A power grid typhoon fault analysis and dispatching method and system considering time accumulation

Abstract

This invention discloses a method and system for power grid typhoon fault analysis and scheduling considering time accumulation. The method includes: obtaining the wind speed sensed by equipment at various time periods during the typhoon evolution process based on power grid topology and typhoon data; performing tower failure probability evolution considering the time accumulation effect; calculating the failure rate of conductors at different time periods and calculating the probability of conductor interruption; calculating the fault probability time series prediction curve for each line, and obtaining the line fault probability time series by combining it with the line operating status correction; analyzing the abnormal evolution process of the power grid under extreme typhoon weather conditions; obtaining the system abnormal state considering extreme weather factors and power flow redistribution; and generating a rescheduling scheme for restoring supply and demand balance. This invention can quantitatively predict the fault risk of lines throughout the entire typhoon life cycle. The prediction results reflect the different impacts of components with different structural forms and aging degrees on the overall reliability of the lines, and have high engineering applicability.

Description

Technical Field

[0001] This invention belongs to the technical field of power system disaster prevention and mitigation and operation risk assessment, and relates to a power grid typhoon fault analysis and dispatching method and system that considers time accumulation. Background Technology

[0002] In recent years, against the backdrop of global warming, typhoons and severe tropical storms making landfall in coastal areas have shown a trend of increasing frequency and intensity. Extreme weather conditions such as strong winds and torrential rains pose serious threats to wind farms, transmission lines, and distribution networks, causing large-scale power outages and severely impacting the safe and stable operation of the power system and urban socio-economic development.

[0003] Existing research mainly focuses on two levels. One is power grid typhoon risk assessment and fault evolution modeling. Based on typhoon trajectories and wind field models, it establishes the relationship between the spatiotemporal distribution of wind speed and the abnormal states of power grid equipment, analyzing the spatiotemporal evolution of wind-induced fault probability, power flow redistribution, and cascading fault chains to quantify the power grid operational risks during typhoons. The other is distribution network / line fault probability modeling based on vulnerability curves. For equipment such as distribution network lines, towers, and substations, given known disaster intensity parameters such as wind speed and water level, it constructs wind-induced / flood vulnerability curves, providing the equipment failure probability at different wind speeds or water depths. Combined with dynamic network reconfiguration or microgrid partitioning, it assesses and optimizes post-disaster power supply resilience.

[0004] The above research provides a reference for typhoon-related power grid risk assessment and fault modeling: on the one hand, it presents the spatiotemporal mapping relationship between typhoon wind fields and equipment status; on the other hand, it provides a quantitative modeling approach for component vulnerability and fatigue accumulation. Among existing methods for typhoon-related power grid risk assessment and fault modeling, schemes considering spatiotemporal evolution treat tropical cyclones as spatiotemporal events, calculate wind speeds at different times using wind field models, and form a risk indicator system by combining multi-scenario power flow data; methods based on vulnerability curves utilize historical data and engineering experience to construct equipment failure probability curves, map wind and flood field data to obtain failure probabilities, and support dynamic reconfiguration of the distribution network; models based on linear fatigue accumulation use the Palmgren-Miner criterion to accumulate tower fatigue damage caused by wind loads at different times during the typhoon to determine the probability of failure. All three methods focus on fault probability or risk assessment under typhoon scenarios. Although existing schemes have achieved certain results, significant shortcomings remain: The lack of explicit time-cumulative effect in line future dynamic prediction capability, the separation of fatigue accumulation and vulnerability curve modeling makes it difficult to reflect the comprehensive wind load effect, ignores the impact of the coupling between power grid electrical operating conditions and meteorological load on failure probability, and makes it difficult to support proactive defense strategies such as pre-disaster differentiated inspection and reinforcement. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a power grid typhoon fault analysis and scheduling method and system that considers time accumulation. Based on typhoon trajectory and wind field evolution, it integrates the time accumulation effect and the coupling relationship of line operation status to predict transmission line faults, realizing dynamic fault risk prediction throughout the entire life cycle of a typhoon. It can be used for pre-disaster early warning, pre-arrangement of maintenance resources, and line reinforcement decisions.

[0006] The present invention adopts the following technical solution.

[0007] The first aspect of this invention proposes a power grid typhoon fault analysis and scheduling method considering time accumulation, comprising: Based on the power grid topology and typhoon data, the wind speeds sensed by the towers and conductors at various time points during the typhoon's evolution were obtained. The evolution of the tower failure probability is based on the wind speed sensed by the tower at different time periods, taking into account the cumulative effect of time, so as to obtain the cumulative probability of tower failure. Based on the wind speed sensed by the conductor at different time periods, the failure rate of the conductor caused by the wind pressure of the typhoon at different time periods is calculated, and then the probability of the conductor being interrupted is calculated. Based on the cumulative probability of tower failure and the probability of conductor interruption, the time series prediction curve of the failure probability of each line is calculated, and the line failure probability time series considering the operating status is obtained by combining the line operating status correction. Based on the time series of line failure probabilities, a spatiotemporal matrix of line failure probability under extreme typhoon weather conditions is constructed and sampled to obtain a spatiotemporal matrix of line operation status. At the same time, the abnormal power generation of each wind farm in each time period is collected to construct a spatiotemporal matrix of abnormal wind farm output. The abnormal state of the power grid system is deduced based on the time series of line fault probability, the spatiotemporal matrix of line operation status and the spatiotemporal matrix of wind farm abnormal output. Based on the abnormal state of the power grid system obtained from the simulation, a rescheduling strategy is generated to restore the supply and demand balance when the system is in a fault operation state.

