with the injection and production characteristics of the gas storage, and solve and generate the pipeline network scheduling plan and the gas storage injection and production plan.

[0010] Furthermore, the basic data described in step S1 include gas source and user data, pipeline network parameters, gas storage reservoir parameters, system operation costs, pipeline network scheduling plan, and gas storage reservoir injection and production plan.

[0011] Furthermore, the objective function described in step S2 is to minimize the economic and environmental costs of the natural gas pipeline network system of the gas storage, which is composed of pipeline transportation cost, gas storage cost, gas storage injection and production cost, carbon emission cost and natural gas shortage penalty cost, and the relationship is:

[0012] minf=f tran +f storage +f injwit +f carb +f pena

[0013] Where, f is the total cost of the pipe network system operation; f tran is the pipeline transportation cost; f storage is the storage cost of gas storage; f injwit is the injection and production cost of gas storage; carb is the carbon emission cost; f pena Penalty costs for lack of gas;

[0014] The pipeline transportation cost is the cost of natural gas occupying the pipeline capacity resources when flowing in the pipeline network, and the relationship is:

[0015] f tran =t T(i,j)A p C tran q ij,t L ij

[0016] In the formula, C tran is the unit transportation cost coefficient; q ij,t is the pipeline flow rate; L ij is the length of the pipeline;

[0017] The storage cost of a gas storage facility refers to the cost incurred when natural gas is stored in the gas storage facility and occupies the storage space. The relationship is:

[0018]

[0019] In the formula, C storage is the unit gas storage cost coefficient; is the gas storage capacity of the gas storage facility;

[0020] The injection and production cost of a gas storage facility refers to the cost of using the mechanical equipment of the gas storage facility during the injection or production of natural gas. The relationship is:

[0021]

[0022] In the formula, C inj is the unit gas injection cost coefficient; C wit is the unit gas production cost coefficient; The gas injection flow rate for the gas storage; Gas flow rate for gas storage;

[0023] The carbon emission cost can be calculated from the unit carbon tax price, the carbon emission intensity coefficient of electricity and the equipment power. The relationship is:

[0024]

[0025] In the formula, C car is the unit carbon tax price; e car is the carbon emission intensity coefficient of electricity; The power consumption of the compressor station of the pipeline network; The power consumption of the gas storage compressor station;

[0026] In order to fully meet the natural gas demand of users and avoid insufficient supply, a virtual natural gas shortage penalty cost is considered, and the relationship is:

[0027]

[0028] In the formula, C pena Penalty cost factor for lack of gas; Flow required by users; i,t Actual output traffic for users.

[0029] Furthermore, the constraints described in step S3 include: node constraints, pipeline constraints, compressor station constraints, and gas storage constraints;

[0030] The node constraints are:

[0031]

[0032] In the formula, s i,t is the gas source input flow; d i,t Output traffic for users; Input flow rate for gas collection at gas storage; is the gas injection output flow of the gas storage; p i,t is the node pressure;

[0033] The pipeline constraints are:

[0034]

[0035] In the formula, q ij is the pipeline flow rate; p i is the starting pressure of the pipeline; p j is the pipeline end point pressure; is a binary variable for the pipeline forward flow; is a binary variable for pipeline reverse flow; M is the maximum value; is the pipeline flow resistance coefficient; D ij is the pipe diameter; ij is the pipeline friction coefficient;

[0036] The pipeline flow direction variable must satisfy the flow direction uniqueness constraint, and the relationship is:

[0037]

[0038] The pipeline flow rate should meet the minimum and maximum gas transmission capacity restrictions, and the relationship is:

[0039]

[0040] The friction coefficient λ is one of the important parameters for gas flow calculation. It is related to factors such as the natural gas flow state and the roughness of the pipeline. The friction coefficient can be accurately calculated using the Colebrook formula. The relationship is:

[0041]

[0042] In the formula, τ is the equivalent roughness of the tube wall; Re is the Reynolds number;

[0043] In the compressor constraint, only one device can be opened at the same time, the compressor unit and the bypass valve, and the relationship is:

[0044]

[0045] In the formula, is the binary variable of the compressor unit switch state; is the bypass valve switch state binary variable; is the binary variable of the overall switch status of the compressor station;

[0046] When natural gas flows through the bypass valve, the pressures at the upstream and downstream nodes of the compressor station are equal, and the relationship is:

[0047]

[0048] When natural gas is pressurized by the compressor unit, the upstream node pressure is related to the compressor inlet pressure, and the downstream node pressure is related to the compressor exhaust pressure. The relationship is:

[0049]

[0050]

[0051] In the formula, is the compressor inlet pressure; is the compressor exhaust pressure;

[0052] The compressor intake and exhaust pressures should meet the maximum and minimum boost pressure ratio constraints of the compressor, and the relationship is:

[0053]

[0054] The pressure head indicates the energy provided by the compressor to pressurize a unit mass of natural gas. The relationship is:

[0055]

[0056] In the formula, ΔH ij,t is the compressor pressure head; m is the natural gas expansion index;

[0057] According to the compressor head, combined with the compressor station flow, the power consumption of the pipeline network compressor station can be calculated, and the relationship is:

[0058]

[0059] In the formula, The power consumption of the compressor station; is the compressor efficiency;

[0060] The power consumption of the compressor station in the pipeline network should meet the minimum and maximum power constraints, and the relationship is:

