Gas unit supply restoration prediction method and system supporting power restoration decisions

Abstract

The application provides a gas turbine unit gas supply recovery prediction method and system supporting power recovery decision, and belongs to the technical field of power system safety and stability. First, partial differential equations describing dynamic flow are linearized, and on this basis, finite difference method is used to convert them into linear constraints. Then, the gas source, compression station and load and other non-pipeline elements in the natural gas pipeline network are modeled, the influence of electrically-driven compressor and electrically-driven gas source recovery on the natural gas pipeline network is embodied, and the natural gas supply recovery time of the gas turbine unit is obtained as an important basis for formulating the recovery strategy of the gas turbine unit. The application models the gas source, compression station and load and other non-pipeline elements in the natural gas pipeline network, embodies the influence of electrically-driven compressor and electrically-driven gas source recovery on the natural gas pipeline network, accurately decides the natural gas supply recovery time of the gas turbine unit, supports the smooth start of the gas turbine unit, and accelerates the recovery of the power grid power generation capacity.

Description

Technical Field

[0001] This invention relates to the field of power system safety and stability technology, specifically to a gas turbine unit gas supply recovery prediction method and system for power system recovery decision-making after a major power outage. Background Technology

[0002] Currently, the coupling between power grids and natural gas grids is becoming increasingly close, and the proportion of gas turbine units in power systems continues to increase. For environmental and economic reasons, electrically driven compressors and gas sources are widely used in natural gas systems. During system recovery, effective analysis of the dynamic processes of the natural gas grid can accurately determine the natural gas supply recovery time for gas turbine units, supporting their smooth startup, accelerating the system recovery process, and reducing power outage losses.

[0003] A natural gas network is a complex network composed of gas sources, pipelines, compression stations, and other auxiliary equipment, bidirectionally coupled to the power grid through gas turbine units, electrically driven compression stations, and electrically driven gas sources. In recent years, domestic and international scholars have studied the impact of coupled operation of the power grid and natural gas network. Examples include: analyzing the steady-state model of a gas-power combined system considering the influence of natural gas system temperature; proposing a hybrid power flow calculation method that couples a thermal system to the gas-power combined system; calculating the optimal power flow of the gas-power combined system considering the correlation between uncertain variables; and considering the dynamic processes of the natural gas system in the gas-power combined system, independently optimizing the natural gas and power systems, and achieving coordinated optimization of the combined system through iterative methods. In summary, all of the above studies are based on steady-state power flow models of the natural gas system, neglecting the different time scales of the natural gas network and the power grid, and failing to consider the dynamic response process of the natural gas network during system recovery. Summary of the Invention

[0004] The purpose of this invention is to provide a modeling method for gas sources, pipelines, compression stations and other auxiliary equipment, as well as electrically driven compression stations and electrically driven gas sources in a natural gas network, in order to analyze the dynamic impact of power restoration of electrically driven compression stations and electrically driven gas sources on the natural gas pipeline network after a major power outage, thereby analyzing the natural gas supply restoration time of gas turbine units, and providing a gas turbine unit gas supply restoration prediction method and system to support the smooth start-up of gas turbine units after a major power outage, so as to solve at least one of the technical problems existing in the background art.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] On one hand, the present invention provides a method for predicting the recovery of gas supply to a gas turbine unit, characterized in that it includes:

[0007] The partial differential equations describing dynamic flow are linearized and transformed into linear constraints using the finite difference method.

[0008] Based on linear constraints, a dynamic constraint model of the natural gas pipeline network is constructed to reflect the impact of electric-driven compressors and electric-driven gas source recovery on the natural gas pipeline network.

[0009] Based on the initial and boundary constraints given by the natural gas pipeline network, the dynamic constraint model of the natural gas pipeline network is solved to obtain the dynamic distribution of gas pressure and flow rate.

[0010] A natural gas supply constraint model for gas turbine units is constructed based on the dynamic distribution of gas pressure and flow rate.

[0011] The natural gas supply constraint model for the gas turbine unit is calculated to obtain the natural gas supply recovery time.

[0012] Preferably, a dynamic constraint model for the natural gas pipeline network is constructed, including:

[0013] The mathematical model of one-dimensional isothermal flow of natural gas along a pipeline is characterized by a set of partial differential equations:

[0014]

[0015]

[0016] Π=c 2 ρ (4)

[0017] In the formula: ρ is the density of natural gas; ω is the flow velocity of natural gas; Π is the pressure of natural gas; g is the acceleration due to gravity; θ is the inclination angle of the pipeline; D is the diameter of the pipeline; λ is the coefficient of friction of the pipeline; c is the speed of sound of natural gas in the pipeline; τ is time; x is the axial spatial distance of the pipeline;

[0018] Linearization is performed by introducing a base value for natural gas flow rate:

[0019]

[0020] Define the mass flow rate M as:

[0021] M=ρωA (6)

[0022] In the formula: A is the cross-sectional area of ​​the pipe;

[0023] Substituting equation (5) into momentum equation (2), and then into momentum equation (2) and continuity equation (3), we get:

[0024]

[0025]

[0026] Equations (4), (7), and (8) form a set of linear partial differential equations describing the dynamics of a natural gas pipeline.

