A power distribution network repair comprehensive evaluation method

Abstract

The application discloses a kind of distribution network repair comprehensive evaluation method, it is related to distribution network repair evaluation technical field.The distribution network repair comprehensive evaluation method includes the following steps: according to distribution network fault data analysis obtains preset distribution network repair scheme;Distribution network aging hidden danger evaluation is carried out;Distribution network structural evaluation is carried out;Distribution network repair transportation evaluation is carried out;preset distribution network repair scheme is judged and adjusted according to distribution network repair analysis result.The application obtains distribution network repair analysis result by successively carrying out distribution network aging hidden danger evaluation, distribution network structural evaluation and distribution network repair transportation evaluation, judges and adjusts preset distribution network repair scheme according to distribution network repair analysis result, reaches the effect of improving the adaptability of distribution network repair transportation to extreme adverse environment, solves the problem of insufficient adaptability of distribution network repair transportation to extreme adverse environment in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power distribution network repair evaluation, and particularly relates to a power distribution network repair comprehensive evaluation method. BACKGROUND

[0002] With the rapid development of economy, the demand for electricity is increasing, and the stability, safety and reliability of power supply are crucial. As an important part of the power system, the operation state of the power distribution network is directly related to the power quality of the general public. However, due to the complex structure of the power distribution network, the changeable operation environment, the aging of equipment and other factors, the power distribution network repair work faces great challenges.

[0003] The existing power distribution network repair comprehensive evaluation method is realized by the following methods, including a repair technology based on fault monitoring, which monitors the operation state of the power distribution network in real time, and starts the repair process as soon as a fault is detected; a repair technology based on artificial intelligence, which analyzes the operation data of the power distribution network using artificial intelligence technology to predict potential fault points and perform maintenance in advance; a repair technology based on GIS, which combines geographic information systems with power distribution network repair to achieve rapid positioning of fault points and rational allocation of repair resources.

[0004] For example, the patent application with publication number CN115455726A discloses a two-stage repair and recovery rolling optimization method for power distribution network under extreme disasters, which includes: first, collecting traffic network and power distribution network information to construct a traffic network-power distribution network coupled network, then constructing a construction team and mobile energy storage dispatching optimization model considering renewable energy output and load demand uncertainty in a long time scale and solving it, then constructing a power supply output and switch action optimization model in a short time scale and solving it, and based on the rolling optimization principle, the repair scheme in the power grid recovery process is rolled and corrected until the power distribution network is restored to normal operation state.

[0005] For example, the patent application with publication number CN113239526A discloses a power distribution network fault risk evaluation method based on a comprehensive probability algorithm, which includes: calculating the power distribution network load point outage probability and estimating the fault outage loss by a power distribution network equipment failure probability calculation method considering weather factors and a power distribution network fault outage probability calculation method based on feeder partitioning, and then evaluating the fault outage risk of the evaluation object and making repair decisions according to the power distribution network load point outage probability and fault outage loss.

[0006] However, in the process of implementing the technical scheme of the present application, the present application has found that the above-mentioned technology at least has the following technical problems:

[0007] In the prior art, power distribution network repair often occurs under extremely severe weather, but power distribution network repair under extremely severe weather has various difficulties, and it is necessary to comprehensively analyze the internal and external environmental factors of the power distribution network under extremely severe weather to obtain a power distribution network repair scheme, and there is a problem of insufficient adaptability of power distribution network repair transportation to extremely severe environment. SUMMARY

[0008] The embodiment of the present application provides a power distribution network repair comprehensive evaluation method, which solves the problem of insufficient adaptability of power distribution network repair transportation to extremely severe environment in the prior art, and achieves the effect of improving the adaptability of power distribution network repair transportation to extremely severe environment.

[0009] The embodiment of the present application provides a power distribution network repair comprehensive evaluation method, which includes the following steps: obtaining a preset power distribution network repair scheme according to power distribution network fault data analysis; performing power distribution network aging hidden danger evaluation to obtain power distribution network aging hidden danger evaluation results; performing power distribution network structural evaluation in combination with power distribution network aging hidden danger evaluation results analysis to obtain power distribution network structural evaluation results; performing power distribution network repair transportation evaluation in combination with power distribution network structural evaluation results analysis to obtain power distribution network repair transportation effectiveness demand level value; obtaining power distribution network repair analysis results according to power distribution network repair transportation effectiveness demand level value analysis and judgment, and adjusting the preset power distribution network repair scheme according to the power distribution network repair analysis results.

[0010] Further, the specific process of obtaining the preset power distribution network repair scheme according to the power distribution network fault data analysis is as follows: collecting power distribution network fault data through a power distribution network fault monitoring device, wherein the power distribution network fault data includes power distribution network fault time data, power distribution network fault location data, power distribution network fault type data and power distribution network fault equipment data; analyzing the power distribution network fault data according to a principal component analysis algorithm to obtain power distribution network fault repair demand resource data and power distribution network fault repair demand priority; matching the power distribution network fault repair demand resource data and the power distribution network fault repair demand priority with a power distribution network preset repair standard scheme library to obtain the preset power distribution network repair scheme; and the power distribution network preset repair standard scheme library includes corresponding power distribution network preset repair standard schemes under different power distribution network fault repair demand priorities and different power distribution network fault repair demand resource data.

[0011] Further, the specific process of obtaining the preset power distribution network repair scheme by matching is as follows: obtaining extreme weather meteorological data, using multi-scenario modeling to predict and analyze power distribution network fault repair demand and power distribution network fault repair resource configuration under the extreme weather meteorological data to obtain a power distribution network fault repair resource configuration additional value, correcting the power distribution network preset repair standard scheme in the power distribution network preset repair standard scheme library according to the power distribution network fault repair resource configuration additional value to obtain the preset power distribution network repair scheme.

