Power grid geological disaster risk assessment method and system based on dynamic data

Abstract

The invention belongs to the technical field of geological disaster risk assessment, and particularly relates to a power grid geological disaster risk assessment method and system based on dynamic data, and the method comprises the steps: analyzing historical meteorological data according to historical geological disaster data, and generating geological disaster associated meteorological data and geological disaster rating; dividing the power transmission line according to the pole and tower material information and the pole and tower terrain information of the power transmission line, and generating a pole and tower area with the same material and a pole and tower area with the same terrain; sorting the historical geological disaster data according to the geological disaster rating, and generating a power grid disaster influence table; performing retrieval analysis on the power grid disaster influence table to generate regional influence degrees; according to the geological disaster associated meteorological data, analyzing historical meteorological data, and obtaining a geological disaster recovery index; according to historical power grid disaster data, analyzing a geological disaster recovery index, and generating a disaster response capability value; and according to the real-time meteorological data, analyzing the regional influence degree and the disaster response capability value, and generating a geological disaster risk assessment value.

Description

Technical Field

[0001] The present invention belongs to the technical field of geological disaster risk assessment, and in particular relates to a method and system for evaluating geological disaster risks in power grids based on dynamic data. Background Art

[0002] Power grids are widely distributed and pass through various complex geological areas. They are vulnerable to geological disasters such as earthquakes and landslides. Earthquake vibrations loosen the foundations of poles and towers, causing them to collapse, break lines, and damage substation buildings and equipment. Landslides cause poles to shift and deform, lines to stretch and break, and squeeze substation facilities. Mud and rock flows destroy the foundations of poles and towers, break lines, bury equipment, and cause short-circuit failures in substations, seriously affecting the safe and stable operation of the power grid, hindering the normal transmission of electricity, and causing great inconvenience and losses to social production and life. Conducting geological disaster risk assessments on power grids, in areas where power grids have been built, the assessment results can help formulate targeted reinforcement measures and enhance the disaster resistance of power grid facilities.

[0003] Existing power grid geological disaster risk assessment methods mainly rely on static historical data, which makes it difficult to capture the dynamic factors of geological conditions and meteorological changes in a timely manner. Due to limited monitoring equipment in areas with complex terrain, it is difficult to comprehensively collect geological data, and the data is not updated in a timely manner, which cannot adapt to the complex and changeable actual situation. When faced with sudden disasters, it is impossible to respond and adjust quickly. The analysis of risk response capabilities is limited, and it is difficult to fully integrate data from different sources and types. As a result, the risk assessment results are lagging and one-sided, which reduces the reference value of the risk assessment results for power grid disaster prevention and mitigation.

[0004] The patent document with publication number CN119671278A discloses a method, device and computer equipment for assessing geological disaster risks along power grids. The method includes: constructing a sample database based on historical geological disaster data in the target area along the power grid; constructing a training sample database based on at least two environmental influencing factors and the sample database, and training the training sample database based on preset machine learning method parameters to obtain at least two geological disaster risk assessment models; comparing the geological disaster risk assessment models to obtain a target risk assessment model; and conducting a geological disaster assessment on the target area using the target risk assessment model. This method can improve the accuracy of geological disaster risk assessment along power grids; significantly reduce personnel costs and time costs, and improve risk assessment efficiency, but it does not propose features such as the terrain zoning flattening index of tower materials, and in particular lacks the linkage between real-time meteorological data and emergency repair resources;

[0005] The invention with publication number CN117788245A discloses a geological hazard risk assessment method and system based on a fuzzy comprehensive evaluation method, the method comprising: step 1, collecting geological data and historical geological hazard data of an assessment area; step 2, obtaining evaluation index data and establishing a geological hazard risk assessment index set; step 3, determining the evaluation results and establishing a geological hazard risk comment set; step 4, establishing an evaluation matrix to perform single-factor evaluation on geological hazard influencing factors in the assessment area; step 5, constructing a comprehensive evaluation matrix of the membership between the evaluation indicators and the evaluation results; step 6, determining the weight of each evaluation indicator based on the hierarchical analysis method; step 7, calculating the fuzzy matrix through fuzzy operation according to the weight of each evaluation indicator and the comprehensive evaluation matrix, and determining the evaluation result in combination with the maximum membership principle, but without combining the power grid emergency repair response capability or dynamic meteorological data. Summary of the Invention

[0006] The purpose of the present invention is to provide a power grid geological disaster risk assessment method and system based on dynamic data to address the problems existing in the prior art, which solves the problems raised in the background technology, such as the difficulty in comprehensively collecting geological data for complex terrain, the limited analysis of risk response capabilities, the inability to respond and adjust quickly in the face of sudden disaster events, and the difficulty in comprehensively integrating data from different sources and different types, resulting in the lag and one-sidedness of risk assessment results.

[0007] In order to achieve the above objects, the technical solution adopted by the present invention is:

[0008] S1. Obtain historical geological disaster data and historical meteorological data;

[0009] S2. Analyze historical meteorological data based on historical geological disaster data, obtain meteorological data associated with geological disasters, and generate geological disaster ratings;

[0010] S3 collects transmission line tower material information and tower terrain information, respectively, according to the tower material information and tower terrain information to divide the transmission line, generate the same material tower area and the same terrain tower area;

[0011] S4. Based on the geological disaster rating, organize historical geological disaster data and generate a grid disaster impact table;

[0012] S5. Using the same material tower area and the same terrain tower area as the benchmark, perform a search and analysis in the power grid disaster impact table to generate the tower area impact degree;

[0013] S6. Analyze historical meteorological data based on meteorological data associated with geological disasters to obtain a geological disaster recovery index;

[0014] S7. Obtain historical power grid disaster data and combine it with the geological disaster recovery index to generate a disaster response capability value;

[0015] S8. Obtain real-time meteorological data and generate a geological disaster risk assessment value based on regional impact and disaster response capability values.

[0016] Preferably, generating a table of power grids affected by disasters specifically includes the following steps:

[0017] Organize historical geological disaster data and obtain information on the time when geological disasters occurred;

[0018] Collect historical natural environment data of the power grid area and the correlation between meteorological disaster triggering from geological disaster monitoring agencies;

[0019] Refer to the time information of geological disasters, search the historical natural environment data of the power grid area, and obtain the environmental data before the geological disaster;

[0020] Organize historical geological disaster data and historical meteorological data, match them according to time and space dimensions, and generate historical disaster environment data;

[0021] The environmental data before geological disasters and historical disaster environmental data are sorted and classified respectively to generate geological data before disasters, meteorological data before disasters, geological data during disasters and meteorological data during disasters;

[0022] According to the correlation between meteorological disasters, geological data and meteorological data in disasters are analyzed to obtain meteorological data associated with geological disasters and generate disaster-associated change trends;

[0023] Cluster analysis is performed on the geological data before and during the disaster, and the meteorological data before and during the disaster to generate disaster geological characteristic data and disaster meteorological characteristic data;

[0024] According to the associated change trend of disasters, the geological characteristic data and meteorological characteristic data of disasters are analyzed to obtain the evolution trend of standard disasters and generate geological disaster ratings;

[0025] Obtain historical disaster data of transmission lines, organize and analyze the data based on different tower material areas and different terrain areas, and generate regional disaster coefficients;

[0026] Combining the regional disaster coefficient and geological disaster rating, a power grid disaster impact table is generated.

