Fault evolution analysis method for power transmission and distribution-gas integrated energy system under extreme typhoon disaster

Abstract

The invention provides a power transmission and distribution-gas integrated energy system fault evolution analysis method under an extreme typhoon disaster, and the method comprises the steps: calculating the time-varying fault probability of a power transmission and distribution network element based on a mechanical stress model of a typhoon wind-rain load, and generating an initial cut-off set through Monte Carlo sampling; through transmission-distribution network coupled affine load flow calculation, a serious overload line caused by load flow transfer is identified, and protection removal is executed; a dynamic affine model is adopted to analyze a power transmission and distribution-gas load shedding strategy, a natural gas pipe storage equation and electricity-gas coupling equipment operation constraint are combined, the influence of power line on pressure fluctuation and pipe storage change of a natural gas system is quantified, and overload power of a general overload line is balanced; processing a bilinear term, and converting non-convex constraint by adopting rotation second-order cone relaxation; and in combination with coupling operation constraints of an electrically-driven compressor, a gas turbine and power-to-gas equipment, a natural gas system fault propagation risk caused by power line breaking and power transmission and distribution-gas load shedding is quantified.

Description

Technical Field

[0001] The present invention belongs to the technical field of disaster prevention and mitigation and intelligent dispatching of power systems, and specifically relates to a fault evolution analysis method for an integrated power transmission and distribution and gas energy system under extreme typhoon disasters. Background Art

[0002] In recent years, the frequent occurrence of low-probability, high-loss extreme typhoon disasters has severely impacted the safe operation of integrated electricity-gas systems (IEGS). As typhoon paths and wind circles evolve, the high wind speeds and heavy loads of typhoons can generate strong mechanical stresses, causing initial faults and disconnections in power components of surface transmission and distribution networks. In reality, due to the deepening of energy interactions, faults induced by extreme typhoons will further evolve, exacerbating the risk of system-wide damage. However, existing research on energy system failures during typhoons often overlooks the propagation of faults within the power system and between the electrical and gas coupling, failing to clarify the fault evolution process of integrated electricity-gas systems during typhoons, making it difficult to accurately grasp the true faults induced by typhoons in IEGs. Furthermore, new integrated energy systems often incorporate a high proportion of renewable energy, resulting in intermittent and fluctuating output, and fluctuating system load demand. These factors significantly impact the load shortfall caused by system failures caused by typhoons. Existing research on failures during typhoons often ignores these source-load uncertainties, leading to biased formulation of subsequent recovery strategies and resulting in additional energy and economic losses.

[0003] Currently, research on typhoon-induced failures in energy systems primarily focuses on the impact of mechanical stresses caused by typhoons. This approach relies on calculating the probability of typhoon-induced power line failures. However, this approach overlooks the evolution of typhoon-induced failures in the integrated power transmission and distribution system, making it difficult to accurately capture the system failures caused by typhoons. In reality, after a typhoon causes initial failures in power components, the failures will further evolve within the power system and between the power and gas systems, inducing power line overloads and coupled power and gas failures. A few studies have analyzed the cascading failure process within the power system, but they do not subdivide the power system into the transmission and distribution networks, ignoring the power flow transfer relationship between the two during fault evolution, resulting in biased simulation results.

[0004] Furthermore, current research on energy system failures during typhoon disasters often relies on forecast information for modeling renewable energy output and load demand, rarely considering the impact of uncertainty on typhoon-induced failures. In practice, the forecast accuracy of renewable energy output and load demand during typhoon disasters is lower than in normal conditions, leading to increased uncertainty and a significant impact on failures and their evolution. Among traditional approaches to handling uncertainty, robust methods, due to overconservatism, may lead to an expansion of failure scenarios; interval methods struggle to reflect the impact of uncertain variables on failure evolution outcomes; and the variable distribution information required for stochastic optimization methods is difficult to obtain in extreme scenarios.

[0005] Furthermore, current research does not consider the actual situation of faults spreading from the power system to the natural gas system during typhoon disasters, and ignores the electric-gas coupled fault process, resulting in the fault scenario being limited to the power system. It is difficult to quantify the actual impact of surface typhoon disasters on the deep underground natural gas network, resulting in additional energy and economic losses.

[0006] Finally, existing research on energy system failures under typhoon disasters often fails to consider the differences in transmission speeds between electricity and gas energy flows, and ignores the time scale issue in the study of integrated energy system failures. In practice, the natural gas flow rate is much slower than the electric power flow, so the steady-state model used in traditional fault analysis methods is not completely accurate. Moreover, for the integrated energy system of transmission network, distribution network and gas transmission network, no research can clarify the failure evolution process under typhoon disasters. Summary of the Invention

[0007] To address the shortcomings and deficiencies of existing technologies—particularly the difficulty in quantifying the evolution of faults in integrated electrical energy systems during extreme typhoon disasters, the unclear cross-system fault propagation mechanism, and the inaccurate recovery strategies caused by source-load uncertainty—the present invention provides a method and system for analyzing the evolution of faults in integrated power transmission and distribution and gas energy systems. Its innovative design achieves full-chain fault tracing through a two-layer architecture with spatiotemporal decoupling. On a millisecond timescale, affine power flow calculations based on coordinated transmission and distribution network collaboration accurately capture line overload conditions caused by power flow transfers and prevent system collapse through protective disconnection mechanisms. On a minute-by-minute timescale, the system, combined with the slow dynamic characteristics of natural gas, quantifies the fault propagation effects of power load reduction strategies on deep-buried pipeline networks.

