A lightning protection strategy determination method, device, equipment and storage medium

Abstract

The application discloses a lightning protection strategy determination method and device, equipment and a storage medium. The method comprises the following steps: acquiring index data of lightning protection measures under a preset index factor; determining a target measure level of the lightning protection measures according to the index data, evaluation values of at least two first-type index levels corresponding to the preset index factor, and evaluation values of at least two second-type index levels corresponding to the preset index factor; and determining an execution strategy of the lightning protection measures according to the target measure level of the lightning protection measures. According to the scheme provided by the application, the index data of the lightning protection measures can be evaluated to determine the target measure level of the lightning protection measures and the execution strategy, so that an effective lightning protection measure execution strategy can be determined, and the loss caused by lightning hazards can be reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power distribution network, and particularly relates to a lightning protection strategy determination method and device, equipment and a storage medium. BACKGROUND

[0002] With the continuous development of the national economy, the requirement for power stability is higher and higher, and solving the lightning damage problem of distribution line is of great significance for the stable operation of power grid.

[0003] For the distribution line, there are many lightning protection measures, but the lightning protection effect, reconstruction fund, maintenance difficulty and modification of different lightning protection measures are different, how to determine the optimal lightning protection strategy to help the power department to determine the reasonable lightning protection means is a problem to be solved at present. SUMMARY

[0004] The present application provides a lightning protection strategy determination method, device, equipment and storage medium, which can determine the effective lightning protection measure execution strategy and reduce the loss caused by lightning damage.

[0005] According to one aspect of the present application, a lightning protection strategy determination method is provided, comprising:

[0006] Obtaining index data of lightning protection measures under a preset index factor;

[0007] According to the index data, the evaluation value of at least two first type index levels corresponding to the preset index factor, and the evaluation value of at least two second type index levels corresponding to the preset index factor, determining the target measure level of the lightning protection measures;

[0008] According to the target measure level of the lightning protection measures, determining the execution strategy of the lightning protection measures.

[0009] According to another aspect of the present application, a lightning protection strategy determination device is provided, comprising:

[0010] The acquisition module is used for obtaining index data of lightning protection measures under a preset index factor;

[0011] The level determination module is used for determining the target measure level of the lightning protection measures according to the index data, the evaluation value of at least two first type index levels corresponding to the preset index factor, and the evaluation value of at least two second type index levels corresponding to the preset index factor;

[0012] The strategy determination module is used for determining the execution strategy of the lightning protection measures according to the target measure level of the lightning protection measures.

[0013] According to another aspect of the present application, an electronic device is provided, comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected with the at least one processor; wherein

[0016] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the lightning protection strategy determination method according to any one of the embodiments of the present application.

[0017] According to another aspect of the present application, a computer readable storage medium is provided, which stores computer instructions for enabling a processor to implement the lightning protection strategy determination method according to any one of the embodiments of the present application when executed by the processor.

[0018] The technical solution of the embodiments of the present application acquires the index data of the lightning protection measure under the preset index factor, determines the target measure level of the lightning protection measure according to the index data, the evaluation values of the at least two first-type index levels corresponding to the preset index factor, and the evaluation values of the at least two second-type index levels corresponding to the preset index factor, and finally determines the execution strategy of the lightning protection measure according to the target measure level of the lightning protection measure. By evaluating the index data of the lightning protection measure according to the index data, the target measure level of the lightning protection measure is determined to determine the execution strategy, and the effective lightning protection measure execution strategy can be determined to minimize the loss caused by the lightning disaster problem.

[0019] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0021] Figure 1 is a flowchart of a lightning protection strategy determination method provided by the first embodiment of the present application;

[0022] Figure 2 is a flowchart of a lightning protection strategy determination method provided by the second embodiment of the present application;

[0023] Figure 3 is a flowchart of a lightning protection strategy determination method provided by the third embodiment of the present application;

[0024] Figure 4 is a flow chart of a lightning protection strategy determination method provided by the fourth embodiment of the present application;

[0025] Figure 5 is a flow chart of a lightning protection strategy determination method provided by the fifth embodiment of the present application;

[0026] Figure 6 is a structural diagram of a lightning protection strategy determination device provided by the sixth embodiment of the present application;

[0027] Figure 7 is a structural diagram of an electronic device provided by the seventh embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to make the personnel in the technical field better understand the present application scheme, the technical scheme in the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor should belong to the protection scope of the present application.