[0027] Preferably, generating the tower area influence comprises the following steps:

[0028] Search the power grid disaster impact table based on the material tower area and terrain tower area to obtain the disaster coefficient of each tower area;

[0029] Analyze historical disaster data of transmission lines to obtain historical disaster recovery time;

[0030] Collect grid planning information to obtain the transmission line characteristics, number of covered users, and tower adaptation coefficients of each tower area;

[0031] According to the transmission line characteristics of each tower area, the disaster coefficient of each tower area is analyzed to obtain the power grid damage index of each area;

[0032] Combine the number of users covered by each tower area and the damage index of each area to generate the regional user damage value;

[0033] According to the tower adaptation coefficient, the damage value of users in the area with the same terrain type is analyzed to generate the regional impact.

[0034] Preferably, generating the geological disaster recovery index specifically includes the following steps:

[0035] Obtain historical meteorological recovery time based on geological disaster-associated meteorological data and disaster-associated change trends;

[0036] By analyzing the changing trends associated with disasters, the historical meteorological recovery time is analyzed to generate a time period series;

[0037] Organize and classify historical power grid disaster data to obtain key power historical data and steady-state power historical data;

[0038] Analyze key power historical data based on time period series to obtain key power restoration time;

[0039] Based on the time period series, the historical meteorological calming time and key power restoration time of the same terrain are analyzed to generate the key power restoration delay coefficient;

[0040] Based on the time period series, the critical power restoration time of the same area is compared with the steady-state power restoration time in the steady-state power historical data to generate the restoration transition time;

[0041] Analyze the restoration transition time and the steady-state power restoration time in the steady-state power history data to generate a steady-state power restoration delay coefficient;

[0042] The key power restoration delay coefficient and the steady-state power restoration delay coefficient are ratio-processed to generate a geological disaster recovery index.

[0043] Preferably, generating the disaster response capability value specifically includes the following steps:

[0044] Through the Geological Disaster Monitoring Bureau, obtain the historical disaster frequency and historical damage value of ground buildings in various terrains;

[0045] Analyze the historical frequency of disasters and the historical damage values of ground buildings in each terrain to generate a terrain risk index;

[0046] Organize historical power grid disaster data according to the terrain risk index to generate power grid disaster records under terrain risk;

[0047] Obtaining a historical record of power grid emergency repairs in the same terrain, wherein the historical record includes the number of historical repair personnel, the number of historical repair equipment, and the historical repair time;

[0048] Based on the time period sequence, the historical emergency repair time is divided. Combined with the power grid disaster records under terrain risks, the historical number of emergency repair personnel and historical number of emergency repair equipment corresponding to different emergency repair time periods in each disaster record are generated.

[0049] Based on the emergency repair time period, the historical number of emergency repair personnel and the historical number of emergency repair equipment corresponding to different emergency repair time periods in each disaster record are analyzed to generate the comprehensive value of emergency repair resources in each time period;

[0050] The comprehensive value of emergency repair resources in each time period is averaged and combined with the geological disaster recovery index to generate the disaster response capability value.

[0051] Preferably, generating a geological disaster risk assessment value specifically includes the following steps:

[0052] Arrange historical geological disaster data in descending order of geological disaster rating to obtain a disaster rating sequence, and combine it with regional impact to generate a disaster regional impact mapping sequence;

[0053] According to the disaster rating sequence, the disaster response capability values corresponding to various geological hazards are analyzed to generate a disaster rating response capability mapping sequence;

[0054] The disaster regional impact mapping sequence and the disaster rating response capability mapping sequence are sorted and analyzed in turn to generate the maximum regional impact, minimum regional impact, maximum disaster response capability, minimum disaster response capability, and the geological disaster rating corresponding to each maximum value;

[0055] According to the geological disaster rating corresponding to each extreme value, the maximum and minimum regional impact values, as well as the maximum and minimum disaster response capabilities, are analyzed respectively, and the impact change coefficient and response capability change coefficient are generated in turn;

[0056] Obtain the terrain type where the power transmission line to be evaluated is located;

[0057] Analyze real-time meteorological data based on meteorological data associated with geological hazards to generate estimated geological hazard ratings;

[0058] Taking the influence variation coefficient and response capacity variation coefficient as weight values, the influence and disaster response capacity values of the areas with the same terrain type as the power transmission line to be assessed under the expected geological disaster rating are weighted and averaged to generate the geological disaster risk assessment value.

[0059] A power grid geological disaster risk assessment system based on dynamic data, applicable to the above-mentioned risk assessment method, includes:

[0060] A data collection module is used to collect historical geological disaster data, historical meteorological data, transmission line tower material information, tower topography information, and historical power grid disaster data, and transmit the data to the data integration module and the data management module;

[0061] A data integration module is used to integrate and analyze the received data, obtain geological disaster associated meteorological data by analyzing historical meteorological data, generate a geological disaster rating, analyze historical meteorological data based on the geological disaster associated meteorological data, obtain a geological disaster recovery index, generate a disaster response capability value, and transmit the data to the data management module, the risk assessment module, and the data display module;

[0062] A data management module, which is used to summarize and store the received data, divide the transmission lines according to the tower material information and the tower terrain information, generate areas of towers of the same material and areas of towers of the same terrain, perform retrieval and analysis in the power grid disaster impact table based on the areas of towers of the same material and areas of towers of the same terrain, generate regional impact, and transmit the data to the data integration module, the risk assessment module, and the data display module;

[0063] A risk assessment module is used to analyze the received data, generate a geological disaster risk assessment value based on real-time meteorological data, combined with the regional impact and disaster response capability value, and transmit the data to the data display module;

[0064] The data display module is used to organize the received data and output the organized results for display.

[0065] Preferably, the data collection module specifically includes:

[0066] A first collection unit, which is used to collect historical natural environment data of the power grid area and the correlation between meteorological disaster triggering from the geological disaster monitoring agency, obtain historical data of the power grid transmission line system and historical data of power grid emergency repairs, and transmit the data to the data integration module;

[0067] The second collection unit is used to obtain historical geological disaster data, historical meteorological data, historical disaster frequencies of various terrains and historical damage values of ground buildings through the Geological Disaster Monitoring Bureau, and transmit the data to the data integration module.

