Risk assessment and scheduling method and system based on main and distribution networks

Abstract

The invention discloses a risk assessment and scheduling method and system based on a main distribution network, and the method comprises the steps: recognizing a fault of the main distribution network, and transmitting a first alarm signal based on the recognized fault; setting an observation period, obtaining all alarm signal fault types in the observation period, and constructing a fault-weight corresponding table; based on the fault-weight corresponding table, calculating a comprehensive risk coefficient of all fault types in the observation period; judging the comprehensive risk coefficient, and sending out a second alarm signal based on a first judgment result; and constructing a scheduling objective function based on the operation and maintenance cost, and solving the scheduling objective function in combination with the operation and maintenance information of the first alarm signal at the current moment. According to the method, risk analysis is associated through real-time alarm, so that the risk conditions of the same week based on different areas can be compared, or the risk conditions of different periods of the same area can be compared; the target function is constructed through the matching cost, the labor cost and the transportation cost, the resource configuration is optimized, and the transportation cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid risk assessment and dispatching, and particularly to a risk assessment and dispatching method and system based on the main and distribution networks. Background Art

[0002] As an important part of the power system, the stability of the main and distribution networks is directly related to the reliability and security of power supply. Fault identification plays a crucial role in this field. It can not only quickly locate the source of the problem, reduce power outage time, but also prevent potential large-scale power outage events. Once a fault occurs, efficient dispatching of personnel, vehicles, and tools is the key to restoring power supply. Reasonable resource allocation can ensure the rapid response and effective execution of emergency repair work, reducing the impact on residents' lives and industrial production. In addition, precise dispatching can also reduce costs, improve resource utilization, and avoid unnecessary waste. Therefore, optimizing fault identification and resource dispatching strategies is of great significance for enhancing the resilience and efficiency of the entire power system.

[0003] However, in the current fault diagnosis process, a relatively simple method is usually adopted for the allocation of human, transportation, and equipment resources, that is, directly using available resources for processing. This method does not deeply analyze the compatibility between resources, nor evaluate the cooperation effect and cost difference of different personnel, vehicles, and tools to determine which combination can complete the work most efficiently and at the lowest cost. The existing resource allocation decision-making process lacks in-depth correlation between resource adaptability and cost, which makes the accuracy and practicality of the dispatching decision-making scheme not high. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a risk assessment and dispatching method and system based on the main and distribution networks to solve the problems in the prior art that lack of analysis of the compatibility between resources and cannot deeply correlate resource adaptability and cost, resulting in low accuracy and practicality of the decision-making scheme.

[0006] To solve the above technical problems, the present invention provides the following technical solutions:

[0007] In the first aspect, the present invention provides a risk assessment and dispatching method based on the main and distribution networks, including:

[0008] Identifying the faults of the main and distribution networks and sending a first alarm signal based on the identified faults;

[0009] Setting an observation period, obtaining all the fault types of the alarm signals within the observation period, and constructing a fault-weight correspondence table;

[0010] Calculate the comprehensive risk coefficient of all fault types within the observation period based on the fault-weight correspondence table;

[0011] Judge the comprehensive risk coefficient and send a second warning signal based on the first judgment result;

[0012] Construct a scheduling objective function based on the operation and maintenance cost, and solve the scheduling objective function in combination with the operation and maintenance information at the current moment of the first warning signal.

[0013] As a preferred solution of the risk assessment and scheduling method based on the main and distribution networks of the present invention, wherein: constructing a scheduling objective function based on the operation and maintenance cost includes:

[0014] Obtain the matching cost, labor cost, and transportation cost;

[0015] Among them, the reciprocal of the matching cost is taken in the scheduling objective function;

[0016] Set and assign the weight coefficients of each cost, and obtain the scheduling objective function of the comprehensive cost after summation.

[0017] As a preferred solution of the risk assessment and scheduling method based on the main and distribution networks of the present invention, wherein: the matching cost is calculated through the personnel matching situation coefficient, vehicle matching situation coefficient, and tool matching situation coefficient;

[0018] The personnel matching situation coefficient is a matching coefficient based on qualifications and experience;

[0019] When the vehicle fault type corresponds to the damage type in the fault-weight correspondence table, set the first vehicle matching situation coefficient, otherwise, set it to the second vehicle matching situation coefficient;

[0020] When all the tools corresponding to the damage type in the fault-weight correspondence table for the tool fault type are prepared, set the first tool matching situation coefficient; if there are tools missing, set the second tool matching situation coefficient based on the number of missing tools;

[0021] Set the corresponding weights of each matching situation coefficient, and obtain the matching cost after summation.

