Distribution line distance electricity-related public safety hidden danger analysis method

Abstract

The invention discloses a distribution line distance electricity-related public safety hidden danger analysis method, relates to the technical field of distribution line safety, and solves the problem that a traditional distribution line safety analysis method neglects influence factors such as environmental conditions, load fluctuation and equipment aging. According to the method, the historical state data of the power distribution line distance are combined, the factors influencing the power-related public safety hidden danger are confirmed, the relation between the power distribution line distance and the power-related public safety hidden danger is dynamically analyzed, the potential safety hazard development trend existing in a future power distribution line is simulated, and real-time planning is carried out. In addition, uncertain factors including environmental conditions, load fluctuation, line aging and the like are comprehensively considered, potential safety hazards possibly occurring in different conditions of the distribution line are comprehensively and accurately evaluated based on the Monte Carlo prediction model, and the credibility is improved. Besides, corresponding management strategies and measures are formulated according to the potential safety hazard probability and the risk level under different conditions, powerful support is provided for risk decision making, and the public security related to electricity is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution line safety, and in particular to a method for analyzing power distribution line distance-related public safety hazards. Background Art

[0002] Modern society has an increasing demand for electricity supply, and as an important part of the power system, the safety and reliability of distribution lines are crucial to public safety related to electricity. However, in actual operation, distribution lines face various potential safety hazards, such as ground faults, overloads, short circuits, insulation damage, etc. These safety hazards may lead to serious accidents such as power system interruptions, fires, electric shocks, etc., posing huge risks to personal safety and property.

[0003] Traditional distribution line safety analysis methods mainly rely on experience and static models, and usually use empirical rules or statistical data-based models to evaluate the safety of distribution lines. These methods ignore the impact of environmental conditions, load fluctuations, equipment aging and other factors. The uncertainty and dynamic changes of these factors make it difficult for traditional analysis methods to accurately evaluate safety hazards in these complex situations.

[0004] In view of this, a method for analyzing public safety hazards related to electricity distribution line distance is needed, which fully considers the historical data, current environment and application requirements required for public safety hazards related to electricity, applies modern inspection technology, ensures the stable operation of power demand, and improves the work efficiency of manual inspection. Summary of the invention

[0005] In view of the problem that the traditional power distribution line safety analysis method in the prior art ignores the influence of environmental conditions, load fluctuations, equipment aging and other factors, the uncertainty and dynamic changes of these factors make it difficult for traditional analysis methods to accurately evaluate the safety hazards in these complex situations. The present invention provides a method for analyzing the public safety hazards of power distribution lines, which can fully consider the historical data, current environment and application requirements required for the public safety hazards of power distribution lines, apply modern inspection technology, ensure the stable operation of power demand, improve the work efficiency of manual inspections, and thus overcome the limitations of traditional methods and improve the accuracy and credibility of the public safety analysis of power distribution lines. The specific technical scheme is as follows:

[0006] A method for analyzing the hidden dangers of power distribution line distance to public safety, comprising the following steps:

[0007] S1: Establish a historical database of distribution line distances, including obtaining power loads, environmental conditions, and equipment status;

[0008] S2: Determine the key factors of public safety hazards related to electricity, including weather conditions, equipment aging, load fluctuations and safe distances;

[0009] S3: Establish a mathematical model based on Monte Carlo prediction technology, consider the relationship between distribution lines and safety hazards, and use historical data to conduct quantitative analysis and early warning estimates of safety risks in the future;

[0010] S4: By simulating the sample data, analyze and predict the potential safety hazards of distribution line distances, and obtain the probability and risk level of potential safety hazards under different circumstances;

[0011] S5: Develop corresponding risk management strategies and measures based on the analysis results.

[0012] Preferably, the establishment of a historical database of distribution line distances is specifically as follows: determining the high voltage level and safety range, environmental conditions based on the power load, the environmental conditions and the equipment status, determining the line load-bearing capacity and toughness under extreme weather conditions, maintenance records, confirming the line health status and maintenance quality, accident reports, and recording the causes of accidents, extent of losses and response measures.

[0013] Preferably, the key factors also include:

[0014] Natural environmental factors, including snow loads on distribution lines and the degree of swaying of distribution lines caused by strong winds;

[0015] The line structure, including the distance from the lowest point of the distribution line between two towers to the ground, the high-voltage safety range that the distribution line can withstand load fluctuations, the straight-line distance to trees and houses within the safety range, and the age of the line.