[0068] Preferably, the data integration module specifically includes:

[0069] A first integration unit is configured to analyze geological data and meteorological data in disasters according to the correlation between meteorological disaster triggering, obtain meteorological data associated with geological disasters, generate disaster associated change trends, analyze disaster geological characteristic data and disaster meteorological characteristic data according to the disaster associated change trends, obtain standard disaster evolution trends, generate geological disaster ratings, analyze historical disaster data of transmission lines according to different tower material areas and different terrain areas, generate regional type disaster coefficients, combine the geological disaster ratings, generate a power grid disaster impact table, and transmit the data to the data management module and the risk assessment module;

[0070] The second integration unit is used to analyze the historical disaster data of the transmission line, obtain the historical disaster recovery time, analyze the disaster coefficient of each tower area according to the transmission line characteristics of each tower area, obtain the power grid damage index of each area, combine the number of users covered by each tower area and the damage index of each area, generate the regional user damage value, analyze the user damage value of the area with the same terrain type according to the tower adaptation coefficient, generate the regional impact, and transmit the data to the data management module and the risk assessment module;

[0071] A third integration unit is used to analyze the historical meteorological recovery time based on the disaster-associated change trend, generate a time period sequence, analyze the time information based on the time period sequence, generate a key power restoration delay coefficient and a steady-state power restoration delay coefficient, generate a geological disaster recovery index by calculating the ratio of the key power restoration delay coefficient and the steady-state power restoration delay coefficient, and transmit the data to the data management module and the risk assessment module;

[0072] The fourth integration unit is used to analyze the historical frequency of disasters and the historical damage values of ground buildings in various terrains, generate a terrain risk index, analyze the historical number of emergency repair personnel and the historical number of emergency repair equipment corresponding to different emergency repair time periods in each disaster record, generate a comprehensive value of emergency repair resources for each time period, average the comprehensive value of emergency repair resources for each time period, combine it with the geological disaster recovery index, generate a disaster response capability value, and transmit the data to the data management module and the risk assessment module.

[0073] Preferably, the data management module specifically includes:

[0074] a first management unit, configured to retrieve historical natural environmental data of the power grid area with reference to time information of geological disaster occurrence, obtain environmental data before the geological disaster, match them according to time and space dimensions, generate geological data before the disaster, meteorological data before the disaster, geological data during the disaster, and meteorological data during the disaster, and transmit the data to a data integration module and a data display module;

[0075] A second management unit, which is used to organize and classify historical power grid disaster data, obtain key power historical data and steady-state power historical data, analyze the key power historical data based on a time period sequence, obtain key power restoration time, and transmit the data to the data integration module and the data display module;

[0076] The third management unit is used to organize historical power grid disaster data according to the terrain risk index, generate power grid disaster records under terrain risks, divide historical emergency repair times according to time period sequences, and combine power grid disaster records under terrain risks to generate the historical number of emergency repair personnel and the historical number of emergency repair equipment corresponding to different emergency repair time periods in each disaster record, and transmit the data to the data integration module, risk assessment module and data display module.

[0077] Compared with the prior art, the present invention has the following beneficial effects:

[0078] The present invention proposes a method for assessing geological disaster risks in power grids based on dynamic data. The method analyzes historical meteorological data based on historical geological disaster data, obtains meteorological data associated with geological disasters, generates geological disaster ratings, collects tower material information and tower terrain information of transmission lines, divides transmission lines based on tower material information and tower terrain information, generates tower areas with the same material and tower areas with the same terrain, organizes historical geological disaster data based on geological disaster ratings, generates a grid disaster impact table, and uses tower areas with the same material and tower areas with the same terrain as benchmarks to perform retrieval and analysis in the grid disaster impact table to generate regional impact scores. According to the meteorological data associated with geological disasters, historical meteorological data are analyzed to obtain the geological disaster recovery index, historical power grid disaster data are obtained, and the geological disaster recovery index is combined to generate a disaster response capability value. Real-time meteorological data are obtained, and the regional impact and disaster response capability value are combined to generate a geological disaster risk assessment value. Through this method, the requirements for geological monitoring equipment in areas with complex terrain can be effectively reduced, and the adaptability to actual conditions can be improved. When facing sudden disaster events, it can respond and adjust quickly, strengthen the analysis of risk response capabilities, reduce the lag and one-sidedness of risk assessment results, and improve the reference value of risk assessment results for power grid disaster prevention and mitigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 This is a flow chart of the method for assessing the risk of geological disasters in power grids based on dynamic data proposed by the present invention;

[0080] Figure 2 A flow chart of the method for generating a table of power grid affected by disasters;

[0081] Figure 3 A flow chart of the method for generating the tower area influence degree;

[0082] Figure 4 A flow chart of the method for generating geological hazard recovery index;

[0083] Figure 5 A flow chart of the method for generating disaster response capacity values;

[0084] Figure 6 A flow chart of the method for generating geohazard risk assessment values;

[0085] Figure 7 This is a structural diagram of the power grid geological disaster risk assessment system based on dynamic data proposed in Example 2. DETAILED DESCRIPTION

[0086] The technical solution of the present invention is described in detail below with reference to the accompanying drawings and specific implementation methods.

[0087] Example 1

[0088] like Figure 1 FIG. 1 is a flow chart of a method for assessing geological disaster risks in a power grid based on dynamic data provided by this embodiment, comprising the following steps:

[0089] S1. Obtain historical geological disaster data and historical meteorological data;

[0090] S2. Analyze historical meteorological data based on historical geological disaster data, obtain meteorological data associated with geological disasters, and generate geological disaster ratings;

[0091] S3 collects transmission line tower material information and tower terrain information, respectively, according to the tower material information and tower terrain information to divide the transmission line, generate the same material tower area and the same terrain tower area;

[0092] S4. Based on the geological disaster rating, organize historical geological disaster data and generate a grid disaster impact table;

[0093] S5. Using the same material tower area and the same terrain tower area as the benchmark, perform a search and analysis in the power grid disaster impact table to generate the regional impact degree;

[0094] S6. Analyze historical meteorological data based on meteorological data associated with geological disasters to obtain a geological disaster recovery index;

[0095] S7. Obtain historical power grid disaster data and combine it with the geological disaster recovery index to generate a disaster response capability value;

[0096] S8. Obtain real-time meteorological data and generate a geological disaster risk assessment value based on regional impact and disaster response capability values.

[0097] This method analyzes historical meteorological data based on historical geological disaster data, obtains meteorological data associated with geological disasters, generates geological disaster ratings, collects tower material information and tower terrain information of transmission lines, divides transmission lines according to the tower material information and tower terrain information, generates tower areas with the same material and tower areas with the same terrain, organizes historical geological disaster data according to the geological disaster ratings, generates a power grid disaster impact table, uses tower areas with the same material and tower areas with the same terrain as benchmarks, performs retrieval and analysis in the power grid disaster impact table, generates regional impact, analyzes historical meteorological data based on meteorological data associated with geological disasters, obtains a geological disaster recovery index, obtains historical power grid disaster data, combines the geological disaster recovery index to generate a disaster response capability value, obtains real-time meteorological data, combines the regional impact and the disaster response capability value, and generates a geological disaster risk assessment value.

