Earthquake risk monitoring method and system for regional power grid

Abstract

The invention discloses an earthquake risk monitoring method and system for a regional power grid, and belongs to the technical field of electric power. In order to solve the problems of low earthquake emergency response efficiency and large economic loss of existing power grid facilities, the invention provides an earthquake risk monitoring method for a regional power grid, and the method comprises the steps: dividing the regional power grid into a plurality of function systems, and obtaining a corresponding power grid equipment vulnerability curve for power grid equipment in each function system; calculating the maximum peak accelerations at the respective functional systems before and after the earthquake; calculating to obtain respective damage probabilities of the power grid equipment under the two conditions; and an earthquake anti-risk strategy aiming at the power grid equipment. According to the method, pre-earthquake prevention is added, and a strategy is reasonably formulated for power equipment in combination with a vulnerability curve and an earthquake oscillation attenuation formula; and continuous operation and rapid recovery capability of the core power system can be maintained under earthquake shock, the efficiency is high, and greater economic loss and social loss caused by power failure can be avoided.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric power facilities, and more specifically, relates to a method and system for monitoring earthquake risks in a regional power grid. Background Art

[0002] As a vital lifeline, the power system is closely linked to the economy, people's livelihoods, and social stability. Power system failures can not only result in enormous economic losses but can also cause social unrest and serious consequences. China's southwest region boasts abundant hydropower resources. Due to limitations such as insulation distances, power equipment often utilizes pillar-type structures, resulting in a high center of gravity, flexible structures, and high seismic vulnerability. Active efforts should be made to strengthen the seismic resistance of power systems, analyzing and assessing the seismic hazard and reliability of regional power systems. Studying the seismic vulnerability of structures is an effective way to assess their seismic hazard and reliability, and can also be used for seismic reinforcement analysis, which is widely used in disaster prevention engineering. Seismic mitigation efforts for power facilities have attracted significant attention within domestic research, and various methods for studying seismic vulnerability have been proposed, including theoretical analysis and simulation calculations, shaking table testing, and statistical analysis of earthquake damage. However, existing research is limited to the plotting of vulnerability curves and cannot translate vulnerability into an assessment of the probability of equipment damage. Existing power grid risk assessment methods typically rely on simple statistical data or static models, lacking real-time monitoring and dynamic assessment capabilities. This makes it difficult to effectively integrate equipment vulnerability curves for pre-earthquake risk prediction and post-earthquake damage assessment, resulting in significant economic losses. Furthermore, traditional emergency response systems in power grids are often manually controlled, resulting in slow transmission of damage information and long response times, making them unable to meet the requirements for efficient earthquake disaster emergency management.

[0003] Corresponding improvements have also been made to address the above-mentioned issues. For example, Chinese patent application number CN202210855684.8, published on November 1, 2022, discloses a method, device, and storage medium for earthquake risk assessment of group buildings based on probability density evolution theory. The method includes probabilistic earthquake hazard analysis and group building earthquake vulnerability analysis, specifically including: obtaining a historical earthquake catalog database; dividing potential earthquake source areas; determining seismic activity parameters and earthquake motion attenuation relationships; generating an earthquake hazard curve; determining a consistent hazard spectrum; generating a random artificial earthquake motion time history sample curve; obtaining a group building database; establishing a multi-degree-of-freedom bending-shear layer model and determining parameters; determining the maximum inter-story displacement angle based on the random artificial earthquake motion time history sample curve using the central difference method; determining the probability density distribution function of the maximum inter-story displacement angle; determining the probability of each building being in different damage states; and changing the earthquake return period to generate an earthquake vulnerability curve. The shortcomings of this patent are that actual earthquake activity may be affected by complex geological structures, resulting in a disconnect between the hazard curve and the actual risk; and there are still many deficiencies in practical application.

[0004] Another example is Chinese patent application number CN202211300758.8, published on December 16, 2022. The patent discloses a method for assessing the impact of earthquakes on power grids and related equipment. The method includes: obtaining earthquake information; constructing an earthquake intensity circle based on the spatial coordinates of the earthquake location and the earthquake intensity corresponding to the earthquake location; searching for power equipment located within the earthquake intensity circle and obtaining basic information about the power equipment; comparing the seismic resistance data of the power equipment with the earthquake intensity corresponding to the location of the power equipment in the earthquake intensity circle to obtain the degree of damage to the power equipment; and generating an assessment report based on the degree of damage and the priority of the power equipment in the power grid. The shortcoming of this patent is that for a power grid containing tens of thousands of devices, comparing the intensity circle and device data one by one may cause calculation delays, affecting the timeliness of emergency response. Summary of the Invention

[0005] 1. Problems to be solved

[0006] To address the slow efficiency and significant economic losses associated with earthquake emergency response in existing power grids, this paper provides a method and system for monitoring earthquake risks in regional power grids. By enhancing pre-earthquake preparedness and integrating vulnerability curves with earthquake attenuation formulas to formulate rational and precise strategies for power equipment, this method helps maintain the continuous operation and rapid recovery capabilities of core power systems during earthquakes, while minimizing the economic and social losses caused by power failures.

[0007] 2. Technical solution

[0008] To solve the above problems, the present invention adopts the following technical solutions.