[0022] As a preferred solution of the risk assessment and scheduling method based on the main and distribution networks of the present invention, wherein: obtaining the labor cost includes:

[0023] Construct a personnel information table for storing personnel information, where the personnel information includes the person's name, job number, ID number, license status, and professional title level;

[0024] Obtain the labor cost corresponding to each person through expert fuzzy evaluation.

[0025] As a preferred solution of the risk assessment and scheduling method based on the main and distribution networks according to the present invention, wherein: obtaining the transportation cost includes:

[0026] Construct a person-vehicle-tool information table based on the personnel information table;

[0027] Among them, the personnel information further includes the real-time position of the personnel, including the position of the personnel at the fault repair site and the final position of the personnel after the fault repair is completed;

[0028] The vehicle information includes the vehicle model and the current location of the vehicle,

[0029] The tool information includes the tool type, tool number, and the location of the tool;

[0030] The transportation cost is the sum of the distances of the personnel, vehicle, and tool from the fault point.

[0031] As a preferred solution of the risk assessment and scheduling method based on the main and distribution networks according to the present invention, wherein: the scheduling objective function further includes constraint conditions, specifically:

[0032] Personnel idle situation constraint, vehicle idle situation constraint, and tool idle situation constraint;

[0033] Set idle and non-idle representative values respectively based on their respective idle situations.

[0034] As a preferred solution of the risk assessment and scheduling method based on the main and distribution networks according to the present invention, wherein: combining the operation and maintenance information at the current moment of the first warning signal, solving the scheduling objective function specifically includes:

[0035] Obtain the person-vehicle-tool matching situation coefficient, the person-vehicle-tool information table, and the idle state;

[0036] Take the partial derivative of each person-vehicle-tool matching situation coefficient variable in the objective function to obtain the gradient;

[0037] According to the gradient and the learning rate, update the variable to ensure that the updated variable meets its respective constraint state;

[0038] If the change in the objective function value is less than the preset threshold, or the maximum number of iterations is reached, stop the iteration, otherwise, continue to take the partial derivative of the variable for iteration;

[0039] Output the optimal solution, including the optimal person-vehicle-tool matching situation coefficient, the optimal idle state of the person-vehicle-tool, and the minimum comprehensive cost.

[0040] In a second aspect, the present invention provides a risk assessment and scheduling system based on the main and distribution networks, including:

[0041] An identification module, configured to identify the main and distribution network faults, and send a first alarm signal based on the identified faults;

[0042] A first construction module, configured to set an observation period, obtain all the fault types of the alarm signals within the observation period, and construct a fault-weight correspondence table;

[0043] A calculation module, configured to calculate the comprehensive risk coefficient of all the fault types within the observation period based on the fault-weight correspondence table;

[0044] A judgment module, configured to judge the comprehensive risk coefficient and send a second alarm signal based on the first judgment result;

[0045] A second construction and solution module, configured to construct a scheduling objective function based on the operation and maintenance costs, and solve the scheduling objective function in combination with the operation and maintenance information at the current moment of the second alarm signal.

[0046] In a third aspect, the present invention provides an electronic device, including:

[0047] A memory and a processor;

[0048] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the risk assessment and scheduling method based on the main and distribution network are implemented.

[0049] In a fourth aspect, the present invention provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by a processor, the steps of the risk assessment and scheduling method based on the main and distribution network are implemented.