[0012] Further, the obtained power distribution network aging hidden danger evaluation result specifically comprises: dividing the power distribution network functional areas according to the power distribution network functional area data, respectively evaluating the power distribution network aging hidden dangers of different power distribution network functional areas to obtain power distribution network aging hidden danger evaluation data of different power distribution network functional areas, training the power distribution network aging hidden danger evaluation data according to a neural network algorithm to obtain a plurality of power distribution network aging hidden danger prediction values, and summing and averaging to obtain a power distribution network aging hidden danger prediction evaluation value; the power distribution network aging hidden danger prediction evaluation value is used to indicate the prediction influence degree of the power distribution network aging hidden danger on power distribution network repair.

[0013] Further, the specific process of obtaining the power distribution network structural evaluation result is: comparing and analyzing the power distribution network aging hidden danger prediction evaluation value and a preset power distribution network aging hidden danger prediction evaluation threshold value to obtain a difference value between the power distribution network aging hidden danger prediction evaluation value and the preset power distribution network aging hidden danger prediction evaluation threshold value, denoted as a power distribution network aging hidden danger prediction difference value; if the power distribution network aging hidden danger prediction difference value is not lower than a preset power distribution network aging hidden danger prediction difference threshold value, the power distribution network aging hidden danger equipment corresponding to the power distribution network aging hidden danger prediction evaluation value is set as a device to be replaced, the power distribution network functional area corresponding to the device to be replaced is recorded as a power distribution network functional area to be replaced, and the number of power distribution network functional areas to be replaced and the number of power distribution network devices to be replaced are obtained; the preset power distribution network aging hidden danger prediction evaluation threshold value is used to describe the demand degree of structural replacement corresponding to the power distribution network aging hidden danger prediction; a repair decision model is analyzed according to the number of power distribution network functional areas to be replaced, the number of power distribution network devices to be replaced, and the power distribution network aging hidden danger prediction difference value to obtain a power distribution network structural replacement demand evaluation value; the power distribution network structural replacement demand evaluation value is used to describe the demand level of the power distribution network needing to be structurally replaced.

[0014] Further, obtaining the power distribution network structural replacement demand evaluation value further comprises: obtaining the number of power distribution network functional areas to be replaced, the number of power distribution network devices to be replaced, and the power distribution network aging hidden danger prediction difference value; collecting power distribution network historical operation data through power distribution network operation monitoring equipment, the power distribution network historical operation data including power distribution network equipment service life data, power distribution network equipment failure rate data, power distribution network maintenance cost data, and power distribution network reliability index data; constructing a repair decision model according to the power distribution network historical operation data, and analyzing the repair decision model according to the number of power distribution network functional areas to be replaced, the number of power distribution network devices to be replaced, and the power distribution network aging hidden danger prediction difference value to obtain the power distribution network structural replacement demand evaluation value.

[0015] Further, the specific process of obtaining the power distribution network repair transportation efficiency demand level value through the combination of the power distribution network structural evaluation result analysis is: obtaining the power distribution network repair demand transportation vehicle data through the matching analysis of the number of power distribution network functional areas to be replaced and the number of power distribution network equipment to be replaced and the vehicle transportation capacity data, wherein the power distribution network repair demand transportation vehicle data includes transportation vehicle load data, vehicle self-weight tonnage data and vehicle average speed data; obtaining extreme severe weather and climate data, wherein the extreme severe weather and climate data includes wind speed and wind power data, rainfall data, snowfall data, fog and haze visibility data and seismic intensity and seismic sensation data; obtaining the power distribution network repair transportation efficiency demand level value through the analysis of the power distribution network repair demand transportation vehicle data and the extreme severe weather and climate data by using the simulated annealing algorithm; and the power distribution network repair transportation efficiency demand level value is used to describe the power distribution network repair demand transportation vehicle repair transportation efficiency level under the extreme severe weather.

[0016] Further, the specific process of obtaining the power distribution network repair transportation efficiency demand level value through the combination of the power distribution network structural evaluation result analysis is: obtaining the power distribution network repair demand transportation vehicle data through the matching analysis of the number of power distribution network functional areas to be replaced and the number of power distribution network equipment to be replaced and the vehicle transportation capacity data, wherein the power distribution network repair demand transportation vehicle data includes transportation vehicle load data, vehicle self-weight tonnage data and vehicle average speed data; obtaining extreme severe weather and climate data, wherein the extreme severe weather and climate data includes wind speed and wind power data, rainfall data, snowfall data, fog and haze visibility data and seismic intensity and seismic sensation data; obtaining the power distribution network repair transportation efficiency demand level value through the analysis of the power distribution network repair demand transportation vehicle data and the extreme severe weather and climate data by using the simulated annealing algorithm; and the power distribution network repair transportation efficiency demand level value is used to describe the power distribution network repair demand transportation vehicle repair transportation efficiency level under the extreme severe weather.

[0017] Further, the specific process of obtaining the power distribution network repair transportation efficiency demand level value through the combination of the power distribution network structural evaluation result analysis is: obtaining the power distribution network repair demand transportation vehicle data through the matching analysis of the number of power distribution network functional areas to be replaced and the number of power distribution network equipment to be replaced and the vehicle transportation capacity data, wherein the power distribution network repair demand transportation vehicle data includes transportation vehicle load data, vehicle self-weight tonnage data and vehicle average speed data; obtaining extreme severe weather and climate data, wherein the extreme severe weather and climate data includes wind speed and wind power data, rainfall data, snowfall data, fog and haze visibility data and seismic intensity and seismic sensation data; obtaining the power distribution network repair transportation efficiency demand level value through the analysis of the power distribution network repair demand transportation vehicle data and the extreme severe weather and climate data by using the simulated annealing algorithm; and the power distribution network repair transportation efficiency demand level value is used to describe the power distribution network repair demand transportation vehicle repair transportation efficiency level under the extreme severe weather.