[0061]

[0062] The compressor determines the feasible operating range of the equipment through the so-called characteristic map, which is a nonlinear bounded non-convex set that defines the feasible combinations of compressor speed, flow and pressure head. The relationship is:

[0063]

[0064] In the formula, ω ij,t is the compressor speed; is the flow rate of a single compressor; Θ ij is the non-convex feasible domain of the compressor;

[0065] The gas storage constraints include gas storage operation constraints, gas storage flow constraints, gas storage inventory constraints, and injection and production well constraints:

[0066] The gas storage operation constraints are:

[0067]

[0068] In the formula, is a binary variable of gas storage injection status; is a binary variable of gas storage gas extraction status;

[0069] The gas storage flow constraint is:

[0070]

[0071] During the injection and production process of the gas storage, the inventory will decrease according to the injection flow rate, or increase according to the production flow rate. The relationship is:

[0072]

[0073] In the formula, G u,t For gas storage inventory; dur t is the cycle duration;

[0074] The gas storage inventory constraint is:

[0075]

[0076] The function of the bottom gas is to maintain the working pressure of the gas storage reservoir and cannot be extracted at will. Therefore, the actual gas storage volume of the gas storage reservoir should be equal to the inventory minus the bottom gas volume. The relationship is:

[0077]

[0078] The injection and production well constraints are:

[0079]

[0080] Where n u,t Number of wells opened for gas storage; is the gas injection flow rate of a single well; is the gas production flow rate of a single well;

[0081] The number of wells opened in the gas storage reservoir should meet the minimum and maximum number of wells opened, and the relationship is:

[0082]

[0083] The gas injection flow or gas production flow of a single well should meet the minimum and maximum flow constraints, and the relationship is:

[0084]

[0085] As the inventory increases or decreases, the gas reservoir pressure of the gas storage will rise or fall. The relationship between the inventory and the gas reservoir pressure can be established through the gas reservoir material balance equation to determine the gas reservoir pressure in each period. The relationship is:

[0086]

[0087] In the formula, is the gas reservoir pressure of the gas storage;

[0088] When natural gas flows from the bottom of the well to the gas reservoir, it needs to overcome the formation resistance by seepage. The relationship is:

[0089]

[0090] In the formula, is the bottom hole pressure of the gas storage reservoir; is the gas reservoir laminar flow coefficient; is the gas reservoir turbulence coefficient;

[0091] When natural gas flows from the wellhead to the bottom of the well, it needs to overcome the friction resistance of the injection and production wells. The relationship is:

[0092]

[0093]

[0094] In the formula, is the wellhead pressure of the gas storage reservoir; is the flow resistance coefficient of the injection-production well.

[0095] Furthermore, the multi-period supply and demand balance scheduling optimization model of the natural gas pipeline network coupled with the injection and production characteristics of the gas storage described in step S3 adopts two methods of hierarchical solution and overall solution when solving the model:

[0096] The specific steps of the hierarchical solution strategy are as follows:

[0097] (1) Simplify the gas storage into a pipeline network node with natural gas inflow and outflow, and combine the injection and production flow boundary and gas storage volume boundary of the gas storage to form a pipeline network scheduling optimization model considering the simple gas storage node. Input the multi-cycle gas source supply and user demand data of the pipeline network, and solve the mathematical model to obtain the pipeline network scheduling plan, as well as the gas storage injection and production state variables, injection and production flow variables and connecting pipeline pressure variables; fix the above gas storage variables and input them into the next level model as the associated variables between models;

[0098] (2) Taking into account the hydraulic characteristics of the underground gas reservoir and injection and production wells of the gas storage, as well as the pressure regulation function characteristics of the ground compressor station, a gas storage injection and production optimization model that takes into account the characteristics of the ground and underground facilities is formed; based on the injection and production status, injection and production flow rate, and connecting pipeline pressure variables fixed by the first-level model, the second-level gas storage injection and production optimization model is solved to determine the optimal number of wells opened in the gas storage, injection and production well flow rate, underground gas reservoir and injection and production well pressure, and ground facility operating parameters in each time period, and obtain a detailed gas storage injection and production plan;

[0099] (3) Based on the pipeline network dispatching plan obtained by the first level solution and the gas storage reservoir injection and production plan obtained by the second level solution, the various operating costs of the system are clarified to form a complete pipeline network supply and demand balance optimization result;

[0100] The specific steps of the overall solution strategy are as follows:

[0101] (1) The pipeline network scheduling optimization model and the gas storage injection and production optimization model are directly coupled. Based on the multi-cycle supply and demand data of the pipeline network, the operating costs and constraint characteristics of the pipeline network and the gas storage are considered at the same time, and the overall optimization result of the pipeline network supply and demand balance is solved to achieve global optimization of the pipeline network scheduling plan and the gas storage injection and production plan.

[0102] (2) Based on the gas storage injection and production plan obtained by the overall solution, the operating costs of the system are clarified to form a complete pipeline network supply and demand balance optimization result.

[0103] Furthermore, the pipeline network optimization plan described in step S3 includes system operation cost, pipeline network scheduling plan and gas storage injection and production plan.

[0104] The pipeline network scheduling scheme is a management and optimization strategy for natural gas flowing in the pipeline network; the gas storage injection and production scheme is a strategy for injecting natural gas into the gas storage or extracting natural gas from the gas storage.