[0008] Preferably, obtaining the wind speeds sensed by towers and conductors at various time periods during the typhoon's evolution based on the power grid topology and typhoon data includes: Obtain the geographical coordinates of the power grid transmission lines and their towers, and establish a power grid line topology model; The typhoon evolution process is discretized into multiple time periods with a fixed step size to form a unified time axis and obtain the typhoon center path data sequence, including the typhoon's maximum wind speed, the coordinates of the typhoon center, and the radius of the maximum wind speed for each time period. Based on the power grid topology model and the typhoon center path data sequence, the wind speed sensed by the towers and conductors in each time period is calculated.

[0009] Preferably, the evolution of the tower failure probability based on the wind speed sensed by the tower in each time period, considering the cumulative effect over time, to obtain the cumulative probability of tower failure, includes: The amount of single wind-induced fatigue damage to the tower in each time period is calculated based on the wind speed sensed by the tower in each time period, the critical wind speed that causes fatigue, the wind speed that causes immediate damage in a single time period, and the fatigue coefficient. Based on the linear accumulation criterion, the cumulative fatigue damage coefficient of the tower at the end of each time period is calculated according to the single wind-induced fatigue damage amount, and the probability of the tower not failing in each time period is calculated using an exponential non-failure probability model. The probability of the tower remaining intact until the end of each time period is obtained by multiplying the non-failure probability. Thus, the cumulative probability of the tower failing from the beginning to the end of each time period is obtained.

[0010] Preferably, the step of calculating the failure rate of the conductor caused by the typhoon's wind pressure at different time periods based on the wind speed sensed by the conductor at each time period, and then calculating the probability of conductor interruption, includes: The failure rate of the power lines caused by typhoon wind pressure at different times is calculated based on the wind speed sensed by the power lines at various time periods, using the following formula:

[0011] In the formula, For the first i The conductor in the first j Failure rate over a given period; Indicates the wind pressure influencing factor; W Ai,j Indicates the first i The conductor in the first j The wind pressure perceived during the time period, according to the first i The conductor in the first j The wind speed was calculated based on the wind speed sensed during the time period. W imax This represents the maximum wind pressure generated when a typhoon passes through. This represents the maximum wind pressure under normal conditions.

[0012] The probability of a conductor breaking in each of the preceding time periods is calculated based on the failure rate of the conductor in different time periods.

[0013] Preferably, a fault probability time series prediction curve for each line is calculated based on the cumulative probability of tower failure and the probability of conductor interruption, and a line fault probability time series considering the operating status is obtained by combining the line operating status correction, including: Based on the cumulative probability of tower failure and the probability of conductor interruption, the cumulative probability of each line consisting of towers and conductors experiencing at least one fault in each previous time period is calculated along the time axis, thus obtaining the fault probability time series prediction curve for each line. The fault probability time series prediction curve of each line is corrected by using the operation status influence function constructed based on the line operation status information of each time period, so as to obtain the line fault probability time series considering the operation status.

[0014] Preferably, the abnormal state of the power grid system is derived based on the time series of line fault probabilities, the spatiotemporal matrix of line operating status, and the spatiotemporal matrix of wind farm abnormal output, including: The abnormal state of the power grid is obtained based on the abnormal output of the wind farm and the operating status of the power lines; and the power flow redistribution is analyzed based on the abnormal state of the power grid to obtain the status of each line in the power grid system. t The transmitted power vector at each moment is used to identify overloaded lines and obtain... t Probability of line failure under constant overload:

[0015] In the formula, P fl,t For overloaded lines l The transmission power; Indicates overload circuit l The transmission power limit; Indicates overload circuit l Rated transmission power; based on t The failure probability of the overloaded line at any time is sampled to obtain... t Abnormal transition state of a line under time-to-time power flow redistribution: ,in, For the line l exist t The fault status at any given moment; according to Sure t The line fault status at time +1, combined with t Wind farm anomaly output vector at time +1 get t The power grid system is in an abnormal state at time +1, where t The line fault status at time +1 is:

[0016] In the formula, Represents the sampling function; For the line l exist t Line fault probability before time +1.

[0017] Preferably, based on the abnormal state of the power grid system obtained from the simulation, a rescheduling strategy for restoring supply and demand balance is generated when the system is in a fault operation state, including: According to the abnormal state of the power grid system, when the system is in a fault operation state, rescheduling is carried out: the supply and demand balance is restored by adjusting the units and emergency load reduction or generator tripping. After the supply and demand balance is restored, the line transmission power is determined by power flow analysis, and the overloaded line is disconnected according to the line transmission power. If rescheduling causes the interconnected power grid system to split into multiple islands during anomaly propagation, different management measures will be taken according to the type of island to ensure its independent operation: If there is no generator on the island, then remove all loads from the island. If there is only one generator on the island, and the total load demand is... Less than the generator output power Therefore, the generator power is reduced, and the power reduction is: ,in This represents the generator's minimum output power. If there is only one generator on the island, and the total load demand is... Greater than the generator output power Then, the generator's power will be increased by: ,in This represents the generator's maximum output power.

[0018] Preferably, the restoration of supply and demand balance by adjusting the generator unit and emergency load reduction or generator tripping includes: (1) If the power supply is less than the load demand and the regulation capacity is sufficient, the generator power will be increased. The adjusted power is:

[0019] In the formula, For the unit Maximum output power For the unit Rated power, To measure the imbalance between supply and demand; If the power supply is less than the load demand and the regulation capacity is insufficient, the unit power will be increased to the maximum and an emergency load reduction will be carried out. (2) If the power supply exceeds the load demand and the adjustment capability is sufficient, then the unit power should be reduced. The adjusted power is:

[0020] In the formula, For the unit Minimum output power; If the power supply exceeds the load demand and the regulation capacity is insufficient, the generator power will be reduced to the minimum and the generator will trip.