[0018] Further, the specific constraint formula of the power distribution network repair transportation effectiveness demand level value is: the maximum load data, the maximum tonnage data of the self weight of the transportation vehicle and the average maximum speed data of the transportation vehicle are subjected to data standardization processing to obtain the maximum load standard data, the maximum tonnage standard data of the self weight of the transportation vehicle and the average maximum speed standard data of the transportation vehicle;

[0019] φ=tanh[(Z Z +Z D +Z S +β)*δ]

[0020] In the formula, φ represents the power distribution network repair transportation effectiveness demand level value, δ represents the power distribution network structural replacement demand evaluation value, β represents the power distribution network aging hidden danger prediction evaluation value, Z Z represents the maximum load standard data of the transportation vehicle, Z D represents the maximum tonnage standard data of the self weight of the transportation vehicle, and Z S represents the average maximum speed standard data of the transportation vehicle.

[0021] The one or more technical solutions provided in the embodiments of the application have at least the following technical effects or advantages:

[0022] 1. The power distribution network repair analysis result is obtained by sequentially performing power distribution network aging hidden danger evaluation, power distribution network structural evaluation and power distribution network repair transportation evaluation, so that the preset power distribution network repair scheme is judged and adjusted according to the power distribution network repair analysis result, thereby improving the adaptability of power distribution network repair transportation to extreme harsh environments, and solving the problem of insufficient adaptability of power distribution network repair transportation to extreme harsh environments in the prior art.

[0023] 2. The power distribution network repair transportation effectiveness demand level value is obtained by combining the power distribution network structural evaluation result analysis through power distribution network repair transportation evaluation, so that accurate transportation effectiveness demand evaluation can help repair personnel to reasonably arrange tasks and reduce safety risks caused by weather, thereby realizing the safety of power distribution network repair transportation in extreme harsh environments.

[0024] 3. The preset power distribution network repair scheme is judged and adjusted according to the power distribution network repair analysis result, so that resources are redistributed according to actual transportation demand, so that each repair site can be timely and effectively supported, thereby realizing the efficiency of power distribution network repair transportation in extreme harsh environments. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 A power distribution network repair comprehensive evaluation method flowchart is provided for the embodiments of the application;

[0026] Figure 2 A flowchart for obtaining a power distribution network structural evaluation result is provided for the embodiments of the application;

[0027] Figure 3 A flowchart of determining and adjusting a preset distribution network emergency repair plan based on distribution network emergency repair analysis results is provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The embodiments of the present application solve the problem in the prior art that distribution network emergency repair transportation is insufficiently adaptable to extremely harsh environments by providing a comprehensive evaluation method for distribution network emergency repair. The preset distribution network emergency repair plan is adjusted based on the analysis results of distribution network emergency repair aging, structure and transportation, thereby achieving the effect of improving the adaptability of distribution network emergency repair transportation to extremely harsh environments.

[0029] The technical solution in the embodiment of the present application is to solve the problem that the above-mentioned distribution network emergency repair transportation is not adaptable enough to extremely harsh environments. The overall idea is as follows:

[0030] By sequentially conducting distribution network aging hazard assessment, distribution network structural assessment, and distribution network emergency repair and transportation assessment, we obtained the distribution network emergency repair analysis results. Based on the distribution network emergency repair analysis results, we judged and adjusted the preset distribution network emergency repair plan, thereby achieving the effect of improving the adaptability of distribution network emergency repair and transportation to extremely harsh environments.

[0031] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0032] like Figure 1 As shown, it is a flow chart of the comprehensive evaluation method for distribution network emergency repair provided by an embodiment of the present application, and the method includes the following steps: obtaining a preset distribution network emergency repair plan based on distribution network fault data analysis; performing a distribution network aging hidden danger assessment to obtain a distribution network aging hidden danger assessment result; performing a distribution network structural assessment, and analyzing the distribution network aging hidden danger assessment result in combination with the distribution network aging hidden danger assessment result to obtain a distribution network structural assessment result; performing a distribution network emergency repair transportation assessment, and analyzing the distribution network structural assessment result in combination with the distribution network structural assessment result to obtain a distribution network emergency repair transportation effectiveness demand level value; analyzing and judging the distribution network emergency repair transportation effectiveness demand level value to obtain a distribution network emergency repair analysis result, and judging and adjusting the preset distribution network emergency repair plan based on the distribution network emergency repair analysis result.

[0033] Further, the specific process of obtaining the preset power distribution network repair scheme based on power distribution network fault data analysis is as follows: collecting power distribution network fault data through power distribution network fault monitoring equipment, including power distribution network fault time data, power distribution network fault location data, power distribution network fault type data, and power distribution network fault equipment data; analyzing the power distribution network fault data based on the principal component analysis algorithm to obtain power distribution network fault repair demand resource data and power distribution network fault repair demand priority; matching the power distribution network fault repair demand resource data and the power distribution network fault repair demand priority with the power distribution network preset repair standard scheme library to obtain the preset power distribution network repair scheme; the power distribution network preset repair standard scheme library includes corresponding power distribution network preset repair standard schemes under different power distribution network fault repair demand priorities and different power distribution network fault repair demand resource data.

[0034] In this embodiment, principal component analysis (PCA) or other machine learning algorithms are used to analyze the fault data to extract main features, which helps to identify key factors affecting power distribution network fault repair. Based on the analysis results, the types of resources required for repair (such as personnel, equipment, materials) are determined, and the urgency of the fault, i.e., the repair demand priority, is evaluated. Through association rule mining algorithms, the relationship between fault features and repair resource demand is identified, and a power distribution network preset repair standard scheme library containing different fault types and priorities is established based on historical power distribution network repair data.