[0027] Preferably, the Wendroff finite difference scheme is used to transform equations (4), (7), and (8) into algebraic equations, resulting in a set of linear algebraic equations (9)-(11) for the dynamic model of the natural gas pipeline network:

[0028]

[0029]

[0030]

[0031] In the formula: ρtn,i is the node density of natural gas; Πtn,i is the node pressure of natural gas; Mtin,ij and Mtout,ij represent the mass flow rates of natural gas flowing into and out of the pipeline, respectively; L ij Δt is the differential space step size, i.e., the pipe length; Δt is the differential time step size, i.e., the recovery time period length; S N S represents the set of gas transmission nodes; P The collection of gas pipelines in the system; S T It is the set of all recovery periods.

[0032] Preferably, based on the initial and boundary conditions given by the gas transmission pipeline network, solving equations (9)-(11) yields the dynamic distribution of gas pressure and flow rate. Initial constraints refer to the values ​​at a previous steady state on the pipeline network. Boundary constraints refer to the boundary conditions at the pipeline end, including node flow balance constraints, pressure boundaries, flow boundaries, and gas supply limitations.

[0033]

[0034]

[0035]

[0036]

[0037]

[0038]

[0039]

[0040]

[0041]

[0042] In the formula: utc,ij and uts,i are 0-1 integer decision variables, representing the power supply status of the electric-driven compressor station and the electric-driven gas source, respectively. If the power supply has been restored, the value is 1; otherwise, the value is 0. Π0nc,ij, Π0c,ij, Π0ns,i and Π0s,i represent the outlet pressure setpoints of the non-electric-driven compressor station, the electric-driven compressor station, the non-electric-driven gas source and the electric-driven gas source, respectively. Πtn-ns,i and Πtn-s,i represent the node gas pressures of the non-electric-driven gas source and the electric-driven gas source, respectively. Mtin-ns,i, Mtin-s,i and Mtout-l,i represent the pipeline natural gas flow rates of the non-electric-driven gas source, the electric-driven gas source and the natural gas load, respectively. M ns,i , M s,i These represent the upper and lower limits of the gas supply capacity of the non-electrically driven gas source and the electrically driven gas source, respectively; M l,i S represents the natural gas load; I S represents the set of pipe junctions; i→j S j→k Let S represent the sets of upstream nodes of natural gas inflow node j and downstream nodes of natural gas outflow node j, respectively; C S NC S S S NS S GL These represent the collections of electrically driven compressor stations, non-electrically driven compressor stations, electrically driven gas sources, non-electrically driven gas sources, and natural gas loads, respectively.

[0043] Equation (12) represents the natural gas flow balance constraint; Equation (13) indicates that the outlet pressure of the non-electrically driven compressor station is always at the set value; Equation (14) indicates that when the electrically driven compressor station loses power supply, it enters the bypass mode, that is, the gas pressure at the beginning of the compressor station is equal to the gas pressure at the end. After the power supply is restored, the electrically driven compressor station will keep the outlet pressure at the set value; Equation (15) represents the flow constraint of the compressor station; Equation (16) indicates that the outlet pressure of the non-electrically driven gas source is always at the set value; Equation (17) indicates that after the power supply is lost, the electrically driven gas source does not have the ability to control the outlet pressure. After the power supply is restored, the electrically driven gas source will keep the outlet pressure at the set value; Equations (18) and (19) are the upper limit constraint and lower limit constraint of the gas source output, respectively. For the electrically driven gas source, after the power supply is lost, it does not have the ability to supply gas; Equation (20) represents the natural gas consumption of the load node.

[0044] Preferably, the pressure constraint (14) of the electric-driven compressor station and the pressure constraint (17) of the electric-driven air source are constraints containing conditional judgments. The constraints are processed using the "Big M method" by introducing a very large positive integer N to transform them into linear inequality constraints:

[0045]

[0046]

[0047]

[0048]

[0049] Preferably, a natural gas supply constraint model for the gas turbine unit is constructed, including:

[0050]

[0051] In the formula: utf,i is a 0-1 integer decision variable, representing whether the gas turbine unit has the conditions for gas supply. If it does, the value is 1; otherwise, the value is 0. Πtn-f,i is the gas pressure at the gas supply node of the gas turbine unit. Π f,i This refers to the minimum gas pressure requirement for the gas supply node of the gas turbine unit; S F This represents the collection of gas turbine units in the system.

[0052] In a second aspect, the present invention provides a gas turbine unit gas supply recovery prediction system, comprising:

[0053] The transformation module is used to linearize the partial differential equations describing dynamic flow, and transforms them into linear constraints using the finite difference method.

[0054] The first construction module is used to build a dynamic constraint model of the natural gas pipeline network based on linear constraints, which reflects the impact of electric-driven compressors and electric-driven gas source recovery on the natural gas pipeline network.

[0055] The first calculation module is used to solve the dynamic constraint model of the natural gas pipeline network based on the initial constraints and boundary constraints given by the natural gas pipeline network, and obtain the dynamic distribution of gas pressure and flow rate.

[0056] The second building module is used to construct a natural gas supply constraint model for gas turbine units based on the dynamic distribution of gas pressure and flow rate;

[0057] The second calculation module is used to calculate the natural gas supply constraint model of the gas turbine unit and obtain the natural gas supply recovery time of the gas turbine unit.

[0058] Thirdly, the present invention provides a non-transitory computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the gas turbine unit gas supply recovery prediction method as described above.