[0105] The present invention provides a method for optimizing multi-period supply and demand balance scheduling of a natural gas pipeline network coupled with the injection and production characteristics of a gas storage reservoir, the method comprising: obtaining basic data of a target pipeline network, establishing an objective function of a multi-period supply and demand balance scheduling optimization model of a natural gas pipeline network coupled with the injection and production characteristics of a gas storage reservoir; constructing constraint conditions of a multi-period supply and demand balance scheduling optimization model of a natural gas pipeline network coupled with the injection and production characteristics of a gas storage reservoir; solving a multi-period supply and demand balance scheduling optimization model of a natural gas pipeline network considering the injection and production characteristics of a coupled gas storage reservoir, and generating a pipeline network scheduling plan and a gas storage reservoir injection and production plan. The present invention couples the injection and production characteristics of a gas storage reservoir, proposes a method for optimizing multi-period supply and demand balance of a natural gas pipeline network, combines multi-period supply and demand fluctuations with injection and production peak regulation of a gas storage reservoir, and fully studies the comprehensive scheduling process of a natural gas pipeline network system containing a gas storage reservoir, and can significantly reduce the operating cost of the gas storage system and enhance the feasibility and economy of the natural gas transportation and storage links under the goal of ensuring supply and demand balance. BRIEF DESCRIPTION OF THE DRAWINGS

[0106] Figure 1 It is a flow chart of the present invention;

[0107] Figure 2 This is a schematic diagram of the natural gas pipeline network structure;

[0108] Figure 3 Supply and demand results for the natural gas grid;

[0109] Figure 4 The injection and production flow and gas storage volume results of the gas storage;

[0110] Figure 5 These are the parameters of the gas storage reservoir and injection and production wells. DETAILED DESCRIPTION

[0111] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0112] like Figure 1 As shown, the present invention provides a multi-period supply and demand balance scheduling optimization method for a natural gas pipeline network coupled with the injection and production characteristics of a gas storage reservoir, comprising the following steps:

[0113] S1: Obtain the basic data of the target natural gas pipeline network;

[0114] S2: Establish the objective function of the multi-period supply and demand balance scheduling optimization model of the natural gas pipeline network coupled with the injection and production characteristics of the gas storage;

[0115] S3: Generate model constraints, and combine the objective function to establish a multi-period supply and demand balance scheduling optimization model for the natural gas pipeline network coupled with the injection and production characteristics of the gas storage, and solve and generate the pipeline network scheduling plan and the gas storage injection and production plan.

[0116] In one embodiment, the basic data described in step S1 includes gas source and user data, pipeline network parameters, gas storage reservoir parameters, system operation costs, pipeline network scheduling plan, and gas storage reservoir injection and production plan.

[0117] In one embodiment, the objective function described in step S2 is to minimize the economic and environmental costs of the natural gas pipeline network system of the gas storage, which is composed of pipeline transportation cost, gas storage cost, gas storage injection and production cost, carbon emission cost and natural gas shortage penalty cost, and the relationship is:

[0118] minf=f tran +f storage +f injwit +f carb +f pena

[0119] The pipeline transportation cost is the cost of natural gas occupying the pipeline capacity resources when flowing in the pipeline network, and the relationship is:

[0120] f tran =C tranq ij,t L ij

[0121] t T(i,j)A p

[0122] The storage cost of a gas storage facility refers to the cost incurred when natural gas is stored in the gas storage facility and occupies the storage space. The relationship is:

[0123]

[0124] The injection and production cost of a gas storage facility refers to the cost of using the mechanical equipment of the gas storage facility during the injection or production of natural gas. The relationship is:

[0125]

[0126] The carbon emission cost can be calculated from the unit carbon tax price, the carbon emission intensity coefficient of electricity and the equipment power. The relationship is:

[0127]

[0128] In order to fully meet the natural gas demand of users and avoid insufficient supply, a virtual natural gas shortage penalty cost is considered, and the relationship is:

[0129]

[0130] In one embodiment, the constraints described in step S3 include: node constraints, pipeline constraints, compressor station constraints, and gas storage constraints;

[0131] The node constraints are:

[0132]

[0133] The pipeline constraints are:

[0134]

[0135]

[0136] The pipeline flow direction variable must satisfy the flow direction uniqueness constraint, and the relationship is:

[0137]

[0138] The pipeline flow rate should meet the minimum and maximum gas transmission capacity restrictions, and the relationship is:

[0139]

[0140] The friction coefficient λ is one of the important parameters for gas flow calculation. It is related to factors such as the natural gas flow state and the roughness of the pipeline. The friction coefficient can be accurately calculated using the Colebrook formula. The relationship is:

[0141]

[0142] In the compressor constraint, only one device can be opened at the same time, the compressor unit and the bypass valve, and the relationship is:

[0143]

[0144] When natural gas flows through the bypass valve, the pressures at the upstream and downstream nodes of the compressor station are equal, and the relationship is:

[0145]

[0146] When natural gas is pressurized by the compressor unit, the upstream node pressure is related to the compressor inlet pressure, and the downstream node pressure is related to the compressor exhaust pressure. The relationship is:

[0147]

[0148]

[0149] The compressor intake and exhaust pressures should meet the maximum and minimum boost pressure ratio constraints of the compressor, and the relationship is:

[0150]

[0151] The pressure head indicates the energy provided by the compressor to pressurize a unit mass of natural gas. The relationship is:

[0152]

[0153] According to the compressor head, combined with the compressor station flow, the power consumption of the pipeline network compressor station can be calculated, and the relationship is:

[0154]

[0155] The power consumption of the compressor station in the pipeline network should meet the minimum and maximum power constraints, and the relationship is:

[0156]

[0157] The compressor determines the feasible operating range of the equipment through the so-called characteristic map, which is a nonlinear bounded non-convex set that defines the feasible combinations of compressor speed, flow and pressure head. The relationship is:

[0158]

[0159] The gas storage constraints include gas storage operation constraints, gas storage flow constraints, gas storage inventory constraints, and injection and production well constraints:

[0160] The gas storage operation constraints are:

[0161]

[0162] The gas storage flow constraint is:

[0163]

[0164] During the injection and production process of the gas storage, the inventory will decrease according to the injection flow rate, or increase according to the production flow rate. The relationship is:

[0165]

[0166] The gas storage inventory constraint is:

[0167]

[0168] The function of the bottom gas is to maintain the working pressure of the gas storage reservoir and cannot be extracted at will. Therefore, the actual gas storage volume of the gas storage reservoir should be equal to the inventory minus the bottom gas volume. The relationship is:

[0169]

[0170] The injection and production well constraints are:

[0171]

[0172] The number of wells opened in the gas storage reservoir should meet the minimum and maximum number of wells opened, and the relationship is:

[0173]

[0174] The gas injection flow or gas production flow of a single well should meet the minimum and maximum flow constraints, and the relationship is:

[0175]

[0176] As the inventory increases or decreases, the gas reservoir pressure of the gas storage will rise or fall. The relationship between the inventory and the gas reservoir pressure can be established through the gas reservoir material balance equation to determine the gas reservoir pressure in each period. The relationship is:

[0177]

[0178] When natural gas flows from the bottom of the well to the gas reservoir, it needs to overcome the formation resistance by seepage. The relationship is:

[0179]

[0180] When natural gas flows from the wellhead to the bottom of the well, it needs to overcome the friction resistance of the injection and production wells. The relationship is:

[0181]

[0182] The symbols are shown in Table 1, Table 2 and Table 3.

[0183] Table 1 Index and set of optimization models for multi-period supply and demand balance of natural gas pipeline network considering injection and production characteristics of gas storage

[0184] A Edge Set <![CDATA[A p ]]> Pipeline Edge Collection <![CDATA[A cs ]]> Compressor station side assembly N Node Collection <![CDATA[N s ]]> Supply Node Collection <![CDATA[N d ]]> Demand node collection <![CDATA[N t ]]> Transport Node Collection <![CDATA[N ugs ]]> Gas storage related node set T Period Collection U Gas storage collection

[0185] Table 2 Known parameters of the multi-period supply and demand balance optimization model of the natural gas pipeline network considering the injection and production characteristics of gas storage

[0186]

[0187]

[0188]

[0189] Table 3 Decision variables of the optimization model for multi-period supply and demand balance of natural gas pipeline network considering the injection and production characteristics of gas storage

[0190]

[0191]

[0192]

[0193]

[0194] In one embodiment, the multi-period supply and demand balance scheduling optimization model of the natural gas pipeline network coupled with the injection and production characteristics of the gas storage described in step S3 adopts two methods of hierarchical solution and overall solution when solving the model:

[0195] The specific steps of the hierarchical solution strategy are as follows:

[0196] (1) The gas storage is simplified into a pipeline network node with natural gas inflow and outflow, and the injection and production flow boundary and gas storage volume boundary of the gas storage are combined to form a pipeline network scheduling optimization model considering the simple gas storage node. The multi-cycle gas source supply and user demand data of the pipeline network are input, and the pipeline network scheduling plan, as well as the injection and production state variables, injection and production flow variables and connecting pipeline pressure variables of the gas storage are obtained by solving the mathematical model; the above gas storage variables are fixed and input into the next level model as the associated variables between models.

[0197] (2) Taking into full account the hydraulic characteristics of the underground gas reservoir and injection and production wells of the gas storage, as well as the pressure regulation function characteristics of the ground compressor station, a gas storage injection and production optimization model that takes into account the characteristics of the ground and underground facilities is formed; based on the injection and production status, injection and production flow rate, and connecting pipeline pressure variables fixed by the first-level model, the second-level gas storage injection and production optimization model is solved to determine the optimal number of wells opened in the gas storage, injection and production well flow rate, underground gas reservoir and injection and production well pressure, and ground facility operating parameters in each time period, and obtain a detailed gas storage injection and production plan.

[0198] (3) Based on the pipeline network scheduling plan obtained by the first level solution and the gas storage reservoir injection and production plan obtained by the second level solution, the operating costs of the system are clarified to form a complete pipeline network supply and demand balance optimization result.

[0199] The specific steps of the overall solution strategy are as follows:

[0200] (1) The pipeline network scheduling optimization model and the gas storage injection and production optimization model are directly coupled. Based on the multi-cycle supply and demand data of the pipeline network, the operating costs and constraint characteristics of the pipeline network and the gas storage are considered at the same time, and the overall optimization result of the pipeline network supply and demand balance is solved to achieve global optimization of the pipeline network scheduling plan and the gas storage injection and production plan.