[0035] Further, the specific process of obtaining the preset power distribution network repair scheme is as follows: obtaining extreme weather meteorological data, using multi-scenario modeling to predict and analyze the power distribution network fault repair demand and power distribution network fault repair resource configuration under extreme weather meteorological data, obtaining the power distribution network fault repair resource configuration additional value, and modifying the power distribution network preset repair standard scheme in the power distribution network preset repair standard scheme library based on the power distribution network fault repair resource configuration additional value to obtain the preset power distribution network repair scheme.

[0036] In this embodiment, multi-scenario modeling is used to predict and analyze the power distribution network fault repair demand and power distribution network fault repair resource configuration under extreme weather meteorological data: based on the multi-scenario model, the repair demand under each scenario is predicted, including the demand for repair personnel, equipment, and materials, and resource configuration optimization: combining the predicted repair demand and existing repair resources, the optimization configuration is performed to determine the resource configuration additional value that needs to be increased or adjusted.

[0037] The power distribution network pre-set repair standard scheme is modified: according to the resource configuration additional value, the standard scheme in the power distribution network pre-set repair standard scheme library is modified, including: personnel arrangement: increasing personnel configuration according to the demand, or adjusting the working shift of personnel; equipment deployment: increasing the standby quantity of key equipment, or optimizing the performance of key equipment to quickly respond to faults; material preparation: preparing enough repair materials in advance, such as cables, joints, insulators, etc.

[0038] Further, the power distribution network aging hidden danger evaluation result is obtained, specifically including: dividing the power distribution network function area according to the power distribution network function area data, respectively evaluating the power distribution network aging hidden danger of different power distribution network function areas, obtaining the power distribution network aging hidden danger evaluation data of different power distribution network function areas, training the power distribution network aging hidden danger evaluation data according to the neural network algorithm to obtain a plurality of power distribution network aging hidden danger prediction values, and summing and averaging to obtain a power distribution network aging hidden danger prediction evaluation value; the power distribution network aging hidden danger prediction evaluation value is used to indicate the prediction influence degree of the power distribution network aging hidden danger on the power distribution network repair.

[0039] In the embodiment, in addition to being obtained by periodically or non-periodically detecting the power distribution network equipment, such as insulation test, ground resistance test, etc., to quantitatively analyze the aging state of the equipment, the power distribution network aging hidden danger prediction evaluation value can also be obtained by a calculation formula, and the specific calculation formula is as follows:

[0040]

[0041] In the formula, β represents the power distribution network aging hidden danger prediction evaluation value, the power distribution network function area aging monitoring points are numbered in sequence, L0=1, 2,..., L, L0represents the number of the power distribution network function area aging monitoring points, and L represents the total number of the power distribution network function area aging monitoring points, represents the power distribution network equipment operation time of the L0th power distribution network function area aging monitoring point, represents the power distribution network equipment pre-set scrap time of the L0th power distribution network function area aging monitoring point, represents the power distribution network equipment average failure rate of the L0th power distribution network function area aging monitoring point, and α represents the environmental influence aging correction factor.

[0042] The power distribution network equipment operation time is obtained through real-time monitoring data of power distribution network operation and maintenance management, or is obtained through artificial inspection records.

[0043] The power distribution network equipment pre-set scrap time is obtained through the use life and maintenance condition given by the equipment manufacturer or through the predictive maintenance software in the power distribution network operation and maintenance management.

[0044] The average failure rate of the power distribution network equipment is obtained by statistical analysis of the failure data of the equipment or by failure monitoring in the operation and management of the power distribution network.

[0045] The environmental impact aging correction factor is obtained by analyzing the impact of extreme weather environmental factors, such as temperature, humidity, pollution, etc., on the aging of the equipment through a fault tree analysis algorithm or by professional software, and the value is not less than 0 and not greater than 1.

[0046] The comprehensive analysis of the factor data of the above power distribution network aging hidden danger prediction factors at different power distribution network functional area aging monitoring points makes the evaluation of the power distribution network aging hidden danger prediction evaluation value more accurate and makes the function image of the power distribution network aging hidden danger prediction evaluation value monotonically increasing, so that there is data basis for subsequent power distribution network structural evaluation processing, and the scientificity of the power distribution network repair comprehensive evaluation method is improved.

[0047] Further, the specific process of obtaining the power distribution network structural evaluation result is: comparing the power distribution network aging hidden danger prediction evaluation value with the preset power distribution network aging hidden danger prediction evaluation threshold, obtaining the difference between the power distribution network aging hidden danger prediction evaluation value and the preset power distribution network aging hidden danger prediction evaluation threshold, denoted as the power distribution network aging hidden danger prediction difference; if the power distribution network aging hidden danger prediction difference is not less than the preset power distribution network aging hidden danger prediction difference threshold, the power distribution network aging hidden danger equipment corresponding to the power distribution network aging hidden danger prediction evaluation value is set as the equipment to be replaced, the power distribution network functional area corresponding to the equipment to be replaced is recorded as the power distribution network replacement functional area, and the number of power distribution network replacement functional areas and the number of power distribution network replacement equipment are obtained; the preset power distribution network aging hidden danger prediction evaluation threshold is used to describe the demand degree of the structural replacement corresponding to the power distribution network aging hidden danger prediction; the power distribution network structural replacement demand evaluation value is obtained by analyzing the maintenance decision model according to the number of power distribution network replacement functional areas, the number of power distribution network replacement equipment and the power distribution network aging hidden danger prediction difference; the power distribution network structural replacement demand evaluation value is used to describe the demand level of the power distribution network needing to be structurally replaced.