[0059] Fourthly, the present invention provides a computer program product, including a computer program that, when run on one or more processors, is used to implement the gas turbine unit gas supply recovery prediction method as described above.

[0060] Fifthly, the present invention provides an electronic device, comprising: a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to cause the electronic device to execute instructions for implementing the gas turbine unit gas supply recovery prediction method as described above.

[0061] The beneficial effects of this invention are as follows: It models the gas supply recovery problem of gas turbine units considering the dynamic process of the natural gas network, which is used for power system recovery decision-making; it linearizes the partial differential equations describing the dynamic flow, and then uses the finite difference method to transform them into linear constraints; then it models non-pipeline components such as gas sources, compression stations and loads in the natural gas pipeline network, reflecting the impact of the recovery of electric-driven compressors and electric-driven gas sources on the natural gas pipeline network, accurately determining the timing of natural gas supply recovery for gas turbine units, supporting the smooth start-up of gas turbine units, and accelerating the recovery of power grid generation capacity.

[0062] The advantages of additional aspects of the invention will be set forth more clearly in the following description or will be learned by practice of the invention. Attached Figure Description

[0063] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0064] Figure 1 This is a structural diagram of the gas turbine unit gas supply analysis method considering the dynamic process of the natural gas network under a major power outage scenario, as described in an embodiment of the present invention.

[0065] Figure 2 This is a schematic diagram comparing the gas pressure curves of the gas supply node of the gas turbine unit according to an embodiment of the present invention, wherein... Figure 2 (a) shows the gas pressure curve of gas supply node G1. Figure 2 (b) shows the gas pressure curve of the G6 gas supply node. Detailed Implementation

[0066] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0067] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0068] It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless defined as here.

[0069] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, and / or groups thereof.

[0070] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples.

[0071] To facilitate understanding of the present invention, the present invention will be further explained and described below with reference to the accompanying drawings and specific embodiments. However, the specific embodiments do not constitute a limitation on the embodiments of the present invention.

[0072] Those skilled in the art should understand that the accompanying drawings are merely schematic diagrams of embodiments, and the components in the drawings are not necessarily essential for implementing the present invention.

[0073] Example 1

[0074] During system recovery, as the power grid's generating capacity is restored, the power supply to the gas transmission network's electrically driven facilities will also be restored, causing changes in natural gas network pressure and flow. Compared to the power grid, the natural gas network has a larger time constant and exhibits slow dynamic response characteristics. Therefore, it is necessary to characterize the dynamics of the natural gas network after the restoration of the gas transmission network's electrically driven facilities in order to accurately determine the timing of natural gas supply restoration for gas turbine units. Thus, it is essential to study a gas turbine unit supply restoration decision-making method that considers the dynamic process of the natural gas network, obtaining the natural gas supply restoration time for gas turbine units as an important basis for formulating gas turbine unit restoration strategies.

[0075] For the reasons mentioned above, this embodiment 1 first provides a gas turbine unit gas supply recovery prediction system, including:

[0076] The transformation module is used to linearize the partial differential equations describing dynamic flow, and transforms them into linear constraints using the finite difference method.

[0077] The first construction module is used to build a dynamic constraint model of the natural gas pipeline network based on linear constraints, which reflects the impact of electric-driven compressors and electric-driven gas source recovery on the natural gas pipeline network.

[0078] The first calculation module is used to solve the dynamic constraint model of the natural gas pipeline network based on the initial constraints and boundary constraints given by the natural gas pipeline network, and obtain the dynamic distribution of gas pressure and flow rate.

[0079] The second building module is used to construct a natural gas supply constraint model for gas turbine units based on the dynamic distribution of gas pressure and flow rate;

[0080] The second calculation module is used to calculate the natural gas supply constraint model of the gas turbine unit and obtain the natural gas supply recovery time of the gas turbine unit.

[0081] Secondly, in this embodiment 1, the gas turbine unit gas supply recovery prediction method is further implemented using the above-described system, including:

[0082] The partial differential equations describing dynamic flow are linearized using the transformation module, and then transformed into linear constraints using the finite difference method.

[0083] Using the first building module based on linear constraints, a dynamic constraint model of the natural gas pipeline network is constructed to reflect the impact of electric-driven compressors and electric-driven gas source recovery on the natural gas pipeline network;

[0084] The first calculation module is used to solve the dynamic constraint model of the natural gas pipeline network based on the initial and boundary constraints given by the natural gas pipeline network, so as to obtain the dynamic distribution of gas pressure and flow rate.

[0085] A natural gas supply constraint model for gas turbine units is constructed using the second building module based on the dynamic distribution of gas pressure and flow rate.

[0086] The natural gas supply constraint model of the gas turbine unit is calculated using the second calculation module to obtain the natural gas supply recovery time of the gas turbine unit.

[0087] The construction of a dynamic constraint model for the natural gas pipeline network includes:

[0088] The mathematical model of one-dimensional isothermal flow of natural gas along a pipeline is characterized by a set of partial differential equations:

[0089]

[0090]

[0091] Π=c 2 ρ (4)

[0092] In the formula: ρ is the density of natural gas; ω is the flow velocity of natural gas; Π is the pressure of natural gas; g is the acceleration due to gravity; θ is the inclination angle of the pipeline; D is the diameter of the pipeline; λ is the coefficient of friction of the pipeline; c is the speed of sound of natural gas in the pipeline; τ is time; x is the axial spatial distance of the pipeline;

[0093] Linearization is performed by introducing a base value for natural gas flow rate:

[0094]

[0095] Define the mass flow rate M as:

[0096] M=ρωA (6)

[0097] In the formula: A is the cross-sectional area of ​​the pipe;

[0098] Substituting equation (5) into momentum equation (2), and then into momentum equation (2) and continuity equation (3), we get:

[0099]

[0100]

[0101] Equations (4), (7), and (8) form a set of linear partial differential equations describing the dynamics of a natural gas pipeline.