[0021] A second aspect of this invention proposes a power grid typhoon fault analysis and dispatching system that considers time accumulation, comprising: The wind speed acquisition module is used to obtain the wind speeds sensed by towers and conductors at various time periods during the typhoon's evolution, based on the power grid topology and typhoon data. The tower failure probability evolution module is used to evolve the tower failure probability based on the wind speed sensed by the tower in each time period, taking into account the cumulative effect of time, and to obtain the cumulative probability of tower failure. The conductor breakage probability calculation module is used to calculate the failure rate of the conductor caused by the wind pressure of the typhoon at different time periods based on the wind speed sensed by the conductor at each time period, and then calculate the probability of the conductor breaking. The fault probability prediction and correction module is used to calculate the fault probability time series prediction curve of each line based on the cumulative probability of tower failure and the probability of conductor interruption, and to obtain the line fault probability time series considering the operating status by combining the line operation status correction. The power grid anomaly evolution analysis module is used to construct a spatiotemporal matrix of line failure probability under extreme weather conditions under typhoon conditions based on the line fault probability time series and sample it to obtain a spatiotemporal matrix of line operation status. At the same time, it collects the abnormal power generation of each wind farm in each time period and constructs a spatiotemporal matrix of abnormal output of wind farm. The power grid system abnormal state analysis module is used to deduce the abnormal state of the power grid system based on the time series of line fault probability, the spatiotemporal matrix of line operation status and the spatiotemporal matrix of wind farm abnormal output. The rescheduling module is used to generate rescheduling strategies to restore supply and demand balance when the system is in a fault operation state, based on the abnormal state of the power grid system obtained from the simulation.

[0022] A third aspect of the present invention provides a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to perform operations according to the instructions to execute the steps of the method.

[0023] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method.

[0024] Compared with the prior art, the beneficial effects of the present invention include at least the following: This invention explicitly introduces a line fault prediction mechanism based on the cumulative fatigue effect over time: it evolves the tower failure probability considering the cumulative effect over time based on wind speed to obtain the cumulative probability of tower failure. By establishing single damage and cumulative damage models at the component level and combining them with the temporal changes in typhoon wind speed, the comprehensive effect of the typhoon is reflected in the hourly evolution of the fault probability, thereby achieving quantitative prediction of line fault risk throughout the entire typhoon life cycle, rather than static assessment at a single moment.

[0025] This invention constructs a unified framework for multi-level failure probabilities of poles and lines: based on the cumulative probability of pole failure and the probability of conductor interruption, the time series prediction curve of the failure probability of each line is calculated. By unifying the fatigue failure and interruption probabilities of key components such as poles and conductors to the line level through a series system reliability model, a bottom-up failure probability aggregation mechanism is formed, so that the prediction results can reflect the different impacts of components with different structural forms and different aging degrees on the overall reliability of the line.

[0026] This invention proposes a comprehensive prediction model that couples meteorological loads with electrical operating conditions: by combining line operating condition corrections to obtain a time series of line fault probabilities that consider operating conditions, and by introducing operating condition parameters such as line current load factor, conductor temperature, and equipment aging on the basis of the traditional relationship between wind speed and fault probability, an operating condition correction factor is constructed to perform a secondary correction on the fault probability output by the physical model, so that the model can reflect both the intensity of external disasters and the internal operating stress, thereby enhancing the engineering applicability of the prediction results.

[0027] This invention breaks through the traditional fixed threshold adjustment mode when generating a rescheduling strategy for restoring supply and demand balance. It introduces key parameters such as supply and demand imbalance, total unit adjustment capacity, and rated / maximum / minimum output power of the units to achieve accurate calculation of adjustment power and avoid over-adjustment or under-adjustment. It also distinguishes between two scenarios of insufficient power supply and excess power supply and performs differentiated calculations to match different adjustment methods such as unit increase, load reduction, unit decrease, and generator tripping. The logic is closed-loop and fits the actual operating conditions. Attached Figure Description

[0028] Figure 1 A schematic diagram of the power grid anomaly propagation process considering the coupling effects of meteorological factors and power flow.

[0029] Figure 2 This is a flowchart of a power grid typhoon fault analysis and scheduling method that considers time accumulation. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0031] This invention provides a method for analyzing and scheduling power grid typhoon faults considering time accumulation. Given a known or predictable typhoon trajectory and intensity evolution, and combining the spatial location information and operating status of transmission lines: First, a wind field-line wind load mapping model evolving over time is established; then, based on linear fatigue accumulation theory and vulnerability curves, a multi-level failure probability evolution model is constructed; meteorological loads are coupled with the electrical operating status of the lines to form time-segmented line fault probability prediction curves, providing a basis for pre-disaster inspection and reinforcement, mobile energy storage, and emergency repair resource deployment. In specific implementation, this involves: acquiring time-series wind loads of transmission lines driven by typhoon trajectory and wind field models; calculating fatigue damage and failure probability of towers and conductors based on time accumulation effects; unified modeling and aggregation mechanism for multi-level fault probabilities of towers, conductors, and lines; prediction of short-term fault probability and line-level fault evolution for single-span lines (conductors); correction of line fault probability by coupling meteorological loads and electrical operating status; and analysis of power grid anomaly propagation coupled with extreme meteorological factors and power flow redistribution. It can also perform dynamic assessment of line risk levels based on fault probability time series. Figure 2 As shown, the method includes: S1: Based on the power grid topology and typhoon data, obtain the wind speeds sensed by towers and conductors at various time points during the typhoon's evolution. v i,j ; More preferably, the acquisition and preprocessing of typhoon trajectory and wind field data specifically includes: S11: Obtain the geographical coordinates of the transmission line and its towers ( x i , y i ), and establish a line topology model.

[0032] S12: Discretize the typhoon evolution process with a fixed step size. T The time periods are divided into a unified timeline; the typhoon center path sequence given by historical measurements or numerical forecasts is obtained.

[0033] in j The time period number. For the first j Maximum wind speed of the typhoon during the period For the radius of maximum wind speed, ( x 0,j , y 0,j ) is the first j Coordinates of the typhoon center during the specified time period.

