CN116680904A - Multisource dynamic monitoring and early warning method for power grid facilities - Google Patents
Multisource dynamic monitoring and early warning method for power grid facilities Download PDFInfo
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Abstract
The invention discloses a multisource dynamic monitoring and early warning method for power grid facilities, which comprises the steps of establishing a dynamic stress characteristic parameter library of historical power grid facilities based on time sequencing; establishing a dynamic deformation characteristic parameter library of a historical power grid facility based on time sequencing; based on the time sequence, connecting the stress characteristic parameter and the deformation characteristic parameter under the time sequence of the contract in parallel to construct a dynamic stress deformation model; the method comprises the steps of obtaining stress characteristic parameters of a target power grid facility at the current moment, and judging deformation characteristic parameters of target power transmission equipment corresponding to the stress characteristic parameters at the current moment according to a dynamic stress deformation model so as to provide judgment basis for corresponding reinforcement measures under the condition of micro damage of the power grid facility. According to the invention, by selecting the basic data change characteristic related to the mechanics of the research disaster geology body and the power grid facility site, various geological disasters are comprehensively covered in early warning, and finally, the intelligent early warning model is obtained more accurately and timely.
Description
Technical Field
The invention relates to the technical field of electrical engineering, in particular to a multisource dynamic monitoring and early warning method for power grid facilities.
Background
Over the years, power transport has evolved to form ultra-long power transport networks across a wide range. The electric power transportation inevitably needs to pass through a plurality of areas with complex geological topography, such as Chong mountain, mountain canyon and the like, with severe environmental conditions and changeable climate along the way. The transmission tower is used as a connection node between the high-voltage transmission line and the ground, and is often required to be built at a mountain steep slope in a suburban area so as to reduce the transmission distance and reduce the electric loss and avoid the interaction with human activities. Such terrain conditions increase the likelihood of geological disasters occurring. Meanwhile, the deformation and damage of the tower foundation are easily caused by the influence of various construction and mining activities around the line, and the safe operation of the line is seriously threatened.
In the prior art, as disclosed in patent document with publication number CN115983093A, a method and a device for predicting geological disasters of a power transmission line tower foundation are provided, belong to the technical field of electric power, and solve the problem of insufficient early warning of the occurrence of the geological disasters in the existing method. The method comprises the following steps: identifying influencing factors of geological disasters of the tower foundation of the power transmission line to determine main reasons for generating the geological disasters; collecting and sorting historical data of geological disasters, and identifying and counting meteorological conditions and geological conditions under different geological disasters; analyzing different rainfall in each region, and constructing rainfall thresholds of different types of geological disasters by combining the rainfall when the historical geological disasters occur; constructing a geological disaster risk prediction model, and generating a geological disaster risk prediction result of the complex weather element; and counting historical disasters and early rainfall, establishing short-term meteorological early warning criteria of the geological disasters of the power transmission line tower foundation by combining regional geological disaster susceptibility zoning results, and carrying out short-term meteorological early warning of the geological disasters of the power transmission line. Although the geological disaster prediction method judges main reasons of geological disasters from influence factors, the situation that the influence factor identification of the geological disasters is omitted or inaccurate exists, so that the reasons cannot be comprehensively and accurately determined, and meanwhile, the short-term weather early warning criteria may have the situation that early warning standards are not strict or accurate enough, so that early warning results have errors.