[0048] In this embodiment, as shown in Figure 2 The flowchart for obtaining the power distribution network structural evaluation result provided by the embodiment of the application is shown in the figure. The power distribution network repair comprehensive evaluation system provided by the embodiment of the application, and the preset power distribution network aging hidden danger prediction difference threshold can be obtained by the following methods, including using methods, quantitatively evaluating the potential risks of equipment aging, and through laboratory simulation and field test, studying the impact of different aging degrees on the performance of the power distribution network equipment.

[0049] Reliability Centered Maintenance (RCM) is the most representative model of the third generation of maintenance management. This equipment management model emphasizes the reliability of the equipment and the consequences of equipment failure as the main basis for developing maintenance strategies. The structural replacement demand evaluation value of the power distribution network is obtained by analyzing the maintenance decision model based on historical power distribution network failure maintenance data, combined with the number of power distribution network functional areas that need to be replaced, the number of power distribution network equipment that needs to be replaced, and the difference between the power distribution network aging hidden danger prediction. The structural replacement demand evaluation value of the power distribution network can also be obtained by a calculation formula, as follows:

[0050]

[0051] In the formula, δ represents the structural replacement demand evaluation value of the power distribution network, the power distribution network functional area structural replacement monitoring points are numbered in turn, H0=1,2,...,H, H0represents the number of power distribution network functional area structural replacement monitoring points, H represents the total number of power distribution network functional area structural replacement monitoring points, represents the number of power distribution network functional communication equipment that needs to be replaced at the H0th power distribution network functional area structural replacement monitoring point, represents the number of power distribution network functional power distribution equipment that needs to be replaced at the H0th power distribution network functional area structural replacement monitoring point, L represents the difference between the power distribution network aging hidden danger prediction, C Y represents the preset power distribution network aging hidden danger prediction difference threshold.

[0052] The power distribution network functional communication equipment includes communication equipment in optical fiber and power carrier communication mode, as well as devices supporting serial communication and Ethernet communication. The data of them is counted to obtain the number of power distribution network functional communication equipment that needs to be replaced.

[0053] The power distribution network functional power distribution equipment includes overhead lines, cables, towers, distribution transformers, switch devices, and reactive compensation capacitors. The data of them is counted to obtain the number of power distribution network functional communication equipment that needs to be replaced.

[0054] The analysis of the above factors of the power distribution network structural replacement demand at different power distribution network functional area structural replacement monitoring points makes the evaluation of the power distribution network aging hidden danger prediction evaluation value more accurate and the function image of the power distribution network aging hidden danger prediction evaluation value rapidly and monotonically increasing. If the number of power distribution network functional communication equipment that needs to be replaced, the number of power distribution network functional power distribution equipment that needs to be replaced, and the difference between the power distribution network aging hidden danger prediction are larger, the power distribution network structural replacement demand evaluation value increases rapidly, making the function image change dramatically, which is convenient for observing the change of the power distribution network structural replacement demand evaluation value.

[0055] When the number of functional communication devices that need to be replaced in the power distribution network and the number of functional power distribution devices that need to be replaced in the power distribution network are 0, the power distribution network aging hidden danger prediction is expected to be the lowest, and the power distribution network structural replacement demand evaluation value is 1. The more the power distribution network functional area structural replacement monitoring points are set, the smaller the monitoring range of each power distribution network functional area structural replacement monitoring point is. Table 1 is an example table of the power distribution network structural replacement demand evaluation value, and Table 1 is as follows:

[0056] Table 1 is an example table of the power distribution network structural replacement demand evaluation value

[0057]

[0058]

[0059] Further, obtaining the power distribution network structural replacement demand evaluation value also includes: obtaining the number of functional areas that need to be replaced in the power distribution network, the number of devices that need to be replaced in the power distribution network, and the power distribution network aging hidden danger prediction difference; collecting historical operation data of the power distribution network through the power distribution network operation monitoring device, the historical operation data of the power distribution network including power distribution network device service life data, power distribution network device failure rate data, power distribution network maintenance cost data, and power distribution network reliability index data; constructing a maintenance decision model according to the historical operation data of the power distribution network, and analyzing the number of functional areas that need to be replaced in the power distribution network, the number of devices that need to be replaced in the power distribution network, and the power distribution network aging hidden danger prediction difference through the maintenance decision model to obtain the power distribution network structural replacement demand evaluation value.

[0060] In this embodiment, the power distribution network structural replacement demand includes both the devices that need to be structurally replaced due to failure and damage and the devices that need to be replaced due to aging. According to the maintenance decision model, the number of functional areas that need to be replaced in the power distribution network, the number of devices that need to be replaced in the power distribution network, and the power distribution network aging hidden danger prediction difference can be analyzed to comprehensively consider various power distribution network structural replacement demands, so that the power distribution network structural evaluation is more comprehensive.

[0061] Further, the specific process of obtaining the power distribution network repair transportation efficiency demand level value based on the power distribution network structural evaluation result analysis is as follows: matching and analyzing the number of functional areas that need to be replaced in the power distribution network and the number of devices that need to be replaced in the power distribution network with the carrier transportation capacity data to obtain power distribution network repair demand transportation carrier data, the power distribution network repair demand transportation carrier data including transportation carrier load data, carrier self-weight tonnage data, and carrier average speed data; obtaining extreme adverse weather and climate data, including wind speed and wind force data, rainfall data, snowfall data, fog and haze visibility data, and earthquake magnitude and seismic intensity data; analyzing the power distribution network repair demand transportation carrier data and the extreme adverse weather and climate data through the simulated annealing algorithm to obtain the power distribution network repair transportation efficiency demand level value; and the power distribution network repair transportation efficiency demand level value is used to describe the power distribution network repair demand transportation carrier in extreme adverse weather.

[0062] In this embodiment, the distribution network emergency repair demand transportation vehicle data is obtained by matching and analyzing the number of functional areas and equipment that need to be replaced in the distribution network with the vehicle transportation capacity data. For example, if the number of functional areas and equipment that need to be replaced in the distribution network is 1 and 1 large truck is needed for transportation, then the distribution network emergency repair transportation data is 1 large truck.