[0034] S13: Based on S11-S12, the wind speed at the line location in each time period is calculated using an axisymmetric vortex model (such as the Rankine vortex model) to obtain the tower or conductor. i Wind speed perceived at different times; Extreme weather conditions, especially high wind speeds during typhoons, can damage power grid equipment, including wind farms and transmission lines. High wind speeds first activate turbine protection mechanisms, causing turbines to deactivate and resulting in wind fluctuations. Furthermore, high wind speeds can apply uneven stress to transmission towers, causing irreversible fatigue damage and potential collapse. Typhoons can also exert excessive wind pressure on overhead lines, leading to line breaks.

[0035] As the typhoon center moves, changes in the relative positions of extreme weather factors and power grid equipment can cause time-varying weather effects and corresponding equipment malfunctions. This is based on the Rankine Vortex wind field model. i (tower or conductor) i )exist j The wind speed perceived during a given time period is denoted as . v i,j , can be represented as:

[0036] in d i,j For the first i The distance between a single tower or single conductor and the center of the typhoon can be expressed as:

[0037] In the formula ( x 0,j , y 0,j ) is the first j Coordinates of the typhoon center during the specified time period.

[0038] S2: Based on the wind speed sensed by the tower at different times. v i,j By performing a tower failure probability evolution that considers the cumulative effect over time, the cumulative probability of tower failure is obtained. ; More preferably, the evolution of tower failure probability considering the cumulative effect over time specifically includes: S21: Based on the wind pressure-wind speed relationship, the tower... i In the jWind speed perceived during the period v i,j Converting this to the corresponding wind pressure or equivalent bending moment yields the amount of single-event wind-induced fatigue damage to the tower during that period. C i,j :

[0039] in, v cr The critical wind speed at which fatigue occurs. v m This refers to the wind speed that is immediately disrupted within a single time period. a , b The fatigue coefficient, which is related to the material and structure, can be determined by experiments or historical data.

[0040] S22: Based on the Palmgern-Miner linear accumulation criterion, according to the amount of wind-induced fatigue damage in a single incident. C i,k Calculate the first i The first tower in the j The cumulative fatigue damage coefficient at the end of the time period;

[0041] in, C i,k This indicates the amount of damage caused by wind speed at a specific time period. k is often used to distinguish damage at different time steps or under specific conditions, and can describe a more refined spatiotemporal evolution process. S23: Using an exponential non-failure probability model, the following is obtained: j Probability of tower not failing within a certain time period :

[0042] in The duration of a single time period.

[0043] S24: Probability of non-failure of cumulative multiplication The probability that the tower remains intact until the end of the j-th time period is obtained.

[0044] Thus, the tower is in front. j The cumulative probability of failure occurring within a time period, i.e., the cumulative probability of the tower failing during the period from the end of time period 1 to the end of time period j:

[0045] To ensure compatibility with existing vulnerability curves, fatigue accumulation results can be equivalently mapped to wind speed-failure probability curves, achieving consistent calibration between the fatigue accumulation model and the vulnerability model.

[0046] S3: Based on wind speed sensed by the conductor at different time periods. v i,j The failure rate of power lines caused by typhoon wind pressure at different times is calculated, thereby determining the probability of power line interruption. ; More preferably, the short-term fault calculation for a single-span line specifically includes: S31: Typhoon-induced short-term power line failure due to wind pressure: set up v i,j Indicates wire i exist j The wind speed perceived during the time period, and the wind pressure experienced by the line. It can be represented as:

[0047] In the formula, and These represent the wind pressure non-uniformity coefficient, wind load coefficient, wind pressure height variation coefficient, and line shape coefficient, respectively. This indicates the angle between the wind direction and the conductor.

[0048] Thus, the wire is obtained. i exist j Failure rate during the period , can be represented as:

[0049] In the formula, For wires i In the j Failure rate over a given period; This represents the wind pressure influence factor, used to describe the relationship between wind speed and wind load. It can be obtained by fitting historical fault statistics of the line. W Ai,j Indicates the first i The conductor in the first j Wind pressure perceived during a given time period; W imax Maximum wind pressure, which is the highest wind pressure that may be generated when a typhoon passes through; This represents the maximum wind pressure under normal conditions.

[0050] S32: The probability of a conductor interruption is calculated based on the failure rate of the conductor at different time periods. wire i in front j The probability of an interruption occurring within a given time period can be expressed as:

[0051] In the formula, For the first i The conductor in the first k Failure rate over a given period; For wires i in front j The probability of an interruption occurring within a time period, i.e., the conductor i From the first period (start) to the second period j The probability of an interruption occurring at the end of the time period; The duration of a single time period.

[0052] S4: Based on the cumulative probability of the tower failing. The probability of wire breakage The fault probability time series prediction curve for each line is calculated, and the line fault probability time series considering the operating status is obtained by combining the line operating status correction. More preferably, the line-level fault probability synthesis and time series prediction specifically includes: S41: Based on the cumulative probability of tower failure and the probability of conductor interruption, for the... n Base tower and n -1 The circuit consists of a conductor segment l It can be calculated that its position in the first place is... j The cumulative probability of at least one failure occurring within a given time period is:

[0053] In the formula, For the first r The cumulative probability of base tower failure. For the first m The probability of a conductor segment being interrupted; Along the time axis j =1,…, T The time series prediction curve of the failure probability for each line can be obtained through calculation. This allows us to depict the evolution of line failure risks over time throughout the entire typhoon process.

[0054] S42: Line operation status coupling correction; To improve the applicability of the prediction results to different operating conditions, this invention further introduces a line operating state correction factor to adjust the obtained component / line fault probabilities. Make corrections: First, obtain operational information such as line current load rate, conductor temperature, and aging coefficient for each time period, and then normalize it.