In the prior art, as disclosed in patent document with publication number of CN106651165A, a rainfall risk classification method and device for geological disaster area assessment and early warning are proposed, and are used for geological disaster area assessment and early warning. Wherein the method comprises the following steps: dividing the whole country into a plurality of points, and calculating the accumulated rainfall of each point in the preset time; determining a first rainfall level and a first rainfall grading weight of each point falling into each province according to the accumulated rainfall of each point in the preset time; dividing the country into a plurality of geological environment areas; and determining a second rainfall level and a second rainfall grading weight of each point falling into each geological environment area according to the accumulated rainfall of each point in the preset time. And coupling the first rainfall grading weight and the second rainfall grading weight corresponding to each point, and generating a rainfall grading graph. According to the method, the rainfall is calculated by dividing the whole country into a plurality of points, the problems of insufficient point density, uneven point distribution and the like possibly exist, so that the prediction result is not universal, meanwhile, the situation that the rainfall classification standard is not matched with the geological environment area division exists in the method for determining the rainfall level and the weight according to the accumulated rainfall of each point in the preset time, and the situation that the prediction result is error exists is caused, more importantly, the influence of the method on the cause of geological disasters only considers the factor of rainfall, and the influence of other conditions such as earthquake, landslide, collapse and the like is not considered, so that the early warning measures for the geological disasters are lacked.
In the prior art, only one influence factor of a plurality of geological disasters is considered, for example, only the geological disasters caused by storm or storm are considered, and the method has the defects of insufficient comprehensive consideration factors of data analysis, insufficient applicability, low causal algorithm efficiency, excessively dependent weather monitoring data and the like in the early warning of power transmission line damage. Therefore, a monitoring and early warning method with comprehensive consideration factors, strong adaptability and high calculation efficiency is urgently needed to be researched.
Disclosure of Invention
The invention aims to solve the technical problems that: aiming at the defects of the prior art, the invention provides a multi-source dynamic monitoring and early warning method, in particular to a three-dimensional collaborative multi-source dynamic monitoring and early warning method aiming at power grid facilities, which aims at solving the defects of insufficient comprehensive consideration factors, insufficient applicability, low causal algorithm efficiency, excessively dependent meteorological monitoring data and the like in the prior art of data analysis in the early warning of power transmission line damage.
A multisource dynamic monitoring and early warning method for power grid facilities comprises the steps of establishing a dynamic stress characteristic parameter library of historical power grid facilities based on time sequencing; establishing a dynamic deformation characteristic parameter library of a historical power grid facility based on time sequencing; based on the time sequence, connecting the stress characteristic parameter and the deformation characteristic parameter under the time sequence of the contract in parallel to construct a dynamic stress deformation model; the method comprises the steps of obtaining stress characteristic parameters of a target power grid facility at the current moment, and judging deformation characteristic parameters of target power transmission equipment corresponding to the stress characteristic parameters at the current moment according to a dynamic stress deformation model so as to provide judgment basis for corresponding reinforcement measures under the condition of micro damage of the power grid facility.
The dynamic stress characteristic parameter library and the dynamic deformation characteristic parameter library based on time sequencing at least comprise monitoring data of power grid facilities before and after occurrence of earthquake, storm and flood natural disaster occurrence nodes for a period of time. Because of uncertainty and randomness in the occurrence of geological disasters, data collection at a single monitoring site may be affected by a variety of factors, such as terrain, weather, geological conditions, etc., resulting in inaccuracy and errors in the data. And through selecting the power grid facilities at different points and the corresponding geological bodies for data acquisition, geological conditions and environmental factors at different points can be fully considered, so that the accuracy and reliability of data are improved.
The detection data of the dynamic stress characteristic parameter library and the dynamic deformation characteristic parameter library are obtained based on a monitoring system which comprises one or more of an unmanned plane, a laser radar, a Beidou satellite system and a total station and ground deformation and stress monitoring comprehensive means. The monitoring system based on various monitoring means can improve the accuracy, the monitoring efficiency, the monitoring range and the monitoring precision of data, and simultaneously can reduce the monitoring cost and the waste of human resources, thereby providing more scientific and accurate data support for the safe operation of power grid facilities.
The stress characteristic parameters at least comprise the magnitude, direction, action point and action time of the stress of the power grid facility; the deformation characteristic parameters at least comprise deformation quantity, deformation direction, deformation rate and deformation type of the power grid facility.
The historical grid facilities comprise a plurality of grid facilities located in different regions and different terrains.