[0009] A method for monitoring earthquake risk in a regional power grid comprises the following steps:

[0010] S1: Divide the regional power grid into several functional systems and obtain a corresponding power grid equipment vulnerability curve for the power grid equipment in each functional system; the power grid equipment vulnerability curve is a log-normal distribution curve formed by the probability of damage of the power grid equipment and the PGA; the PGA is the maximum peak ground acceleration where the power grid equipment is located;

[0011] S2: Obtain the geographical distribution data of each functional system, and calculate the maximum peak acceleration of each functional system before and after the earthquake using the earthquake attenuation formula;

[0012] S3: Calculate the damage probability of the power grid equipment in each of the two cases based on the power grid equipment vulnerability curve and the maximum peak acceleration at the functional system, and multiply the damage probability of a single power grid equipment by the number of power grid equipment of the same type in the functional system to obtain the number of damaged power grid equipment;

[0013] S4: Develop earthquake risk mitigation strategies for power grid equipment based on the amount of damaged equipment.

[0014] Furthermore, the step S2 specifically includes the following steps:

[0015] S21: Obtain the latitude and longitude coordinates of the site of the functional system;

[0016] S22: Calculate the distance between the functional system and the earthquake zone; specifically including:

[0017] Distance calculation before earthquake: calculate the minimum straight-line distance from the functional system to the earthquake zone;

[0018] Distance calculation after earthquake: calculate the actual distance from the functional system to the epicenter of the earthquake zone;

[0019] S23: Calculate the maximum peak acceleration of the functional system according to the earthquake attenuation formula, which is:

[0020] log(PGA)=A+BM+Clog(R+De EM )

[0021] Wherein, PGA is the maximum peak acceleration of the ground where the power grid equipment is located; M is the historical magnitude before the earthquake, and M is the magnitude of the earthquake after the earthquake; R is the distance from the functional system to the earthquake zone; A, B, C, D, and E are the empirical regression coefficients obtained by fitting different regions; e is a constant with a value of 2.718.

[0022] Furthermore, in the case before an earthquake, step S23 specifically includes the following steps:

[0023] S231: Acquire several historical earthquake data;

[0024] S232: Constructing a seismic motion set from a plurality of seismic data, wherein the seismic motion set includes at least one strong seismic motion, at least one moderate seismic motion, and an average seismic motion obtained by averaging the plurality of seismic data;

[0025] S233: Obtain the magnitude of each earthquake motion in the earthquake motion set, and then use the earthquake motion attenuation formula to calculate the maximum peak acceleration of the functional system under earthquake motions of different intensities.

[0026] Furthermore, the relationship between the damage probability of the power grid equipment and the PGA in the power grid equipment vulnerability curve in step S1 is:

[0027]

[0028] Among them, P 受损 (PGA = x) is the probability of damage to electrical equipment when PGA = x in the input earthquake motion; Φ() is the cumulative distribution function of the standard normal distribution; μ and σ are the mean and variance of lnx, respectively.

[0029] Furthermore, the step S1 further includes classifying the power grid equipment in each functional system according to equipment type and voltage level, and then obtaining the corresponding power grid equipment vulnerability curve after the classification is completed.

[0030] Furthermore, the method further includes step S5: evaluating the damage risk of the power grid equipment before and after the earthquake based on the amount of damaged power grid equipment, and then visually presenting the damage risk.

[0031] Furthermore, the earthquake risk resistance strategy for the power grid equipment in step S4 includes correspondingly increasing or decreasing the number of backup devices of the power grid equipment: when the number of damaged power grid equipment reaches a first set value, the backup number of the power grid equipment is increased; when the number of damaged power grid equipment is less than a second set value, the backup number of the power grid equipment is reduced, and the first set value is greater than the second set value.

[0032] A system for a method for monitoring earthquake risk of a regional power grid as described in any one of the above items comprises:

[0033] Power grid equipment vulnerability curve module: used to store the log-normal distribution curve formed by the damage probability of power grid equipment and PGA

[0034] Earthquake intensity recording module: used to record the parameters of earthquakes occurring in the area where the regional power grid is located; and calculate the maximum peak acceleration of the functional system where the power grid equipment is located;

[0035] Vibration monitoring module: used to collect real-time data on grid equipment in each functional system within the regional power grid when an earthquake occurs;

[0036] Risk assessment module: used to calculate the probability of damage to power grid equipment and the amount of damaged power grid equipment; and generate earthquake risk mitigation strategies;

[0037] Database: used to store relevant parameters of earthquakes that occurred in the regional power grid in the past.

[0038] Furthermore, the vibration monitoring module includes sensors provided on the power grid equipment. The installation positions of different types of sensors on the power grid equipment are as follows:

[0039] In the GIS and GIL circuits, sensors are placed on the fixed and sliding supports of the pipelines;

[0040] For pillar-type equipment in the AC filter circuit, the sensor is placed at the root of the pillar insulator of each device;

[0041] In the converter valve hall and converter transformer circuit, sensors are arranged at the roots of the bushings of each device and on the bottom shielding cover of the suspended valve tower.

[0042] Furthermore, it also includes:

[0043] Signal transmission module: used to transmit the results of the risk assessment module to the regional power grid control center;

[0044] Result visualization display module: used to visualize the results of the risk assessment module.