[0055] Then, an operation status influence function is constructed based on the line operation status information for each time period. For example, using linear or exponential forms can make high load rates and severe aging correspond to higher failure gain coefficients.

[0056] Next, the running state influence function is used. Line fault probability obtained from S41 Make corrections:

[0057] in, For the line l in front j The probability of corrective failure in each time period; The line fault probability time series considering operational conditions is obtained.

[0058] S5: Based on the time series of line fault probability obtained in S4, construct the spatiotemporal matrix of line failure probability under extreme weather conditions of typhoon and sample it to obtain the spatiotemporal matrix of line operation status. At the same time, collect the abnormal power generation of each wind farm in each time period and construct the spatiotemporal matrix of abnormal output of wind farm. More preferably, the abnormal evolution process of the power grid under extreme weather conditions during a typhoon specifically includes: S51: Time-varying extreme weather conditions caused by typhoons can lead to wind farms... i Generate time-varying abnormal output P wi,j And it will cause power transmission lines i With a specific probability at different time periods A line fault has occurred.

[0059] Assume the affected wind farms are numbered 1 to 2. N The affected transmission lines are numbered 1 to 1. L The passage of a typhoon is divided into... T Each time period.

[0060] When considering only extreme weather factors, the evolution process of anomaly grids can be represented as a binary tuple. AE =( P w , P l ),in P lic The spatiotemporal matrix representing the probability of line failure, with elements... P w express N The spatiotemporal matrix of the abnormal output of a wind farm: P w =

[0061] In the formula, Pwi,j Indicates the first i Wind farm in the j Abnormal power generation during a given period (obtained from the wind farm data acquisition and monitoring system).

[0062] S52: Based on the line fault probability time series, P lic : P lic =

[0063] In the formula, For the line l in front j The probability of corrective failure in each time period; S53: Due to P lic This matrix cannot reflect the actual operating status of the line and needs to be determined by sampling to establish the spatiotemporal matrix of equipment fault status. S lic =

[0064] In the formula, Indicates branch l (line l )exist j The running status of a time period, where 0 indicates that the branch is closed and 1 indicates that the branch is open.

[0065] S6: Based on the abnormal output of the wind farm and the line operation status obtained in S5, the abnormal state of the power grid system considering extreme weather factors and power flow redistribution is obtained. More preferably, during typhoons, line faults caused by extreme weather factors can induce new faults through power flow redistribution, and the two alternately couple and drive abnormal evolution of the power grid.

[0066] To facilitate the description of the system's state evolution, let the time index t = j, where t represents the time when the j-th period of the typhoon ends. Therefore, the data obtained in the previous steps with index j is the input for the system state analysis at time t in this step.

[0067] The specific aspects of abnormal power grid coupling considering extreme weather factors and power flow redistribution include: S61: Confirm t Power grid abnormality at all times; Based on the S5 method, t The abnormal state of the power grid at any given time is represented as follows:

[0068] In the formula Indicates that the wind farm is int The abnormal output vector at time step, Indicates the line is in t The running state vector at time t.

[0069] Analysis is possible t The redistribution of the current at time (i.e. P f,t ):

[0070] In the formula, P f,t Indicates that each line in the system is t The transmitted power vector at any given time; This is a function of the line's power transmission. x t It is a system parameter vector.

[0071] S62: Obtain overload circuit l ( l ∈ The failure probability of ) is:

[0072] In the formula P fl,t For overloaded lines l The transmission power; Indicates overload circuit l The transmission power limit; Indicates overload circuit l The rated transmission power.

[0073] After sampling, the abnormal transition state of the line under power flow redistribution is obtained:

[0074] in, For branches l At any moment t The fault status at that time; S63: Confirm t Line fault status and system abnormal status at +1 time; according to Branch fault vectors caused by extreme weather factors ,available t Branch fault state at time +1:

[0075] In the formula, The following conditional function is represented:

[0076] In the formula, This represents the sampling function. If the branch... l At any moment t In the disconnected state ( ), which will be in the cycle t +1 Keeps the device disconnected; otherwise, it will be based on the time. t +1 indicates the fault probability sampling determination state.

[0077] Finally, combining t The wind power anomaly output vector at time +1 is obtained. t System abnormal state at time +1 .

[0078] S7: Reschedule based on the abnormal state of the power grid system obtained from S6 to restore the supply and demand balance; More preferably, the analysis of abnormal propagation paths in the power grid during a typhoon specifically includes: As can be seen from S6, the transition from one cycle to the next in an abnormal state of the power grid is a complex process, influenced by both power flow redistribution and extreme weather factors.

[0079] Within the T time periods (corresponding to T discrete moments) of the typhoon, each time period corresponds to a unique system state distribution, forming as follows: Figure 1 The abnormal propagation path is shown. On longer timescales (minutes or hours), failure events caused by extreme weather factors... Figure 1 The Chinese character is represented as F D , T D This indicates the development time of extreme weather events. On shorter timescales (seconds or milliseconds), cascading overload faults caused by power flow redistribution... Figure 1 The Chinese character is represented as F C , T C Indicates the time when the cascading failure occurred. S71: Rescheduling considering power flow redistribution; When the system is t When a system is constantly affected by typhoon weather and is in a state of operational failure, it needs to be rescheduled to restore supply and demand balance. First, supply and demand balance is restored by adjusting generating units and implementing emergency load shedding or generator tripping. The adjustment power is calculated separately according to the different power supply volumes. Then, after supply and demand balance is restored through generating unit adjustments or load shedding, power flow analysis is used to determine the line transmission power. Finally, based on the calculated transmission power, the state of overloaded lines is determined.

[0080] The rescheduling process can be broken down into the following steps: Step 1: Unit adjustment and emergency load reduction or generator tripping. The main goal of unit adjustment and emergency load reduction or generator tripping is to restore supply and demand balance.