[0029] It should be noted that the terms "first", "second", "target", "candidate" and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0030] Embodiment One

[0031] Figure 1 is a flow chart of a lightning protection strategy determination method provided by the first embodiment of the present application. The present embodiment is applicable to the case of determining a lightning protection strategy, especially applicable to the case of how to determine an optimal lightning protection strategy based on the grades of various lightning protection measures for a power distribution line. The method can be executed by a lightning protection strategy determination device, which can be realized in the form of software and / or hardware and can be integrated into an electronic device having a lightning protection strategy determination function. As shown in the figure, the method comprises the following steps. Figure 1

[0032] ​S101, acquire index data of the lightning protection measure under a preset index factor.

[0033] The lightning protection measure refers to a measure commonly used in a power distribution line to prevent the line from being struck by lightning disaster. The lightning protection measure can include at least one of erecting a lightning arrester, installing a lightning rod, strengthening line insulation, erecting a coupling ground wire, and reducing a grounding resistance value.

[0034] The index factor refers to an index that can comprehensively evaluate the effect of the lightning protection measure. Specifically, the index factor can include at least one of a lightning trip-out rate reduction degree, a lightning protection cost, a reconstruction difficulty degree, a maintenance difficulty degree, and a service life. The index factor can also include an index that evaluates the effect of the lightning protection measure from other aspects, such as a line environment influence and a tower structure influence. The lightning trip-out rate reduction degree refers to the effect of the lightning protection measure on reducing the lightning trip-out rate of the power distribution line. The lightning protection cost refers to the engineering cost consumed when the corresponding lightning protection measure is adopted.

[0035] Optionally, the trip-out rates of the power distribution line when the lightning protection measure is adopted and when the lightning protection measure is not adopted can be acquired respectively. The lightning trip-out rate reduction degree can be represented according to the proportional relationship between the two. The lightning protection cost of the lightning protection measure can be represented by the proportional relationship between the engineering cost consumed and the total project cost. The reconstruction difficulty degree of each lightning protection measure can be represented by the number of personnel required when the corresponding lightning protection measure is adopted to reconstruct the power distribution line. The maintenance difficulty degree of each lightning protection measure can be represented by the period required to maintain the related equipment after the corresponding lightning protection measure is adopted. The service life can be represented by the serviceable years (e.g., 9 years) of the related equipment after the corresponding lightning protection measure is adopted.

[0036] Optionally, the index data of the lightning protection measure under the preset index factor can be acquired based on the existing execution of the lightning protection measure by experts, or a set number of index data can be randomly selected from a pre-stored index database.

[0037] For example, if the preset index factor is the (lightning) trip-out rate reduction degree, the lightning protection cost, the reconstruction difficulty degree, the maintenance difficulty degree, and the service life, and the lightning protection measure is erecting a lightning arrester, installing a lightning rod, increasing the creepage distance of an insulator (strengthening line insulation), erecting a coupling ground wire, and reducing a grounding resistance value, the index data of each lightning protection measure under the preset index factor can be represented in the form of Table 1 as follows:

[0038] Table 1: Index data

[0039] Reduction in tripping rate Lightning protection cost Difficulty of modification Ease of maintenance Operating life Installation of arrester 0.2P％ 15% of total cost 5-person team August 15 years Reduction in grounding resistance 0.7P％ 33% of total cost 9-person team July 13 years Installation of coupling ground 0.5P％ 20% of total cost 6-person team June 26 years Increase in insulator creepage distance 0.5P％ 10% of total cost 3-person team May 33 years Installation of lightning rod 0.4P％ 10% of total cost 4-person team July 26 years

[0040] S102, determining a target measure level of the lightning protection measure according to the index data, the evaluation values of the at least two first-type index levels corresponding to the preset index factor, and the evaluation values of the at least two second-type index levels corresponding to the preset index factor.

[0041] The index level can be represented in the form of an index threshold. The first-type index level and the second-type index level refer to index levels determined in different ways. The first-type index level can be an index level determined by experience. The second-type index level can be an index level determined by a clustering algorithm. The evaluation value refers to the level threshold of each index level in the data of the index. The target measure level refers to the level to which the effect of the target lightning protection measure belongs. The target measure level can be a recommended lightning protection measure level, a good lightning protection measure level, a general lightning protection measure level, or a non-recommended lightning protection measure level.