[0008] Innovatively integrate physical mechanisms and uncertainty processing: By using a normal distribution model of tower mechanical stress and a Markov process model of overhead lines, an initial tripping probability system under typhoon loads is constructed; the affine form of "center value + noise element" is used to analyze renewable energy output fluctuations and load demand disturbances, allowing power flow calculations to truly reflect source and load uncertainties; energy conversion constraints are established for electric-gas coupled equipment (gas turbines, power-to-gas devices, and electric-driven compressors), revealing the cross-system propagation path of air pressure instability caused by power load shedding.

[0009] Breaking through nonlinear bottlenecks at the solution level: McCormick's linear envelope method is used to handle bilinear terms in the load-shedding model. Rotating second-order cone relaxation is used to transform the gas network's pressure constraints, transforming the complex non-convex problem into an efficiently solvable convex optimization model. This solution, for the first time, achieves a closed-loop tracking of "initial disconnection → overload protection → load-shedding propagation → coupling analysis" during a typhoon, providing core technical support for disaster prevention and scheduling of integrated energy systems.

[0010] The technical solution specifically adopted by the present invention to solve the technical problem is: A fault evolution analysis method for power transmission and distribution-gas integrated energy system under extreme typhoon disasters: Based on the mechanical stress model of typhoon wind-rain load, the time-varying failure probability of transmission and distribution network components is calculated, and the initial interruption set is generated through Monte Carlo sampling; Based on the updated system topology, affine power flow calculation of the transmission-distribution grid coupling is used to identify severely overloaded lines caused by power flow transfer and perform protection removal. A dynamic affine model is used to analyze power-gas load shedding strategies for transmission and distribution. Combining the natural gas pipeline storage equation with the operational constraints of power-gas coupling equipment, the impact of power line interruptions on natural gas system pressure fluctuations and pipeline storage changes is quantified, and the overload power of generally overloaded lines is balanced. Bilinear terms are processed using the McCormick linear envelope method, and non-convex constraints are transformed using rotating second-order cone relaxation. The risk of natural gas system fault propagation caused by power load shedding is quantified by combining the coupled operating constraints of electric-driven compressors, gas turbines, and power-to-gas equipment.

[0011] Furthermore, the calculation of the time-varying failure probability is based on: Model the tower failure rate as a normal distribution function of equivalent wind speed; The overhead line failure rate is modeled as a Markov process of wind speed and rainfall.

[0012] Furthermore, the affine power flow calculation includes: Iteratively solve the power flow equations of the transmission and distribution networks through the master-slave splitting method; The influence of source load uncertainty on tidal current distribution is characterized based on affine arithmetic.

[0013] Furthermore, the dynamic affine model includes: Establish an affine optimization model based on linearized AC power flow for transmission network load shedding; Establish an affine constraint model based on DistFlow equation for load shedding in distribution network; A slow dynamic affine model combined with pipeline storage equations is established for natural gas network load shedding.

[0014] Furthermore, the rotational second-order cone relaxation includes: Decompose the Weymouth equation into bidirectional conduction constraints; Transform the squared pressure term using an auxiliary variable.

[0015] Furthermore, the fault propagation path includes: The electric drive compressor stops running, causing the node air pressure to fall below the operating threshold and become unstable; Gas load and gas turbine power supply interruption triggered by gas grid pressure fluctuations.

[0016] Furthermore, the operating constraints of the electrical-pneumatic coupling device include: Affine consumption characteristic equation of gas turbine; Affine energy conversion equation for power-to-gas equipment; Affine power equation for an electrically driven compressor.

[0017] And, a fault evolution analysis system for an integrated power transmission and distribution and gas energy system under extreme typhoon disasters, comprising: Initial trip generation module: This module is configured to use a mechanical stress model based on typhoon wind-rain loads, calculate the time-varying failure probability of transmission and distribution network components, and generate an initial trip set through Monte Carlo sampling. Overload protection control module: Based on the updated system topology, it is configured to identify severely overloaded lines caused by power flow transfer and execute protection removal instructions through affine power flow calculation of the transmission-distribution network coupling; Load Shedding Propagation Analysis Module: This module is configured to use a dynamic affine model to analyze power-gas transmission and distribution load shedding strategies. This module combines the natural gas pipeline storage equation with the operating constraints of power-gas coupled equipment to quantify the impact of power line interruptions on natural gas system pressure fluctuations and pipeline storage changes, and balances the overload power of generally overloaded lines. Fault Risk Quantification Module: This module is configured to quantify the risk of natural gas system fault propagation caused by power line disconnection and transmission and distribution power-gas load shedding, incorporating constraints on power-gas coupled equipment. Nonlinear solver engine: Configured to handle bilinear terms via McCormick's linear envelope method and transform non-convex constraints via rotated second-order cone relaxation.

[0018] Furthermore, the nonlinear solution engine includes: Gas network constraint conversion unit: configured to decompose the Weymouth equation into bidirectional conduction constraints; Auxiliary variable processing unit: configured to convert the square term of air pressure through auxiliary variables; Second-Order Cone Relaxation Element: Configured to construct a rotational second-order cone constraint group.

[0019] Furthermore, the load shedding propagation analysis module is connected to the SCADA system for real-time acquisition of: Transmission network node voltage data; Gas network pipeline pressure data.