[0081] Since the cost of load reduction or tripping is higher than the cost of unit adjustment, unit ramping has a higher scheduling priority than emergency load reduction or tripping.

[0082] Assuming the supply and demand imbalance caused by the fault is For regulating units : (1) If the power supply is less than the load demand, i.e. >0, and with sufficient regulatory capacity, i.e., loss of measurement ≤Total regulating capacity Then the unit power will be increased, and the adjusted power will be:

[0083] In the formula, For the unit Maximum power output, For the unit Rated power; If the power supply is less than the load demand, that is >0, and insufficient regulatory capacity, i.e. If so, the unit power will be increased to maximum, and emergency load reduction will be implemented. The load reduction amount is:

[0084] (2) If the power supply exceeds the load demand, i.e. <0, and the regulating capacity is sufficient, that is, the loss of balance is not less than the total regulating capacity, i.e. If so, the unit power will be reduced, and the adjusted power will be:

[0085] In the formula, For the unit Minimum output power; If the power supply exceeds the load demand, that is <0, and insufficient regulatory capacity, i.e. If the unit adjustment still cannot restore the supply-demand balance, the unit power should be reduced to the minimum, and the generator should be tripped.

[0086] Step 2: Power Flow Analysis: After restoring supply and demand balance through unit adjustment or load reduction, the transmission power of the line is determined through power flow analysis.

[0087] Step 3: Disconnect the overloaded line: Determine the status of the overloaded line based on the transmission power calculated in Step 2.

[0088] S72: Managing Isolated Microgrids Considering that system rescheduling and power flow redistribution may cause the interconnected system to split into multiple islands during the propagation of anomalies, the following measures are taken according to the type of island to ensure independent operation.

[0089] If there is no generator on the island, all loads on the island should be removed:

[0090] If there is only one generator on the island, and the total load demand is... P ds Less than generator output P g0 The generator's power reduction P gd for:

[0091] If there is only one generator on the island, and the total load demand is... P ds Greater than generator output P g0 The generator will increase its power. P gu for:

[0092] Embodiment 2 of the present invention, based on the same technical concept as Embodiment 1, provides a power grid typhoon fault analysis and dispatching system that considers time accumulation. The system includes: The wind speed acquisition module is used to obtain the wind speed sensed by the power grid equipment at different time periods during the typhoon's evolution, based on the power grid topology and typhoon data. The tower failure probability evolution module is used to perform tower failure probability evolution based on wind speed and considering the cumulative effect over time, so as to obtain the cumulative probability of tower failure. The power line breakage probability calculation module is used to calculate the failure rate of power lines caused by wind pressure from typhoons at different times based on wind speed, and then calculate the probability of power line breakage. The fault probability prediction and correction module is used to calculate the fault probability time series prediction curve for each line based on the cumulative probability of tower failure and the probability of conductor interruption, and to obtain the line fault probability time series considering the operating status by combining the line operating status correction. The power grid anomaly evolution analysis module is used to construct a spatiotemporal matrix of line failure probability under extreme weather conditions under typhoon conditions based on the line fault probability time series and sample it to obtain a spatiotemporal matrix of line operation status. At the same time, it collects the abnormal power generation of each wind farm in each time period and constructs a spatiotemporal matrix of abnormal output of wind farm. The power grid system abnormal state analysis module is used to obtain the abnormal state of the power grid system, taking into account extreme weather factors and power flow redistribution, based on the abnormal output of wind farms and the operating status of lines. The rescheduling module is used to reschedule based on abnormal power grid system conditions in order to restore supply and demand balance.

[0093] Based on the above system, real-time assessment of transmission line fault risks under extreme weather conditions such as typhoons can be achieved. Specifically: The system first acquires meteorological information such as typhoon path, wind speed, and wind field gradient. Combined with the geographical location of the line and towers, it maps the wind field intensity generated by the typhoon's evolution over time onto each tower and each span, thereby obtaining wind load parameters such as wind speed, wind pressure, and equivalent bending moment in real time.

[0094] The system then performs a time-series analysis of the material fatigue characteristics of the tower and conductor based on wind load parameters. By calculating the fatigue damage caused by a single wind event and the cumulative fatigue damage coefficient, the system obtains the changes in the non-failure probability and failure probability of the components over time during the entire typhoon process.

[0095] Based on this, the system further estimates the instantaneous failure rate and cumulative interruption probability of a single span line in real time at various time periods according to the stress characteristics and wind pressure unevenness of the overhead line under strong wind. The failure probabilities of the tower and the conductor are then uniformly aggregated to the line level through a series reliability model to form a line fault probability prediction curve that changes over time.

[0096] To enhance the adaptability of the forecast to actual power grid operating conditions, the system in this embodiment also collects operating data such as line current load rate, conductor temperature, and equipment aging coefficient, and uses these as correction factors coupled with the probability of wind-induced faults. This ensures that the final line fault risk not only reflects the intensity of external typhoons but also the combined effect of internal electrical operating stresses.

[0097] When a wind-induced fault causes a line to disconnect, the system automatically performs power flow redistribution analysis, identifies potential overloaded lines and estimates their overload failure probability, and simulates the development of cascading fault chains and the process of islanding, thus extrapolating the power grid fault propagation path throughout the typhoon process.

[0098] Ultimately, the system can automatically provide the risk level, warning start time, and highest risk period for each line based on the hourly fault probability curve and its evolution trend, enabling real-time support for pre-disaster inspection, pre-deployment of maintenance resources, and emergency reinforcement decisions.

[0099] Embodiment 3 of the present invention provides a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to perform operations according to the instructions to execute the steps of the method.

[0100] Embodiment 4 of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method.