[0102] In this embodiment, the Wendroff finite difference scheme is used to transform equations (4), (7), and (8) into algebraic equations, resulting in a set of linear algebraic equations (9)-(11) for the dynamic model of the natural gas pipeline network:

[0103]

[0104]

[0105]

[0106] In the formula: ρtn,i is the node density of natural gas; Πtn,i is the node pressure of natural gas; Mtin,ij and Mtout,ij represent the mass flow rates of natural gas flowing into and out of the pipeline, respectively; L ij Δt is the differential space step size, i.e., the pipe length; Δt is the differential time step size, i.e., the recovery time period length; S N S represents the set of gas transmission nodes; P The collection of gas pipelines in the system; S TIt is the set of all recovery periods.

[0107] Based on the initial and boundary conditions given by the gas transmission pipeline network, the dynamic distribution of gas pressure and flow rate can be obtained by solving equations (9)-(11). The initial constraint refers to the previous steady-state value of the pipeline network. The boundary constraint refers to the boundary conditions at the end of the pipeline, including the flow balance constraint at the node, the gas pressure boundary, the flow rate boundary, and the gas supply limit of the gas source.

[0108]

[0109]

[0110]

[0111]

[0112]

[0113]

[0114]

[0115]

[0116]

[0117] In the formula: utc,ij and uts,i are 0-1 integer decision variables, representing the power supply status of the electric-driven compressor station and the electric-driven gas source, respectively. If the power supply has been restored, the value is 1; otherwise, the value is 0. Π0nc,ij, Π0c,ij, Π0ns,i and Π0s,i represent the outlet pressure setpoints of the non-electric-driven compressor station, the electric-driven compressor station, the non-electric-driven gas source and the electric-driven gas source, respectively. Πtn-ns,i and Πtn-s,i represent the node gas pressures of the non-electric-driven gas source and the electric-driven gas source, respectively. Mtin-ns,i, Mtin-s,i and Mtout-l,i represent the pipeline natural gas flow rates of the non-electric-driven gas source, the electric-driven gas source and the natural gas load, respectively. M ns,i , M s,i These represent the upper and lower limits of the gas supply capacity of the non-electrically driven gas source and the electrically driven gas source, respectively; M l,i S represents the natural gas load; I S represents the set of pipe junctions; i→j S j→k Let S represent the sets of upstream nodes of natural gas inflow node j and downstream nodes of natural gas outflow node j, respectively; C S NC S SS NS S GL These represent the collections of electrically driven compressor stations, non-electrically driven compressor stations, electrically driven gas sources, non-electrically driven gas sources, and natural gas loads, respectively.

[0118] Equation (12) represents the natural gas flow balance constraint; Equation (13) indicates that the outlet pressure of the non-electrically driven compressor station is always at the set value; Equation (14) indicates that when the electrically driven compressor station loses power supply, it enters the bypass mode, that is, the gas pressure at the beginning of the compressor station is equal to the gas pressure at the end. After the power supply is restored, the electrically driven compressor station will keep the outlet pressure at the set value; Equation (15) represents the flow constraint of the compressor station; Equation (16) indicates that the outlet pressure of the non-electrically driven gas source is always at the set value; Equation (17) indicates that after the power supply is lost, the electrically driven gas source does not have the ability to control the outlet pressure. After the power supply is restored, the electrically driven gas source will keep the outlet pressure at the set value; Equations (18) and (19) are the upper limit constraint and lower limit constraint of the gas source output, respectively. For the electrically driven gas source, after the power supply is lost, it does not have the ability to supply gas; Equation (20) represents the natural gas consumption of the load node.

[0119] The pressure constraints of the electric-driven compressor station (14) and the pressure constraints of the electric-driven gas source (17) are constraints containing conditional judgments. The constraints are processed using the "Big M method", which introduces a very large positive integer N to transform them into linear inequality constraints:

[0120]

[0121]

[0122]

[0123]

[0124] Construct a natural gas supply constraint model for gas turbine units, including:

[0125]

[0126] In the formula: utf,i is a 0-1 integer decision variable, representing whether the gas turbine unit has the conditions for gas supply. If it does, the value is 1; otherwise, the value is 0. Πtn-f,i is the gas pressure at the gas supply node of the gas turbine unit. Π f,i This refers to the minimum gas pressure requirement for the gas supply node of the gas turbine unit; S F This represents the collection of gas turbine units in the system.

[0127] The objective function of the natural gas supply constraint model for gas turbine units is to restore the natural gas supply to the gas turbine units as quickly as possible. The mathematical expression is:

[0128]

[0129] In the formula: utf,i is a 0-1 integer decision variable, representing whether the gas turbine unit has the conditions for gas supply; if it does, it takes the value 1, otherwise it takes the value 0; S T S is the set of all recovery periods; F This represents the collection of gas turbine units in the system.