[0042] Optionally, the historical index data of the power distribution line in the history under different lightning protection measures and under different preset index factors can be analyzed. At least two index levels are determined according to experience. The maximum threshold associated with each index level is taken as the evaluation value of the index level, that is, the evaluation values of the at least two first-type index levels corresponding to the preset index factor are determined.

[0043] Optionally, a clustering algorithm can be used to determine the number of second-type index levels and the maximum threshold of each index level based on a preset rule. The maximum threshold associated with each index level is taken as the evaluation value of the index level, that is, the evaluation values of the at least two second-type index levels corresponding to the preset index factor are determined.

[0044] Optionally, after determining the index data, the evaluation values of the at least two first-type index levels corresponding to the preset index factor, and the evaluation values of the at least two second-type index levels corresponding to the preset index factor, the evaluation values of the first-type index levels and the evaluation values of the second-type index levels can be comprehensively arranged according to a preset calculation rule to determine the comprehensive evaluation values of each lightning protection measure. Finally, based on the relationship between the comprehensive evaluation values and the preset measure levels, the target measure levels of each lightning protection measure are determined. The evaluation values of the first-type index levels and the evaluation values of the second-type index levels can also be directly input into a pre-trained model to output the measure levels corresponding to the lightning protection measures, that is, the target measure levels of the lightning protection measures are determined.

[0045] For example, if the preset index factors are the trip-out rate reduction degree, the lightning protection cost, the reconstruction difficulty degree, the maintenance difficulty degree, and the operation life, the line specified trip-out rate is p%, the number of first-type index levels is 4, and A1, B1, C1, and D1 are used to represent them respectively, the evaluation value table of each first-type index level corresponding to different preset index factors can be represented in the form of Table 2 as follows:

[0046] Table 2: Evaluation value table of the first type of index grade

[0047] A1 B1 C1 D1 Lightning protection cost 10% of total cost 20% of total cost 30% of total cost 50% of total cost Difficulty of modification 4 persons required for modification 6 persons required for modification 8 persons required for modification 10 persons required for modification Ease of maintenance Maintenance cycle of 3 months Maintenance cycle of 6 months Maintenance cycle of 9 months Maintenance cycle of 12 months Operating life 10 years 20 years 30 years 40 years Reduction in tripping rate 0.2P％ 0.4P％ 0.6P％ 0.8P％

[0048] As shown in Table 2, for example, when the preset index factor is lightning protection fund, four first type of index grades are set for the index data, and the evaluation value (threshold value) of the first first type of index grade is not more than 10% of the total fund.

[0049] For example, if the preset index factor is the reduction degree of tripping rate, lightning protection fund, reconstruction difficulty, maintenance difficulty, and operation life, the tripping rate of the line is p%, and the number of the second type of index grade is four, which are represented by A2, B2, C2, and D2 respectively, then the evaluation value table of each first type of index grade corresponding to different preset index factors can be represented in the form of Table 3 as follows:

[0050] Table 3: Evaluation value table of the second type of index grade

[0051] A2 B2 C2 D2 Lightning protection cost 9% of total cost 17% of total cost 28% of total cost 46% of total cost Difficulty of modification 3-person team required for modification 5-person team required for modification 7-person team required for modification 9-person team required for modification Ease of maintenance Maintenance cycle of 3.5 months Maintenance cycle of 6.8 months Maintenance cycle of 9.1 months Maintenance cycle of 11.8 months Operating life 9 years 23 years 27 years 39 years Reduction in tripping rate 0.2P％ 0.3P％ 0.7P％ 0.9P％

[0052] S103, determining an execution strategy of the lightning protection measure according to the target measure grade of the lightning protection measure.

[0053] The execution strategy of the lightning protection measure refers to a strategy representing how to execute the lightning protection measure, for example, the execution strategy can be a strategy of determining whether to execute a certain lightning protection measure.

[0054] Optionally, when the number of lightning protection measures is one, a strategy of determining whether to execute the lightning protection measure can be determined according to the preset rule based on the target measure grade of the lightning protection measure, that is, the execution strategy of the lightning protection measure is determined, for example, if the lightning protection measure is to erect a lightning arrester, and the target measure grade of the lightning protection measure is the recommended lightning protection measure grade, then the execution strategy of the lightning protection measure can be determined as lightning protection reconstruction by erecting a lightning arrester, that is, the execution strategy of the lightning protection measure is determined.