[0098] Example 2

[0099] This embodiment provides a method for generating a table of power grid disaster impacts as in the above embodiment 1, such as Figure 2 As shown, the specific steps include:

[0100] a. Organize historical geological disaster data and obtain information on the time when geological disasters occurred;

[0101] b. Collect historical natural environment data of the power grid area and its correlation with meteorological disaster triggering from geological disaster monitoring agencies;

[0102] c. Refer to the time information of the geological disaster, search the historical natural environment data of the power grid area, obtain the environmental data before the geological disaster, use the time information of the geological disaster as a reference item, compare the historical natural environment data of the power grid area according to the time information, determine the time of the geological disaster, integrate the historical natural disaster data of the power grid area corresponding to the three days before the geological disaster, and generate the environmental data before the geological disaster;

[0103] d. Organize historical geological disaster data and historical meteorological data, match them according to the time dimension and space dimension, and generate historical disaster environment data. Organize historical geological disaster data and historical meteorological data separately, obtain the time and location corresponding to historical geological disaster data and historical meteorological data respectively, use the location as the first matching point, match the location of historical geological disaster data and historical meteorological data, and generate historical geological disaster data and historical meteorological data at the same location. Use time as the second matching point, match the time of historical geological disaster data and historical meteorological data at the same location to generate historical disaster environment data.

[0104] e. Organize and classify the environmental data before geological disasters and the environmental data of historical disasters to generate geological data before disasters, meteorological data before disasters, geological data during disasters, and meteorological data during disasters;

[0105] f. Based on the correlation between meteorological disasters, analyze the geological data and meteorological data associated with the disaster, obtain meteorological data associated with the geological disaster, generate the associated change trend of the disaster, determine the various special meteorological parameters based on the correlation between meteorological disasters, and compare the change in the geological data associated with the disaster with the values of the various special meteorological parameters contained in the meteorological data according to the change time. Generate the change in the geological data associated with the disaster corresponding to the change in the values of the various special meteorological parameters contained in the meteorological data, record it as the associated meteorological data of the geological disaster, and generate the associated change trend of the disaster by combining the time information;

[0106] g. Perform cluster analysis on the geological data before and during the disaster, and the meteorological data before and during the disaster to generate disaster geological characteristic data and disaster meteorological characteristic data. By comparing the geological parameters of the geological data before and during the disaster one by one, mark the geological parameters that have changed due to the disaster, and associate them with the type of geological disaster to generate disaster geological characteristic data. By comparing the meteorological parameters of the meteorological data before and during the disaster one by one, mark the meteorological parameters that have changed due to the disaster, and associate them with the type of geological disaster to generate disaster meteorological characteristic data.

[0107] h. Analyze the geological and meteorological characteristics of disasters based on the associated change trends of disasters, obtain the evolution trend of standard disasters, and generate geological disaster ratings;

[0108] i. Obtain historical disaster data on transmission lines, organize and analyze the data based on different tower material areas and different terrain areas, and generate regional disaster coefficients;

[0109] j. Combine the regional disaster coefficient and geological disaster rating to generate a power grid disaster impact table.

[0110] It is understandable that the occurrence of geological disasters is often accompanied by a series of physical processes and energy release, which will have multiple impacts on the surrounding environment. For example, geological disasters such as landslides and mudslides will stir up a large amount of dust into the atmosphere, affecting the visibility and particle concentration of the air, while changing the heat capacity and thermal conductivity of the local air, thereby changing meteorological factors such as temperature and humidity. Earthquakes will trigger crustal movement and the release of underground gas, leading to changes in atmospheric composition, and violent ground vibrations will also affect local air flow movement, interfere with normal meteorological cycles, and cause fluctuations in meteorological environmental data such as air pressure and wind direction. In addition, large-scale vegetation destruction and terrain changes caused by geological disasters will also indirectly affect meteorological environmental data. Natural environmental data, including ground Geological environment data and meteorological environment data. Meteorological environment data fluctuates in real time. There is randomness in analyzing historical disaster data only through historical meteorological data. Therefore, it is necessary to analyze historical meteorological data and historical disaster data from the perspective of time information. The triggering correlation of meteorological disasters means that changes in a single meteorological parameter will lead to geological disasters. There is a positive triggering causal relationship between the two. Heavy rainfall is an important inducement of disasters such as mudslides and landslides. The greater the rainfall and rainfall intensity, and the longer the duration, the more likely the rock and soil will become unstable due to saturation, causing geological disasters. The short-term accumulation of large amounts of water caused by heavy rain will also increase the probability of collapse. In terms of temperature, at high altitudes or in polar regions, the rapid rise in temperature causes large-scale melting of snow, and a large amount of meltwater will trigger Mudslides and floods. In addition, large temperature differences will cause rocks to expand and contract frequently, which will accelerate rock fragmentation and increase the risk of collapse. When the wind speed is too high, additional forces will be exerted on the slope rock and soil, especially in areas with loose soil and sparse vegetation, which can easily lead to loose soil. According to the correlation between meteorological disasters, the meteorological parameters that directly cause geological disasters can be obtained. By sorting out the meteorological data in the disaster through the meteorological parameters that directly cause geological disasters, disaster-related parameters can be generated. According to the fluctuation time of the disaster-related parameters, the geological data in the disaster can be analyzed to generate geological disaster data synchronized with the meteorological fluctuations, and then generate meteorological data associated with geological disasters. The fluctuations of the geological characteristic data of the disaster and the fluctuations of the meteorological characteristic data of the disaster can be used to analyze the disaster. The associated change trends are analyzed to generate the fluctuation rates of the disaster geological characteristics and the disaster meteorological characteristics corresponding to each time period, and then the standard disaster evolution trend is generated. According to the standard disaster evolution trend, each historical geological disaster is rated, and the historical disaster data of the transmission line are analyzed to generate the damage frequency and damage proportion of towers of different materials in the same terrain. The tower material area disaster coefficient and the terrain area disaster coefficient are determined by weighted averaging. The regional disaster coefficients with different geological disaster ratings are averaged from the perspectives of the tower material area and the terrain area, and the average values of the tower material area disaster coefficient and the terrain area disaster coefficient are respectively matched with the geological disaster rating to generate a power grid disaster impact table.

[0111] Example 3

[0112] This embodiment provides the specific steps for generating the influence of the tower area in the method described in Example 1. Figure 3 As shown, specifically including:

[0113] Search the power grid disaster impact table based on the material tower area and terrain tower area to obtain the disaster coefficient of each tower area;

[0114] Analyze the historical disaster data of transmission lines to obtain historical disaster recovery time. Divide the historical disaster data of transmission lines according to the power supply status, and obtain the time from power supply interruption to power supply restoration, which is recorded as the historical disaster recovery time;

[0115] Collect grid planning information to obtain the transmission line characteristics, number of covered users, and tower adaptation coefficients of each tower area;

[0116] According to the transmission line characteristics of each tower area, the disaster coefficient of each tower area is analyzed to obtain the power grid damage index of each area;

[0117] Combine the number of users covered by each tower area and the damage index of each area to generate the regional user damage value;

[0118] According to the tower adaptation coefficient, the damage value of users in the area with the same terrain type is analyzed to generate the regional impact.