[0130] Example 2

[0131] In this embodiment 2, a gas turbine supply restoration analysis method for power system restoration decision-making after a major power outage is provided. The gas turbine supply restoration problem considering the dynamic process of the natural gas network is modeled as a mixed integer linear programming model, with the following specific features:

[0132] Determine the objective function for restoring the natural gas supply to the gas turbine units as quickly as possible;

[0133] Then, the partial differential equations describing the dynamic flow are linearized, and on this basis, the finite difference method is used to transform them into linear constraints to characterize the dynamic process of the natural gas pipeline network.

[0134] Furthermore, models are created for non-pipeline components in the natural gas pipeline network, such as gas sources, compression stations, and loads, to reflect the impact of electric-driven compressors and electric-driven gas source recovery on the natural gas pipeline network.

[0135] Finally, the natural gas supply of the gas turbine unit was modeled to obtain the natural gas supply recovery time of the gas turbine unit.

[0136] The objective function is as follows:

[0137] The objective function is to restore the natural gas supply to the gas turbine unit as quickly as possible, and its mathematical expression is:

[0138]

[0139] In the formula: utf,i is a 0-1 integer decision variable, representing whether the gas turbine unit has the conditions for gas supply; if it does, it takes the value 1, otherwise it takes the value 0; S T S is the set of all recovery periods; F This represents the collection of gas turbine units in the system.

[0140] The specific steps for dynamic constraint modeling of natural gas pipelines are as follows:

[0141] The mathematical model for one-dimensional isothermal flow of natural gas along a pipeline is characterized by a set of partial differential equations, including the continuity equation, momentum equation, and state equation.

[0142]

[0143]

[0144] Π=c2 ρ (4)

[0145] In the formula: ρ is the density of natural gas; ω is the flow velocity of natural gas; Π is the pressure of natural gas; g is the acceleration due to gravity; θ is the inclination angle of the pipeline; D is the diameter of the pipeline; λ is the friction coefficient of the pipeline; c is the speed of sound of natural gas in the pipeline; τ is time; x is the axial spatial distance of the pipeline; In particular, for the momentum equation (2), the first term is the inertial term, the second term is the convection term, the third term is the pressure term, the fourth term is the gravity elevation difference term, and the fifth term is the drag term.

[0146] To address the characteristics of regional gas transmission networks, equation (2) is simplified. First, the convection term and gravity elevation difference term in the momentum equation are ignored. Second, to linearize the velocity square term of the resistance term in the momentum equation, a basic value for natural gas velocity is introduced, as shown in equation (5).

[0147]

[0148] Define the mass flow rate M as:

[0149] M=ρωA (6)

[0150] In the formula: A is the cross-sectional area of ​​the pipe.

[0151] Substituting equation (5) into momentum equation (2), and then into momentum equation (2) and continuity equation (3), we get:

[0152]

[0153]

[0154] In summary, equations (4), (7), and (8) form a set of linear partial differential equations describing the dynamics of a natural gas pipeline.

[0155] In the set of equations describing the dynamics of a natural gas pipeline, equations (7) and (8) are partial differential equations, which increases the complexity of the model.

[0156] In this embodiment 1, the Wendroff finite difference scheme is used to transform equations (4), (7) and (8) into algebraic equations.

[0157]

[0158]

[0159]

[0160] In the formula: ρtn,i is the node density of natural gas; Πtn,i is the node pressure of natural gas; Mtin,ij and Mtout,ij represent the mass flow rates of natural gas flowing into and out of the pipeline, respectively; L ij Δt is the differential space step size, i.e., the pipe length; Δt is the differential time step size, i.e., the recovery time period length; S N S represents the set of gas transmission nodes; P The collection of gas pipelines in the system; S T It is the set of all recovery periods.

[0161] Thus, the dynamic process of the natural gas pipeline is modeled as a set of linear algebraic equations (9)-(11).

[0162] Modeling of initial and boundary constraints for the natural gas network, detailed as follows:

[0163] Based on the initial and boundary conditions given by the gas transmission pipeline network, the dynamic distribution of gas pressure and flow rate can be obtained by solving equations (9)-(11). The initial constraint refers to the previous steady-state value of the pipeline network. The boundary constraint refers to the boundary conditions at the end of the pipeline, including the flow balance constraint at the node, the gas pressure boundary, the flow rate boundary, and the gas supply limit of the gas source.

[0164]

[0165]

[0166]

[0167]

[0168]

[0169]

[0170]

[0171]

[0172]

[0173] In the formula: utc,ij and uts,i are 0-1 integer decision variables, representing the power supply status of the electric-driven compressor station and the electric-driven gas source, respectively. If the power supply has been restored, the value is 1; otherwise, the value is 0. Π0nc,ij, Π0c,ij, Π0ns,i and Π0s,i represent the outlet pressure setpoints of the non-electric-driven compressor station, the electric-driven compressor station, the non-electric-driven gas source and the electric-driven gas source, respectively. Πtn-ns,i and Πtn-s,i represent the node gas pressures of the non-electric-driven gas source and the electric-driven gas source, respectively. Mtin-ns,i, Mtin-s,i and Mtout-l,i represent the pipeline natural gas flow rates of the non-electric-driven gas source, the electric-driven gas source and the natural gas load, respectively. M ns,i , M s,i These represent the upper and lower limits of the gas supply capacity of the non-electrically driven gas source and the electrically driven gas source, respectively; M l,i S represents the natural gas load; I S represents the set of pipe junctions; i→j S j→k Let S represent the sets of upstream nodes of natural gas inflow node j and downstream nodes of natural gas outflow node j, respectively; C S NC S S S NS S GL These represent the collections of electrically driven compressor stations, non-electrically driven compressor stations, electrically driven gas sources, non-electrically driven gas sources, and natural gas loads, respectively.