[0045] 3. Beneficial effects

[0046] (1) The core of the earthquake risk monitoring of regional power grids in the present invention is to introduce a pre-earthquake monitoring mechanism. By calculating the damage probability of power grid equipment before an earthquake, risk pre-control and resource optimization can be reasonably carried out, and spare parts can be reasonably stored for important power grid equipment. After an earthquake occurs, spare parts can be used to replace and repair important equipment immediately to ensure that the power grid can be quickly restored to operation. Another core is to combine the vulnerability curve of power grid equipment and the earthquake attenuation formula to obtain the damage probability of power grid equipment, and convert macro earthquake parameters into the damage probability of specific equipment, which changes the traditional method of only using magnitude or intensity to assess risk and ignoring the assessment inaccuracy caused by spatial attenuation and equipment differences. The whole method not only considers the efficiency of post-earthquake recovery, but also considers the prevention before the earthquake, providing a sufficient theoretical basis for the seismic reinforcement of the power grid and the formulation of emergency plans, thereby realizing the construction of a safer, more reliable and self-healing power guarantee system, which helps to maintain the continuous operation and rapid recovery capability of the core power system under the impact of an earthquake, and avoid secondary disasters and social chaos caused by large-scale power outages.

[0047] (2) When facing this situation before an earthquake, the present invention adopts the minimum straight-line distance from the functional system to the earthquake zone as the epicenter distance, because the most unfavorable earthquake effect on the functional system comes from the earthquake source with the shortest straight-line distance to the functional system on the nearby earthquake fault zone. Using the most unfavorable scenario for setting can ensure the conservatism of risk assessment and ensure that the risk assessment result corresponds to the most extreme earthquake motion scenario that the functional system may withstand; at the same time, a seismic motion set is constructed based on historical earthquake data. The seismic motion set includes seismic motions of different levels. The probability of damage to power grid equipment is determined according to the seismic motions of different levels, and then the risk results under seismic motions of different levels are obtained. Through the combination of typicality + extremeness + diversity, a scientific seismic motion input set is provided for regional power grid seismic resistance assessment, ensuring the comprehensiveness of the prevention results before the earthquake;

[0048] (3) The present invention classifies the power grid equipment in each functional system, taking into account the differences in equipment types and the importance and design standards of the equipment reflected by the voltage level in the power grid, and can screen out the priority of the power grid equipment, optimize resource allocation, and improve the accuracy of the matching of the vulnerability curve of the power grid equipment. After classification, the damage of important equipment can be quickly identified after an earthquake to guide the order of emergency repairs. The visualization of damage risks can intuitively and efficiently facilitate decision makers to quickly locate key protection objects, improve decision-making efficiency, and enhance collaborative capabilities.

[0049] (4) The system of the present invention realizes the transformation of earthquake risk assessment from experience-driven to data-driven through the synergy between various modules. It can not only realize the rapid repair and maintenance of power grid equipment after the earthquake, but also conduct risk assessment of power grid equipment before the earthquake in advance, so as to formulate earthquake risk resistance strategies for power grid equipment, better resist risks when an earthquake occurs, ensure the continuous operation and rapid recovery capability of the power system, and avoid greater economic and social losses caused by power failures; at the same time, the system combines the fragility curve and the earthquake motion attenuation formula to calculate the damage probability of power equipment, integrate multi-dimensional risk driving factors, and ensure the accuracy of the results. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a schematic diagram illustrating the epicenter distance for pre- and post-earthquake risk assessment of the regional power grid functional system in this application;

[0051] Figure 2 This is a schematic diagram of the system page overview in this application;

[0052] Figure 3 This is a schematic diagram of the process in this application. DETAILED DESCRIPTION

[0053] The present invention is further described below with reference to specific embodiments and accompanying drawings.

[0054] like Figure 3 As shown, a method for monitoring earthquake risk of a regional power grid includes the following steps:

[0055] S1: Divide the regional power grid into several functional systems and obtain a corresponding power grid equipment vulnerability curve for the power grid equipment in each functional system; the power grid equipment vulnerability curve is a log-normal distribution curve formed by the probability of damage of the power grid equipment and the PGA; the PGA is the maximum peak ground acceleration where the power grid equipment is located;

[0056] Specifically, in this step S1, by dividing the regional power grid into functional systems, the risk assessment is refined to facilitate the rapid identification of the corresponding area; at the same time, the macro earthquake parameters are converted into specific power grid equipment damage probabilities in combination with the power grid equipment vulnerability curve to quantify the risk capacity; the power grid equipment vulnerability curve is used to generate the logarithmic normal distribution relationship between the damage probability of each power grid equipment and the PGA based on the characteristics of various types of power grid equipment and historical earthquake data, that is, the power grid equipment vulnerability curve can be used to quickly obtain the damage probability of power grid equipment under different PGAs;

[0057] In an example, the construction of the power grid equipment vulnerability curve can be obtained as follows:

[0058] Taking into account the seismic code and ATC-63's earthquake motion selection recommendations, screen the earthquake motion records that meet the conditions (such as specific site categories, magnitude ranges, etc.) from the earthquake database, calculate multiple parameters of each earthquake motion (such as the maximum peak ground acceleration PGA, peak velocity PGV), and standardize these parameters; establish a refined finite element model in accordance with the design drawings of the power grid equipment in the Abaqus finite element software, input the artificial wave of the vibration table test in the software for simulation, and compare it with the results of the vibration table test to verify the accuracy of the finite element model; input all earthquake motion samples in Abaqus, and perform finite element time history analysis to calculate the structural response of the power grid equipment under different PGA. Calculate the failure probability of the equipment, P is the failure probability; n f is the number of earthquake motions that cause casing failure; N is the total number of earthquake motions in the benchmark sample; a scatter plot of equipment PGA-failure probability is made and fitted with the log-normal cumulative function to obtain the benchmark fragility curve using all earthquake motion samples.