The dynamic stress deformation model is built by a finite element analysis model method, an application statistical analysis method, a determination function method and a mixed model method. One or more analysis methods are selected, so that the accuracy, applicability, reliability, flexibility and optimization of the establishment process of the model can be improved, and more comprehensive and accurate data support is provided for safe operation of power grid facilities and ground disaster early warning.
Based on an indoor model test and a displacement loading numerical simulation technology, acquiring an internal force change rule of a historical power grid facility and a disaster-affected geological foundation under the condition of different directional deformation, and acquiring deformation damage characteristics of mechanics and dynamics. The displacement loading numerical simulation technology of the indoor model test is adopted, the constraint of time and space of a site real-time survey mode is eliminated, the internal force change rule can be more conveniently researched, and positive effects are achieved on improving early warning capability and maintenance efficiency.
Based on deformation damage characteristics under the action of different stress mechanisms, an optical fiber grating sensing technology is adopted, the actual working performance of the structure is determined from the strength, the rigidity and the actual damage form of the structure, and corresponding reinforcement measures are provided for different micro-damage conditions. The mode enables the structural safety and reliability of the power grid facilities to be improved, improves the maintenance efficiency, reduces the maintenance cost and provides scientific basis for the design and improvement of the structure.
And carrying out sensitivity analysis on the established mathematical model to determine a sensitivity factor of deformation of the power grid facility, constructing a power grid facility damage evaluation mathematical model according to the selected sensitivity factor, and obtaining the corrected intelligent early warning model by utilizing the limited cycle of PDCA. The process is continuously optimized and improved through cyclic iteration, so that the efficiency and the precision are improved, and the waste of time and resources is reduced.
And based on the result presented by the intelligent early warning model, evaluating the operation safety level of the target power grid equipment corresponding to the result to be used for selecting operation maintenance measures. And combining the early warning result with the implementation-selecting measures to form a complete logic self-consistent intelligent early warning technology.
The invention has the technical effects that:
(1) According to the invention, by selecting power grid facilities and corresponding geological bodies at different places and collecting data, accidental errors caused by single monitoring place are avoided, and the accuracy of data processing results and final early warning models is improved.
(2) Aiming at the problems of large crossing of mountain power transmission line engineering and large movable space range, the invention improves the traditional monitoring means on the aspects of complicated mountain terrain environment and 'inexhaustible, inaccurate measurement and difficult early warning' in the ground monitoring of mountain areas. According to the invention, the real-time monitoring system of the transmission tower and the geological disasters is constructed by integrating comprehensive means such as unmanned aerial vehicle, laser radar, beidou satellite system, total station, ground deformation and stress monitoring, so that the real-time monitoring and early warning of the transmission tower and the surrounding geological disasters can be realized, and the labor cost is obviously reduced. The unmanned aerial vehicle can realize high-altitude shooting and inspection of the transmission tower, the laser radar can realize high-precision measurement of the terrain, the Beidou satellite system can realize positioning and navigation of the unmanned aerial vehicle and the total station, the total station can realize accurate measurement of the transmission tower, and ground deformation and stress monitoring can realize real-time monitoring and early warning of geological disasters. By comprehensively utilizing the monitoring means, the invention can realize omnibearing monitoring and early warning of the mountain power transmission line engineering and provides powerful technical support for safe operation of the power transmission line. .
(3) According to the invention, the change characteristics of the basic data related to the mechanics of the disaster-affected geological body and the power grid facility site are selected and researched, so that the early warning is not limited to the influence caused by a certain geological disaster, various geological disasters are comprehensively included through multisource monitoring data and dynamic changes thereof, the corresponding relation of the deformation damage characteristics of the mechanics and dynamics of the disaster-affected geological body and the power grid facility site is established, and finally, an intelligent early warning model is obtained, so that the early warning is more accurate and timely.