[0119] It is understandable that pole towers are the key supporting structures of power transmission lines in power grids. The number of users they cover reflects the scale of the power supply task undertaken by the pole towers. The more users the pole towers cover, the more families, businesses and institutions rely on the pole towers and the transmission lines connected to them to obtain electricity. Once the pole towers fail or are damaged, it will cause power outages for a large number of users, which will lead to a series of serious consequences such as stagnation of production activities, disruption of residents' lives, interruption of public services, etc., which will have a great impact on the social economy and people's lives. Therefore, the number of users covered by the pole towers can intuitively reflect the importance and possible impact of a specific pole tower and the related transmission lines in the power grid on the entire power supply system. The transmission line characteristics of the pole towers include line length, voltage level and pole tower density. The line length determines the range of line exposure to the risk environment. Longer lines are more susceptible to self- The voltage level reflects the importance of the line in the power grid. Once a high-voltage line is damaged, the scope and degree of impact are greater. In terms of line type, overhead lines are easily affected by strong winds, lightning strikes, etc. Although cable lines are highly stable, they are difficult to maintain. The density of pole towers reflects the density of the line support structure, which will affect the stability of the line and the probability of disaster. According to the power grid planning information, the standard value of the transmission line characteristics is obtained. The standard value of the transmission line characteristics is used as the weight. The transmission line characteristics of each tower area are weighted and summed to generate the tower area characteristic value. The tower area characteristic value and the disaster coefficient of each tower area are weighted to obtain the power grid damage index of each area. The damage index of each area is used as the weight value. The number of users covered by each tower area is weighted and summed to generate the regional user damage value. The tower adaptation coefficient and the regional user damage value are multiplied to generate the regional impact.

[0120] Example 4

[0121] This embodiment provides a method for generating a geological disaster recovery index in the embodiment 1, referring to Figure 4 As shown, specifically including:

[0122] According to the meteorological data associated with geological disasters and the changing trends of the associated disasters, the historical meteorological calming time is obtained. The fluctuation characteristics of the meteorological data when the meteorological calming time is determined by the changing trends of the associated disasters. The fluctuation of each meteorological parameter in the meteorological data associated with geological disasters is statistically analyzed, and the meteorological parameters that meet the fluctuation characteristics of the meteorological data are marked. The meteorological parameters that meet the fluctuation characteristics of the meteorological data are sorted out from a time perspective to obtain the time information when all meteorological parameters meet the characteristics, which is recorded as the historical meteorological calming time.

[0123] By analyzing the changing trends associated with disasters, the historical meteorological recovery time is analyzed to generate a time period series;

[0124] Organize and classify historical power grid disaster data to obtain key power historical data and steady-state power historical data;

[0125] Analyze key power historical data based on time period series to obtain key power restoration time;

[0126] Based on the time period series, the historical meteorological calming time and key power restoration time of the same terrain are analyzed to generate the key power restoration delay coefficient;

[0127] Based on the time period series, the critical power restoration time of the same area is compared with the steady-state power restoration time in the steady-state power historical data to generate the restoration transition time;

[0128] Analyze the restoration transition time and the steady-state power restoration time in the steady-state power history data to generate a steady-state power restoration delay coefficient;

[0129] The key power restoration delay coefficient and the steady-state power restoration delay coefficient are ratio-processed to generate a geological disaster recovery index.

[0130] It can be understood that critical power refers to the part of power in the power system that is used to maintain the operation of critical infrastructure and ensure power supply to important users, such as power supply to important places such as hospitals. Steady-state power means that the power system can form a stable power supply, that is, the power system is fully restored to normal. Referring to the trend of changes associated with disasters, the historical meteorological recovery time is analyzed, and the time taken for a precipitation fluctuation of 10 mm is used as a periodic sequence. The time is calibrated through the time period series, and the ratio of the critical power recovery time to the historical meteorological recovery time of the same terrain is weighted and averaged with the number of time period series to generate the critical power recovery delay coefficient. The time difference between the critical power recovery time in the same area and the steady-state power recovery time in the steady-state power historical data is calculated to generate the recovery transition time. The ratio of the recovery transition time to the steady-state power recovery time in the steady-state power historical data is used as the steady-state power recovery delay coefficient.

[0131] Specifically, the calculation steps of the key power restoration delay coefficient K1 are:

[0132] The calculation is based on the time period sequence. Let the time period sequence data be n, the index value be i, and the historical meteorological calm time for the same terrain be T m , the critical power recovery time is T k , then the calculation formula of the key power restoration delay coefficient is:

[0133]

[0134] In actual calculations, first determine the time period sequence. For example, take the time it takes for precipitation to fluctuate by 10 mm as one period. Count the ratios of key power restoration time to historical meteorological calm time over multiple periods, and then take the average to obtain the key power restoration delay coefficient.

[0135] The calculation steps of the steady-state power recovery delay coefficient are:

[0136] Based on the time period sequence, the critical power restoration time T k and the steady-state power recovery time T in the steady-state power history data s Compare and calculate:

[0137]

[0138] The steady-state power restoration delay coefficient reflects the difference between the critical power restoration time and the steady-state power restoration time, and is measured by the ratio of the time difference between the two to the steady-state power restoration time.

[0139] The calculation steps of geological disaster recovery index are as follows:

[0140] The ratio of the key power recovery delay coefficient K1 and the steady-state power recovery delay coefficient K2 is obtained:

[0141]

[0142] Through this formula, the key power restoration delay coefficient and the steady-state power restoration delay coefficient are combined to comprehensively reflect the relationship between the recovery of meteorological conditions and the recovery of the power system after a geological disaster, thereby deriving the geological disaster recovery index.

[0143] Example 5

[0144] This embodiment provides the steps for generating the disaster response capability value in the embodiment 1, referring to Figure 5 As shown, specifically including:

[0145] Through the Geological Disaster Monitoring Bureau, obtain the historical disaster frequency and historical damage value of ground buildings in various terrains;

[0146] Analyze the historical frequency of disasters and the historical damage values of ground buildings in each terrain to generate a terrain risk index;

[0147] Organize historical power grid disaster data according to the terrain risk index to generate power grid disaster records under terrain risk;

[0148] Obtaining a historical record of power grid emergency repairs in the same terrain, wherein the historical record includes the number of historical repair personnel, the number of historical repair equipment, and the historical repair time;

[0149] Based on the time period sequence, the historical emergency repair time is divided. Combined with the power grid disaster records under terrain risks, the historical number of emergency repair personnel and historical number of emergency repair equipment corresponding to different emergency repair time periods in each disaster record are generated.

[0150] Based on the emergency repair time period, the historical number of emergency repair personnel and the historical number of emergency repair equipment corresponding to different emergency repair time periods in each disaster record are analyzed to generate the comprehensive value of emergency repair resources in each time period;

[0151] The comprehensive value of emergency repair resources in each time period is averaged and combined with the geological disaster recovery index to generate the disaster response capability value.