[0059] In an example, the regional power grid is divided according to the different functions it exhibits within the regional power grid and the grid equipment and distribution it contains, which can include multiple functional systems such as transmission system, monitoring system, power generation system, distribution system, converter station, substation, etc.

[0060] S2: Obtaining geographical distribution data of each functional system, and calculating the maximum peak acceleration of each functional system before and after the earthquake using the earthquake motion attenuation formula;

[0061] There are two core points in this step. The first is to calculate the PGA of power grid equipment at different locations based on the earthquake attenuation formula, avoiding the traditional method of using only magnitude or intensity to assess risks, ignoring spatial attenuation and equipment differences, and avoiding the problem of poor accuracy caused by a one-size-fits-all approach; the second is to add calculations for the situation before the earthquake, which is calculated based on historical earthquake data, so that earthquake risk monitoring is no longer limited to the post-earthquake scenario. The introduction of pre-earthquake risk monitoring can effectively keep calm when an earthquake occurs and carry out post-earthquake power grid equipment restoration work in an orderly manner, thereby ensuring the rapid resumption of power grid operation.

[0062] S3: Calculate the damage probability of the power grid equipment in each of the two cases based on the power grid equipment vulnerability curve and the maximum peak acceleration at the functional system, and multiply the damage probability of a single power grid equipment by the number of power grid equipment of the same type in the functional system to obtain the number of damaged power grid equipment;

[0063] Specifically, in this step, the destruction probability of a single power grid device is first calculated, and then the number of similar power grid devices is combined to obtain the number of damaged devices. The number of damaged devices provides a quantitative indicator at the system level, which helps to more accurately and comprehensively assess the overall reliability and risk level of the power grid system when an earthquake occurs, facilitating subsequent resource allocation and emergency preparedness.

[0064] S4: Develop earthquake risk mitigation strategies for power grid equipment based on the amount of damaged equipment.

[0065] Specifically, in step S4, the earthquake risk resistance strategy is to determine the damage risk of power grid equipment of the same type based on the number of damaged power grid equipment. For power grid equipment with high damage risk, the earthquake risk resistance strategy is to increase the number of spare parts reserves, increase the tools and facilities for repairing the power grid equipment, and strengthen the operation training and emergency repair training of the power grid equipment; for power grid equipment with low damage risk, the earthquake risk resistance strategy is to reduce the number of spare parts reserves; for power grid equipment with medium damage risk, the earthquake risk resistance strategy is to increase the storage of a certain number of spare parts, which is less than the number of spare parts with high damage risk, and strengthen daily preventive measures; the threshold settings for low, medium and high risks are manually set in combination with the region and the characteristics of the power grid equipment.

[0066] In summary, a core of the earthquake risk monitoring of the regional power grid in this embodiment is the introduction of a pre-earthquake monitoring mechanism: due to the inability to accurately predict earthquake activity information, the complexity of earthquake activity, and insufficient data on the probability of damage to power grid equipment, it is difficult for existing technologies to conduct pre-earthquake risk assessment of regional power grids. Most of the existing technologies focus on post-earthquake assessment and repair to improve the accuracy of post-earthquake assessment. However, this embodiment focuses on calculations for both pre-earthquake and post-earthquake situations, which can achieve dual assessments of equipment risks before and after the earthquake. By calculating the probability of damage to power grid equipment before an earthquake, risk pre-control and resource optimization can be reasonably carried out, and spare parts can be reasonably stored for important power grid equipment. After an earthquake occurs, spare parts can be used to immediately replace and repair important equipment to ensure rapid resumption of power grid operation.

[0067] Another core is to combine the vulnerability curve of power grid equipment and the earthquake motion attenuation formula to obtain the destruction probability of power grid equipment, and convert the macro earthquake parameters into the damage probability of specific equipment. This changes the traditional method of assessing risks only by magnitude or intensity, ignoring the assessment inaccuracies caused by spatial attenuation and equipment differences. The entire method not only considers the efficiency of post-earthquake recovery, but also takes into account the prevention before the earthquake, providing a sufficient theoretical basis for the seismic reinforcement of the power grid and the formulation of emergency plans, thereby realizing the construction of a safer, more reliable and self-healing power security system, which helps to maintain the continuous operation and rapid recovery capabilities of the core power system under earthquake impacts, and avoid secondary disasters and social chaos caused by large-scale power outages.

[0068] At the same time, it is explained here that the above operations can be performed on each grid device in the functional system. Monitoring each grid device makes the entire monitoring process more comprehensive, does not miss any grid device, and has higher accuracy. The above operations can also be performed on important grid devices in the functional system to achieve targeted monitoring and ensure that important grid devices are well protected in the extreme case of earthquakes while taking into account costs.

[0069] In a specific embodiment, Figure 2 As shown, step S2 specifically includes the following steps:

[0070] S21: Obtain the latitude and longitude coordinates of the site of the functional system;

[0071] S22: Calculate the distance between the functional system and the earthquake zone; specifically including:

[0072] Pre-earthquake distance calculation: Calculate the minimum straight-line distance from the functional system to the earthquake zone. This pre-earthquake calculation takes into account that earthquake sources may be distributed throughout the entire earthquake fault zone. The most adverse earthquake effect on each functional system in the regional power grid comes from the source on the nearby fault zone with the shortest straight-line distance to the functional system. Therefore, during the assessment process, the minimum epicentral distance for each functional system should be the minimum straight-line distance between the functional system in the regional power grid and the nearby fault zone.