(4) According to the invention, effective data are extracted through sensitivity analysis, invalid and redundant data are removed, so that the data processing efficiency can be improved, and the accuracy of early warning work can be improved. The sensitivity analysis is a commonly used data analysis method, and by performing sensitivity test on data, the influence degree of the data on the output result of the model is evaluated, the dependence degree of the model on the data is determined, the model parameters are optimized, and the like. In the early warning work, invalid and redundant data are removed through sensitivity analysis, and effective data with larger influence on the early warning result are extracted, so that the accuracy and reliability of the early warning work are improved. Meanwhile, the sensitivity analysis can optimize parameters of the early warning model, improve the prediction capability and accuracy of the early warning model, and provide more scientific and effective support for early warning work. Therefore, the sensitivity analysis method has important application value and practical significance, and can provide more accurate and reliable data support for early warning work.
Drawings
FIG. 1 is a flow chart of the monitoring and early warning of geological disasters.
Detailed Description
The following detailed description refers to the accompanying drawings.
Example 1
The invention relates to a multisource dynamic monitoring and early warning method for power grid facilities, which is shown in fig. 1 and comprises the following steps:
s1, acquiring multi-source monitoring data.
Specifically, the acquisition of the multi-source monitoring data may be performed by means of the monitoring module 100, where the monitoring module 100 includes a monitoring subunit and a monitoring integration unit, and the number of the monitoring subunits may be determined according to actual needs, and the embodiment does not limit the number of the monitoring subunits. The monitoring subunit can be placed at a plurality of different places selected in advance, the selection of the places is followed to cover various geological disasters, and the variety of the domestic geological disasters with different occurrence probabilities according to historic records at least comprises earthquakes, storm winds, debris flows, ground subsidence and the like, and detected objects comprise but are not limited to various devices on transmission lines such as transmission towers, distribution transformers, distribution lines and distribution cabinets. The monitoring sub-units are used for continuously and dynamically collecting and sorting the multisource monitoring data covering deformation damage characteristics of disaster-affected geological bodies and power grid facility sites at different places, wherein the monitoring sub-units are used for acquiring monitoring data, and the multisource monitoring data comprises one or more of an unmanned plane, a laser radar, a Beidou satellite system and a total station and a monitoring system which integrates ground deformation and stress monitoring comprehensive means. The deformation damage characteristic refers to dynamic stress characteristics and corresponding dynamic deformation characteristics of the power grid facility, wherein the dynamic stress characteristic parameters at least comprise the size, direction, action point and action time of the stress of the power grid facility, and the deformation characteristic parameters at least comprise the deformation quantity, deformation direction, deformation rate and deformation type of the power grid facility.
Preferably, the monitoring integration unit is applicable and forms a parameter library, and the parameter library comprises a set of characteristic parameters of stress and deformation corresponding to a plurality of power grid facilities located in different regions and different terrains, and the parameter library can store monitoring data of all monitoring subunits and correspond the characteristic parameters of stress and deformation according to time sequence to form a plurality of characteristic parameter groups of stress and deformation associated with time periods. The parameter sets can reflect the stress and deformation conditions of the power grid facilities in different time periods, and provide important data support for the safe operation of the power grid facilities. In summary, the monitoring integration unit may perform preprocessing and integration so that the subsequent analysis module performs more accurate and reasonable data analysis.
S2: and monitoring data processing analysis.