[0152] It is understandable that the frequency of geological disasters in different terrains and the losses to power grids caused by geological disasters vary significantly. In mountainous areas, the terrain is undulating and the rock and soil are unstable. Heavy rainfall, earthquakes and other factors can easily trigger geological disasters such as landslides and mud-rock flows, which occur more frequently. Once a disaster occurs, due to the complex mountain terrain, most power grid lines are built on the mountain, which makes maintenance difficult. In addition, the lines are damaged over a wide area, resulting in a large power outage area and a long time to restore power supply. In plain areas, the terrain is flat and the geological structure is relatively stable, so the frequency of geological disasters is relatively low. However, plain areas are densely populated, economically developed, with a large power grid load and a wide and dense distribution of lines. Once they suffer from disasters such as ground subsidence and flooding, they will affect many transmission lines. Large-scale power outages will have a great impact on industrial production, Commercial activities and residents' lives are seriously affected, and the economic losses are huge. As for hilly areas, the terrain is relatively small, and the frequency of geological disasters is lower than that in mountains, but higher than that in plains. The power grid layout is relatively scattered. When affected by geological disasters, the degree of loss is between that in mountains and plains. Most of the time, local lines are damaged, and the impact range is limited. By multiplying the historical frequency of disasters in each terrain and the historical damage value of ground buildings, the terrain risk index can be obtained. By multiplying the historical number of emergency repair personnel and the historical number of emergency repair equipment corresponding to different emergency repair time periods in each disaster record, the comprehensive value of emergency repair resources in each time period can be obtained. According to the geological disaster recovery index of each time period, the average value of the comprehensive amount of emergency repair resources is weighted and accumulated to generate the disaster response capability value.

[0153] Example 6

[0154] This embodiment provides the steps for generating geological disaster risk assessment values in the embodiment 1, referring to Figure 6 As shown, specifically including:

[0155] Arrange historical geological disaster data in descending order of geological disaster rating to obtain a disaster rating sequence, and combine it with regional impact to generate a disaster regional impact mapping sequence;

[0156] According to the disaster rating sequence, the disaster response capability values corresponding to various geological hazards are analyzed to generate a disaster rating response capability mapping sequence;

[0157] The disaster regional impact mapping sequence and the disaster rating response capability mapping sequence are sorted and analyzed in turn to generate the maximum regional impact, minimum regional impact, maximum disaster response capability, minimum disaster response capability, and the geological disaster rating corresponding to each maximum value;

[0158] According to the geological disaster rating corresponding to each extreme value, the maximum and minimum regional impact values, as well as the maximum and minimum disaster response capabilities, are analyzed respectively, and the impact change coefficient and response capability change coefficient are generated in turn;

[0159] Obtain the terrain type where the power transmission line to be evaluated is located;

[0160] Based on the meteorological data associated with geological disasters, the real-time meteorological data are analyzed to generate an estimated geological disaster rating; the meteorological parameter values in the real-time meteorological data are compared with the meteorological parameter values in the meteorological data associated with geological disasters to generate the difference values of the real-time meteorological parameters; the difference values of the real-time meteorological parameters are averaged to generate the mean meteorological deviation; the meteorological data associated with geological disasters are compared with the disaster meteorological characteristic data corresponding to the standard disaster evolution trend to determine the standard geological disaster rating; the standard geological disaster rating is multiplied by the mean meteorological deviation to generate the estimated geological disaster rating;

[0161] Taking the influence variation coefficient and response capacity variation coefficient as weight values, the influence and disaster response capacity values of the areas with the same terrain type as the power transmission line to be assessed under the expected geological disaster rating are weighted and averaged to generate the geological disaster risk assessment value.

[0162] It is understandable that the type of terrain determines the basic geological conditions, which in turn have a key impact on the occurrence of geological disasters. For example, mountains are prone to landslides and collapses, and their rock and soil are often broken after weathering, while plains are prone to ground subsidence. At the same time, the terrain also controls the hydrological characteristics, affecting the convergence, runoff and groundwater level of surface water. For example, valleys are prone to form catchment areas, increasing the risk of mudslides. Different terrains also make the intensity and methods of human engineering activities different, which indirectly changes the stability of the geological environment. Combining these factors closely related to the terrain can more comprehensively reflect the possibility and degree of harm of geological disasters, thereby generating geological disaster risks. Risk assessment value, disaster regional impact mapping sequence represents the order of disaster rating sequence, wherein each rating corresponds to the regional impact, disaster rating response capability mapping sequence represents the order of disaster rating sequence, wherein each rating corresponds to the disaster response capability value, the difference between the maximum regional impact and the minimum regional impact is divided by the difference between the geological hazard ratings corresponding to the maximum regional impact and the minimum regional impact, to generate the impact variation coefficient, the difference between the maximum disaster response capability and the minimum disaster response capability is divided by the difference between the geological hazard ratings corresponding to the maximum disaster response capability and the minimum disaster response capability, to generate the response capability variation coefficient.

[0163] Example 7

[0164] This embodiment proposes a power grid geological disaster risk assessment system based on dynamic data, which is applicable to the risk assessment method proposed above, including:

[0165] A data collection module is used to collect historical geological disaster data, historical meteorological data, transmission line tower material information, tower topography information, and historical power grid disaster data, and transmit the data to the data integration module and the data management module;

[0166] A data integration module is used to integrate and analyze the received data, obtain geological disaster associated meteorological data by analyzing historical meteorological data, generate a geological disaster rating, analyze historical meteorological data based on the geological disaster associated meteorological data, obtain a geological disaster recovery index, generate a disaster response capability value, and transmit the data to the data management module, the risk assessment module, and the data display module;

[0167] A data management module, which is used to summarize and store the received data, divide the transmission lines according to the tower material information and the tower terrain information, generate areas of towers of the same material and areas of towers of the same terrain, perform retrieval and analysis in the power grid disaster impact table based on the areas of towers of the same material and areas of towers of the same terrain, generate regional impact, and transmit the data to the data integration module, the risk assessment module, and the data display module;

[0168] A risk assessment module is used to analyze the received data, generate a geological disaster risk assessment value based on real-time meteorological data, combined with the regional impact and disaster response capability value, and transmit the data to the data display module;

[0169] The data display module is used to organize the received data and output the organized results for display.

[0170] The data collection module specifically includes:

[0171] The first collection unit is used to collect historical natural environment data of the power grid area and the correlation between meteorological disaster triggering from the geological disaster monitoring agency, obtain historical data of the power grid transmission line system and historical records of power grid emergency repairs, and transmit the data to the data integration module.

[0172] The second collection unit is used to obtain historical geological disaster data, historical meteorological data, historical disaster frequencies of various terrains and historical damage values of ground buildings through the Geological Disaster Monitoring Bureau, and transmit the data to the data integration module.

[0173] The data integration module specifically includes:

[0174] The first integrated unit is used to analyze the geological data and meteorological data in disasters according to the correlation between meteorological disaster triggering, obtain the meteorological data associated with geological disasters, generate the disaster associated change trend, analyze the disaster geological characteristic data and the disaster meteorological characteristic data according to the disaster associated change trend, obtain the standard disaster evolution trend, generate the geological disaster rating, analyze the historical disaster data of the transmission line according to different tower material areas and different terrain areas, generate the regional type disaster coefficient, combine the geological disaster rating, generate the power grid disaster impact table, and transmit the data to the data management module and the risk assessment module.

[0175] The second integrated unit is used to analyze the historical disaster data of the transmission line, obtain the historical disaster recovery time, analyze the disaster coefficient of each tower area according to the transmission line characteristics of each tower area, obtain the power grid damage index of each area, combine the number of users covered by each tower area and the damage index of each area, generate the regional user damage value, analyze the user damage value of the area with the same terrain type according to the tower adaptation coefficient, generate the regional impact, and transmit the data to the data management module and the risk assessment module.