[0073] Distance calculation after earthquake: calculate the actual distance from the functional system to the epicenter of the earthquake zone;

[0074] S23: Calculate the maximum peak acceleration of the functional system according to the earthquake attenuation formula, which is:

[0075] log(PGA)=A+BM+Clog(R+De EM )

[0076] Wherein, PGA is the maximum peak ground acceleration where the power grid equipment is located; M before the earthquake is the historical magnitude, and M after the earthquake is the magnitude of the current earthquake; R is the distance between the functional system and the seismic zone; A, B, C, D, and E are the empirical regression coefficients obtained by fitting different regions; e is a constant with a value of 2.718; the values ​​of A, B, C, D, and E can be referred to in Table 1 below:

[0077] Table 1 Reference table of different values

[0078]

[0079] In this embodiment, when applying the seismic motion attenuation formula in the scenario before an earthquake, using the most unfavorable scenario for setting can ensure the conservatism of the risk assessment and ensure that the risk assessment results correspond to the most extreme seismic motion scenario that the functional system may withstand; and the seismic motion attenuation formula is used both before and after the earthquake, and the PGA of each power grid device is different with different distances, realizing the transformation of earthquake risk assessment from experience-driven to data-driven, and improving the accuracy of the prediction.

[0080] In a specific embodiment, before an earthquake, step S23 specifically includes the following steps:

[0081] S231: Acquire several historical earthquake data;

[0082] S232: Constructing a seismic motion set from a plurality of seismic data, wherein the seismic motion set includes at least one strong seismic motion, at least one moderate seismic motion, and an average seismic motion obtained by averaging the plurality of seismic data;

[0083] S233: Obtain the magnitude of each earthquake motion in the earthquake motion concentration and calculate the minimum straight-line distance from the functional system to the earthquake zone in each earthquake motion, and then use the earthquake motion attenuation formula to calculate the maximum peak acceleration at the functional system under earthquake motions of different intensities.

[0084] In this embodiment, the core innovation lies in constructing a seismic motion set when facing the pre-earthquake scenario. The seismic motion set contains seismic motions of different levels. The damage probability of power grid equipment is determined based on the different levels of seismic motion, and then the risk results under different levels of seismic motion are obtained. Through the combination of typicality + extremeness + diversity, a scientific seismic motion input set is provided for the regional power grid seismic resistance assessment, ensuring the comprehensiveness of the pre-earthquake prevention results.

[0085] In a specific embodiment, the relationship between the damage probability of the power grid equipment in the power grid equipment vulnerability curve in step S1 and the PGA is:

[0086]

[0087] Among them, P 受损 (PGA = x) is the probability of damage to electrical equipment when PGA = x during the input earthquake; Φ() is the cumulative distribution function of the standard normal distribution; μ and σ are the mean and variance of lnx, respectively. Knowing PGA through this relationship allows us to determine the probability of damage to the power grid equipment.

[0088] In a specific embodiment, step S1 further includes classifying the power grid equipment in each functional system according to equipment type and voltage level, and then obtaining the corresponding power grid equipment vulnerability curve after the classification is completed.

[0089] In this embodiment, taking into account the differences in equipment types and the importance and design standards of equipment reflected in the power grid by voltage levels, the priority of power grid equipment can be screened, resource allocation can be optimized, and the accuracy of the matching of the vulnerability curve of power grid equipment can be improved. Specifically, it can be shown in Table 2 below: Table 2 shows some equipment in the regional power grid. These five equipment are divided into "transformer type" according to equipment type: main transformer A, distribution transformer B; "switch equipment type": GIS switch C, outdoor circuit breaker D; "measuring equipment type": voltage transformer E; divided into "220kv type" according to voltage level: main transformer A, voltage transformer E; "110kv type" GIS switch C; "35kv type": outdoor circuit breaker D;

[0090] Table 2 Classification of power grid equipment

[0091] Device Name Device Type Voltage level Main transformer A transformer 220kV Distribution transformer B transformer 10kV GIS switch C switchgear 110kV Outdoor circuit breaker D switchgear 35kV Voltage transformer E Measuring equipment 220kV Distribution Line F transmission lines 10kV

[0092] In one specific embodiment, step S5 is also included: assessing the damage risk of power grid equipment before and after the earthquake based on the number of damaged power grid devices, and then visually presenting the damage risk. In this embodiment, the damage risk is categorized into three levels: high, medium, and low, based on the number of damaged devices. The threshold for the number of damaged devices is manually set based on the site environment. Visualizing the damage risk allows decision makers to intuitively and efficiently identify key protection targets, improving decision-making efficiency and enhancing collaborative capabilities.

[0093] In one specific embodiment, the earthquake risk mitigation strategy for the power grid equipment in step S4 includes increasing or decreasing the number of backup devices for the power grid equipment accordingly: when the number of damaged power grid equipment reaches a first set value, the number of backup devices for the power grid equipment is increased; when the number of damaged power grid equipment is less than a second set value, the number of backup devices for the power grid equipment is decreased, where the first set value is greater than the second set value. In this embodiment, by rationally increasing or decreasing the number of backup devices for the power grid equipment, costs are balanced while ensuring that the power grid equipment can be quickly repaired and replaced to resume operation after an earthquake. Furthermore, by simply storing a reasonable number of backup devices, the operation is simple, requiring no complex theoretical knowledge or complicated process operations, and thus saving labor costs.