[0174] Constraint (12) is a natural gas flow balance constraint; constraint (13) indicates that the outlet pressure of the non-electrically driven compressor station is always at the set value; constraint (14) indicates that when the electrically driven compressor station loses power supply, it enters bypass mode, that is, the gas pressure at the beginning of the compressor station is equal to the gas pressure at the end. After the power supply is restored, the electrically driven compressor station will keep the outlet pressure at the set value; constraint (15) is a flow constraint of the compressor station; constraint (16) indicates that the outlet pressure of the non-electrically driven gas source is always at the set value; constraint (17) indicates that after the power supply is lost, the electrically driven gas source does not have the ability to control the outlet pressure. After the power supply is restored, the electrically driven gas source will keep the outlet pressure at the set value; constraints (18) and (19) are upper and lower limit constraints of gas source output. For the electrically driven gas source, after the power supply is lost, it does not have the ability to supply gas; constraint (20) is the natural gas consumption of the load node.

[0175] The pressure constraint of the electric-driven compressor station (14) and the pressure constraint of the electric-driven gas source (17) are constraints containing conditional judgments. In this embodiment 1, the "big M method" is used to process the constraints, and a very large positive integer N is introduced to transform it into a linear inequality constraint.

[0176]

[0177]

[0178]

[0179]

[0180] Finally, in this embodiment 1, the natural gas supply constraint modeling for the gas turbine unit is as follows:

[0181]

[0182] In the formula: utf,i is a 0-1 integer decision variable, representing whether the gas turbine unit has the conditions for gas supply. If it does, the value is 1; otherwise, the value is 0. Πtn-f,i is the gas pressure at the gas supply node of the gas turbine unit. Π f,i SF represents the minimum gas pressure requirement for the gas supply node of the gas turbine unit; SF represents the collection of gas turbine units in the system.

[0183] Constraint (25) is the gas pressure requirement of the gas turbine unit for the gas supply node. The successful start-up and normal operation of the gas turbine unit require the gas supply pressure to reach a certain value. If the gas supply node pressure is too low, the gas turbine unit will experience operational failure or even shutdown. When the gas pressure of the gas supply node of the gas turbine unit is restored to above the minimum gas pressure value, the natural gas supply of the gas turbine unit is restored.

[0184] Given that the Wendroff difference scheme has second-order accuracy, second-order accuracy difference schemes generally suffer from numerical oscillation problems near discontinuities. Discontinuities occur at the pipeline gas pressure boundary during the electric-driven compressor station and gas source recovery process, which may lead to oscillations when calculating the numerical solution. To ensure the accuracy of the decision, this paper adopts the method of averaging the gas pressure values ​​of consecutive time periods to handle numerical oscillations, and verifies in the example analysis section that the proposed processing method can meet the decision requirements. Constraint (25) is processed as follows:

[0185]

[0186] In the formula, The average gas pressure during the period when the gas supply node of the gas turbine unit is connected.

[0187] Finally, in this second embodiment, the gas turbine supply analysis method considering the dynamic process of the natural gas network under a major power outage scenario is applied to... Figure 1 The test system shown.

[0188] exist Figure 1In the test system shown, G1, G2, G4, G6, and G8 are gas turbine units, CP1 and CP2 are electrically driven compression stations; GS3 is an electrically driven gas source, and the other gas sources are non-electrically driven gas sources. The test scenario is that after a major power outage, the natural gas pipeline network operates under low gas pressure and limited natural gas supply, affecting the gas supply of the gas turbine units; the power grid performs a black start, and grid loads 7, 25, and 29 recover at 120 minutes, 140 minutes, and 100 minutes, respectively.

[0189] according to Figure 1 Based on the test system and scenario information shown, a mixed-integer linear programming model for gas turbine unit gas supply recovery considering the dynamic process of the natural gas network was established. The model was solved to obtain the timing of gas turbine unit gas supply recovery. The solution results are shown in Table 1 and... Figure 2 As can be seen, the gas turbine unit gas supply analysis method considering the dynamic process of the natural gas network described in Embodiment 2 accurately depicts the dynamic process of gas pressure in the natural gas network during the recovery process and effectively determines the gas turbine unit gas supply recovery time.

[0190] Table 1

[0191]

[0192] Example 3

[0193] Embodiment 3 of the present invention provides a non-transitory computer-readable storage medium for storing computer instructions. When the computer instructions are executed by a processor, a gas turbine unit gas supply recovery prediction method is implemented. The method includes:

[0194] The partial differential equations describing dynamic flow are linearized and transformed into linear constraints using the finite difference method.

[0195] Based on linear constraints, a dynamic constraint model of the natural gas pipeline network is constructed to reflect the impact of electric-driven compressors and electric-driven gas source recovery on the natural gas pipeline network.