[0050] Compared with the prior art, the beneficial effects of the present invention are as follows: Through real-time alarm associated risk analysis, the present invention can compare the risk situations in different regions during the same week or compare the risk situations in different periods of the same region; By matching costs, labor costs, and transportation costs to construct an objective function, the present invention can optimize resource allocation, reduce transportation distance, and lower transportation costs. By quantifying information and solving the objective function, the present invention can quickly respond, accurately schedule appropriate resources, and improve the repair efficiency; And it can dynamically adjust the scheduling strategy to adapt to different fault scenarios. Description of the Drawings

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0052] Figure 1 Schematic diagram of the overall process of the risk assessment and scheduling method based on the main and distribution networks according to an embodiment of the present invention. Specific embodiments

[0053] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0054] Example 1, referring to Figure 1 This is an embodiment of the present invention, which provides a risk assessment and scheduling method based on the main and distribution networks, including:

[0055] S100: Identify the faults of the main and distribution networks and send the first alarm signal based on the identified faults;

[0056] S200: Set an observation period, obtain the fault types of all alarm signals within the observation period, and construct a fault-weight correspondence table;

[0057] S300: Calculate the comprehensive risk coefficient of all fault types within the observation period based on the fault-weight correspondence table;

[0058] S400: Judge the comprehensive risk coefficient and send the second alarm signal based on the first judgment result;

[0059] S500: Construct a scheduling objective function based on the operation and maintenance cost, and solve the scheduling objective function in combination with the operation and maintenance information at the current moment of the second alarm signal.

[0060] It should be noted that the fault types of the main and distribution networks are relatively complex, usually including short circuits, grounding faults, equipment aging, etc., and the fault impact weights may change dynamically with load changes. The fault impacts of the main and distribution networks in different regions may also be different. Static weight allocation does not consider regional characteristics and is difficult to adapt; there may be correlations between the faults of the main and distribution networks, such as a certain fault triggering a chain reaction. Therefore, it is necessary to comprehensively consider the risks; and the operation and maintenance cost is affected by various factors. An inaccurate scheduling strategy often leads to waste of resources and increased costs.

[0061] Therefore, through the steps of S100 - S500 described above, it is possible to fully issue an alarm based on the fault conditions and alarm conditions within the period, send out the first alarm signal, and also count the alarm conditions within the statistical period and calculate the comprehensive risk assessment coefficient based on this, and set a comparison threshold. When the risk assessment coefficient exceeds the threshold, the second alarm signal is sent out. Finally, an objective function is constructed based on the matching cost, labor cost, and transportation cost, and the optimal scheduling strategy can be obtained by solving the objective function.

[0062] Embodiment 2, referring to Figure 1 , which is an embodiment of the present invention. Based on the above embodiment, a risk assessment and scheduling method based on the main and distribution networks is provided.

[0063] In the embodiment of the present application, in step S100, the main and distribution network faults are identified, and the first alarm signal is sent based on the identified faults. The fault identification can be performed through a fault identification model, specifically, it can be a support vector machine (SVM), which is suitable for non - linear classification problems;

[0064] In an alternative embodiment, the main and distribution network faults in step S100 can also be identified through a random forest, which is suitable for multi - classification problems and has strong robustness to noise data; or through a long short - term memory network (LSTM), which can capture complex fault patterns;

[0065] Specifically, the above - mentioned identification methods are selected according to different main and distribution network situations, and all can be obtained through the following training:

[0066] Collect historical fault data, such as time - series data of current, voltage, power, frequency, etc., and label the fault types;

[0067] Extract time - series features, such as sliding window statistics, frequency - domain features, etc.;

[0068] Perform normalization, standardization, and denoising processing on the features;

[0069] Train the corresponding fault model with the labeled feature data, adjust the hyperparameters through cross - validation, and optimize the model performance;

[0070] Evaluate the classification accuracy and generalization ability of the model through an independent validation set, and further adjust the model parameters according to the validation results until the expected goal is achieved.

[0071] In another alternative embodiment, the main and distribution network faults in step S100 can also be identified through a real - time monitoring system, such as: SCADA system, smart meters, fault indicators, etc. to obtain the first alarm signal, and identify the fault types according to the characteristics of the alarm signal, such as: sudden increase in current, sudden drop in voltage, etc.;

[0072] It should be noted that the above first warning signal is used to remind the management personnel to start the dispatching or maintenance work.

[0073] In the embodiment of the present application, in step S200, a fault-weight correspondence table is constructed. This step mainly quantifies by experts or staff in the relevant field according to the importance or difficulty of the fault. The larger the weight value, the greater the proportion of the corresponding fault in the subsequent calculation.

[0074] In another alternative embodiment, in step S200, when constructing the fault-weight correspondence table, weight allocation can also be performed by statistically analyzing the occurrence frequency, average repair time, economic loss, etc. of each fault type based on historical fault data. For example, fault types with a high occurrence frequency and a long repair time have a higher weight; fault types that cause a large economic loss have a higher weight.