[0094] In a specific embodiment, a system for a method for monitoring earthquake risk of a regional power grid as described in any one of the above items includes:

[0095] Power grid equipment vulnerability curve module: used to store the log-normal distribution curve formed by the damage probability and PGA of power grid equipment; this module generates the log-normal distribution relationship between the damage probability and PGA of each power grid equipment based on the characteristics of various power grid equipment and historical earthquake data;

[0096] Earthquake intensity recording module: used to record the parameters of earthquakes occurring in the area where the regional power grid is located; and calculate the maximum peak acceleration at the functional system where the power grid equipment is located; specifically, this module can collect earthquake motions occurring near the regional power grid, record the earthquake response spectrum in three directions (horizontally north-south, horizontally east-west, and vertically) and determine the precise longitude and latitude of the epicenter, and then model the propagation of earthquake waves through the earthquake attenuation formulas in different regions to obtain the specific intensity of the earthquake waves when they reach the actual locations of important equipment in various functional systems of the regional power grid (that is, calculate the maximum peak acceleration at the functional system through the earthquake attenuation formula); specifically, this module is connected to the earthquake rapid reporting interface of the China Earthquake Networks Center, automatically obtains parameters such as the depth of the epicenter, magnitude, and epicenter location, and combines the local geological structure model and the earthquake attenuation relationship to calculate the PGA value of each power grid equipment location;

[0097] Vibration monitoring module: used to collect real-time data on grid equipment in each functional system within the regional power grid during an earthquake. The vibration monitoring module includes sensing devices such as accelerometers, displacement meters, and laser rangefinders. It can collect vibration data from equipment at a frequency of no less than 100 Hz during an earthquake and input it into the risk assessment module.

[0098] Risk Assessment Module: This module calculates the probability of damage to power grid equipment and the amount of damaged equipment; it also generates earthquake risk mitigation strategies. Specifically, based on the vulnerability curves of power grid equipment, the intensity attenuation of the earthquake, and the vibration state of the equipment, it assesses the potential damage risks to key equipment in various functional systems within the regional power grid before and after the earthquake, and outputs the assessment results.

[0099] Database: used to store the relevant parameters of earthquakes that have occurred in the regional power grid in the past, as well as the relevant parameters of earthquakes when an earthquake occurs. The relevant parameters include basic information such as the magnitude and intensity of the local earthquake. It also stores detailed data such as the operating status, maintenance records, and post-earthquake damage of power grid equipment. By storing various key data, efficient data sharing between different departments and institutions is achieved, and it also provides a basis for the future construction of regional power grids and earthquake relief.

[0100] In other words, this system is divided into two situations: Before an earthquake: First, information statistics are collected for all functional systems in the regional power grid to be assessed, the geographical distribution data of each functional system in the regional power grid is obtained, the latitude and longitude coordinates of the functional system sites are determined, and the number of various types of power grid equipment at different voltage levels is calculated. Then, the system inputs the collected acceleration response spectrum of local historical earthquake motions. Based on the earthquake intensity, the minimum straight-line distance between each functional system of the regional power grid and the nearby fault zone, and the local earthquake attenuation law, the system calculates the damage probability of each power grid equipment in the functional system under historical earthquake motion, multiplies the probability by the total number of corresponding equipment in the corresponding functional system, and rounds it up. Finally, based on the overall damage situation of the regional power grid and the estimated number of damaged major equipment, the system can optimize and adjust the number of spare parts for each major equipment.

[0101] After an earthquake: When an earthquake occurs, the system can quickly obtain the magnitude of the earthquake and the longitude and latitude coordinates of the epicenter, automatically calculate the actual distance between each functional system of the regional power grid and the epicenter, and combine the local earthquake motion attenuation law to obtain the actual earthquake magnitude after attenuation at the location of each major electrical equipment. The system also calculates the probability of damage to the corresponding equipment under the action of this earthquake through the equipment's vulnerability curve.

[0102] It's also worth noting that the system is equipped with a machine learning algorithm that uses in-depth learning and repeated training based on a large amount of data collected, including power grid equipment damage records, earthquake intensity, epicenter distance, epicenter location, and equipment vibration status. Using this data, the system's model can identify and learn the complex relationship between earthquake intensity and power grid equipment damage, thereby establishing an earthquake damage risk assessment model and improving the speed of equipment earthquake risk assessment. Furthermore, through supervised learning algorithms, the system can continuously optimize equipment vulnerability curves and accurately predict post-earthquake equipment damage.

[0103] The system of the present invention realizes the transformation of earthquake risk assessment from experience-driven to data-driven through the synergy between various modules. It can not only realize the rapid repair and maintenance of power grid equipment after the earthquake, but also conduct risk assessment of power grid equipment before the earthquake in a proactive manner, so as to formulate earthquake risk resistance strategies for power grid equipment, better resist risks when an earthquake occurs, ensure the continuous operation and rapid recovery capability of the power system, and avoid greater economic and social losses caused by power failures; at the same time, the system combines the fragility curve and the earthquake motion attenuation formula to calculate the destruction probability of power equipment, integrate multi-dimensional risk driving factors, and ensure the accuracy of the results.