[0176] The third integrated unit is used to analyze the historical meteorological recovery time through the disaster-associated change trend, generate a time period sequence, analyze the time information based on the time period sequence, generate the key power recovery delay coefficient and the steady-state power recovery delay coefficient, generate the geological disaster recovery index by calculating the ratio of the key power recovery delay coefficient and the steady-state power recovery delay coefficient, and transmit the data to the data management module and the risk assessment module.

[0177] The fourth integration unit is used to analyze the historical frequency of disasters and the historical damage values of ground buildings in various terrains, generate a terrain risk index, analyze the historical number of emergency repair personnel and the historical number of emergency repair equipment corresponding to different emergency repair time periods in each disaster record, generate a comprehensive value of emergency repair resources for each time period, average the comprehensive value of emergency repair resources for each time period, combine it with the geological disaster recovery index, generate a disaster response capability value, and transmit the data to the data management module and the risk assessment module.

[0178] The data management module specifically includes:

[0179] The first management unit is used to refer to the time information of the geological disaster, retrieve the historical natural environment data of the power grid area, obtain the environmental data before the geological disaster, match them according to the time dimension and space dimension, generate pre-disaster geological data, pre-disaster meteorological data, geological data during the disaster and meteorological data during the disaster, and transmit the data to the data integration module and the data display module.

[0180] The second management unit is used to organize and classify historical power grid disaster data, obtain key power historical data and steady-state power historical data, analyze key power historical data based on time period series, obtain key power restoration time, and transmit data to the data integration module and data display module.

[0181] The third management unit is used to organize historical power grid disaster data according to the terrain risk index, generate power grid disaster records under terrain risks, divide historical emergency repair times according to time period sequences, and combine power grid disaster records under terrain risks to generate the historical number of emergency repair personnel and historical number of emergency repair equipment corresponding to different emergency repair time periods in each disaster record, and transmit the data to the data integration module, risk assessment module and data display module.

[0182] To sum up, the advantages of the method and system provided by the present invention are: it can effectively reduce the requirements for geological monitoring equipment in areas with complex terrain, improve adaptability to actual conditions, and can quickly respond and adjust in the face of sudden disaster events, strengthen the analysis of risk response capabilities, reduce the lag and one-sidedness of risk assessment results, and improve the reference value of risk assessment results for power grid disaster prevention and mitigation.

[0183] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or some technical features can be replaced by equivalents without departing from the spirit of the technical solution of the present invention. They should all be included in the scope of the technical solution for protection of the present invention.

Claims

1. A method for assessing geological disaster risks in power grids based on dynamic data, characterized in that: The steps include: S1. Obtain historical geological disaster data and historical meteorological data; S2. Analyze historical meteorological data based on historical geological disaster data, obtain meteorological data associated with geological disasters, and generate geological disaster ratings; S3 collects transmission line tower material information and tower terrain information, respectively, according to the tower material information and tower terrain information to divide the transmission line, generate the same material tower area and the same terrain tower area; S4. Based on the geological disaster rating, organize historical geological disaster data and generate a grid disaster impact table; S5. Using the same material tower area and the same terrain tower area as the benchmark, perform a search and analysis in the power grid disaster impact table to generate the tower area impact degree; S6. Analyze historical meteorological data based on meteorological data associated with geological disasters to obtain a geological disaster recovery index; S7. Obtain historical power grid disaster data and combine it with the geological disaster recovery index to generate a disaster response capability value; S8. Obtain real-time meteorological data and generate a geological disaster risk assessment value based on regional impact and disaster response capability values.

2. The method for assessing power grid geological disaster risk based on dynamic data according to claim 1, characterized in that: The step S4 generates a table of power grids affected by disasters, specifically comprising the following steps: Organize historical geological disaster data and obtain information on the time when geological disasters occurred; Collect historical natural environment data of the power grid area and the correlation between meteorological disaster triggering from geological disaster monitoring agencies; Refer to the time information of geological disasters, search the historical natural environment data of the power grid area, and obtain the environmental data before the geological disaster; Organize historical geological disaster data and historical meteorological data, match them according to time and space dimensions, and generate historical disaster environment data; The environmental data before geological disasters and historical disaster environmental data are sorted and classified respectively to generate geological data before disasters, meteorological data before disasters, geological data during disasters and meteorological data during disasters; According to the correlation between meteorological disasters, geological data and meteorological data in disasters are analyzed to obtain meteorological data associated with geological disasters and generate disaster-associated change trends; Cluster analysis is performed on the geological data before and during the disaster, and the meteorological data before and during the disaster to generate disaster geological characteristic data and disaster meteorological characteristic data; According to the associated change trend of disasters, the geological characteristic data and meteorological characteristic data of disasters are analyzed to obtain the evolution trend of standard disasters and generate geological disaster ratings; Obtain historical disaster data of transmission lines, organize and analyze the data based on different tower material areas and different terrain areas, and generate regional disaster coefficients; Combining the regional disaster coefficient and geological disaster rating, a power grid disaster impact table is generated.

3. The method for assessing power grid geological disaster risk based on dynamic data according to claim 1, characterized in that: The step S5 of generating the tower area influence degree specifically includes the following steps: Search the power grid disaster impact table based on the tower areas with the same material and the tower areas with the same terrain to obtain the disaster coefficient of each tower area; Analyze historical disaster data of transmission lines to obtain historical disaster recovery time; Collect grid planning information to obtain the transmission line characteristics, number of covered users, and tower adaptation coefficients of each tower area; According to the transmission line characteristics of each tower area, the disaster coefficient of each tower area is analyzed to obtain the power grid damage index of each area; Combine the number of users covered by each tower area and the damage index of each area to generate the regional user damage value; According to the tower adaptation coefficient, the damage value of users in the area with the same terrain type is analyzed to generate the tower area impact.

4. The method for assessing power grid geological disaster risk based on dynamic data according to claim 1, characterized in that: The step S6 of obtaining the geological disaster recovery index specifically includes the following steps: Obtain historical meteorological recovery time based on geological disaster-associated meteorological data and disaster-associated change trends; By analyzing the changing trends associated with disasters, the historical meteorological recovery time is analyzed to generate a time period series; Organize and classify historical power grid disaster data to obtain key power historical data and steady-state power historical data; Analyze key power historical data based on time period series to obtain key power restoration time; Based on the time period series, the historical meteorological calming time and key power restoration time of the same terrain are analyzed to generate the key power restoration delay coefficient; Based on the time period series, the critical power restoration time of the same area is compared with the steady-state power restoration time in the steady-state power historical data to generate the restoration transition time; Analyze the restoration transition time and the steady-state power restoration time in the steady-state power history data to generate a steady-state power restoration delay coefficient; The key power restoration delay coefficient and the steady-state power restoration delay coefficient are ratio-processed to generate a geological disaster recovery index.