According to the dynamic change of the multi-source monitoring data in the duration time obtained by the on-site real-time monitoring in the step S1, establishing a mechanical analysis model by means of the analysis module 200 to obtain the quantitative relation between the power grid facility stress distribution and the deformation and damage amount under the influence of geological disasters; specifically, the analysis module 200 may apply mathematical methods including statistical analysis, deterministic function, and hybrid model methods to build corresponding mathematical models according to the dynamic changes of the monitored data. The mathematical model is obtained by the analysis module 200 by means of statistical analysis, wherein the data collection and the data preprocessing are first required, and the two steps are completed by the monitoring module 100 in the step S1; secondly, the analysis module 200 analyzes the preprocessed data, including descriptive statistical analysis, correlation analysis, regression analysis and the like, so as to determine the relationship and trend between the data, and the step is the most critical step before model establishment, and whether the relationship and trend between the data are accurate or not directly influences the reliability and applicability after final model establishment; then, according to the result of data analysis, selecting a proper statistical model comprising a linear regression model, a nonlinear regression model, a time sequence model and the like, and establishing a preliminary mathematical model; and finally, checking the established mathematical model, wherein the checking content comprises evaluation of indexes such as fitting degree, prediction precision and the like of the model.
S3: constructing an intelligent early warning model;
in the monitoring and early warning of the power grid facility, the intelligent early warning model is an important tool, is also a terminal which can be directly operated by an operator and is fed back, and the state evaluation and prediction of the power grid facility are realized by using the early warning module 300 to the mathematical model obtained in the step S2. The early warning module 300 can adopt a prediction method based on quantitative relation, so that the prediction method can calculate the predicted deformation of the power grid facilities at the disaster-affected geology under the set working condition, and compare the predicted deformation with the on-site actual monitoring data, thereby obtaining the comparison error of the predicted deformation and the on-site actual monitoring data. To improve the accuracy and reliability of the predictions, multiple times and multiple-place cyclic fit corrections are required to ensure that the errors are less than a certain range.
Specifically, in the process of constructing the intelligent early warning model, the sensitivity factor of the deformation of the electric power facility can be determined through sensitivity analysis. The sensitivity analysis is an analysis method for evaluating the influence degree of data on the model output result, is particularly suitable for optimizing model parameters in the scene of large data quantity and data redundancy, and can assist in determining the reliability and stability of the model output result and evaluating the dependence degree of the model on the data. The sensitivity analysis includes the following steps:
1. determining the target and range of the sensitivity test: first, the target and range of the sensitivity test need to be defined, and the model and data to be tested need to be determined.
2. Method and index for determining sensitivity test: according to the target and range of the sensitivity test, a proper sensitivity test method and index are selected. Common sensitivity test methods include single factor sensitivity analysis, multi-factor sensitivity analysis, global sensitivity analysis, and the like.
3. Data were collected and pre-processed: data to be tested are collected and preprocessed, including data cleaning, data conversion, data standardization, and the like.
4. Sensitivity testing was performed: and carrying out sensitivity test on the data according to the selected sensitivity test method and the index. Common sensitivity test methods include parametric perturbation, monte Carlo simulation, sobol sensitivity analysis, and the like.
5. Analysis of sensitivity test results: and according to the result of the sensitivity test, analyzing the influence degree of the data on the output result of the model, evaluating the reliability and stability of the model, and determining the dependence degree of the model on the data to obtain a sensitivity factor for optimizing the model parameters.
6. Suggested and improved measures are proposed: and according to the result of the sensitivity test, corresponding suggestions and improvement measures are provided, and the model is optimized. And constructing a mathematical model for evaluating equipment damage according to the selected sensitive factors, and predicting the deformation of the electric power facility under the set working condition.
And carrying out an indoor model test and a displacement loading numerical simulation technology simultaneously on the basis of carrying out sensitivity analysis. The indoor model test is a common test method for researching the mechanical property and the earthquake resistance of a building structure, and the steps generally comprise:
1. the design test scheme is as follows: according to the research purpose and requirement, a test scheme is designed, including the size, the material, the loading mode, the position and the number of the measuring points and the like of a test model.
2. Manufacturing a test model: according to the test scheme, a test model is made. The test model should conform to the geometry and material characteristics of the actual structure while having good repeatability and comparability.
3. Installing a measuring device: measurement equipment including strain gauges, displacement meters, accelerometers, etc. are mounted on the test model. The measuring equipment should be installed at key parts of the test model in order to measure the mechanical properties and the anti-seismic properties of the structure.