[0055] Optionally, when the number of lightning protection measures is at least two, the number of lightning protection measures to be adopted can be determined first, and then a preset number of lightning protection measures meeting a screening condition are screened out based on the target measure grade of the lightning protection measure according to the preset rule, and a strategy of executing the lightning protection measures meeting the screening condition is determined, that is, the execution strategy of the lightning protection measure is determined.

[0056] Optionally, the execution strategy can include the number of lightning protection measures to be adopted, and can also include the execution order of each lightning protection measure to be adopted, which is not limited in the embodiment.

[0057] The technical solution of this invention involves acquiring indicator data of lightning protection measures under preset indicator factors. Based on the indicator data, the evaluation values ​​of at least two first-class indicator levels corresponding to the preset indicator factors, and the evaluation values ​​of at least two second-class indicator levels corresponding to the preset indicator factors, the target measure level of the lightning protection measures is determined. Finally, based on the target measure level of the lightning protection measures, the implementation strategy of the lightning protection measures is determined. By evaluating the indicator data of the lightning protection measures and determining the target measure level, an effective lightning protection implementation strategy can be determined, minimizing losses caused by lightning damage.

[0058] Optionally, one possible method for determining the rating value of the second type of indicator level is as follows: based on the preset indicator factor, perform clustering processing on historical operating data to obtain at least two cluster centers corresponding to the preset indicator factor; and determine the rating values ​​of at least two second type of indicator levels corresponding to the preset indicator factor based on the at least two cluster centers corresponding to the preset indicator factor.

[0059] Historical operational data refers to the indicator data generated during the historical operation of power distribution lines. Cluster centers are the cluster centers of the indicator data.

[0060] Optionally, the FCM (Fuzzy C-Means) clustering algorithm can be used to cluster historical running data. Based on the clustering results, a preset number of cluster centers can be selected, thus obtaining at least two cluster centers corresponding to the preset index factors.

[0061] Optionally, after determining at least two cluster centers, the determined cluster centers can be directly used as the evaluation values ​​of the second-class indicator level. That is, the number of evaluation values ​​of the second-class indicator level corresponding to each preset indicator factor is the same as the number of cluster centers. If the number of cluster centers is greater than the number of evaluation values ​​of the second-class indicator level for each preset indicator factor, then at least two evaluation values ​​of the second-class indicator level can be selected from at least two cluster centers according to the preset screening rules, that is, the evaluation values ​​of at least two second-class indicator levels corresponding to the preset indicator factor can be determined.

[0062] In this way, a more accurate assessment value for the second category of indicators can be determined, which will facilitate the subsequent determination of the corresponding measure level for lightning protection measures.

[0063] Example 2

[0064] Figure 2 This is a flowchart of a lightning protection strategy determination method provided in Embodiment 2 of the present invention. Based on the above embodiments, this embodiment further explains in detail the process of "obtaining index data of lightning protection measures under preset index factors," such as... Figure 2 As shown, the method includes:

[0065] S201, obtaining first data of the lightning protection measures under a first type of index factor in the preset index factors according to a simulation modeling result of the distribution network line.

[0066] The distribution network line refers to a line in a power distribution network. The simulation modeling result is obtained by simulating and modeling the lightning protection measures by using simulation software. The first type of index factor refers to an index factor of index data that needs to be determined by using the simulation software, such as a reduction degree of tripping rate. The first data refers to index data of the lightning protection measures under the first type of index factor.

[0067] Optionally, the ATP-EMTP (The Alternative Transients Program-The Electromagnetic Transients Program) simulation software can be used to simulate and model each lightning protection measure, and obtain the simulation modeling result of the distribution network line.

[0068] Optionally, the index data of each lightning protection measure under the reduction degree of tripping rate can be determined and integrated from the simulation modeling result of the distribution network line, that is, the first data of the lightning protection measures under the first type of index factor in the preset index factors can be obtained.

[0069] For example, if the lightning protection measures are to erect a lightning arrester, install a lightning rod, increase the creepage distance of an insulator, erect a coupling ground wire, and reduce the grounding resistance value, and the first type of index factor is the reduction degree of tripping rate, the first data of the lightning protection measures under the first type of index factor in the preset index factors can be represented in the form of Table 4 as follows:

[0070] Table 4: first data table

[0071] Reduction in tripping rate Installation of arrester 0.2P％ Reduction in grounding resistance 0.7P％ Installation of coupling ground 0.5P％ Increase in insulator creepage distance 0.5P％ Installation of lightning rod 0.4P％

[0072] S202, obtaining second data of the lightning protection measures under a second type of index factor in the preset index factors according to historical operation data of the distribution network line.