[0196] Based on the initial and boundary constraints given by the natural gas pipeline network, the dynamic constraint model of the natural gas pipeline network is solved to obtain the dynamic distribution of gas pressure and flow rate.

[0197] A natural gas supply constraint model for gas turbine units is constructed based on the dynamic distribution of gas pressure and flow rate.

[0198] The natural gas supply constraint model for the gas turbine unit is calculated to obtain the natural gas supply recovery time.

[0199] Example 4

[0200] Embodiment 4 of the present invention provides a computer program (product), including a computer program that, when run on one or more processors, is used to implement a gas turbine unit gas supply recovery prediction method, the method comprising:

[0201] The partial differential equations describing dynamic flow are linearized and transformed into linear constraints using the finite difference method.

[0202] Based on linear constraints, a dynamic constraint model of the natural gas pipeline network is constructed to reflect the impact of electric-driven compressors and electric-driven gas source recovery on the natural gas pipeline network.

[0203] Based on the initial and boundary constraints given by the natural gas pipeline network, the dynamic constraint model of the natural gas pipeline network is solved to obtain the dynamic distribution of gas pressure and flow rate.

[0204] A natural gas supply constraint model for gas turbine units is constructed based on the dynamic distribution of gas pressure and flow rate.

[0205] The natural gas supply constraint model for the gas turbine unit is calculated to obtain the natural gas supply recovery time.

[0206] Example 5

[0207] Embodiment 6 of the present invention provides an electronic device, including: a processor, a memory, and a computer program; wherein, the processor is connected to the memory, and the computer program is stored in the memory. When the electronic device is running, the processor executes the computer program stored in the memory to cause the electronic device to execute instructions for implementing a gas turbine unit gas supply recovery prediction method, the method including:

[0208] The partial differential equations describing dynamic flow are linearized and transformed into linear constraints using the finite difference method.

[0209] Based on linear constraints, a dynamic constraint model of the natural gas pipeline network is constructed to reflect the impact of electric-driven compressors and electric-driven gas source recovery on the natural gas pipeline network.

[0210] Based on the initial and boundary constraints given by the natural gas pipeline network, the dynamic constraint model of the natural gas pipeline network is solved to obtain the dynamic distribution of gas pressure and flow rate.

[0211] A natural gas supply constraint model for gas turbine units is constructed based on the dynamic distribution of gas pressure and flow rate.

[0212] The natural gas supply constraint model for the gas turbine unit is calculated to obtain the natural gas supply recovery time.

[0213] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0214] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0215] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0216] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment, whereby a series of operational steps are performed to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0217] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that, based on the technical solutions disclosed in the present invention, various modifications or variations that can be made by those skilled in the art without creative effort should be included within the scope of protection of the present invention.

Claims

1. A method for predicting the recovery of gas supply to a gas turbine unit, characterized in that, include: The partial differential equations describing dynamic flow are linearized and transformed into linear constraints using the finite difference method. Based on linear constraints, a dynamic constraint model of the natural gas pipeline network is constructed to reflect the impact of the restoration of electric-driven compressors and electric-driven gas sources on the natural gas pipeline network. This model includes initial constraints and boundary constraints. Initial constraints refer to the previous steady-state values ​​of the pipeline network, while boundary constraints refer to the boundary conditions at the pipeline ends, including node flow balance constraints, pressure boundaries, flow boundaries, and gas source supply limitations. The pressure boundaries include pressure constraints for the electric-driven compressor station and pressure constraints for the electric-driven gas source. The pressure constraint for the electric-driven compressor station indicates that if the electric-driven compressor station loses power, it enters bypass mode, meaning the gas pressure at the beginning of the compressor station is equal to the gas pressure at the end. After power is restored, the electric-driven compressor station will maintain the outlet pressure at the set value. The pressure constraint for the electric-driven gas source indicates that after power loss, the electric-driven gas source does not have the ability to control the outlet pressure. After power is restored, the electric-driven gas source will maintain the outlet pressure at the set value. Based on the initial and boundary constraints given by the natural gas pipeline network, the dynamic constraint model of the natural gas pipeline network is solved to obtain the dynamic distribution of gas pressure and flow rate. A natural gas supply constraint model for gas turbine units is constructed based on the dynamic distribution of gas pressure and flow rate. The natural gas supply constraint model for the gas turbine unit is calculated to obtain the natural gas supply recovery time.

2. The gas turbine unit gas supply recovery prediction method according to claim 1, characterized in that, Constructing a dynamic constraint model for the natural gas pipeline network, including: The mathematical model of one-dimensional isothermal flow of natural gas along a pipeline is characterized by a set of partial differential equations: （2）； （3）； （4）； In the formula: ω represents the density of natural gas; ω represents the flow velocity of natural gas. ρ is the natural gas pressure; g is the acceleration due to gravity; θ is the pipe inclination angle; D is the pipe diameter; λ is the pipe friction coefficient; c is the speed of sound of natural gas in the pipe; τ is time; x is the axial spatial distance of the pipe. Linearization is performed by introducing a base value for natural gas flow rate: （5）； Define the mass flow rate M as: （6）； In the formula: A is the cross-sectional area of ​​the pipe; Substituting equation (5) into momentum equation (2), and then into momentum equation (2) and continuity equation (3), we get: （7）； （8）； Equations (4), (7), and (8) form a set of linear partial differential equations describing the dynamics of a natural gas pipeline.