[0063] Furthermore, the specific process of analyzing the distribution network emergency repair demand transportation vehicle data and extreme weather and climate data through the simulated annealing algorithm is as follows: setting the target vehicle transportation safety function and the target vehicle transportation speed function according to the distribution network emergency repair demand transportation vehicle data and the extreme weather and climate data; the target vehicle transportation safety function is used to indicate that the function target is set with vehicle transportation safety as the priority target; the target vehicle transportation speed function is used to indicate that the function target is set with vehicle transportation speed as the priority target; through the simulated annealing algorithm, the distribution network emergency repair demand transportation vehicle data and the extreme weather and climate data are iteratively trained and analyzed multiple times according to the target vehicle transportation safety function and the target vehicle transportation speed function, and the maximum load data of the transportation vehicle, the maximum tonnage data of the vehicle's own weight and the average maximum speed data of the vehicle are output; the distribution network emergency repair transportation effectiveness demand level value is obtained based on the analysis of the maximum load data of the transportation vehicle, the maximum tonnage data of the vehicle's own weight and the average maximum speed data of the vehicle.

[0064] In this embodiment, the target vehicle transportation safety function and the target vehicle transportation speed function are both set to include the vehicle's load capacity factor, deadweight factor, speed factor, and the impact of extreme weather factors such as wind speed, rainfall, snowfall, haze, and earthquake magnitude on transportation efficiency.

[0065] The simulated annealing algorithm also includes the following supplementary steps: initializing simulated annealing parameters, setting the initial temperature and cooling rate, and randomly selecting an initial solution from the target vehicle transportation safety function and the target vehicle transportation speed function as the starting point of the simulated annealing algorithm; for each iteration, generating a new candidate solution based on the current solution, and the methods for generating new solutions include randomly exchanging vehicle tasks and adjusting vehicle driving routes; evaluating the objective function value of the new solution, and accepting the new solution as the current solution if the new solution is better or if the new solution is accepted with a certain probability (using the Metropol is criterion); after each certain number of iterations, reducing the temperature, for example, by multiplying it by the cooling rate, and terminating the algorithm when the temperature drops to a certain threshold or reaches the upper limit of the number of iterations.

[0066] Further, the specific process of adjusting the preset power distribution network repair scheme according to the analysis result of the power distribution network repair is: comparing the power distribution network repair transportation effectiveness demand level value with the preset power distribution network repair transportation effectiveness threshold value; if the power distribution network repair transportation effectiveness demand level value is not higher than the preset power distribution network repair transportation effectiveness threshold value, the preset power distribution network repair scheme is not adjusted; if the power distribution network repair transportation effectiveness demand level value is higher than the preset power distribution network repair transportation effectiveness threshold value, the preset power distribution network repair scheme adjusts the corresponding power distribution network repair demand transportation vehicle factor according to the maximum load data of the transportation vehicle, the maximum tonnage data of the self-weight of the vehicle and the average maximum speed data of the vehicle.

[0067] In the embodiment, as shown in Figure 3 the flowchart of adjusting the preset power distribution network repair scheme according to the analysis result of the power distribution network repair provided by the embodiment of the application, the method for obtaining the preset power distribution network repair transportation effectiveness threshold value includes using the operations research method, such as linear programming and network flow optimization, combining with the actual situation of the repair, calculating or obtaining through analyzing the actual data of the power distribution network repair in the historical time, such as the success rate, the required time and the resource consumption of the repair task.

[0068] The supplementary steps of adjusting the corresponding power distribution network repair demand transportation vehicle factor include evaluating the repair demand, determining the list of equipment and materials that need to be transported and the total weight and volume required, analyzing the performance of the vehicle, determining which vehicles can meet the repair demand according to the maximum load, the maximum tonnage of the self-weight and the average maximum speed of the transportation vehicle, optimizing the dispatch of the transportation vehicle to ensure that the required equipment and materials can be transported to the repair site in the shortest time, considering the road conditions and the weather, adjusting the transportation plan according to the road conditions and the weather to ensure the safety and timeliness of the transportation, dynamically adjusting the dispatch of the transportation vehicle during the repair process to adapt to the possible changes in demand, for example, in an earthquake, there are quite a few associated disasters, which may cause very poor road conditions and make it difficult for trucks to pass, so ships can be used for water transportation or large unmanned aerial vehicles can be used for air transportation according to the specific situation.

[0069] Further, the specific constraint formula of the power distribution network repair transportation effectiveness demand level value is: performing data standardization processing on the maximum load data of the transportation vehicle, the maximum tonnage data of the self-weight of the vehicle and the average maximum speed data of the vehicle to obtain the maximum load standard data of the transportation vehicle, the maximum tonnage standard data of the self-weight of the vehicle and the average maximum speed standard data of the vehicle;

[0070] φ=tanh[(Z Z +Z D +Z S +β)*δ]

[0071] In the formula, φ represents the power distribution network repair transportation effectiveness demand level value, δ represents the power distribution network structural replacement demand evaluation value, β represents the power distribution network aging hidden danger prediction evaluation value, ZZ represents the maximum load standard data of the transport vehicle, Z D represents the maximum deadweight standard data of the vehicle, Z S represents the average maximum speed standard data of the vehicle.

[0072] In the embodiment, the comprehensive factors of the power distribution network repair transportation efficiency demand are analyzed by the function, so that the power distribution network repair transportation efficiency demand level value is concentrated between 0 and 1, so that the evaluation effect of the power distribution network repair transportation efficiency demand can be analyzed.