[0020] And, a computer device includes a memory, a processor and a computer program stored in the memory, and the processor implements the above method when executing the computer program.

[0021] A non-transitory computer-readable storage medium stores a computer program, which implements the method described above when executed by a processor.

[0022] Compared with the prior art, the present invention and its preferred embodiments have at least the following beneficial effects: 1. Breakthrough in the ability to track the evolution of electrical-gas system faults This pioneering two-layer spatiotemporal decoupling architecture accurately captures line overloads caused by power flow shifts at the millisecond timescale, while simultaneously quantifying the slow dynamic response of the gas grid at the minute scale. This mechanism overcomes the technical blind spot of traditional methods that ignore differences in energy flow transmission speeds (electricity travels at near-light speed, compared to natural gas's approximately 10 m / s flow rate).

[0023] 2. Improved accuracy of uncertainty analysis in extreme scenarios A "central value + noise element" model based on affine arithmetic embeds renewable energy output fluctuations and load demand disturbances into the entire fault evolution process. Compared with traditional robust optimization or stochastic programming methods, this significantly reduces the impact of source-load forecast bias on analysis results during typhoon disasters.

[0024] 3. Visualization of cross-system fault propagation paths By modeling the operational constraints of coupled equipment such as electric compressors and gas turbines, the researchers revealed for the first time the path by which surface typhoon hazards affect deeply buried gas pipelines. For example, the failure of an electric compressor can trigger a chain reaction of pressure instability, providing clear intervention targets for halting the propagation of faults.

[0025] 4. Optimizing the efficiency of solving complex models The McCormick envelope method and rotating second-order cone relaxation technique are used to effectively handle bilinear terms and non-convex constraints in the load shedding model. Field testing has shown that this method improves the solution speed of large-scale systems while maintaining accuracy.

[0026] 5. Enhanced compatibility with high proportion of new energy The affine model adaptively handles the high fluctuation characteristics of wind and solar power output, fills the gap in disaster analysis of integrated energy systems containing high-penetration new energy, and supports accurate modeling of new energy penetration scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments: Figure 1 A schematic diagram of the IEGS fault evolution process under a typhoon disaster modeled by an embodiment of the present invention; Figure 2 This is an overall flow chart of an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to make the features and advantages of the present invention more clearly understood, the following embodiments are given for detailed description: It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meanings as those commonly understood by those skilled in the art to which this application belongs.

[0029] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0030] This paper addresses the issue of power line overload and electric-gas coupled failures caused by initial typhoon-induced power component failures. It proposes a fault evolution analysis method for an integrated power transmission and distribution system under extreme typhoon disasters. By comprehensively considering the impact of typhoon wind and rain load stresses, the initial fault interruption of system power components is identified. Then, considering the coupled connection between the transmission and distribution networks, an affine power flow calculation model for the constructed transmission and distribution network under typhoon disasters is solved based on a master-slave split power flow calculation method. This model considers power flow transfer under source-load fluctuations and analyzes the protective interruption of severely overloaded lines caused by power flow transfer over very short timescales. Next, load reduction measures are implemented in the integrated power transmission and distribution system to eliminate the safety hazards of generally overloaded lines and balance system power. Affine arithmetic is used to analyze the supporting role of renewable energy sources during the load reduction process and the impact of load demand fluctuations. Furthermore, the impact of disturbances on the gas grid is considered over a longer timescale, and a model is constructed based on the slow dynamic characteristics of the gas grid and the steady-state characteristics of the power system to understand the process of electric-gas coupled failures. This method simulates the fault evolution process of the power transmission and distribution-gas integrated energy system under typhoon disasters, can effectively track the impact of source-load fluctuations on system fault conditions, and provide a reference for the formulation of recovery strategies.

[0031] Its main design points include: (1) A two-layer affine fault evolution model for the power transmission and distribution integrated energy system under typhoon disasters is constructed. The power system is subdivided into the transmission network and the distribution network. The process of fault evolution within the power system and between the power and gas systems, which induces power line overload and power-gas coupling faults, is considered. Affine arithmetic is used to deal with the source and load uncertainty in the evolution of typhoon-induced faults. (2) The upper layer constructs an affine line overload protection disconnection model for the transmission-distribution network under typhoon disasters: Considering the coupling connection between the transmission and distribution networks, based on the master-slave split power flow calculation method, the constructed affine power flow calculation model of the transmission-distribution network under typhoon disasters is solved. Considering the power flow transfer under source-load fluctuations, the power flow transfer caused by the severe overload line protection disconnection in an extremely short time scale is analyzed. In this process, due to the difference in the transmission speed of different energy flows of electricity and gas, the state of the natural gas network is almost unchanged; (3) The lower layer constructs an affine load reduction model for the power transmission and distribution-gas integrated energy system under typhoon disasters: In order to eliminate the safety hazards of general overloaded lines in the upper layer model and maintain the power balance of the system, load reduction measures are implemented for the power transmission and distribution-gas integrated energy system. Based on affine arithmetic analysis, the auxiliary role of new energy and the impact of load demand fluctuations in the load reduction process are analyzed. The implementation of load reduction measures takes a certain amount of time, and the impact of disturbances on the gas grid should be considered on a longer time scale. Therefore, the present invention takes into account the actual situation of faults spreading from the power system to the natural gas system under typhoon disasters, and models them based on the slow dynamic characteristics of the gas grid and the steady-state characteristics of the power system to grasp the power-gas coupled fault process. Among them, the McCormick envelope and rotating second-order cone method are used to convexify the affine non-convex terms in the model.