[0075] In another alternative embodiment, in step S200, when constructing the fault-weight correspondence table, weight allocation can be based on the degree of fault impact. Exemplarily, different proportion weights are allocated according to the degree of impact of the fault on the main distribution network, such as the power outage range, economic loss, repair difficulty, etc.

[0076] It should be noted that the purpose of constructing the fault-weight correspondence table in step S200 is to quantify the importance of each fault type, provide a basis for the calculation of the comprehensive risk coefficient, and at the same time form a complete fault information database to provide data basis for the calculation of the comprehensive risk coefficient and resource scheduling in the subsequent steps.

[0077] In the embodiment of the present application, in step S300, based on the fault-weight correspondence table, the comprehensive risk coefficient of all fault types within the observation period is calculated. Specifically, the comprehensive risk coefficient is expressed as:

[0078]

[0079] In the formula, C(T) is the comprehensive evaluation coefficient within the period, λ i is the weight coefficient corresponding to the fault Pi in the fault-weight correspondence table, P i (T) is the statistical number of the fault Pi within the period T.

[0080] In an alternative embodiment, the comprehensive risk coefficient in step S300 can be optimized to a weighted average risk coefficient based on the above form. By dividing by the total number of faults, the comprehensive risk coefficient is normalized, which is convenient for comparison between different periods.

[0081] In another alternative embodiment, in step S300, the comprehensive risk coefficient can also be calculated based on the comprehensive risk coefficient of the present application, and a time decay factor can be considered to be added, so that the impact of recently occurring faults on the risk coefficient increases, and the impact of long-term faults gradually decreases.

[0082] It should be noted that by quantifying the comprehensive risk coefficient, the overall risk level of the main and distribution networks within the observation period T can be intuitively reflected, thereby providing data support for subsequent risk judgment and resource scheduling.

[0083] In the embodiment of the present application, in step S400, the comprehensive risk coefficient is judged, and a second warning signal is sent based on the first judgment result. The comparison threshold C(θ1) can be set, and the comprehensive risk coefficient C(T) within the period T is compared with the comparison threshold C(θ1). If C(T) ≥ C(θ1), the second warning signal is sent; otherwise, no warning is sent.

[0084] In an alternative embodiment, in step S400, the comprehensive risk coefficient can also be judged by the change trend of the comprehensive risk coefficient C(T) to determine whether to send a warning. For example, the average value of the comprehensive risk coefficients in the recent k periods is calculated and the change rate ΔC. If C(T) is significantly higher than or ΔC exceeds a certain threshold, the second warning signal is sent;

[0085] In another alternative embodiment, in step S400, the judgment of the comprehensive risk coefficient can also be a combined judgment form of threshold + trend. The change rate comparison value Δθ is set. For example:

[0086] If C(T) ≥ C(θ1) and ΔC ≥ Δθ, the second warning signal is sent;

[0087] If C(T) < C(θ1), but ΔC ≥ Δθ, a risk increase signal is sent.

[0088] It should be noted that the second warning signal reflects the risk coefficient within the period, which is used to evaluate the fault situation within the period and the risk degree contained therein. It is more convenient for managers to compare the risk situations between different regions in the same week or between different periods in the same region, and can timely detect the rising trend of risks and take preventive measures in advance; at the same time, according to the comprehensive risk coefficient, the faults can be sorted by priority to provide a higher level of warning information to support risk classification, decision-making, etc.

[0089] In the embodiment of the present application, in step S500, the scheduling objective function is constructed based on the operation and maintenance cost, including the following steps A1 - A2:

[0090] A1: Obtain the matching cost, labor cost, and transportation cost;

[0091] Among them, the reciprocal of the matching cost is taken in the scheduling objective function;

[0092] A2: Set and assign the weight coefficients for each cost, and obtain the scheduling objective function of the comprehensive cost after summation;

[0093] Specifically, the scheduling objective function is expressed as:

[0094]

[0095] In the formula, C 匹配 is the matching cost, C 人工 is the labor cost, C 运输 is the transportation cost, and μ1, μ2, and μ3 are the weight coefficients of the matching cost, labor cost, and transportation cost respectively, reflecting the influence degrees of the matching cost, labor cost, and transportation cost in the process of solving the objective function, which are given by experts in the field or other relevant staff according to the actual situation. The larger this value is, the greater the influence degree.