[0101] Compared with the prior art, the beneficial effects of the present invention include at least the following: This invention explicitly introduces a line fault prediction mechanism based on the cumulative fatigue effect over time: the failure probability of the tower is evolved considering the cumulative effect over time based on wind speed, and the cumulative probability of tower failure is obtained. By establishing a single damage amount and cumulative damage model based on the Palmgren-Miner criterion at the component level, and combining the temporal changes of typhoon wind speed, the comprehensive effect of the typhoon is reflected in the hourly evolution of the fault probability, so as to achieve quantitative prediction of the fault risk of the line throughout the entire typhoon life cycle, rather than static assessment at a single moment.

[0102] This invention constructs a unified framework for multi-level failure probabilities of poles and lines: based on the cumulative probability of pole failure and the probability of conductor interruption, the time series prediction curve of the failure probability of each line is calculated. By unifying the fatigue failure and interruption probabilities of key components such as poles and conductors to the line level through a series system reliability model, a bottom-up failure probability aggregation mechanism is formed, so that the prediction results can reflect the different impacts of components with different structural forms and different aging degrees on the overall reliability of the line.

[0103] This invention presents a comprehensive prediction model that couples meteorological loads with electrical operating conditions. It combines line operating condition corrections to obtain a time series of line fault probabilities that takes into account operating conditions. By introducing operating condition parameters such as line current load factor, conductor temperature, and equipment aging on the basis of the traditional relationship between wind speed and fault probability, an operating condition correction factor is constructed to perform a secondary correction on the fault probability output by the physical model. This allows the model to reflect both the intensity of external disasters and the internal operating stress, thereby enhancing the engineering applicability of the prediction results.

[0104] When restoring supply and demand balance, this invention breaks through the traditional fixed threshold adjustment mode and introduces key parameters such as supply and demand imbalance, total unit adjustment capacity, and rated / maximum / minimum output power of the unit to achieve accurate calculation of adjustment power and avoid over-adjustment or under-adjustment. It also distinguishes between two scenarios of insufficient power supply and excess power supply and performs differentiated calculations, and matches different adjustment methods such as unit increase, load reduction, unit decrease, and generator tripping accordingly. The logic is closed-loop and fits the actual operating conditions.

[0105] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0106] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0107] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0108] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A power grid typhoon fault analysis and scheduling method considering time accumulation, characterized in that, The method includes: Based on the power grid topology and typhoon data, the wind speeds sensed by the towers and conductors at various time points during the typhoon's evolution were obtained. The evolution of the tower failure probability is based on the wind speed sensed by the tower at different time periods, taking into account the cumulative effect of time, so as to obtain the cumulative probability of tower failure. Based on the wind speed sensed by the conductor at different time periods, the failure rate of the conductor caused by the wind pressure of the typhoon at different time periods is calculated, and then the probability of the conductor being interrupted is calculated. Based on the cumulative probability of tower failure and the probability of conductor interruption, the time series prediction curve of the failure probability of each line is calculated, and the line failure probability time series considering the operating status is obtained by combining the line operating status correction. Based on the time series of line failure probabilities, a spatiotemporal matrix of line failure probability under extreme typhoon weather conditions is constructed and sampled to obtain a spatiotemporal matrix of line operation status. At the same time, the abnormal power generation of each wind farm in each time period is collected to construct a spatiotemporal matrix of abnormal wind farm output. The abnormal state of the power grid system is deduced based on the time series of line fault probability, the spatiotemporal matrix of line operation status and the spatiotemporal matrix of wind farm abnormal output. Based on the abnormal state of the power grid system obtained from the simulation, a rescheduling strategy is generated to restore the supply and demand balance when the system is in a fault operation state.

2. The power grid typhoon fault analysis and scheduling method considering time accumulation according to claim 1, characterized in that: The wind speeds sensed by towers and conductors at various time points during the typhoon's evolution, obtained based on power grid topology and typhoon data, include: Obtain the geographical coordinates of the power grid transmission lines and their towers, and establish a power grid line topology model; The typhoon evolution process is discretized into multiple time periods with a fixed step size to form a unified time axis and obtain the typhoon center path data sequence, including the typhoon's maximum wind speed, the coordinates of the typhoon center, and the radius of the maximum wind speed for each time period. Based on the power grid topology model and the typhoon center path data sequence, the wind speed sensed by the towers and conductors in each time period is calculated.

3. The power grid typhoon fault analysis and scheduling method considering time accumulation according to claim 1, characterized in that: The evolution of the tower failure probability, based on the wind speed sensed by the tower at various time periods and considering the cumulative effect over time, yields the cumulative probability of tower failure, including: The amount of single wind-induced fatigue damage to the tower in each time period is calculated based on the wind speed sensed by the tower in each time period, the critical wind speed that causes fatigue, the wind speed that causes immediate damage in a single time period, and the fatigue coefficient. Based on the linear accumulation criterion, the cumulative fatigue damage coefficient of the tower at the end of each time period is calculated according to the single wind-induced fatigue damage amount, and the probability of the tower not failing in each time period is calculated using an exponential non-failure probability model. The probability of the tower remaining intact until the end of each time period is obtained by multiplying the non-failure probability. Thus, the cumulative probability of the tower failing from the beginning to the end of each time period is obtained.

4. The power grid typhoon fault analysis and scheduling method considering time accumulation according to claim 1, characterized in that: The method of calculating the failure rate of the conductor caused by the wind pressure of the typhoon at different time periods based on the wind speed sensed by the conductor at each time period, and then calculating the probability of conductor interruption, includes: The failure rate of the power lines caused by typhoon wind pressure at different times is calculated based on the wind speed sensed by the power lines at various time periods, using the following formula: In the formula, For the first i The conductor in the first j Failure rate over a given period; Indicates the wind pressure influencing factor; W Ai,j Indicates the first i The conductor in the first j The wind pressure perceived during the time period, according to the first i The conductor in the first j The wind speed was calculated based on the wind speed sensed during the time period. W imax This represents the maximum wind pressure generated when a typhoon passes through. This represents the maximum wind pressure under normal conditions. The probability of a conductor breaking in each of the preceding time periods is calculated based on the failure rate of the conductor in different time periods.