[0032] The following describes the implementation process of the above solution of the present invention through specific embodiments: 1. Fault evolution process of power transmission and distribution-gas integrated energy system under typhoon disaster As the typhoon's path and wind circle continue to develop, its high wind speeds and heavy loads will generate strong mechanical stress, causing initial faults and disconnections in power components of the surface transmission and distribution network. This type of fault represents the typhoon's initial disturbance to the IEGS, known as "initial disconnection."

[0033] The fault then evolves further within the IEGS. The system topology change caused by the initial trip triggers a power flow shift, leading to power flow overloads on some lines. Line power flow overloads are categorized as severe or moderate. The system will quickly initiate a protective trip on the severely overloaded line, further altering the system topology. Because the transmission speed of electricity approaches the speed of light, while that of natural gas is only approximately 10 m / s, the state of the natural gas grid barely changes during the instant when a power line is severely overloaded and tripped. After the severe overloaded line is tripped, the system must implement load shedding measures to eliminate safety hazards on the moderately overloaded line and maintain power balance.

[0034] Compared to the short-term protective tripping of severely overloaded lines, system load shedding requires significant time, and the impact of disturbances on the natural gas network must be considered. Line tripping and system load shedding may cause electrically driven coupling equipment to shut down, triggering electrical-gas coupling failures. Therefore, even if a typhoon is a surface disaster, it can still impact the deeply buried natural gas network. For example, the shutdown of an electrically driven compressor can cause a severe decompression in the natural gas pipeline, leading to airflow blockage and impacting the natural gas supply to gas load nodes. Furthermore, the natural gas network may reduce its energy support to the power system, compromising the resilience and mutual support between subsystems.

[0035] In summary, the IEGS fault evolution process under typhoon disaster constructed in this embodiment is as follows: Figure 1 As shown, it includes: "initial disconnection" of power components, power line overload and electric-pneumatic coupling fault.

[0036] 2. Initial disconnection model of power components under typhoon disaster A coordinate system is established based on the geographical location of the system, and the typhoon-related moving path is obtained through weather forecast information. The moving path is depicted with the typhoon eye position as the center, as shown in the formula: shown.

[0037] Where: x t and y t represents the coordinates of the typhoon center at time t; x t-1 and y t-1 Indicates the coordinates of the typhoon center at time t-1; Indicates the direction angle of the typhoon's movement; v t is the moving speed; Δt is the time interval.

[0038] The Batts model is used to model the symmetrical wind field of a typhoon, as shown in Eq. - shown.

[0039] Where: R max is the maximum radius of the typhoon's wind circle; ΔP tis the pressure difference between the periphery and the center of the typhoon at time t (hPa); v gx is the vertical speed of the typhoon; θ is the empirical coefficient; f is the Coriolis force coefficient of the earth's rotation; v Rmax is the maximum wind speed of the typhoon; v t is the horizontal speed of the typhoon; V rin and V rout The distance between the line and the typhoon eye is not greater than or greater than R max : The instantaneous wind speed at the time of landing; r is the distance between the line and the typhoon eye; x is the typhoon intensity attenuation parameter; ΔP0 is the pressure difference between the periphery and the center of the typhoon at the initial moment (hPa); γ is the angle between the typhoon and the coastline at the time of landfall; t is the time from the current moment to the initial moment.

[0040] In addition to strong wind loads, typhoon rain loads will also impose stress on the system towers. The stress effect of the load can be measured by calculating the equivalent wind speed, as shown in the formula: shown.

[0041] Where: is the equivalent wind speed of the tower z at a height of 10 m at time t; V 10,z,t is the average wind speed at the moment before z at a height of 10 m at time t; H z,t is the average rainfall at tower z just before time t; a equ 、b equ 、c equ d equ 、e equ is the equivalent coefficient.

[0042] Assuming that the fragility of the tower conforms to the normal distribution, the failure rate R of tower z at time t is calculated using the equivalent wind speed z,t As shown.

[0043] Where: R z,t is the failure rate of tower z at time t; z,t and μ z,t is the standard deviation and average value of the equivalent wind speed of tower z at time t; x is the ln( ).

[0044] In addition to towers, overhead lines will also be directly affected by typhoons. The time-varying failure rate of overhead lines can be calculated as ij,t As shown.

[0045] Where: ij,t is the time-varying fault rate of the overhead line at time t; L ij is the line length; α ij , β ij and γ ij is the correlation coefficient; V ij,t and V des are the average wind speed and wind speed design value of line ij in the period before time t; H ij,t and H des are the average rainfall and design rainfall value of line ij in the period before time t, respectively.

[0046] Solving the overhead line failure rate R based on Markov process ij,t As shown.

[0047] Where: R ij,t is the overhead line failure rate at time t; R ij,t-1 is the overhead line failure rate at t-1.

[0048] The collapse of the tower will cause the failure of the entire line. Combining the failure probabilities of the towers and overhead lines, the total line failure probability of the system is calculated R all,ij,t As shown.

[0049] Where: R all,ij,t is the total line failure probability of the system at time t.

[0050] Finally, the Monte Carlo sampling and system information entropy methods are combined to determine the fault state of the power components and obtain the "initial disconnection" of the system. shown.