[0104] Because previous systems focused on post-earthquake equipment risk assessment and were mostly manually controlled, the transmission of damage information for each device was slow and the response time was long, making it difficult to meet the efficiency requirements of earthquake disaster emergency management. Therefore, in view of the above factors, a system for earthquake risk monitoring of regional power grids was developed. The system combines local historical earthquake damage to conduct pre-earthquake risk prediction. After an earthquake occurs, this system can integrate multiple dimensional technologies such as earthquake intensity, equipment vulnerability, and dynamic real-time monitoring of vibration and risk assessment to achieve real-time monitoring and assessment of the post-earthquake status of regional power grid equipment. At the same time, pre-earthquake prediction information and earthquake damage assessment information are quickly transmitted to the power grid control center via the network, enhancing the overall resilience of the power system to emergencies.

[0105] In a specific embodiment, the vibration monitoring module includes sensors provided on the power grid equipment. The installation positions of different types of sensors on the power grid equipment are as follows:

[0106] In the GIS and GIL circuits, sensors are placed on the fixed and sliding supports of the pipelines;

[0107] The pillar-type equipment in the AC filter circuit has high stress at the root of the pillar insulator under earthquake action, which is easy to be damaged. Sensors are arranged at the root of the pillar insulator of each device.

[0108] In the converter valve hall and converter transformer circuit, the high-voltage wall bushings, suspended converter valves, and converter transformer bushings are most susceptible to damage under earthquakes. Sensors are placed at the bushing roots of each device and on the bottom shielding cover of the suspended valve tower.

[0109] In this embodiment, the vibration state of the equipment during operation is monitored in real time by sensors, and earthquake motion parameters are input to predict the damage probability of each electrical equipment before the earthquake and the damage situation after the earthquake. The evaluation results are reported in a timely manner to improve the resilience of the regional power grid.

[0110] In a specific embodiment, it also includes:

[0111] Signal transmission module: used to transmit the results of the risk assessment module to the regional power grid control center. This module quickly transmits the results to the regional power grid control center through the network or other communication methods to enable timely scheduling decisions and improve power grid resilience. Wireless communication technology or optical fiber communication technology can be used to quickly transmit the results of the risk assessment module to the power grid control center and related emergency response decision-making platforms within 5 minutes after an earthquake occurs in the epicenter area.

[0112] Results Visualization Module: This module visualizes the results of the risk assessment module. Specifically, it constructs a 1:1 scale digital twin 3D model that dynamically displays the equipment's epicenter response. It also displays grid damage distribution, equipment status statistics, and dispatch recommendations through an interactive graphical user interface.

[0113] In addition, the system can also realize multi-platform notifications, quickly notifying relevant personnel such as dispatchers, engineers and emergency management personnel through SMS, email, mobile applications, etc., avoiding the drawbacks of one-level transmission and ensuring the timeliness of information transmission.

[0114] In order to further understand the solution of this application, the following examples are given:

[0115] Taking the converter transformer in the functional system as an example, the Yunnan regional power grid, the earthquake attenuation formula in Yunnan is:

[0116] lg(PGA)=(-2.7317+0.0889M)lg(R+13)+0.288M+3.5549

[0117] After the earthquake, the system immediately obtained the earthquake's latitude and longitude, as well as its magnitude M. It then calculated the epicenter distance R at the valve hall circuit. Substituting this into the above formula for earthquake attenuation in Yunnan Province, it derived the maximum peak acceleration PGA of the actual ground motion at the valve hall circuit. The fragility curve parameters for the 220kV converter transformer are μ = -0.9973; σ = 0.6478; Therefore, the probability of damage to the converter transformer in the regional power grid substation system can be calculated as:

[0118]

[0119] The system saves the calculated results in a database and generates Excel spreadsheets containing resilience indicators such as the probability of damage to each device and the estimated number of damaged devices, which are then transmitted to the grid control center and relevant departments. To more directly assess the damage to key electrical equipment within the regional power grid, the system utilizes digital twin technology to visualize and create a platform interface for each functional system within the regional power grid.

[0120] Overview diagram as follows Figure 2As shown, key equipment, such as the converter transformer in this example, is visualized as a 3D model in the center column of the interface. After inputting earthquake motion, a vibration video of the equipment and the location of seismic weaknesses can be intuitively obtained. The upper half of the left tab contains a physical image of the equipment, transmitted in real time by monitoring equipment deployed near the key equipment. The deployment method can vary depending on the characteristics and importance of the equipment. For example, cameras can be deployed around the foundation of the converter transformer to obtain all-round, multi-angle real-time monitoring photos and videos, further optimizing analysis results and obtaining the most accurate monitoring data. The lower half of the left tab also includes detailed information about the equipment, such as specific voltage and maintenance time, to help operators understand the normal parameters of the equipment and carry out daily maintenance work in a more organized manner. The upper half of the right tab displays the equipment vulnerability curve, while the lower half details the real-time monitoring data, including the Fourier acceleration response spectrum of the equipment's real-time monitoring in the x, y, and z directions after the earthquake input. This allows personnel to conduct risk assessments of electrical equipment based on the equipment's real-time vibration conditions and vulnerability curves.

[0121] The examples described in the present invention are merely descriptions of the preferred embodiments of the present invention and are not intended to limit the concept and scope of the present invention. Without departing from the design concept of the present invention, various modifications and improvements made to the technical solutions of the present invention by engineers and technicians in this field should fall within the scope of protection of the present invention.