[0096] In an alternative embodiment, other operation and maintenance costs, such as time cost and / or equipment loss cost, can also be added to the constructed scheduling objective function to more comprehensively reflect the actual situation of operation and maintenance scheduling.

[0097] In the above formula, the matching cost reflects the matching degree of personnel, vehicles, and tools to the faults to be repaired. Among them, the personnel matching cost reflects the matching situation of personnel, including the matching situation of personnel qualifications and whether personnel have various licenses required for fault repair, etc. The labor cost reflects the usage cost corresponding to the currently selected personnel, and this value is obtained through comprehensive consideration of the qualification situation, professional title situation, working years, etc. of different personnel, and the labor cost corresponding to each person is given directly by the expert system evaluation or the personnel system. The transportation cost reflects the distance between the currently selected personnel, vehicles, and tools and the fault point. This value reflects the transportation cost between personnel, vehicles, and tools and the fault point. That is, personnel, vehicles, and tools closer to the fault point are preferably selected, and the transportation costs of personnel, vehicles, and tools themselves are the respective independent lowest transportation costs or the combined lowest transportation costs in the optional cases.

[0098] It should be noted that the reason for preferably choosing these three cost forms in this step is that they can directly reflect resource adaptability, labor cost, and transportation expenses, which are the most core cost components in operation and maintenance scheduling; by optimizing these costs, the resource scheduling efficiency can be significantly improved, the operation and maintenance costs can be reduced, the operation reliability of the main and distribution networks can be enhanced, and at the same time, the computing power can be reduced and the computing power cost can be lowered.

[0099] It should also be noted that the values of the matching cost, labor cost, and transportation cost are all obtained based on the specific information of employees, vehicles, and tools. Therefore, before setting the coefficients, it is necessary to construct a specific information table of people-vehicle-tools to record and store the specific information of personnel, vehicles, and tools. Among them, the personnel information includes the name, job number, ID number of the personnel, license situation, professional title situation, location of the personnel (which can be updated in real time according to the reporting situation of the specific personnel terminal, including the location of the personnel at the fault repair site and the final location of the personnel after the fault repair is completed), and working years, etc. The vehicle information includes the vehicle model and the current location of the vehicle, and the current location of the vehicle is updated in real time according to the positioning situation of the in-vehicle navigation system or other positioning devices. The information of the tools includes the tool type, tool number, and the location of the tool, and the location of the tool is replaced by the location of the tool storage where the tool is stored (positioned by the behavior of tool storage and retrieval), etc.

[0100] At the same time, construct a fault-person-vehicle-tool matching table. The fault-person-vehicle-object matching table corresponds to the damage type and the personnel qualifications, vehicle types, and tool lists required under this damage type, as shown in Table 1 below:

[0101] Table 1 Fault-Person-Vehicle-Object Matching Table

[0102]

[0103] Based on the above constructed and stored operation and maintenance information, perform the following steps of calculation:

[0104] In the embodiment of the present application, in A1 of step S500, the matching cost is calculated through the personnel matching situation coefficient, the vehicle matching situation coefficient, and the tool matching situation coefficient. Specifically:

[0105] The personnel matching situation coefficient is a matching coefficient based on qualifications and experience;

[0106] When the vehicle fault type corresponds to the damage type in the fault-weight correspondence table, set the first vehicle matching situation coefficient, otherwise, set it as the second vehicle matching situation coefficient;

[0107] When all the tools corresponding to the damage type in the fault-weight correspondence table for the tool fault type are available, set the first tool matching situation coefficient; if there are missing tools, set the second tool matching situation coefficient based on the number of missing tools;

[0108] Set the corresponding weights of each matching situation coefficient, and sum them to obtain the matching cost;

[0109] Specifically, it can be expressed based on the above description as:

[0110]

[0111] In the formula, is the matching weight coefficient of personnel matching situation, vehicle matching situation and tool matching situation; P 人_匹配 is the personnel matching situation coefficient; P 车_匹配 is the vehicle matching situation coefficient. When the vehicle type corresponds to the damage type in the table, then P 车_匹配 = 1, otherwise P 车_匹配 = 0; P 物_匹配 is the tool matching situation coefficient. When all the tools corresponding to the damage type are prepared, P 物_匹配 = 1, otherwise, it is valued according to the number of missing tool parts x, which is: P 物_匹配 = 1 - x·δ, where δ is the decreasing coefficient, and P 物_匹配 decreases to 0 at least.