[0051] Where: W s is the system information entropy value; Ω B Represents the total line set of the transmission and distribution network; g i,t Indicates whether line ij has a fault at time t, if so, it is 1, otherwise it is 0.

[0052] The reasonable entropy value cannot be too large or too small, as shown in the formula shown.

[0053] Where: W min and W max are the minimum and maximum values ​​of information entropy respectively.

[0054] 3. Two-layer affine fault evolution model of power transmission and distribution-gas integrated energy system under typhoon disaster (1) Affine modeling of uncertain variables In order to consider the impact of source-load uncertainty fluctuations on the fault evolution analysis of the gas transmission and distribution system, the present invention characterizes the uncertain variables as a combination of central values ​​and noise elements based on the affine theory, as shown in Equation shown.

[0055] Where: P DG,i,t is the active output noise element coefficient of distributed renewable energy i at time t; is the affine analytical expression of the active power output of distributed renewable energy i at time t; P DG,i,t,0 is the active power output center value of distributed renewable energy i at time t; ε DG,i,t is the noise element of the active power output of distributed renewable energy i at time t; P T,i,t 、P D,m,t and F L,p,t are the noise element coefficients of the active load i of the transmission network, the active load m of the distribution network, and the gas load p at time t; 、 and are the affine analytical expressions of the active load i of the transmission network, the active load m of the distribution network, and the gas load p at time t; P T,i,t,0 、P D,m,t,0 and F L,p,t,0 are the central values ​​of the active load i of the transmission network, the active load m of the distribution network, and the gas load p at time t; ε T,i,t , ε D,m,t and ε L,p,t are the noise elements of the transmission network active load i, distribution network active load m and gas load p at time t respectively.

[0056] (2) Transmission-distribution network emulation line overload protection interruption model under upper-level typhoon disaster In order to consider the system power flow transfer affected by source-load fluctuations under typhoon disasters, the power and node voltage are represented as affine analytical expressions. Then, according to the power balance equation of the power system, the affine power flow calculation model of the transmission-distribution network can be constructed as follows: shown.

[0057] In the formula: superscript “ " indicates conjugation; IPQ , I PV and I PH are the sets of PQ, PV and balance nodes respectively; N e is the number of system nodes; Y ik is the (i, k)th element of the node admittance matrix; is the affine voltage of node k; is the conjugate number of the affine injection power of node i; is the conjugate number of the affine voltage at node i; and is the affine injected active power and affine reactive power of node i; j is the imaginary unit; is the affine voltage of node i; The voltage value given for the balance node; The voltage amplitude given to the PV node.

[0058] The basic iterative form of master-slave splitting is used to calculate the transmission and distribution network power flow. The specific steps are as follows: Step 1: Set the power interaction nodes between the networks, assign them initial voltage values, and set the number of iterations to 0.

[0059] Step 2: Calculate the distribution network power flow equation using the boundary node voltage updated in the previous iteration. If this is the first iteration, calculate using the initial value.

[0060] Step 3: Calculate the transmission network power flow equation using the boundary node voltages obtained in step 2. After the distribution and transmission network power flow calculations, update the boundary node voltages and the number of iterations.

[0061] Step 4: Determine whether the boundary node voltage difference between two adjacent iterations is less than the convergence threshold. If so, stop the iteration and output the power flow calculation results. Otherwise, return to step 2.

[0062] After the initial disconnection, the power flow shifts, and the line may become overloaded due to a significant change in transmission power. Overloaded lines are further divided into severely overloaded lines and generally overloaded lines. Severely overloaded lines, when the transmission power exceeds the critical limit, will trigger the protection device to operate and disconnect in a very short time, while generally overloaded lines can eliminate the overload through load reduction measures. The present invention constructs an affine expression for the protection disconnection of severely overloaded lines, as shown in Equation (16).

[0063] Where: is the affine active power flow of line ij; is the affine overload removal probability of line ij; p0 is the probability of hidden fault of line protection, which is extremely small; and are the normal limit and critical value of the transmission power of line ij respectively.

[0064] (2) Affine load reduction model for the power transmission and distribution-gas integrated energy system under lower-level typhoon disasters After the protection of the severely overloaded line is removed, the overload of the general overloaded line can be eliminated through load reduction measures. In addition, in order to deal with the unbalanced power generated by the line fault interruption, load reduction measures are urgently needed. Considering the difference in the transmission speed of electric energy and air flow, the transmission and distribution networks use a steady-state model, while the natural gas network uses a dynamic model. The affine objective function of the IEGS load reduction model is as follows: shown.

[0065] Where: 、 and are the affine analytical expressions of load loss of transmission, distribution and gas grid respectively; C T 、C D and C L are the load loss cost coefficients in the transmission, distribution and gas grids, respectively; 、 and are the residual rate affine analytical expressions of the active load i of the transmission network, the active load m of the distribution network and the gas load p at time t, reflecting the residual load situation; Ω TE ,Ω DE and Ω G are the node sets of transmission, distribution and gas grids respectively.

[0066] Affine load shedding modeling on the transmission grid side: To account for the reactive power impact of transmission-distribution grid interaction, a linearized AC power flow model is used. In addition, the constraints also include: unit output constraints , Unit climbing constraints , power balance constraints and safety constraints .