[0016] Preferably, the step S3 is specifically as follows:

[0017] Perform entity abstraction and construct a probability model between the distribution line distance and public safety hazards, so as to solve the abstract random problem with a mathematical model. The probability model is as follows:

[0018]

[0019] Among them, f d (x) is the probability density function of the safety hazard relationship; x is the input distribution line distance; μ d is the standard deviation of the function; σ d is the expectation of the function;

[0020] The Monte Carlo method is used to simulate the probability of public safety hazards and calculate the expectation and standard deviation under the influence of various factors;

[0021] The actual influencing factors corresponding to the known safety hazard impact results are compared with the simulation results achieved by the simulation experiment to determine the error probability; at the same time, the data of the distribution line distance is input to determine the estimate, that is, to determine the probability result of the safety hazard and realize quantitative analysis.

[0022] Preferably, the step S4 calculates a public safety hazard risk index based on the simulation prediction result, and the public safety hazard risk index includes a leakage probability, a tree threat probability and a personnel threat probability.

[0023] Preferably, the step S4 specifically includes: evaluating the gap between the risk indicator and the safety standard, obtaining a quantitative coefficient of the safety risk, and the risk level is divided into 5 levels according to the severity, including:

[0024] Level 5: Low risk: Establish safety inspection and monitoring mechanisms, strengthen safety publicity and education, and maintain public safety and social order;

[0025] Level 4: Medium to low risk: strengthen monitoring and inspection, conduct hidden danger investigation and rectification, and improve safety awareness and prevention capabilities;

[0026] Level 3 medium risk: formulate and implement corresponding emergency plans, dispatch appropriate personnel and resources to conduct risk assessment, and reduce potential hazards and risks;

[0027] Level 2: Medium to high risk, take measures to protect more people or property to prevent the situation from further expanding and affecting;

[0028] Level 1 high risk, activate emergency plan and emergency response mechanism.

[0029] Preferably, the step S5 specifically includes: formulating a risk prediction result report and decision support according to the risk level.

[0030] A computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the above-mentioned method for analyzing public safety hazards related to power distribution line distance.

[0031] A processor, the processor is used to run a program, wherein when the program is run, the method for analyzing the public safety hazards of power distribution line distance as described above is executed

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. Combined with the historical status data of distribution line distance, identify the factors affecting the hidden dangers of public safety related to electricity, dynamically analyze the relationship between the distribution line distance and the hidden dangers of public safety related to electricity, simulate the development trend of the hidden dangers of the distribution line in the future and make real-time planning;

[0034] 2. Comprehensively consider uncertain factors, including environmental conditions, load fluctuations, line aging, etc., and based on the Monte Carlo prediction model, comprehensively and accurately evaluate the potential safety hazards of distribution lines under different circumstances, thereby improving the credibility of the analysis results;

[0035] 3. Formulate corresponding management strategies and measures based on the probability and risk level of safety hazards in different situations, provide strong support for risk decision-making, and ensure public safety involving electricity. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0037] Figure 1 It is a schematic diagram of the pole tower spacing;

[0038] Figure 2 It is a network logic flow chart of the present invention. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0041] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0042] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0043] Combine the following Figure 1-2 , the implementation scheme of the present invention is further described in detail.

[0044] In one embodiment of the present invention, a method and system for analyzing power distribution line distance-related public safety hazards based on Monte Carlo prediction are provided, comprising the following steps:

[0045] Step 1: Establish a historical database of distribution line distances, including factors that affect the safety and quality of distribution lines, such as power load, environmental conditions, and equipment status;

[0046] Step 2: Determine the key factors of public safety hazards related to electricity, such as weather conditions, equipment aging, load fluctuations, safety distance and other influencing factors;

[0047] Step 3: Establish a mathematical model based on Monte Carlo prediction technology, consider the relationship between distribution lines and safety hazards, and use historical data to conduct quantitative analysis and early warning estimates of safety risks in the future;

[0048] Step 4: By simulating the sample data, analyze and predict the potential safety hazards of distribution line distances, and obtain the probability and risk level of potential safety hazards under different circumstances;

[0049] Step 5: Based on the analysis results, formulate corresponding risk management strategies and measures to provide technical support to decision makers while ensuring public safety related to electricity.