4. Preloading: preloading is carried out on the test model so as to eliminate the initial stress and strain of the test model and ensure the accuracy and reliability of the test result.
5. And (3) carrying out a loading test: according to the test protocol, a loading test is performed. The loading test is carried out according to a preset loading mode and loading speed, and meanwhile, the data of stress, strain, displacement, acceleration and the like of the test model are recorded.
6. Analysis of test data: and according to the test data, analyzing the mechanical property and the earthquake resistance of the test model. The analysis method comprises stress strain analysis, displacement analysis, frequency analysis, modal analysis and the like.
7. Making conclusions and suggestions: based on the test results, conclusions and suggestions are made. The conclusion should include the mechanical properties and the anti-seismic properties of the test model, and the suggestion should include structural improvement measures and anti-seismic reinforcement schemes.
8. Writing a test report: and writing a test report according to the test result. The test report should include the contents of test protocols, test results, analytical methods, conclusions, suggestions, and the like.
Meanwhile, the displacement loading numerical simulation technology is synchronously carried out with the indoor model test, and is also a commonly used structural mechanics analysis method for researching the mechanical property and deformation characteristics of the structure under the displacement loading. The basic principle is that the geometric shape, material characteristics, loading mode and other information of the structure are converted into a mathematical model by a numerical simulation method, and then the model is solved by a computer program to obtain the mechanical parameters of the structure, such as stress, strain, displacement and the like. The numerical simulation technology of displacement loading mainly comprises the following aspects:
1. establishing a mathematical model: and establishing a mathematical model according to the information such as the geometric shape, the material characteristics, the loading mode and the like of the structure. Common mathematical models include finite element models, boundary element models, discrete element models, and the like.
2. Determining boundary conditions: and determining boundary conditions according to the loading mode, loading speed and other information. Boundary conditions include support constraints of the structure, displacement and force of the loading point, etc.
3. And (3) carrying out numerical solution: and solving the mathematical model by using a computer program to obtain mechanical parameters such as stress, strain, displacement and the like of the structure. Common numerical solving methods include finite element methods, boundary element methods, discrete element methods, and the like.
4. Analysis of the numerical results: and according to the numerical result, analyzing the mechanical property and deformation characteristics of the structure. The analysis method comprises stress strain analysis, displacement analysis, frequency analysis, modal analysis and the like.
5. Making conclusions and suggestions: based on the numerical results, conclusions and suggestions are made. The conclusion should include the mechanical properties and deformation characteristics of the structure, and the suggestion should include improvements and reinforcement schemes for the structure.
The obtained sensitivity factors are obtained through sensitivity analysis, the weight of the sensitivity factors in various parameters is improved to reduce the repetition times of simulation experiments and the arrangement of loading experiments, and the numerical simulation technology of displacement loading can also help to limit numerical boundary conditions to optimize the evaluation process.
And performing on-site deformation monitoring, comparing the difference between actual monitoring data and predicted data, performing PDCA (digital versatile analysis) circulation, and predicting the operation deformation state of the electric power facility within an acceptable error range by using a mathematical model after limited circulation. And according to the prediction data, evaluating the operation safety level of the electric power facilities, and providing an intelligent early warning model to finally form an intelligent early warning technology.
Further, the internal force change rule of the victim equipment and the foundation under the condition of different directional deformation is developed, and the deformation damage characteristics of mechanics and dynamics are obtained. And measuring the stress change by adopting a fiber bragg grating sensing technology according to deformation data under the action of different stress mechanisms, and researching the real-time monitoring technology of the internal force change of the power transmission equipment under different stress mechanisms. The actual working performance of the structure is determined from the strength, the rigidity and the actual damage form of the structure, and corresponding reinforcement measures are provided for different micro-damage conditions.