[0201] (2) Based on the gas storage injection and production plan obtained by the overall solution, the operating costs of the system are clarified to form a complete pipeline network supply and demand balance optimization result.

[0202] In one embodiment, the pipeline network optimization plan described in step S3 includes system operation cost, pipeline network scheduling plan and gas storage injection and production plan.

[0203] The pipeline network scheduling scheme is a management and optimization strategy for natural gas flowing in the pipeline network; the gas storage injection and production scheme is a strategy for injecting natural gas into the gas storage or extracting natural gas from the gas storage.

[0204] In order to verify the effectiveness of the established mathematical model and solution method, the natural gas pipeline network example with gas storage is optimized and solved to obtain the optimal decision-making plan under different working conditions, and a comparative analysis is conducted. A small-scale natural gas pipeline network example with a single gas storage is established, mainly used to analyze the impact of gas storage peak regulation on the supply and demand balance of the natural gas pipeline network, and to compare the solution effects of the overall solution and the hierarchical solution.

[0205] A small-scale natural gas pipeline network with a single gas storage reservoir contains 1 gas source, 5 users, 1 gas storage reservoir, 3 compressor stations and 10 pipelines. Figure 2 The detailed pipeline network structure parameters are shown in Table 4, the compressor station parameters are shown in Table 5, and the gas storage reservoir parameters are shown in Table 6.

[0206] Table 4 Pipeline network structure parameter data

[0207]

[0208]

[0209] Table 5 Compressor station parameters

[0210]

[0211] Table 6 Gas storage parameters

[0212]

[0213]

[0214] Specific application example 1: Gas storage peak load optimization analysis

[0215] The optimization results of solving the peak-shaving models without and with consideration of gas storage are shown below.

[0216] (1) Analysis of pipeline network supply and demand optimization results

[0217] The natural gas pipeline network supply and demand results are obtained as follows: Figure 3 Without considering the peak load regulation of gas storage, during the peak demand period of users, i.e. January, February, November and December, the insufficient gas supply capacity caused a shortage of user demand, and the total gas shortage for the whole year was 12×10 8 m 3 On the contrary, by combining the peak-shaving function of the gas storage and making reasonable decisions on the injection and production plan of the gas storage, the shortage of gas supply capacity is effectively compensated, so that the needs of users in all periods are met.

[0218] (2) Analysis of economic optimization results

[0219] The results of the operation cost of the pipeline network system are obtained: when the gas storage peak load is not considered, the system operation cost is 2.217 billion yuan, including 758 million yuan of pipeline transportation cost, 19 million yuan of carbon emission cost and 1.44 billion yuan of gas shortage penalty cost; when the gas storage peak load is considered, the system operation cost is 1.989 billion yuan, including 915 million yuan of pipeline transportation cost, 763 million yuan of gas storage cost, 254 million yuan of gas storage injection and production cost and 36 million yuan of carbon emission cost. Considering the peak load of gas storage, the peak load of gas storage effectively compensates for the shortage of user demand, and there is no gas shortage penalty cost. It can be seen from the cost structure that the sum of the gas storage cost and injection and production cost of the gas storage is as high as 51.69%, which also reflects that the decision of the injection and production plan of the gas storage has an important influence on the optimization of the system operation cost.

[0220] (3) Analysis of optimization results of gas storage injection and production scheme

[0221] When considering the peak load regulation of gas storage, the injection and production flow and gas storage volume of gas storage are as follows: Figure 4 During the low demand period, i.e., from March to October, the gas storage will inject the excess natural gas from the gas source into the gas reservoir, which will increase the gas storage capacity. At the end of the injection period, the cumulative gas storage capacity of the gas storage is 12×10 8 m 3 During the high-demand period, i.e. November and December in winter and January and February in the following year, the gas storage will extract natural gas to supplement the shortage of gas supply, thus completing a complete peak-shaving process.

[0222] Considering the peak load regulation of gas storage, the results of gas storage reservoir and injection and production well parameters are as follows: Figure 5 As shown in the figure. During the injection period from March to October, with the increase of gas storage volume, the pressure parameters of the gas storage reservoir continued to increase. During the gas production period from November to February of the following year, with the continuous production of natural gas, the pressure parameters of the gas storage reservoir continued to decrease. During the injection period, the bottom hole pressure of the gas storage reservoir was higher than the wellhead pressure. This is because when the natural gas flows vertically from the wellhead to the bottom hole, the potential energy of the natural gas is converted into kinetic energy, which increases the bottom hole pressure. However, the gas reservoir pressure of the gas storage reservoir is lower than the bottom hole pressure. This is because when the natural gas flows from the bottom hole to the gas reservoir, it consumes its own energy by overcoming the formation resistance in the form of seepage. In addition, during the gas production period, the natural gas first flows from the gas reservoir to the bottom hole. Due to the need to consume energy to overcome the formation resistance, the bottom hole pressure is lower than the gas reservoir pressure. Then, the natural gas flows from the bottom hole to the wellhead. During the vertical ascent of the natural gas, the kinetic energy of the natural gas is converted into potential energy, making the wellhead pressure lower than the bottom hole pressure. Therefore, the node pressure results of the gas storage reservoir in each period are consistent with the hydraulic characteristics of the gas reservoir and the injection and production wells, verifying the correctness of the established gas storage model. In addition, the flow rate of injection and production wells in gas storage is mainly concentrated in the range of 20.2 to 31.4×10 4 m 3 The number of wells opened is mainly maintained in the range of 16 to 35. Therefore, the mathematical model established in this paper can accurately feedback the changes in injection and production parameters of gas storage reservoirs in each period, helping engineers to better understand the production dynamics of gas storage reservoirs.