[0050] Specifically, step 1 establishes a historical database of distribution lines to provide a data basis for subsequent Monte Carlo prediction simulation and safety hazard analysis, mainly including: power load, determination of high voltage level and safety range, environmental conditions, determination of line load-bearing capacity and toughness under extreme weather conditions, maintenance records, confirmation of line health status and maintenance quality, accident reports, and recording of accident causes, extent of losses and response measures.

[0051] Specifically, step 2 determines the key factors of public safety hazards related to electricity, including natural environmental factors, such as the snow load on the distribution line, the degree of swaying of the distribution line by strong winds; line structure, the distance from the lowest point of the distribution line between two towers to the ground, the high-voltage safety range of the distribution line load fluctuation and the straight-line distance of trees, houses, etc. within the safety range, and the age of the line;

[0052] Specifically, step 3 establishes a Monte Carlo prediction model, evaluates the risk level by analyzing the relationship between the distribution line distance and public safety hazards, and provides real-time warning;

[0053] The Monte Carlo model is a numerical calculation method based on random sampling and statistical analysis. In the analysis of distribution line distance and public safety hazards, a large number of random samples are used to simulate and evaluate the safety risks between uncertain factors, thereby providing a more accurate potential risk level. The following three main steps are followed:

[0054] 1. Abstract the above problems into entities, construct a probability model between the distance between distribution lines and public safety hazards, and use mathematical models to solve abstract random problems;

[0055]

[0056] Among them, f d (x) is the probability density function of the safety hazard relationship; x is the input distribution line distance; μ d is the standard deviation of the function; σ d is the expectation of the function;

[0057] 2. Use the Monte Carlo method to simulate the probability of public safety hazards, calculate the expectation and standard deviation under the influence of various factors, and simulate the results of public safety hazards based on the Monte Carlo theory;

[0058] 3. Compare the actual influencing factors corresponding to the known safety hazard impact results with the simulation results achieved by the simulation experiment to determine the error probability; at the same time, input the data of the distribution line distance to determine the estimate, that is, determine the probability result of the safety hazard to achieve quantitative analysis.

[0059] Specifically, step 4 calculates the risk indicators of public safety hazards based on the simulation prediction results, such as leakage probability, tree threat probability, personnel threat probability, etc. The gap between the risk indicators and the safety standards is evaluated to obtain a quantitative coefficient on the safety risk.

[0060] Specifically, step 5 formulates risk prediction result report and decision support according to the risk level to help managers take corresponding measures to maintain the stability and safety of distribution lines. The risk level is divided into 5 levels according to the severity, including: Level 5 low risk, establish a safety inspection and monitoring mechanism, strengthen safety publicity and education, and maintain public safety and social order; Level 4 medium and low risk, strengthen monitoring and inspection, conduct hidden danger investigation and rectification, and improve safety awareness and prevention capabilities; Level 3 medium risk, formulate and implement corresponding emergency plans, dispatch appropriate personnel and resources to conduct risk assessment, and reduce potential hazards and risks; Level 2 medium and high risk, take prompt measures to protect more people or property to prevent the situation from further expanding and affecting; Level 1 high risk, activate emergency plans and emergency response mechanisms, and take prompt and effective measures to deal with them.

[0061] In summary, the present invention combines the historical status data of distribution line distances to identify factors that affect electricity-related public safety hazards, dynamically analyzes the relationship between distribution line distances and electricity-related public safety hazards, simulates the development trend of safety hazards in future distribution lines, and performs real-time planning. Moreover, the present invention comprehensively considers uncertain factors, including environmental conditions, load fluctuations, line aging, etc., and based on the Monte Carlo prediction model, comprehensively and accurately evaluates the safety hazards that may arise in distribution lines under different circumstances, thereby improving the credibility of the analysis results. In addition, the present invention also formulates corresponding management strategies and measures based on the probability and risk level of safety hazards in different situations, provides strong support for risk decision-making, and ensures public safety related to electricity. Therefore, the technical solution of the present invention is sufficient to solve the problems raised in the background technology.

[0062] Those of ordinary skill in the art will appreciate that the units (or steps, the same below) of the examples described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition of each example has been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0063] In the embodiments provided by the present invention, it should be understood that the division of units is only a logical function division, and there may be other division methods in actual implementation, for example, multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored, etc.