Based on the method, an intelligent early warning model which can provide corresponding reinforcement guiding measures under the condition of micro damage of the power grid facilities can be obtained. The model can evaluate and predict the state of the power grid facilities according to the monitoring data and the prediction result, and provides corresponding reinforcement guiding measures to ensure the safe operation of the power grid facilities. In addition, the intelligent early warning model can also be continuously iterated through continuous monitoring and analysis, so that the accuracy and reliability of prediction are improved.
In summary, the prediction method based on the quantitative relation is one of the important methods in monitoring and early warning of the power grid facilities, the prediction result can be obtained through calculation and comparison, and the intelligent early warning model can be obtained through repeated number and multi-place cyclic fitting correction. The model can evaluate and predict the state of the power grid facilities, and provide corresponding reinforcement guiding measures, thereby providing important data support for the safe operation of the power grid facilities.
Example 2
This embodiment is a further improvement of embodiment 1, and the repeated contents are not repeated.
In order to ensure the safe operation of the electric power facilities, the influence degree of geological disasters on the electric power facilities is required to be evaluated, and corresponding operation safety levels and corresponding operation measures are formulated according to evaluation results. The evaluation basis can be comprehensively judged based on multiple aspects. In particular, there are a wide variety of methods for assessing geological disasters of electrical facilities, including quantitative and qualitative methods. The quantitative method is generally based on a mathematical model, such as a probabilistic statistical model, a physical model or a machine learning model, to calculate the probability and possibly the extent of influence of the occurrence of a geological disaster. The qualitative method is generally based on expert knowledge and experience to judge the occurrence probability and influence degree of the geological disaster, and can also be used for determining the operation safety level of the electric power facility and corresponding operation measures and the improvement direction and degree of the measures according to the historical rush repair experience record and through analyzing the historical rush repair experience record, the influence degree of the geological disaster on the electric power facility is known. In addition, in the process of evaluating geological disasters of electric power facilities, various factors such as geological conditions, meteorological conditions, topography, land utilization, surrounding environment and the like need to be considered. At the same time, the characteristics of the electric power facilities, such as equipment type, equipment age, equipment state, maintenance condition, etc. need to be considered
Preferably, the operation safety level can be divided into a first level, a second level and a third level, which respectively represent that the influence degree of geological disasters on the electric power facilities is low to high. In particular, the primary security representative geological disaster has no obvious effect on the electric power facilities and cannot affect the long-term normal operation of the facilities. At the moment, the normal operation of the equipment can be ensured by only carrying out primary measures corresponding to the equipment, such as basic routine overhaul and maintenance. The secondary security represents that geological disasters have certain influence on electric power facilities, and the partial damage or shutdown of equipment can be caused to cause certain influence. At this time, secondary measures corresponding to the primary measures, such as regular and targeted overhaul and maintenance, are required to ensure the normal operation of the equipment. Three-level security represents that geological disasters have a great influence on electric power facilities, and damage or shutdown of equipment is likely to be caused, so that serious threat is caused. At this time, three-level measures corresponding to the device are needed, such as timely arrangement of personnel for comprehensive rush repair, so as to ensure safe operation of the device. In a word, according to the influence degree of geological disasters on the electric power facilities, corresponding operation safety levels and corresponding operation measures are formulated, so that the method is an important measure for guaranteeing the safe operation of the electric power facilities.
Further, evaluating the outcome of a geological disaster of an electrical facility should be a dynamic process, requiring constant updating and perfecting. When the early warning model detects that the stress or deformation of the electric power facility is changed, the evaluation result also needs to be updated correspondingly. This is because the occurrence of geological disasters may result in secondary occurrence due to the influence of external factors. Secondary occurrence of geologic hazards is often due to natural or artificial factors, such as rainfall, earthquake, human development, etc. These factors can cause the stability of the original geological disaster to change, thereby inducing a new geological disaster. For example, some mountain geological disasters, such as landslide, debris flow, etc., often occur after rainfall, and natural disasters such as earthquakes may also cause secondary occurrence of the geological disasters. In addition, human development activities may also have an impact on the stability of geological disasters, such as mining, construction, etc. activities may lead to secondary occurrences of geological disasters. Therefore, the work of dynamically evaluating the geological disasters of the electric power facilities can avoid the actual situation that the maintenance measures are not matched with the disaster points, plays a positive role in avoiding the phenomena of missing and missing operation maintenance measures and the like, and improves the stability and safety of the electric power facilities before and after the disaster, particularly when secondary geological disasters occur.