[0223] Specific application example 2: Comparative analysis of solution methods

[0224] The model is solved using hierarchical solution and overall solution to explore the differences in solution results and solution efficiency of different solution methods. The optimization results are shown below.

[0225] (1) Iteration convergence analysis

[0226] The hierarchical solution method was adopted. The first level solved the pipeline network scheduling optimization model considering the simple gas storage node. After 4224 iterations, the optimal solution was obtained, the pipeline network scheduling plan was obtained, and the injection and production status, injection and production flow rate and connecting pipeline pressure variables of the gas storage were fixed. The iteration time was 114.93s, and the convergence error accuracy was 0.098%. The overall solution method was adopted. After 8604 iterations, the optimal solution was converged and the pipeline network scheduling plan and the gas storage injection and production plan were obtained at the same time. The iteration time was 267.34s, and the convergence error accuracy was 0.097%. The second level solved the gas storage injection and production optimization model considering the characteristics of the ground and underground facilities. After 1260 iterations, the optimal solution was obtained, and the detailed number of gas storage wells, injection and production well flow rate, underground gas reservoir and injection and production well pressure, and ground facility operation parameters were obtained to form a complete gas storage injection and production plan. The iteration time was 47.58s, and the convergence error accuracy was 0.099%. From the iterative convergence curves of the two solution methods, it can be seen that the overall solution method has more iterations and longer iteration time. In contrast, the hierarchical solution has fewer iterations and the iteration time is 39.21% shorter than the overall solution. Therefore, from the perspective of solution efficiency, the hierarchical solution method has greater advantages.

[0227] (2) Economic analysis

[0228] The results of the operation cost of the pipeline network system are obtained after solving. Due to the consistent natural gas demand of users, the hierarchical solution and the overall solution have the same pipeline transportation cost, gas storage cost and gas storage injection and production cost, which are 915 million yuan, 763 million yuan and 254 million yuan respectively. However, there are differences in the carbon emission costs between the two solution methods. During the operation of the pipeline network system, the pipeline network compressor station is used to pressurize natural gas to ensure the long-distance transportation of natural gas, and the gas storage compressor station is used to pressurize natural gas to achieve smooth injection of natural gas into underground high-pressure gas reservoirs. These compressor station facilities will contribute a large amount of carbon dioxide emissions in the process of consuming energy. Under the hierarchical solution method, the total carbon emission cost of the system for the whole year is 37.647 million yuan, the carbon emission cost of the pipeline network is 30.331 million yuan, and the carbon emission cost of the gas storage is 7.316 million yuan. Under the overall solution method, the total carbon emission cost of the system for the whole year is 36.346 million yuan, of which the carbon emission cost of the pipeline network compressor station is 33.773 million yuan and the carbon emission cost of the gas storage compressor station is 2.573 million yuan. Therefore, the carbon emission cost of the overall solution method is 1.301 million yuan less than that of the hierarchical solution method, a reduction of 3.45%. According to the carbon emission calculation formula, 6,505 tons of carbon dioxide emissions can be directly reduced throughout the year. It can be seen that the overall solution method can better balance the mutual influence between different objectives and obtain a globally optimal pipeline network scheduling and gas storage injection and production plan to further improve the economic and environmental benefits of pipeline network operation.

[0229] (3) Compressor station boost analysis

[0230] The difference in compressor station boosting schemes is the main reason for the difference in emission costs. The boosting pressure ratio and pipeline pressure results of the compressor station are obtained, among which the pipeline pressure result is taken as an example of the solution result of the injection period in June. In the natural gas pipeline network, the compressor station CS2 is located above the gas storage connection pipeline. The compressor station can be used to adjust the natural gas pressure entering the gas storage from the pipeline network during the injection period. Under the hierarchical solution method, in order to reduce the carbon emission cost of the first-level pipeline network scheduling optimization model, the pipeline network shuts down all compressor stations CS2 during the injection period, thereby reducing the pressure of the gas storage connection pipeline. However, the reduction in the pressure of the gas storage connection pipeline also reduces the pressure of the natural gas entering the gas storage, which puts higher requirements on the boosting capacity of the gas storage compressor station, and ultimately causes the boosting pressure ratio of the gas storage compressor station to remain at a level of 1.64 to 2.73. On the contrary, under the overall solution method, the pipeline network started the compressor station CS2 to pressurize the natural gas during the gas injection period, which increased the pressure of the gas storage connecting pipeline, thereby increasing the pressure of the natural gas entering the gas storage, relieving the pressure increase burden of the gas storage compressor station, and keeping the pressure increase ratio of the gas storage compressor station at 1.21-1.60. Obviously, the pressure increase ratio of the gas storage compressor station under the hierarchical solution method is much higher than that of the overall solution method, which makes the gas storage compressor station consume more energy and cause greater carbon emission costs, resulting in the total carbon emission cost of the hierarchical solution method being higher than that of the overall solution method.

[0231] The above description is only an example of a specific implementation method in this specification and is not intended to limit the embodiments of this specification. For those skilled in the art, the embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of this specification should be included in the scope of the claims of the embodiments of this specification.