[0067] Where: 、 are affine equality and less than or equal to operators respectively; M is a sufficiently large positive number; Z T,ij,t is a binary variable representing the operating status of the transmission line ij at time t, which is 1 for normal operation and 0 otherwise; and are the affine active power and affine reactive power of line ij at time t; B ij and G ij are the mutual susceptance and mutual conductance between node i and node j respectively; and are the affine phase angles of node i and node j at time t; and are the affine voltages of node i and node j at time t respectively; and are the upper and lower limits of active power output of thermal power unit i respectively; and are the upper and lower limits of reactive power output of thermal power unit i respectively; and are the affine active and affine reactive outputs of thermal power unit i at time t; and are the affine active and affine reactive outputs of thermal power unit i at time t-1 respectively; and are the upper limits of the sliding and climbing rates of the active output of thermal power unit i, respectively; and are the upper limits of the sliding and climbing rates of the reactive output of thermal power unit i, respectively; is the affine active power output of gas turbine i at time t; is the affine power consumption of power-to-gas device i at time t; is the affine power consumption of the electrically driven compressor i at time t; is the affine surplus rate of reactive load i of the transmission network at time t; is the size of the affine reactive load i of the transmission network at time t; is the upper limit of the transmission power of branch ij; and are the upper and lower limits of the phase angle difference between nodes i and j respectively; and are the upper and lower limits of the voltage at node i; U ref,t and θ ref,t is the voltage and phase angle of the balance node at time t; U0 is the voltage value of the balance node.

[0068] Affine load reduction modeling on the distribution network side: Modeling based on the DistFlow power flow model, with constraints including active and reactive power balance constraints , load reduction constraints , branch voltage drop constraint , branch flow equation , node voltage constraints , branch current constraints and branch power flow constraints .

[0069] Where: , are the affine active and reactive powers flowing from node n to node m at time t; is the affine current flowing from node n to node m at time t; r mk and x mk are the resistance and reactance of branch mk respectively; , are the affine active and reactive powers flowing from node m to node k at time t; b1 and b2 are the initial node set of the branch with terminal node m and the end node set of the branch with initial node m, respectively; Z D,mk,t is a binary variable representing the operating status of line mk at time t, which is 1 when operating normally and 0 otherwise; and are the affine voltages of node m and node k at time t respectively; is the affine current flowing from node m to node k at time t; y m,t is a binary variable representing the working status of node m at time t, which is 1 when it is operating normally and 0 otherwise; and are the upper and lower limits of the voltage at node m respectively; and k are the upper and lower limits of the current flowing from node m to node k; and are the upper and lower limits of active power flowing from node m to node k respectively; and are the upper and lower limits of the reactive power flowing from node m to node k respectively.

[0070] Among them, the formula In order to reduce the complexity of the model solution, this embodiment uses variables and replace and , then the formula The affine analytical expression of is further processed into .

[0071] Where: is the auxiliary variable of the affine voltage of node m at time t; is the auxiliary variable of the affine current flowing from node m to node k at time t.

[0072] Mode In the example, expanding the affine equation yields the central value equation , the first-order constraint And the second-order constraint after second-order cone relaxation .

[0073] Where: P mk,t,0 , Q mk,t,0 are the central values ​​of the affine active and reactive power flowing from node m to node k at time t; P mk,t , Q mk,t are the noise element coefficients of the affine active and reactive power flowing from node m to node k at time t; u m,t,0 is the auxiliary variable center value of the affine voltage of node m at time t; l mk,t,0 u is the central value of the auxiliary variable of the affine current flowing from node m to node k at time t; m,t is the auxiliary variable noise element coefficient of the affine voltage of node m at time t; l mk,t is the auxiliary variable noise element coefficient of the affine current flowing from node m to node k at time t.

[0074] Among them, the first-order constraint The bilinear terms contained in will increase the difficulty of solving. The present invention uses McCormick envelope to process the bilinear terms in the affine first-order constraint, introduces auxiliary variables s, and , then use McCormick envelope processing to introduce the formula .

[0075] Where, l max and l min l mk,t The maximum and minimum values ​​of u max and u min u m,t The maximum and minimum values ​​of .

[0076] Formula It can be approximated as the following formula.

[0077] Affine load reduction modeling on the natural gas network side: Constraints include Weymouth equation constraints , node pressure constraint , pipeline flow constraints , Gas source output constraints , gas compressor constraints , node traffic balance constraints and load shedding constraints and custody constraints.

[0078] Where: Ωep, Ωsp and Ω C,p They are the first node set with node p as the end node, the last node set with node p as the first node, and the compressor set with node p as the entrance; is the affine average flow rate of pipe pq at time t; sgn() is the sign function; W pq is the pipeline constant of pipeline pq; and are the affine air pressures at nodes p and q at time t; is the affine output of the gas source p at time t; is the affine flow rate of the compressor pipe h at time t; is the affine gas consumption of gas turbine p at time t; is the affine gas production of the power-to-gas device p at time t; is the affine head-end flow of pipe pq at time t; is the affine terminal flow of the pipeline lp at time t; is the affine terminal flow of pipe pq at time t; and are the upper and lower limits of the air pressure at node p respectively; and are the upper and lower limits of the output of the gas source p respectively; is the flow rate upper limit of compressor h; and They are the upper and lower limits of the compression factor of the compressor respectively; and are the upper flow limits of pipeline pq and compressor pipeline h respectively; is the affine pipe memory of the pipe pq at time t; is the affine pipe memory of pipe pq at time t-1; S pq is the pipe storage constant of pipe pq; Ω GA is a collection of pipelines; is the affine pipe memory of the pipeline pq at the initial moment.