[0112] Among them, the above-mentioned personnel matching situation coefficient P 人_匹配 is the matching coefficient based on qualifications and experience. The comprehensive score EE (score range 0 to 1) is set according to the qualifications (such as license status, professional title level) and experience (such as working years, number of troubleshooting) of the personnel; according to the requirements of the fault type, determine the minimum comprehensive score S required to handle this fault 要求 ; calculate P 人_匹配 , if the score S ≥ S 要求 , then P 人_匹配 = 1; if S < S 要求 , then P 人_匹配 = S / S 要求 .

[0113] In an alternative embodiment, the personnel matching situation coefficient can also be based on the matching coefficient of personnel skill scores. Exemplarily, it can be expressed as: set a skill score for each person, and the score range can be 0 to 1. The higher the score, the stronger the ability; according to the requirements of the fault type, determine the minimum skill score required to handle this fault and make a comparison.

[0114] In another alternative embodiment, the personnel matching situation coefficient can also calculate the matching coefficient according to the historical processing records, count the historical success rate R of each person in handling various faults, and set the minimum success rate required to handle this fault for comparison.

[0115] In the embodiment of the present application, obtaining the labor cost in A1 of step S500 includes:

[0116] Construct a personnel information table for storing personnel information, where the personnel information includes name, employee number, ID number, license status, and professional title level;

[0117] The labor costs corresponding to each person are obtained through expert fuzzy evaluation.

[0118] In the embodiment of the present application, obtaining the transportation cost in A1 of step S500 includes:

[0119] Construct a person-vehicle-tool information table based on the personnel information table;

[0120] Among them, the personnel information also includes the real-time location of the personnel, including the location of the personnel at the fault repair site and the final location of the personnel after the fault repair is completed;

[0121] The vehicle information includes the vehicle model and the current location of the vehicle,

[0122] The tool information includes the tool type, tool number, and the location of the tool;

[0123] The transportation cost is the sum of the distances of the personnel, vehicle, and tool from the fault point.

[0124] It should be noted that constructing a person-vehicle-tool information table is used to record and store the specific information of personnel, vehicles, and tools. Among them, the personnel information includes the name of the personnel, job number, ID number, permit situation, professional title situation, and the location of the personnel. The location of the personnel is updated in real time through the reporting situation of the specific personnel terminal, including the location of the personnel at the fault repair site and the final location of the personnel after the fault repair is completed; the vehicle information includes the vehicle model and the current location of the vehicle, and the current location of the vehicle is updated in real time through the positioning situation of the in-vehicle navigation system or other positioning devices; the tool information includes the tool type, tool number, and the location of the tool. The location of the tool can be replaced by the location of the tool storage where the tool is stored, and is located through the actions of tool out-of-storage and in-storage.

[0125] It should be noted that the above transportation cost reflects the distances of the currently selected personnel, vehicle, and tool from the fault point. This value reflects the transportation cost between the personnel, vehicle, and tool and the fault point. That is, personnel, vehicle, and tool closer to the fault point are preferentially selected, and the transportation costs of the personnel, vehicle, and tool themselves are the respective independent lowest transportation costs or the lowest combined transportation costs under optional circumstances.

[0126] In the embodiment of the present application, the scheduling objective function in step S500 also includes constraint conditions, specifically:

[0127] Constraints on the idle situation of personnel, the idle situation of vehicles, and the idle situation of tools;

[0128] Respectively set representative values of idle and non-idle based on their respective idle situations.

[0129] Specifically, it can be expressed as:

[0130] Q 人 ≠0

[0131] Q 车 ≠0

[0132] Q 物 ≠0

[0133] Wherein, Q 人 is the coefficient of personnel idle situation. When the personnel is in the idle state, it is 1; when the personnel is in the non-idle state, it is 0; Q 车 is the coefficient of vehicle idle situation. When the vehicle is in the idle state, it is 1; when the vehicle is in the non-idle state, it is 0; Q 物 is the coefficient of tool idle situation. When the tool is in the idle state, it is 1; when the tool is in the non-idle state, it is 0.