Claims

1. A multi-period supply and demand balance scheduling optimization method for a natural gas pipeline network coupled with the injection and production characteristics of a gas storage reservoir, characterized in that: The following steps are involved: S1: Obtain the basic data of the target natural gas pipeline network; S2: Establish the objective function of the multi-period supply and demand balance scheduling optimization model of the natural gas pipeline network coupled with the injection and production characteristics of the gas storage; S3: Generate model constraints, and combine the objective function to establish a multi-period supply and demand balance scheduling optimization model for the natural gas pipeline network coupled with the injection and production characteristics of the gas storage, and solve and generate the pipeline network scheduling plan and the gas storage injection and production plan.

2. A method for optimizing multi-period supply and demand balance scheduling of a natural gas pipeline network coupled with injection and production characteristics of a gas storage reservoir as claimed in claim 1, characterized in that: The basic data described in step S1 include gas source and user data, pipeline network parameters, gas storage reservoir parameters, system operation costs, pipeline network scheduling plan, and gas storage reservoir injection and production plan.

3. A multi-period supply and demand balance scheduling optimization method for a natural gas pipeline network coupled with the injection and production characteristics of a gas storage as claimed in claim 1, characterized in that: The objective function described in step S2 is to minimize the economic and environmental costs of the natural gas pipeline network system of the gas storage, which is composed of pipeline transportation cost, gas storage cost, gas storage injection and production cost, carbon emission cost and natural gas shortage penalty cost. The relationship is: minf=f tran +f storage +f injwit +f carb +f pena Where, f is the total cost of the pipe network system operation; f tran is the pipeline transportation cost; f storage is the storage cost of gas storage; f injwit is the injection and production cost of gas storage; carb is the carbon emission cost; f pena Penalty costs for lack of gas; The pipeline transportation cost is the cost of natural gas occupying the pipeline capacity resources when flowing in the pipeline network, and the relationship is: In the formula, C tran is the unit transportation cost coefficient; q ij,t is the pipeline flow rate; L ij is the length of the pipeline; The storage cost of a gas storage facility refers to the cost incurred when natural gas is stored in the gas storage facility and occupies the storage space. The relationship is: In the formula, C storage is the unit gas storage cost coefficient; is the gas storage capacity of the gas storage facility; The injection and production cost of a gas storage facility refers to the cost of using the mechanical equipment of the gas storage facility during the injection or production of natural gas. The relationship is: In the formula, C inj is the unit gas injection cost coefficient; C wit is the unit gas production cost coefficient; The gas injection flow rate for the gas storage; Gas flow rate for gas storage; The carbon emission cost can be calculated from the unit carbon tax price, the carbon emission intensity coefficient of electricity and the equipment power. The relationship is: In the formula, C car is the unit carbon tax price; e car is the carbon emission intensity coefficient of electricity; The power consumption of the compressor station of the pipeline network; The power consumption of the gas storage compressor station; The penalty cost of natural gas shortage is expressed as follows: In the formula, C pena Penalty cost factor for lack of gas; Flow required by users; i,t Actual output traffic for users.