3. The gas turbine unit gas supply recovery prediction method according to claim 2, characterized in that, Using the Wendroff finite difference scheme, equations (4), (7), and (8) are transformed into algebraic equations, resulting in a set of linear algebraic equations (9)-(11) for the dynamic model of the natural gas pipeline network: （9）； （10）； （11）； In the formula: Natural gas node density; This refers to the gas pressure at the natural gas node. L represents the mass flow rate of natural gas flowing out of and into the pipeline, respectively. ij Δt is the differential space step size, i.e., the pipe length; Δt is the differential time step size, i.e., the recovery time period length; S N S represents the set of gas transmission nodes; P The collection of gas pipelines in the system; S T It is the set of all recovery periods.

4. The gas turbine unit gas supply recovery prediction method according to claim 3, characterized in that, Based on the initial and boundary conditions given by the gas pipeline network, the dynamic distribution of gas pressure and flow rate can be obtained by solving equations (9)-(11): （12）； （13）； （14）； （15）； （16）； （17）； （18）； （19）； （20）； In the formula: , These are 0-1 integer decision variables, representing the power supply status of the electric-driven compressor station and the electric-driven air source, respectively. If the power supply has been restored, the variable is set to 1; otherwise, it is set to 0. , , , These represent the outlet pressure setpoints for the non-electrically driven compressor station, the electrically driven compressor station, the non-electrically driven air source, and the electrically driven air source, respectively. , These represent the node pressures of the non-electrically driven gas source and the electrically driven gas source, respectively. , , These represent the pipeline natural gas flow rates for non-electrically driven gas sources, electrically driven gas sources, and natural gas loads, respectively. ns,i , M ns,i , s,i , M s,i These represent the upper and lower limits of the gas supply capacity of the non-electrically driven gas source and the electrically driven gas source, respectively; M l,i S represents the natural gas load; I S represents the set of pipe junctions; i→j S j→k These represent the natural gas inflow nodes. upstream nodes and natural gas outflow nodes The set of downstream nodes; S C S NC S S S NS S GL These represent the collections of electrically driven compressor stations, non-electrically driven compressor stations, electrically driven gas sources, non-electrically driven gas sources, and natural gas loads, respectively.

5. The gas turbine unit gas supply recovery prediction method according to claim 4, characterized in that, The pressure constraints of the electric-driven compressor station (14) and the pressure constraints of the electric-driven air source (17) are constraints containing conditional judgments. The constraints are processed using the "Big M method" by introducing a positive integer N to transform them into linear inequality constraints: （21）； （22）； （23）； （24）。 6. The gas turbine unit gas supply recovery prediction method according to claim 5, characterized in that, Construct a natural gas supply constraint model for gas turbine units, including: （25）； In the formula: The decision variable is an integer from 0 to 1, indicating whether the gas generator unit has the conditions for gas supply. If it does, the value is 1; otherwise, the value is 0. Gas pressure at the gas supply node of the gas turbine unit; This refers to the minimum gas pressure requirement for the gas supply node of the gas turbine unit; S F This represents the collection of gas turbine units in the system.

7. A gas turbine unit gas supply recovery prediction system, characterized in that, include: The transformation module is used to linearize the partial differential equations describing dynamic flow, and transforms them into linear constraints using the finite difference method. The first construction module is used to build a dynamic constraint model of the natural gas pipeline network based on linear constraints, reflecting the impact of the restoration of electric-driven compressors and electric-driven gas sources on the natural gas pipeline network. This model includes initial constraints and boundary constraints. Initial constraints refer to the previous steady-state values ​​of the pipeline network, while boundary constraints refer to the boundary conditions at the pipeline ends, including node flow balance constraints, pressure boundaries, flow boundaries, and gas source supply limitations. The pressure boundaries include pressure constraints for the electric-driven compressor station and pressure constraints for the electric-driven gas source. The pressure constraint for the electric-driven compressor station indicates that if the electric-driven compressor station loses power, it enters bypass mode, meaning the gas pressure at the beginning of the compressor station is equal to the gas pressure at the end. After power is restored, the electric-driven compressor station will maintain the outlet pressure at the set value. The pressure constraint for the electric-driven gas source indicates that after power loss, the electric-driven gas source does not have the ability to control the outlet pressure. After power is restored, the electric-driven gas source will maintain the outlet pressure at the set value. The first calculation module is used to solve the dynamic constraint model of the natural gas pipeline network based on the initial constraints and boundary constraints given by the natural gas pipeline network, and obtain the dynamic distribution of gas pressure and flow rate. The second building module is used to construct a natural gas supply constraint model for gas turbine units based on the dynamic distribution of gas pressure and flow rate; The second calculation module is used to calculate the natural gas supply constraint model of the gas turbine unit and obtain the natural gas supply recovery time of the gas turbine unit.

8. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium is used to store computer instructions, which, when executed by a processor, implement the gas turbine unit gas supply recovery prediction method as described in any one of claims 1-6.

9. A computer program product, characterized in that, Includes a computer program, which, when run on one or more processors, is used to implement the gas turbine unit gas supply recovery prediction method as described in any one of claims 1-6.

10. An electronic device, characterized in that, include: The device includes a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory to cause the electronic device to execute instructions to implement the gas supply recovery prediction method for the gas turbine unit as described in any one of claims 1-6.

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