[0064] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0065] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-0nlyMemory), random access memory (RAM, RandomAccessMemory), mobile hard disk, magnetic disk or optical disk, etc., which can store program code.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A method for analyzing the hidden dangers of power distribution line distance related to public safety, characterized in that: The following steps are involved: S1: Establish a historical database of distribution line distances, including obtaining power loads, environmental conditions, and equipment status; S2: Determine the key factors of public safety hazards related to electricity, including weather conditions, equipment aging, load fluctuations and safe distances; S3: Establish a mathematical model based on Monte Carlo prediction technology, consider the relationship between distribution lines and safety hazards, and use historical data to conduct quantitative analysis and early warning estimates of safety risks in the future; S4: By simulating the sample data, analyze and predict the potential safety hazards of distribution line distances, and obtain the probability and risk level of potential safety hazards under different circumstances; S5: Develop corresponding risk management strategies and measures based on the analysis results.

2. A method for analyzing the potential dangers of power distribution line distance to public safety according to claim 1, characterized in that: The establishment of a historical database of distribution line distances is specifically as follows: based on the power load, the environmental conditions and the equipment status, the high voltage level and safety range, the environmental conditions, the load-bearing capacity and toughness of the line under extreme weather conditions, the maintenance records, the health status of the line and the quality of maintenance, the accident reports, and the causes of the accidents, the extent of the losses and the response measures are determined.

3. A method for analyzing the hidden dangers of power distribution line distance related to public safety according to claim 1, characterized in that: The key factors also include: Natural environmental factors, including snow loads on distribution lines and the degree of swaying of distribution lines caused by strong winds; The line structure, including the distance from the lowest point of the distribution line between two towers to the ground, the high-voltage safety range that the distribution line can withstand load fluctuations, the straight-line distance to trees and houses within the safety range, and the age of the line.

4. A method for analyzing the potential dangers of power distribution line distance to public safety according to claim 1, characterized in that: The step S3 is specifically as follows: Perform entity abstraction and construct a probability model between the distribution line distance and public safety hazards, so as to solve the abstract random problem with a mathematical model. The probability model is as follows: Among them, f d (x) is the probability density function of the safety hazard relationship; x is the input distribution line distance; μ d is the standard deviation of the function; σ d is the expectation of the function; The Monte Carlo method is used to simulate the probability of public safety hazards and calculate the expectation and standard deviation under the influence of various factors; The actual influencing factors corresponding to the known safety hazard impact results are compared with the simulation results achieved by the simulation experiment to determine the error probability; at the same time, the data of the distribution line distance is input to determine the estimate, that is, to determine the probability result of the safety hazard and realize quantitative analysis.

5. The method for analyzing the potential dangers of power distribution line distance to public safety according to claim 1, characterized in that: The step S4 calculates the public safety hidden danger risk index based on the simulation prediction result, and the public safety hidden danger risk index includes the leakage probability, the tree threat probability and the personnel threat probability.

6. A method for analyzing the potential dangers of power distribution line distance to public safety according to claim 5, characterized in that: The step S4 specifically includes: evaluating the gap between the risk index and the safety standard, and obtaining a quantitative coefficient of the safety risk. The risk level is divided into five levels according to the severity, including: Level 5: Low risk: Establish safety inspection and monitoring mechanisms, strengthen safety publicity and education, and maintain public safety and social order; Level 4: Medium to low risk: strengthen monitoring and inspection, conduct hidden danger investigation and rectification, and improve safety awareness and prevention capabilities; Level 3 medium risk: formulate and implement corresponding emergency plans, dispatch appropriate personnel and resources to conduct risk assessment, and reduce potential hazards and risks; Level 2: Medium to high risk, take measures to protect more people or property to prevent the situation from further expanding and affecting; Level 1 high risk, activate emergency plan and emergency response mechanism.

7. A method for analyzing the potential dangers of power distribution line distance to public safety according to claim 1, characterized in that: The step S5 specifically includes: formulating a risk prediction result report and decision support according to the risk level.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method for analyzing public safety hazards related to power distribution line distances as described in any one of claims 1 to 6.

9. A processor, characterized in that: The processor is used to run a program, wherein the program, when running, executes the method for analyzing public safety hazards related to power distribution line distances as described in any one of claims 1 to 6.

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