[0134] In the embodiment of the present application, in step S500, the operation and maintenance information at the current moment of the first warning signal is combined to solve the scheduling objective function, which specifically includes the following steps B1 - B5:

[0135] B1: Obtain the human-vehicle-tool matching situation coefficient, the human-vehicle-tool information table, and the idle state;

[0136] B2: Take the partial derivative of each human-vehicle-tool matching situation coefficient variable in the objective function to obtain the gradient;

[0137] B3: Update the variables according to the gradient and the learning rate to ensure that the updated variables meet their respective constraint states;

[0138] B4: If the change in the objective function value is less than the preset threshold or the maximum number of iterations is reached, stop the iteration; otherwise, continue to take the partial derivative of the variables for iteration;

[0139] B5: Output the optimal solution, including the optimal human-vehicle-tool matching situation coefficient, the optimal idle state of the human-vehicle-tool, and the minimum comprehensive cost.

[0140] In an alternative embodiment, the scheduling objective function in step S500 can also be solved by a genetic algorithm or a particle swarm optimization algorithm.

[0141] It should be noted that by solving the objective function, an optimal scheduling scheme for personnel, vehicles, and tools can be generated based on the idle situation of personnel, vehicles, and tools and the specific information of personnel, vehicles, and tools at the current warning moment, which is convenient for managers to refer to when making decisions.

[0142] In summary, through the organic combination of multiple steps such as fault identification, risk quantification, and resource scheduling, this solution realizes the efficient identification, accurate early warning, and optimized scheduling of main and distribution network faults. It can improve the accuracy and real-time performance of fault identification, quantify fault risks, optimize resource scheduling, enhance operation and maintenance efficiency, so as to improve the operation reliability and operation and maintenance management level of the main and distribution networks, and at the same time reduce operation and maintenance costs.

[0143] Embodiment 3. The above is a schematic solution of a risk assessment and scheduling method based on the main and distribution networks. It should be noted that the technical solution of the system for risk assessment and scheduling based on the main and distribution networks belongs to the same concept as the technical solution of the above-mentioned risk assessment and scheduling method based on the main and distribution networks. For the details not described in detail in the technical solution of the system for risk assessment and scheduling based on the main and distribution networks in this embodiment, reference can be made to the description of the technical solution of the above-mentioned risk assessment and scheduling method based on the main and distribution networks.

[0144] This embodiment also provides a system for a risk assessment and scheduling method based on the main and distribution networks, including:

[0145] An identification module, configured to identify main and distribution network faults and send out a first alarm signal based on the identified faults;

[0146] A first construction module, configured to set an observation period, obtain all the fault types of alarm signals within the observation period, and construct a fault-weight correspondence table;

[0147] A calculation module, configured to calculate the comprehensive risk coefficient of all fault types within the observation period based on the fault-weight correspondence table;

[0148] A judgment module, configured to judge the comprehensive risk coefficient and send out a second alarm signal based on the first judgment result;

[0149] A second construction and solution module, configured to construct a scheduling objective function based on the operation and maintenance costs, and solve the scheduling objective function in combination with the operation and maintenance information at the current moment of the second alarm signal.

[0150] This embodiment also provides an electronic device applicable to the situation of risk assessment and scheduling based on the main and distribution networks, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the risk assessment and scheduling method based on the main and distribution networks as proposed in the above embodiment.

[0151] This embodiment also provides a storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the risk assessment and scheduling method based on the main and distribution networks as proposed in the above embodiment.

[0152] The storage medium proposed in this embodiment and the method for realizing risk assessment and scheduling based on the main and distribution networks proposed in the above embodiment belong to the same inventive concept. Technical details not described in detail in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0153] From the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be implemented by means of software and necessary general-purpose hardware, and of course, it can also be implemented by hardware. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as a floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk or optical disc of a computer, etc., including several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0154] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A risk assessment and dispatching method based on the main and distribution networks, characterized in that It includes: Identify the main and distribution network faults and send the first warning signal based on the identified faults; Set an observation period, obtain all the fault types of warning signals within the observation period, and construct a fault-weight correspondence table; Based on the fault-weight correspondence table, calculate the comprehensive risk coefficient of all fault types within the observation period; Judge the comprehensive risk coefficient and send the second warning signal based on the first judgment result; Construct a scheduling objective function based on the operation and maintenance cost, and solve the scheduling objective function in combination with the operation and maintenance information at the current moment of the first warning signal.