Claims (10)
1. A multi-source dynamic monitoring and early warning method for a power grid facility, the method comprising:
establishing a dynamic stress characteristic parameter library of historical power grid facilities based on time sequencing;
establishing a dynamic deformation characteristic parameter library of a historical power grid facility based on time sequencing;
based on the time sequence, connecting the stress characteristic parameter and the deformation characteristic parameter under the time sequence of the contract in parallel to construct a dynamic stress deformation model;
the method comprises the steps of obtaining stress characteristic parameters of a target power grid facility at the current moment, and judging deformation characteristic parameters of target power transmission equipment corresponding to the stress characteristic parameters at the current moment according to a dynamic stress deformation model so as to provide judgment basis for corresponding reinforcement measures under the condition of micro damage of the power grid facility.
2. The method for multi-source dynamic monitoring and early warning of power grid facilities according to claim 1, wherein the time-ordered dynamic stress characteristic parameter library and dynamic deformation characteristic parameter library comprise monitoring data of the power grid facilities for a period of time before and after occurrence of earthquake, storm and flood natural disaster occurrence nodes.
3. The multi-source dynamic monitoring and early warning method for the power grid facilities according to claim 1 or 2, wherein the detection data of the dynamic stress characteristic parameter library and the dynamic deformation characteristic parameter library are obtained based on a monitoring system which is integrated with one or more of an unmanned plane, a laser radar, a Beidou satellite system and a total station and ground deformation and stress monitoring comprehensive means.
4. The method for multi-source dynamic monitoring and early warning of power grid facilities according to claim 1, wherein the stress characteristic parameters comprise the magnitude, direction, action point and action time of the stress of the power grid facilities; the deformation characteristic parameters at least comprise deformation quantity, deformation direction, deformation rate and deformation type of the power grid facility.
5. The method of claim 1, wherein the historical grid facilities include one or more grid facilities located in different regions and different terrains.
6. The method for multi-source dynamic monitoring and early warning of power grid facilities according to claim 1, wherein the establishment of the dynamic stress deformation model comprises a finite element analysis model method, an application statistical analysis method, a deterministic function method and a mixed model method.
7. The multi-source dynamic monitoring and early warning method for the power grid facilities according to claim 1, wherein the deformation damage characteristics of mechanics and dynamics are obtained by obtaining internal force change rules of historical power grid facilities and disaster-affected geological foundations under different-direction deformation conditions based on an indoor model test and a displacement loading numerical simulation technology.
8. The multi-source dynamic monitoring and early warning method for the power grid facilities according to claim 1, wherein the actual working performance of the structure is determined from the strength, the rigidity and the actual structural failure mode by adopting a fiber bragg grating sensing technology based on deformation failure characteristics under the action of different stress mechanisms, and corresponding reinforcement measures are provided for different micro-damage conditions.
9. The method for multi-source dynamic monitoring and early warning of power grid facilities according to claim 1, wherein the sensitivity analysis is performed on the established mathematical model to determine the sensitivity factor of the deformation of the power grid facilities, the mathematical model for evaluating the damage of the power grid facilities is constructed according to the selected sensitivity factor, and the corrected intelligent early warning model is obtained by using the limited number of cycles of PDCA.
10. The method for multi-source dynamic monitoring and early warning of power grid facilities according to claim 1, wherein the operation safety level of the target power grid facilities corresponding to the result is evaluated for selecting operation maintenance measures based on the result presented by the intelligent early warning model.
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