4. A method for optimizing multi-period supply and demand balance scheduling of a natural gas pipeline network coupled with injection and production characteristics of a gas storage as claimed in claim 1, characterized in that: The constraints described in step S3 include: node constraints, pipeline constraints, compressor station constraints, and gas storage constraints; The node constraints are: In the formula, s i,t is the gas source input flow; d i,t Output traffic for users; Input flow rate for gas collection at gas storage; is the gas injection output flow of the gas storage; p i,t is the node pressure; The pipeline constraints are: In the formula, q ij is the pipeline flow rate; p i is the starting pressure of the pipeline; p j is the pipeline end point pressure; is a binary variable for the pipeline forward flow; is a binary variable for pipeline reverse flow; M is the maximum value; is the pipeline flow resistance coefficient; D ij is the pipe diameter; ij is the pipeline friction coefficient; The pipeline flow direction variable must satisfy the flow direction uniqueness constraint, and the relationship is: The pipeline flow rate should meet the minimum and maximum gas transmission capacity restrictions, and the relationship is: The friction coefficient λ is one of the important parameters for gas flow calculation. It is related to factors such as the natural gas flow state and the roughness of the pipeline. The friction coefficient can be accurately calculated using the Colebrook formula. The relationship is: In the formula, τ is the equivalent roughness of the tube wall; Re is the Reynolds number; In the compressor constraint, only one device can be opened at the same time, the compressor unit and the bypass valve, and the relationship is: In the formula, is the binary variable of the compressor unit switch state; is the bypass valve switch state binary variable; is the binary variable of the overall switch status of the compressor station; When natural gas flows through the bypass valve, the pressures at the upstream and downstream nodes of the compressor station are equal, and the relationship is: When natural gas is pressurized by the compressor unit, the upstream node pressure is related to the compressor inlet pressure, and the downstream node pressure is related to the compressor exhaust pressure. The relationship is: In the formula, is the compressor inlet pressure; is the compressor exhaust pressure; The compressor intake and exhaust pressures should meet the maximum and minimum boost pressure ratio constraints of the compressor, and the relationship is: The pressure head indicates the energy provided by the compressor to pressurize a unit mass of natural gas. The relationship is: In the formula, ΔH ij,t is the compressor pressure head; m is the natural gas expansion index; According to the compressor head, combined with the compressor station flow, the power consumption of the pipeline network compressor station can be calculated, and the relationship is: In the formula, The power consumption of the compressor station; is the compressor efficiency; The power consumption of the compressor station in the pipeline network should meet the minimum and maximum power constraints, and the relationship is: The compressor determines the feasible operating range of the equipment through the so-called characteristic map, which is a nonlinear bounded non-convex set that defines the feasible combinations of compressor speed, flow and pressure head. The relationship is: In the formula, ω ij,t is the compressor speed; is the flow rate of a single compressor; Θ ij is the non-convex feasible domain of the compressor; The gas storage constraints include gas storage operation constraints, gas storage flow constraints, gas storage inventory constraints, and injection and production well constraints: The gas storage operation constraints are: In the formula, is a binary variable of gas storage injection status; is a binary variable of gas storage gas extraction status; The gas storage flow constraint is: During the injection and production process of the gas storage, the inventory will decrease according to the injection flow rate, or increase according to the production flow rate. The relationship is: In the formula, G u,t For gas storage inventory; dur t is the cycle duration; The gas storage inventory constraint is: The function of the bottom gas is to maintain the working pressure of the gas storage reservoir and cannot be extracted at will. Therefore, the actual gas storage volume of the gas storage reservoir should be equal to the inventory minus the bottom gas volume. The relationship is: The injection and production well constraints are: Where n u,t Number of wells opened for gas storage; is the gas injection flow rate of a single well; is the gas production flow rate of a single well; The number of wells opened in the gas storage reservoir should meet the minimum and maximum number of wells opened, and the relationship is: The gas injection flow or gas production flow of a single well should meet the minimum and maximum flow constraints, and the relationship is: As the inventory increases or decreases, the gas reservoir pressure of the gas storage will rise or fall. The relationship between the inventory and the gas reservoir pressure can be established through the gas reservoir material balance equation to determine the gas reservoir pressure in each period. The relationship is: In the formula, is the gas reservoir pressure of the gas storage; When natural gas flows from the bottom of the well to the gas reservoir, it needs to overcome the formation resistance by seepage. The relationship is: In the formula, is the bottom hole pressure of the gas storage reservoir; is the gas reservoir laminar flow coefficient; is the gas reservoir turbulence coefficient; When natural gas flows from the wellhead to the bottom of the well, it needs to overcome the friction resistance of the injection and production wells. The relationship is: In the formula, is the wellhead pressure of the gas storage reservoir; is the flow resistance coefficient of the injection-production well.

5. A method for optimizing multi-period supply and demand balance scheduling of a natural gas pipeline network coupled with injection and production characteristics of a gas storage as claimed in claim 1, characterized in that: The multi-period supply and demand balance scheduling optimization model of the natural gas pipeline network coupled with the injection and production characteristics of the gas storage described in step S4 includes a hierarchical solution and an overall solution: The specific steps of the hierarchical solution strategy are as follows: (1) Simplify the gas storage into a pipeline network node with natural gas inflow and outflow, and combine the injection and production flow boundary and gas storage volume boundary of the gas storage to form a pipeline network scheduling optimization model considering the simple gas storage node. Input the multi-cycle gas source supply and user demand data of the pipeline network, and solve the mathematical model to obtain the pipeline network scheduling plan, as well as the gas storage injection and production state variables, injection and production flow variables and connecting pipeline pressure variables; fix the above gas storage variables and input them into the next level model as the associated variables between models; (2) Taking into account the hydraulic characteristics of the underground gas reservoir and injection and production wells of the gas storage, as well as the pressure regulation function characteristics of the ground compressor station, a gas storage injection and production optimization model that takes into account the characteristics of the ground and underground facilities is formed; based on the injection and production status, injection and production flow rate, and connecting pipeline pressure variables fixed by the first-level model, the second-level gas storage injection and production optimization model is solved to determine the optimal number of wells opened in the gas storage, injection and production well flow rate, underground gas reservoir and injection and production well pressure, and ground facility operating parameters in each time period, and obtain a detailed gas storage injection and production plan; (3) Based on the pipeline network dispatching plan obtained by the first level solution and the gas storage reservoir injection and production plan obtained by the second level solution, the various operating costs of the system are clarified to form a complete pipeline network supply and demand balance optimization result; The specific steps of the overall solution strategy are as follows: (1) The pipeline network scheduling optimization model and the gas storage injection and production optimization model are directly coupled. Based on the multi-cycle supply and demand data of the pipeline network, the operating costs and constraint characteristics of the pipeline network and the gas storage are considered at the same time, and the overall optimization result of the pipeline network supply and demand balance is solved to achieve the global optimization of the pipeline network scheduling plan and the gas storage injection and production plan; (2) Based on the gas storage injection and production plan obtained by the overall solution, the operating costs of the system are clarified to form a complete pipeline network supply and demand balance optimization result.

6. A method for optimizing multi-period supply and demand balance scheduling of a natural gas pipeline network coupled with injection and production characteristics of a gas storage as claimed in claim 1, characterized in that: The pipeline network optimization plan described in step S4 includes system operation cost, pipeline network scheduling plan and gas storage injection and production plan; The pipeline network scheduling scheme is a management and optimization strategy for natural gas flowing in the pipeline network; the gas storage injection and production scheme is a strategy for injecting natural gas into the gas storage or extracting natural gas from the gas storage.

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