2. The risk assessment and dispatching method based on the main and distribution networks according to claim 1, characterized in that Construct a scheduling objective function based on the operation and maintenance cost, including: Obtain the matching cost, labor cost, and transportation cost; Among them, the reciprocal of the matching cost is taken in the scheduling objective function; Set and allocate the weight coefficients of each cost, and sum them up to obtain the scheduling objective function of the comprehensive cost.

3. The risk assessment and scheduling method based on the main and distribution networks according to claim 1 or 2, characterized in that, The matching cost is calculated through the personnel matching situation coefficient, vehicle matching situation coefficient, and tool matching situation coefficient; The personnel matching situation coefficient is a matching coefficient based on qualifications and experience; When the vehicle fault type corresponds to the damaged type in the fault-weight correspondence table, set the first vehicle matching situation coefficient, otherwise, set it to the second vehicle matching situation coefficient; When all the tools corresponding to the damaged type in the fault-weight correspondence table are prepared, set the first tool matching situation coefficient; If there are missing tools, set the second tool matching situation coefficient based on the missing quantity; Set the corresponding weights of each matching situation coefficient and sum them up to obtain the matching cost.

4. The risk assessment and scheduling method based on the main and distribution networks according to claim 3, wherein Obtain the labor cost including: Construct a personnel information table for storing personnel information, where the personnel information includes the person's name, job number, ID number, license status, and professional title level; Obtain the labor cost corresponding to each person through expert fuzzy evaluation.

5. The risk assessment and dispatching method based on the main and distribution networks according to claim 4, characterized in that Obtain the transportation cost including: Construct a person-vehicle-tool information table based on the personnel information table; Among them, the personnel information also includes the real-time location of the personnel, including the location of the personnel at the fault repair site and the final location of the personnel after the fault repair is completed; The vehicle information includes the vehicle model and the current location of the vehicle, The tool information includes the tool type, tool number, and the location of the tool; The transportation cost is the sum of the distances of the personnel, vehicle, and tool from the fault point.

6. The risk assessment and dispatching method based on the main and distribution networks according to claim 5, characterized in that The scheduling objective function also includes constraint conditions, specifically: Personnel idle situation constraint, vehicle idle situation constraint, and tool idle situation constraint; Set the representative values of idle and non-idle based on their respective idle situations.

7. The risk assessment and dispatching method based on the main and distribution networks according to claim 1 or 6, characterized in that Solve the scheduling objective function in combination with the operation and maintenance information at the current moment of the first warning signal, specifically including: Obtain the person-vehicle-tool matching situation coefficient, person-vehicle-tool information table, and idle status; Take the partial derivative of each person-vehicle-tool matching situation coefficient variable in the objective function to obtain the gradient; Update the variable according to the gradient and learning rate to ensure that the updated variable satisfies its respective constraint state; If the change in the objective function value is less than the preset threshold or the maximum number of iterations is reached, stop the iteration, otherwise, continue to take the partial derivative of the variable for iteration; Output the optimal solution, including the optimal human-vehicle-tool matching coefficient, the idle states of the optimal human-vehicle-tool, and the minimum comprehensive cost.

8. A risk assessment and dispatching system based on the main and distribution networks, applied to the method according to any one of claims 1-7, characterized in that, Including: An identification module, configured to identify the main distribution network fault and send out a first warning signal based on the identified fault; A first construction module, configured to set an observation period, obtain all the fault type of warning signals within the observation period, and construct a fault-weight correspondence table; A calculation module, configured to calculate the comprehensive risk coefficient of all the fault types within the observation period based on the fault-weight correspondence table; A judgment module, configured to judge the comprehensive risk coefficient and send out a second warning signal based on the first judgment result; A second construction and solution module, configured to construct a scheduling objective function based on the operation and maintenance cost, and solve the scheduling objective function in combination with the operation and maintenance information at the current moment of the second warning signal.

9. An electronic device, including: A memory and a processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the risk assessment and scheduling method based on the main distribution network according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the risk assessment and scheduling method based on the main distribution network according to any one of claims 1 to 7 are implemented.

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