Claims

1. A method for monitoring earthquake risk in a regional power grid, characterized by: The steps include: S1: Divide the regional power grid into several functional systems and obtain a corresponding power grid equipment vulnerability curve for the power grid equipment in each functional system; the power grid equipment vulnerability curve is a log-normal distribution curve formed by the probability of damage of the power grid equipment and the PGA; the PGA is the maximum peak ground acceleration where the power grid equipment is located; S2: Obtain the geographical distribution data of each functional system, and calculate the maximum peak acceleration of each functional system before and after the earthquake using the earthquake attenuation formula; S3: Calculate the damage probability of the power grid equipment in each of the two cases based on the power grid equipment vulnerability curve and the maximum peak acceleration at the functional system, and multiply the damage probability of a single power grid equipment by the number of power grid equipment of the same type in the functional system to obtain the number of damaged power grid equipment; S4: Develop earthquake risk mitigation strategies for power grid equipment based on the amount of damaged equipment.

2. The earthquake risk monitoring method for a regional power grid according to claim 1, characterized in that: The step S2 specifically includes the following steps: S21: Obtain the latitude and longitude coordinates of the site of the functional system; S22: Calculate the distance between the functional system and the earthquake zone; specifically including: Distance calculation before earthquake: calculate the minimum straight-line distance from the functional system to the earthquake zone; Distance calculation after earthquake: calculate the actual distance from the functional system to the epicenter of the earthquake zone; S23: Calculate the maximum peak acceleration of the functional system according to the earthquake attenuation formula, which is: log(PGA)=A+BM+Clog(R+De EM ) Wherein, PGA is the maximum peak acceleration of the ground where the power grid equipment is located; M is the historical magnitude before the earthquake, and M is the magnitude of the earthquake after the earthquake; R is the distance from the functional system to the earthquake zone; A, B, C, D, and E are the empirical regression coefficients obtained by fitting different regions; e is a constant with a value of 2.

718.

3. The earthquake risk monitoring method for a regional power grid according to claim 2, characterized in that: In the case before an earthquake, step S23 specifically includes the following steps: S231: Acquire several historical earthquake data; S232: Constructing a seismic motion set from a plurality of seismic data, wherein the seismic motion set includes at least one strong seismic motion, at least one moderate seismic motion, and an average seismic motion obtained by averaging the plurality of seismic data; S233: Obtain the magnitude of each earthquake motion in the earthquake motion set, and then use the earthquake motion attenuation formula to calculate the maximum peak acceleration of the functional system under earthquake motions of different intensities.

4. The earthquake risk monitoring method for a regional power grid according to claim 1, characterized in that: The relationship between the damage probability of the power grid equipment in the power grid equipment vulnerability curve in step S1 and the PGA is: Among them, P 受损 (PGA = x) is the probability of damage to electrical equipment when PGA = x in the input earthquake motion; Φ() is the cumulative distribution function of the standard normal distribution; μ and σ are the mean and variance of lnx, respectively.

5. A method for monitoring earthquake risk in a regional power grid according to claim 1 or 4, characterized in that: The step S1 further includes classifying the power grid equipment in each functional system according to equipment type and voltage level, and then obtaining the corresponding power grid equipment vulnerability curve after the classification is completed.

6. The earthquake risk monitoring method for a regional power grid according to claim 1, characterized in that: The method further includes step S5: evaluating the damage risk of the power grid equipment before and after the earthquake based on the amount of damaged power grid equipment, and then visually presenting the damage risk.

7. The earthquake risk monitoring method for a regional power grid according to claim 1, characterized in that: The earthquake risk prevention strategy for the power grid equipment in step S4 includes correspondingly increasing or decreasing the number of backup devices of the power grid equipment: when the number of damaged power grid equipment reaches a first set value, the backup number of the power grid equipment is increased; when the number of damaged power grid equipment is less than a second set value, the backup number of the power grid equipment is reduced, and the first set value is greater than the second set value.

8. A system for monitoring earthquake risk of a regional power grid according to any one of claims 1 to 6, characterized in that: include: Power grid equipment vulnerability curve module: used to store the log-normal distribution curve formed by the damage probability of power grid equipment and PGA Earthquake intensity recording module: used to record the parameters of earthquakes occurring in the area where the regional power grid is located; and calculating the maximum peak acceleration of the functional system where the power grid equipment is located; Vibration monitoring module: used to collect real-time data on grid equipment in each functional system within the regional power grid when an earthquake occurs; Risk assessment module: used to calculate the probability of damage to power grid equipment and the amount of damaged power grid equipment; and generate earthquake risk mitigation strategies; Database: used to store relevant parameters of earthquakes that occurred in the regional power grid in the past.

9. The earthquake risk monitoring system for a regional power grid according to claim 8, characterized in that: The vibration monitoring module includes sensors installed on the power grid equipment. The installation locations of different types of sensors on the power grid equipment are as follows: In the GIS and GIL circuits, sensors are placed on the fixed and sliding supports of the pipelines; For pillar-type equipment in the AC filter circuit, the sensor is placed at the root of the pillar insulator of each device; In the converter valve hall and converter transformer circuit, sensors are arranged at the roots of the bushings of each device and on the bottom shielding cover of the suspended valve tower.

10. The earthquake risk monitoring system for a regional power grid according to claim 8, characterized in that: Also includes: Signal transmission module: used to transmit the results of the risk assessment module to the regional power grid control center; Result visualization display module: used to visualize the results of the risk assessment module.

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