[0073] The technical solutions in the embodiments of the present application have at least the following technical effects or advantages: compared with the patent application with the publication number CN115455726A, which discloses a two-stage repair and recovery rolling optimization method for power distribution networks in extreme disasters, the embodiments of the present application obtain the power distribution network repair transportation efficiency demand level value by combining the power distribution network structural evaluation result analysis with the power distribution network repair transportation evaluation, so that accurate evaluation of transportation efficiency demand can help repair personnel to reasonably arrange tasks, reduce safety risks caused by weather, and thus realize the safety of power distribution network repair transportation in extreme harsh environments; compared with the patent application with the publication number CN113239526A, which discloses a power distribution network fault risk assessment method based on a comprehensive probability algorithm, the embodiments of the present application adjust the preset power distribution network repair scheme by analyzing the power distribution network repair analysis result, so that resources are redistributed according to actual transportation needs, so that each repair site can be timely and effectively supported, and thus the power distribution network repair transportation efficiency in extreme harsh environments is realized.

[0074] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0075] The present application is described with reference to flowcharts and / or block diagrams according to the method, device (system), and computer program product of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices produce a machine that implements the flowcharts and / or block diagrams. Figure 1one or more processes and / or blocks Figure 1 an apparatus for performing the functions specified in the flowchart

[0076] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the flowchart Figure 1 one or more processes and / or blocks Figure 1 an apparatus for performing the functions specified in the flowchart

[0077] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flowchart Figure 1 one or more processes and / or blocks Figure 1 an apparatus for performing the functions specified in the flowchart

[0078] While the preferred embodiments of the application have been described, additional variations and modifications can be made to the embodiments by those skilled in the art once they learn of the basic inventive concepts. Therefore, the appended claims are intended to encompass within their scope all possible variations and modifications of the preferred embodiments.

[0079] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A comprehensive evaluation method for distribution network emergency repair, characterized in that: The following steps are involved: A preset distribution network emergency repair plan is obtained based on the analysis of distribution network fault data, that is, distribution network fault emergency repair demand resource data and distribution network fault emergency repair demand priority are obtained based on the analysis of the distribution network fault data, and these data are matched to obtain the preset distribution network emergency repair plan; the specific process of obtaining the preset distribution network emergency repair plan by matching is as follows: extreme weather meteorological data are obtained, and multi-scenario modeling is used to predict and analyze the distribution network fault emergency repair demand and distribution network fault emergency repair resource configuration under extreme weather meteorological data to obtain the distribution network fault emergency repair resource configuration additional value, and the distribution network preset emergency repair standard plan in the distribution network preset emergency repair standard plan library is modified according to the distribution network fault emergency repair resource configuration additional value to obtain the preset distribution network emergency repair plan; Performing a distribution network aging hidden danger assessment to obtain a distribution network aging hidden danger assessment result, wherein the distribution network aging hidden danger assessment result indicates a predicted impact of the distribution network aging hidden danger on the distribution network emergency repair; Conduct a structural assessment of the distribution network, and combine this with an analysis of the distribution network aging hidden danger assessment results to obtain a distribution network structural assessment result. Specifically, the distribution network aging hidden danger assessment results are used to screen out functional areas of the distribution network that require replacement, and the number of functional areas and equipment that require replacement are obtained. Combined with a difference analysis of the distribution network aging hidden danger predictions, a distribution network structural assessment result is obtained. The distribution network structural assessment result is used to describe the level of demand for structural replacement of the distribution network. Conduct a distribution network emergency repair and transportation assessment, and combine the results of the distribution network structural assessment to determine a distribution network emergency repair and transportation efficiency demand level value. The distribution network emergency repair and transportation efficiency demand level value is used to describe the emergency repair and transportation efficiency level of distribution network emergency repair demand transportation vehicles in extremely severe weather conditions. According to the analysis and judgment of the distribution network emergency repair transportation efficiency demand level value, the distribution network emergency repair analysis result is obtained, and the preset distribution network emergency repair plan is adjusted according to the distribution network emergency repair analysis result.

2. The comprehensive evaluation method for emergency repair of a distribution network according to claim 1, characterized in that: The specific process of obtaining a preset distribution network repair plan based on distribution network fault data analysis is as follows: Collecting distribution network fault data through distribution network fault monitoring equipment, wherein the distribution network fault data includes distribution network fault time data, distribution network fault location data, distribution network fault type data and distribution network fault device data; The distribution network fault data is analyzed according to the principal component analysis algorithm to obtain the distribution network fault repair demand resource data and distribution network fault repair demand priority; According to the distribution network fault repair demand resource data and the distribution network fault repair demand priority, the distribution network preset repair standard solution library is matched to obtain the preset distribution network repair solution; The distribution network preset emergency repair standard solution library includes distribution network preset emergency repair standard solutions corresponding to different distribution network fault emergency repair demand priorities and different distribution network fault emergency repair demand resource data.

3. The comprehensive evaluation method for emergency repair of a distribution network according to claim 1, characterized in that: The distribution network aging hidden danger assessment results obtained specifically include: The distribution network functional areas are divided according to the distribution network functional area data, and the distribution network aging hidden danger assessment is performed on different distribution network functional areas respectively to obtain the distribution network aging hidden danger assessment data of different distribution network functional areas. The distribution network aging hidden danger assessment data is trained according to the neural network algorithm to obtain a number of distribution network aging hidden danger prediction values, and the sum and average are used to obtain the distribution network aging hidden danger prediction assessment value; The distribution network aging hidden danger prediction assessment value is used to refer to the predicted impact of the distribution network aging hidden danger on the distribution network emergency repair.