[0079] In addition, the large M method and the second-order cone relaxation method are combined to deal with non-convex nonlinear equations. Weymouth equation. Different from the fixed pipeline flow direction in day-ahead scheduling, a bidirectional pipeline model is used to meet the needs of different time periods. Therefore, the state variable pq,t Instead of the symbol function sgn( ), pq,t =1 means ≥ 0, otherwise pq,t = 0 means ≤ 0, formula Equivalent to the formula - .

[0080] Where: pq,t is the state variable that represents the flow direction of pipeline pq at time t.

[0081] Introduce auxiliary variable u p,t and v q,t , will be Convert to - .

[0082] Where: u p,t and v q,t is an auxiliary variable representing the air pressure at nodes p and q at time t.

[0083] Finally, the non-convex formula Transformed into a rotational second-order cone constraint, as shown.

[0084] The affine coupling constraints between subsystems include: the consumption characteristic equation of the gas turbine , Energy conversion equation of power-to-gas equipment , Power equation for electric drive compressor And the power transfer node equation between the transmission and distribution network .

[0085] Where: η gt and η p2g are the conversion efficiencies of gas turbines and power-to-gas equipment, respectively; H HV It is the high calorific value of natural gas; is the upper limit of power consumption of power-to-gas equipment i; K c,1 and K c,2 is the compressor parameter; k cp is the compression ratio; and are the affine active and reactive load reduction rates of the transmission network at the transmission-distribution interaction node i at time t, respectively; and are the affine active and reactive loads of the transmission network at the transmission-distribution interaction node i at time t; and are the total injected affine active and reactive powers of the distribution network at the transmission-distribution interaction node i at time t, respectively.

[0086] like Figure 2As shown, based on the above design, the specific steps of the fault evolution analysis method of the power transmission and distribution-gas integrated energy system under extreme typhoon disasters proposed by the present invention are as follows: Step 1: Input typhoon forecast information and network parameters and coupling equipment parameters of the electricity and gas integrated energy transmission and distribution system; Step 2: Based on the proposed initial disconnection model of power components under typhoon disasters, the failure probability of the power lines in the transmission and distribution networks is calculated according to equations (1)-(11), the fault set of the power lines is obtained through Monte Carlo sampling, and the fault probability of the power lines is calculated according to equations (1)-(11). Calculate the system information entropy under different sampling results, according to the formula Obtain the power line fault status and determine whether the system has initially disconnected the power line. If so, output the result and execute step 3. Otherwise, execute step 5. Step 3: Update the system topology according to the fault condition of the power line. Based on the proposed simulative line overload protection disconnection model of the transmission and distribution network under the upper typhoon disaster, according to the formula Combined with the iterative form of master-slave splitting, the power flow transfer distribution of the transmission-distribution network under the influence of source-load fluctuations is calculated. The iterative steps are as follows: (1) Set the power interaction nodes between the networks and assign them the initial voltage value. Set the number of iterations to 0. (2) Calculate the distribution network power flow equation using the boundary node voltage updated in the previous iteration. If it is the first iteration, calculate with the initial value. (3) Calculate the transmission network power flow equation using the boundary node voltages obtained in (2). After the distribution and transmission network power flow calculations, update the boundary node voltages and the number of iterations; (4) Determine whether the boundary node voltage difference between two adjacent iterations is less than the convergence threshold. If so, stop the iteration and output the power flow calculation results. Otherwise, return to (2).

[0087] According to the output transmission and distribution network flow calculation results, it is determined whether the transmission power of any line exceeds its critical limit value, that is, whether there is a seriously overloaded line. If so, according to the formula Execute protection removal, update the system topology, and re-execute step 3 to further consider the possible subsequent power flow transfer. If no power flow transfer exists, execute step 4. Step 4: In order to eliminate the safety hazards of general overloaded lines and balance the system power, based on the proposed affine load reduction model of the power transmission and distribution-gas integrated energy system under the lower typhoon disaster, according to Eq. - Implement system load reduction measures taking into account the uncertainty of source load, and use the objective function Output the affine load shedding distribution of the electricity transmission and distribution-gas integrated energy system, and then execute step 5; Step 5: According to the formula - Obtain the operating status of the electric-gas coupling equipment and the transmission-distribution network interaction node, and obtain the electric-gas coupling fault result by combining the system's affine load shedding distribution and operating status, and then execute step 6; Step 6: According to the formula - The typhoon model determines whether the typhoon has passed through the system. If so, the process ends, otherwise it returns to step 2.

[0088] Based on the same inventive concept, the present invention also provides a computer device, which includes: one or more processors, and a memory for storing one or more computer programs; the program includes program instructions, and the processor is used to execute the program instructions stored in the memory. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is used to implement one or more instructions, specifically for loading and executing one or more instructions in a computer storage medium to implement the above method.

[0089] It should be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium having a computer program stored thereon, which, when executed by a processor, performs the above-described method. The storage medium may be any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0090] It should be noted that, unless otherwise defined, the technical or scientific terms used in the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0091] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other manner. Any person skilled in the art may utilize the above-disclosed technical content to modify or modify the present invention into equivalent embodiments. However, any simple modifications, equivalent variations, and modifications to the above embodiments that do not depart from the technical content of the present invention and are based on the technical essence of the present invention remain within the scope of protection of the present invention.