5. The power grid typhoon fault analysis and scheduling method considering time accumulation according to claim 1, characterized in that: Based on the cumulative probability of tower failure and the probability of conductor interruption, a fault probability time series prediction curve for each line is calculated. This curve is then combined with adjustments based on the line's operating status to obtain a line fault probability time series that considers the operating status, including: Based on the cumulative probability of tower failure and the probability of conductor interruption, the cumulative probability of each line consisting of towers and conductors experiencing at least one fault in each previous time period is calculated along the time axis, thus obtaining the fault probability time series prediction curve for each line. The fault probability time series prediction curve of each line is corrected by using the operation status influence function constructed based on the line operation status information of each time period, so as to obtain the line fault probability time series considering the operation status.

6. The power grid typhoon fault analysis and scheduling method considering time accumulation according to claim 1, characterized in that: Based on the time series of line fault probabilities, the spatiotemporal matrix of line operating status, and the spatiotemporal matrix of wind farm abnormal outputs, the abnormal states of the power grid system are deduced, including: The abnormal state of the power grid is obtained based on the abnormal output of the wind farm and the operating status of the power lines; and the power flow redistribution is analyzed based on the abnormal state of the power grid to obtain the status of each line in the power grid system. t The transmitted power vector at each moment is used to identify overloaded lines and obtain... t Probability of line failure under constant overload: In the formula, P fl,t For overloaded lines l The transmission power; Indicates overload circuit l The transmission power limit; Indicates overload circuit l Rated transmission power; based on t The failure probability of the overloaded line at any time is sampled to obtain... t Abnormal transition state of a line under time-to-time power flow redistribution: ,in, For the line l exist t Fault status at any time, l Take 1- L , L This represents the total number of lines; according to Sure t The line fault status at time +1, combined with t Wind farm anomaly output vector at time +1 get t The power grid system is in an abnormal state at time +1, where t The line fault status at time +1 is: In the formula, Represents the sampling function; For the line l exist t Line fault probability before time +1.

7. The power grid typhoon fault analysis and scheduling method considering time accumulation according to claim 1, characterized in that: Based on the abnormal state of the power grid system obtained from the simulation, when the system is in a fault operation state, a rescheduling strategy is generated to restore the supply and demand balance, including: According to the abnormal state of the power grid system, when the system is in a fault operation state, rescheduling is carried out: the supply and demand balance is restored by adjusting the units and emergency load reduction or generator tripping. After the supply and demand balance is restored, the line transmission power is determined by power flow analysis, and the overloaded line is disconnected according to the line transmission power. If rescheduling causes the interconnected power grid system to split into multiple islands during anomaly propagation, different management measures will be taken according to the type of island to ensure its independent operation: If there is no generator on the island, then remove all loads from the island. If there is only one generator on the island, and the total load demand is... Less than the generator output power Therefore, the generator power is reduced, and the power reduction is: ,in This represents the generator's minimum output power. If there is only one generator on the island, and the total load demand is... Greater than the generator output power Then, the generator's power will be increased by: ,in This represents the generator's maximum output power.

8. The power grid typhoon fault analysis and scheduling method considering time accumulation according to claim 7, characterized in that: The restoration of supply and demand balance by adjusting the generating units and implementing emergency load reduction or generator tripping includes: (1) If the power supply is less than the load demand and the regulation capacity is sufficient, the generator power will be increased. The adjusted power is: In the formula, For the unit Maximum output power For the unit Rated power, To measure the imbalance between supply and demand; If the power supply is less than the load demand and the regulation capacity is insufficient, the unit power will be increased to the maximum and an emergency load reduction will be carried out. (2) If the power supply exceeds the load demand and the adjustment capability is sufficient, then the unit power should be reduced. The adjusted power is: In the formula, For the unit Minimum output power; If the power supply exceeds the load demand and the regulation capacity is insufficient, the generator power will be reduced to the minimum and the generator will trip.

9. A power grid typhoon fault analysis and dispatching system considering time accumulation, operating the method described in any one of claims 1-8, characterized in that, The system includes: The wind speed acquisition module is used to obtain the wind speeds sensed by towers and conductors at various time periods during the typhoon's evolution, based on the power grid topology and typhoon data. The tower failure probability evolution module is used to evolve the tower failure probability based on the wind speed sensed by the tower in each time period, taking into account the cumulative effect of time, and to obtain the cumulative probability of tower failure. The conductor breakage probability calculation module is used to calculate the failure rate of the conductor caused by the wind pressure of the typhoon at different time periods based on the wind speed sensed by the conductor at each time period, and then calculate the probability of the conductor breaking. The fault probability prediction and correction module is used to calculate the fault probability time series prediction curve of each line based on the cumulative probability of tower failure and the probability of conductor interruption, and to obtain the line fault probability time series considering the operating status by combining the line operation status correction. The power grid anomaly evolution analysis module is used to construct a spatiotemporal matrix of line failure probability under extreme weather conditions under typhoon conditions based on the line fault probability time series and sample it to obtain a spatiotemporal matrix of line operation status. At the same time, it collects the abnormal power generation of each wind farm in each time period and constructs a spatiotemporal matrix of abnormal output of wind farm. The power grid system abnormal state analysis module is used to deduce the abnormal state of the power grid system based on the time series of line fault probability, the spatiotemporal matrix of line operation status and the spatiotemporal matrix of wind farm abnormal output. The rescheduling module is used to generate rescheduling strategies to restore supply and demand balance when the system is in a fault operation state, based on the abnormal state of the power grid system obtained from the simulation.

10. A terminal, comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method according to any one of claims 1-8.

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