4. The comprehensive evaluation method for emergency repair of a distribution network according to claim 1, characterized in that: The specific process of obtaining the distribution network structural assessment result is as follows: Comparing and analyzing the distribution network aging hidden danger prediction assessment value with the preset distribution network aging hidden danger prediction assessment threshold, the difference between the distribution network aging hidden danger prediction assessment value and the preset distribution network aging hidden danger prediction assessment threshold is obtained, which is recorded as the distribution network aging hidden danger prediction difference; If the distribution network aging hidden danger prediction difference is not lower than the preset distribution network aging hidden danger prediction difference threshold, the distribution network aging hidden danger device corresponding to the distribution network aging hidden danger prediction assessment value is set as the device that needs to be replaced, and the distribution network functional area corresponding to the device that needs to be replaced is recorded as the distribution network functional area that needs to be replaced, and the number of distribution network functional areas that need to be replaced and the number of distribution network devices that need to be replaced are obtained; The preset distribution network aging hidden danger prediction assessment threshold is used to describe the degree of demand for structural replacement corresponding to the distribution network aging hidden danger prediction; The structural replacement demand assessment value of the distribution network is obtained through maintenance decision model analysis based on the number of functional areas that need to be replaced in the distribution network, the number of equipment that needs to be replaced in the distribution network, and the predicted difference in the hidden dangers of distribution network aging. The distribution network structural replacement demand assessment value is used to describe the demand level for structural replacement of the distribution network.

5. The comprehensive evaluation method for emergency repair of a distribution network according to claim 4, characterized in that: The obtaining of the distribution network structural replacement demand assessment value further includes: Obtain the number of functional areas that need to be replaced in the distribution network, the number of equipment that needs to be replaced in the distribution network, and the predicted difference in the hidden dangers of aging of the distribution network; Collect historical distribution network operation data through distribution network operation monitoring equipment, including distribution network equipment service life data, distribution network equipment failure rate data, distribution network maintenance cost data, and distribution network reliability index data; A maintenance decision model is constructed based on the historical operation data of the distribution network. The structural replacement demand assessment value of the distribution network is obtained through analysis of the maintenance decision model based on the difference in the number of functional areas that need to be replaced in the distribution network, the number of equipment that need to be replaced in the distribution network, and the predicted difference in the aging hidden dangers of the distribution network.

6. The comprehensive evaluation method for emergency repair of a distribution network according to claim 1, characterized in that: The specific process of analyzing the distribution network structural assessment results to obtain the distribution network emergency repair transportation efficiency demand level value is as follows: According to the matching analysis of the number of functional areas and equipment that need to be replaced in the distribution network and the vehicle transportation capacity data, the distribution network emergency repair demand transportation vehicle data is obtained, and the distribution network emergency repair demand transportation vehicle data includes the transportation vehicle load data, the vehicle deadweight tonnage data and the vehicle average speed data; Acquiring extreme weather and climate data, including wind speed and force data, rainfall data, snowfall data, fog and haze visibility data, and earthquake magnitude and sensation data; The distribution network emergency repair demand transportation vehicle data and extreme weather climate data are analyzed through the simulated annealing algorithm to obtain the distribution network emergency repair transportation efficiency demand level value.

7. The comprehensive evaluation method for emergency repair of a distribution network according to claim 6, characterized in that: The specific process of analyzing the distribution network emergency repair demand transportation vehicle data and extreme weather climate data through the simulated annealing algorithm is as follows: According to the transportation vehicle data required for power distribution network emergency repairs and extreme weather data, the target vehicle transportation safety function and target vehicle transportation speed function are set; The target vehicle transportation safety function is used to indicate that the function target is set with vehicle transportation safety as the priority target; The target vehicle transport speed function is used to indicate that the function target is set with the vehicle transport speed as the priority target; Through the simulated annealing algorithm, the target vehicle transportation safety function and the target vehicle transportation speed function are used to iterate the training and analysis of the distribution network emergency repair demand transportation vehicle data and the extreme weather climate data, and the maximum load data of the transportation vehicle, the maximum tonnage data of the vehicle and the average maximum speed data of the vehicle are output; The demand level of distribution network emergency transport efficiency is obtained based on the analysis of the maximum load data of the transport vehicle, the maximum tonnage data of the vehicle's own weight and the average maximum speed data of the vehicle.

8. The comprehensive evaluation method for emergency repair of a distribution network according to claim 1, characterized in that: The specific process of judging and adjusting the preset distribution network emergency repair plan based on the distribution network emergency repair analysis results is as follows: Compare and analyze the distribution network emergency repair and transportation efficiency demand level value with the preset distribution network emergency repair and transportation efficiency threshold value; If the distribution network emergency repair transport efficiency demand level value is not higher than the preset distribution network emergency repair transport efficiency threshold value, the preset distribution network emergency repair plan will not be adjusted; If the distribution network emergency repair transport efficiency demand level value is higher than the preset distribution network emergency repair transport efficiency threshold, the preset distribution network emergency repair plan adjusts the corresponding distribution network emergency repair demand transport vehicle factor according to the maximum load data of the transport vehicle, the maximum tonnage data of the vehicle's own weight, and the average maximum speed data of the vehicle.

9. The comprehensive evaluation method for emergency repair of a distribution network according to claim 8, characterized in that: The specific constraint formula for the distribution network emergency repair transportation efficiency demand level value is: Performing data standardization on the maximum load data of the transport vehicle, the maximum tonnage data of the vehicle's own weight, and the average maximum speed data of the vehicle to obtain the standard data of the maximum load data of the transport vehicle, the standard data of the maximum tonnage data of the vehicle's own weight, and the standard data of the average maximum speed of the vehicle; φ=tanh[(Z Z +Z D +Z S +β)*δ] In the formula, φ represents the demand level of distribution network emergency repair and transportation effectiveness, δ represents the distribution network structural replacement demand assessment value, β represents the distribution network aging hidden danger prediction assessment value, and Z Z Indicates the maximum load standard data of the transport vehicle, Z D Indicates the standard data of the maximum tonnage of the vehicle, Z S Indicates the vehicle's average maximum speed standard data.

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