5. The method for assessing power grid geological disaster risk based on dynamic data according to claim 1, characterized in that: Generating the disaster response capability value in step S7 specifically includes the following steps: Through the Geological Disaster Monitoring Bureau, obtain the historical disaster frequency and historical damage value of ground buildings in various terrains; Analyze the historical frequency of disasters and the historical damage values of ground buildings in each terrain to generate a terrain risk index; Organize historical power grid disaster data according to the terrain risk index to generate power grid disaster records under terrain risk; Obtaining a historical record of power grid emergency repairs in the same terrain, wherein the historical record includes the number of historical repair personnel, the number of historical repair equipment, and the historical repair time; Based on the time period sequence, the historical emergency repair time is divided. Combined with the power grid disaster records under terrain risks, the historical number of emergency repair personnel and historical number of emergency repair equipment corresponding to different emergency repair time periods in each disaster record are generated. Based on the emergency repair time period, the historical number of emergency repair personnel and the historical number of emergency repair equipment corresponding to different emergency repair time periods in each disaster record are analyzed to generate the comprehensive value of emergency repair resources in each time period; The comprehensive value of emergency repair resources in each time period is averaged and combined with the geological disaster recovery index to generate the disaster response capability value.

6. The method for assessing power grid geological disaster risk based on dynamic data according to claim 1, characterized in that: The step S8 generates a geological disaster risk assessment value, specifically including: Arrange historical geological disaster data in descending order of geological disaster rating to obtain a disaster rating sequence, and combine it with regional impact to generate a disaster regional impact mapping sequence; According to the disaster rating sequence, the disaster response capability values corresponding to various geological hazards are analyzed to generate a disaster rating response capability mapping sequence; The disaster regional impact mapping sequence and the disaster rating response capability mapping sequence are sorted and analyzed in turn to generate the maximum regional impact, minimum regional impact, maximum disaster response capability, minimum disaster response capability, and the geological disaster rating corresponding to each maximum value; According to the geological disaster rating corresponding to each extreme value, the maximum and minimum regional impact values, as well as the maximum and minimum disaster response capabilities, are analyzed respectively, and the impact change coefficient and response capability change coefficient are generated in turn; Obtain the terrain type where the power transmission line to be evaluated is located; Analyze real-time meteorological data based on meteorological data associated with geological hazards to generate estimated geological hazard ratings; Taking the influence variation coefficient and response capacity variation coefficient as weight values, the influence and disaster response capacity values of the areas with the same terrain type as the power transmission line to be assessed under the expected geological disaster rating are weighted and averaged to generate the geological disaster risk assessment value.

7. A power grid geological disaster risk assessment system based on dynamic data, used to implement the risk assessment method described in any of claims 1 to 6 above, characterized in that: include: A data collection module is used to collect historical geological disaster data, historical meteorological data, transmission line tower material information, tower topography information, and historical power grid disaster data, and transmit the data to the data integration module and the data management module; A data integration module is used to integrate and analyze the received data, obtain geological disaster associated meteorological data by analyzing historical meteorological data, generate a geological disaster rating, analyze historical meteorological data based on the geological disaster associated meteorological data, obtain a geological disaster recovery index, generate a disaster response capability value, and transmit the data to the data management module, the risk assessment module, and the data display module; A data management module, which is used to summarize and store the received data, divide the transmission lines according to the tower material information and the tower terrain information, generate areas of towers of the same material and areas of towers of the same terrain, perform retrieval and analysis in the power grid disaster impact table based on the areas of towers of the same material and areas of towers of the same terrain, generate regional impact, and transmit the data to the data integration module, the risk assessment module, and the data display module; A risk assessment module is used to analyze the received data, generate a geological disaster risk assessment value based on real-time meteorological data, combined with the regional impact and disaster response capability value, and transmit the data to the data display module; The data display module is used to organize the received data and output the organized results for display.

8. The power grid geological disaster risk assessment system based on dynamic data according to claim 7, characterized in that: The data collection module specifically includes: A first collection unit, which is used to collect historical natural environment data of the power grid area and the correlation between meteorological disaster triggering from the geological disaster monitoring agency, obtain historical data of the power grid transmission line system and historical data of power grid emergency repairs, and transmit the data to the data integration module; The second collection unit is used to obtain historical geological disaster data, historical meteorological data, historical disaster frequencies of various terrains and historical damage values of ground buildings through the Geological Disaster Monitoring Bureau, and transmit the data to the data integration module.

9. The power grid geological disaster risk assessment system based on dynamic data according to claim 7, characterized in that: The data integration module specifically includes: A first integration unit is configured to analyze geological data and meteorological data in disasters according to the correlation between meteorological disaster triggering, obtain meteorological data associated with geological disasters, generate disaster associated change trends, analyze disaster geological characteristic data and disaster meteorological characteristic data according to the disaster associated change trends, obtain standard disaster evolution trends, generate geological disaster ratings, analyze historical disaster data of transmission lines according to different tower material areas and different terrain areas, generate regional type disaster coefficients, combine the geological disaster ratings, generate a power grid disaster impact table, and transmit the data to the data management module and the risk assessment module; The second integration unit is used to analyze the historical disaster data of the transmission line, obtain the historical disaster recovery time, analyze the disaster coefficient of each tower area according to the transmission line characteristics of each tower area, obtain the power grid damage index of each area, combine the number of users covered by each tower area and the damage index of each area, generate the regional user damage value, analyze the user damage value of the area with the same terrain type according to the tower adaptation coefficient, generate the regional impact, and transmit the data to the data management module and the risk assessment module; A third integration unit is used to analyze the historical meteorological recovery time based on the disaster-associated change trend, generate a time period sequence, analyze the time information based on the time period sequence, generate a key power restoration delay coefficient and a steady-state power restoration delay coefficient, generate a geological disaster recovery index by calculating the ratio of the key power restoration delay coefficient and the steady-state power restoration delay coefficient, and transmit the data to the data management module and the risk assessment module; The fourth integration unit is used to analyze the historical frequency of disasters and the historical damage values of ground buildings in various terrains, generate a terrain risk index, analyze the historical number of emergency repair personnel and the historical number of emergency repair equipment corresponding to different emergency repair time periods in each disaster record, generate a comprehensive value of emergency repair resources for each time period, average the comprehensive value of emergency repair resources for each time period, combine it with the geological disaster recovery index, generate a disaster response capability value, and transmit the data to the data management module and the risk assessment module.

10. The power grid geological disaster risk assessment system based on dynamic data according to claim 7, characterized in that: The data management module specifically includes: a first management unit, configured to retrieve historical natural environmental data of the power grid area with reference to time information of geological disaster occurrence, obtain environmental data before the geological disaster, match them according to time and space dimensions, generate geological data before the disaster, meteorological data before the disaster, geological data during the disaster, and meteorological data during the disaster, and transmit the data to a data integration module and a data display module; A second management unit, which is used to organize and classify historical power grid disaster data, obtain key power historical data and steady-state power historical data, analyze the key power historical data based on a time period sequence, obtain key power restoration time, and transmit the data to the data integration module and the data display module; The third management unit is used to organize historical power grid disaster data according to the terrain risk index, generate power grid disaster records under terrain risks, divide historical emergency repair times according to time period sequences, and combine power grid disaster records under terrain risks to generate the historical number of emergency repair personnel and the historical number of emergency repair equipment corresponding to different emergency repair time periods in each disaster record, and transmit the data to the data integration module, risk assessment module and data display module.

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