[0092] The present invention is not limited to the above-mentioned optimal implementation mode. Anyone can derive a fault evolution analysis method for the power transmission and distribution-gas integrated energy system under various other forms of extreme typhoon disasters under the inspiration of the present invention. All equal changes and modifications made according to the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. A method for analyzing the fault evolution of an integrated power transmission and distribution and gas energy system under extreme typhoon disasters, characterized by: Based on the mechanical stress model of typhoon wind-rain load, the time-varying failure probability of transmission and distribution network components is calculated, and the initial interruption set is generated through Monte Carlo sampling; Based on the updated system topology, affine power flow calculation of the transmission-distribution grid coupling is used to identify severely overloaded lines caused by power flow transfer and perform protection removal. A dynamic affine model is used to analyze power-gas load shedding strategies for transmission and distribution. Combining the natural gas pipeline storage equation with the operational constraints of power-gas coupling equipment, the impact of power line interruptions on natural gas system pressure fluctuations and pipeline storage changes is quantified, and the overload power of generally overloaded lines is balanced. Bilinear terms are processed using the McCormick linear envelope method, and non-convex constraints are transformed using rotating second-order cone relaxation. Combined with the coupled operating constraints of electric-driven compressors, gas turbines, and power-to-gas equipment, the risk of natural gas system fault propagation caused by power line disconnection and transmission and distribution power-gas load shedding is quantified.

2. The method for analyzing the fault evolution of an electric power and gas integrated energy system under extreme typhoon disasters according to claim 1 is characterized by: The calculation of the time-varying failure probability is based on: Model the tower failure rate as a normal distribution function of equivalent wind speed; The overhead line failure rate is modeled as a Markov process of wind speed and rainfall.

3. The method for analyzing the fault evolution of an electric power and gas integrated energy system under extreme typhoon disasters according to claim 1 is characterized by: The affine power flow calculation includes: Iteratively solve the power flow equations of the transmission and distribution networks through the master-slave splitting method; The influence of source load uncertainty on tidal current distribution is characterized based on affine arithmetic.

4. The method for analyzing the fault evolution of an electric power transmission and distribution integrated energy system under extreme typhoon disasters according to claim 1 is characterized in that: The dynamic affine model includes: Establish an affine optimization model based on linearized AC power flow for transmission network load shedding; Establish an affine constraint model based on DistFlow equation for load shedding in distribution network; A slow dynamic affine model combined with pipeline storage equations is established for natural gas network load shedding.

5. The method for analyzing the fault evolution of an electric power transmission and distribution integrated energy system under extreme typhoon disasters according to claim 1 is characterized by: The rotational second-order cone relaxation includes: Decompose the Weymouth equation into bidirectional conduction constraints; Transform the squared pressure term using an auxiliary variable.

6. The method for analyzing the fault evolution of an electric power transmission and distribution integrated energy system under extreme typhoon disasters according to claim 1 is characterized by: The fault propagation path includes: The electric drive compressor stops running, causing the node air pressure to fall below the operating threshold and become unstable; Gas load and gas turbine power supply interruption triggered by gas grid pressure fluctuations.

7. The method for analyzing the fault evolution of an electric power transmission and distribution integrated energy system under extreme typhoon disasters according to claim 1 is characterized by: The operating constraints of the electric-pneumatic coupling equipment include: Affine consumption characteristic equation of gas turbine; Affine energy conversion equation for power-to-gas equipment; Affine power equation for an electrically driven compressor.

8. A fault evolution analysis system for power transmission and distribution-gas integrated energy system under extreme typhoon disasters, characterized by: include: Initial trip generation module: This module is configured to use a mechanical stress model based on typhoon wind-rain loads, calculate the time-varying failure probability of transmission and distribution network components, and generate an initial trip set through Monte Carlo sampling. Overload protection control module: Based on the updated system topology, it is configured to identify severely overloaded lines caused by power flow transfer and execute protection removal instructions through affine power flow calculation of the transmission-distribution network coupling; Load Shedding Propagation Analysis Module: This module is configured to use a dynamic affine model to analyze power-gas transmission and distribution load shedding strategies. This module combines the natural gas pipeline storage equation with the operating constraints of power-gas coupled equipment to quantify the impact of power line interruptions on natural gas system pressure fluctuations and pipeline storage changes, and balances the overload power of generally overloaded lines. Fault Risk Quantification Module: This module is configured to quantify the risk of natural gas system fault propagation caused by power line disconnection and transmission and distribution power-gas load shedding, incorporating constraints on power-gas coupled equipment. Nonlinear solver engine: Configured to handle bilinear terms via McCormick's linear envelope method and transform non-convex constraints via rotated second-order cone relaxation.

9. The fault evolution analysis system for the power transmission and distribution-gas integrated energy system under extreme typhoon disasters according to claim 8 is characterized by: The nonlinear solution engine includes: Gas network constraint conversion unit: configured to decompose the Weymouth equation into bidirectional conduction constraints; Auxiliary variable processing unit: configured to convert the square term of air pressure through auxiliary variables; Second-Order Cone Relaxation Element: Configured to construct a rotational second-order cone constraint group.

10. The fault evolution analysis system for the power transmission and distribution-gas integrated energy system under extreme typhoon disasters according to claim 8, characterized in that: The load shedding propagation analysis module is connected to the SCADA system to obtain in real time: Transmission network node voltage data; Gas network pipeline pressure data.

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