[0073] The second type of index factor refers to an index factor determined according to experience. Specifically, the second type of index factor can include at least one of lightning protection cost, difficulty of reconstruction, difficulty of maintenance, and operating life. The second data refers to index data of the lightning protection measures under the second type of index factor.

[0074] Optionally, the historical operation data of the power distribution line can be filtered according to a preset filtering rule, second data of each lightning protection measure under a second type index factor in the preset index factor is filtered from the historical operation data, and the second data is obtained; or index data of each lightning protection measure about different index factors determined by experts or other relevant personnel based on experience can be directly obtained, that is, second data of the lightning protection measure under the second type index factor in the preset index factor is determined.

[0075] For example, if the lightning protection measure is to erect a lightning arrester, install a lightning rod, increase the creepage distance of an insulator, erect a coupling ground wire, and reduce the grounding resistance value, and the second type index factor is lightning protection expenses, reconstruction difficulty, maintenance difficulty, and operation life, the second data of the lightning protection measure under the second type index factor in the preset index factor can be represented in the form of Table 5 as follows:

[0076] Table 5: Second data table

[0077] Lightning protection cost Difficulty of modification Ease of maintenance Operating life Installation of arrester 15% of total cost 5-person team August 15 years Reduction in grounding resistance 33% of total cost 9-person team July 13 years Installation of coupling ground 20% of total cost 6-person team June 26 years Increase in insulator creepage distance 10% of total cost 3-person team May 33 years Installation of lightning rod 10% of total cost 4-person team July 26 years

[0078] S203, determining index data of the lightning protection measure under the preset index factor according to the first data and the second data.

[0079] Optionally, after the first data and the second data are determined, the first data and the second data can be integrated according to a preset rule to generate the index data, that is, the index data of the lightning protection measure under the preset index factor is determined; or the first data and the second data can be input into a pre-trained model to directly output the index data, that is, the index data of the lightning protection measure under the preset index factor is determined.

[0080] For example, determining the index data of the lightning protection measure under the preset index factor according to the first data and the second data can be represented in the form of Table 1 in the above embodiment of the application.

[0081] S204, determining a target measure level of the lightning protection measure according to the index data, evaluation values of at least two first type index levels corresponding to the preset index factor, and evaluation values of at least two second type index levels corresponding to the preset index factor.

[0082] S205, determining an execution strategy of the lightning protection measure according to the target measure level of the lightning protection measure.

[0083] The technical scheme of the embodiment of the present application obtains first data of the lightning protection measure under a first index factor in the preset index factor according to the simulation modeling result of the distribution network line, obtains second data of the lightning protection measure under a second index factor in the preset index factor according to the historical operation data of the distribution network line, and further determines index data of the lightning protection measure under the preset index factor according to the first data and the second data, so as to determine the grade and the execution strategy of the lightning protection measure. In this way, an implementable manner of obtaining the index data is given, the index data better representing the effect of the lightning protection measure can be determined, the grade and the execution strategy of the lightning protection measure are facilitated to be determined subsequently, and the loss caused by the lightning hazard problem is minimized to the greatest extent.

[0084] Embodiment three

[0085] Figure 3 is a flowchart of a lightning protection strategy determination method provided by the embodiment three of the present application. The embodiment further explains and describes in detail the "determining the target measure grade of the lightning protection measure according to the index data, the evaluation values of the at least two first index grades corresponding to the preset index factor, and the evaluation values of the at least two second index grades corresponding to the preset index factor" on the basis of the above-mentioned embodiments, as shown in the following table. Figure 3 The method comprises the following steps:

[0086] S301, obtaining index data of the lightning protection measure under a preset index factor.

[0087] S302, determining a first group of measure scores of the lightning protection measure under a candidate measure grade according to the index data and the evaluation values of the at least two first index grades corresponding to the preset index factor.

[0088] The candidate measure grade refers to the measure grade to which the candidate lightning protection measure belongs, and the candidate measure grade can include a recommended lightning protection measure grade, a good lightning protection measure grade, a general lightning protection measure grade, or a non-recommended lightning protection measure grade. The first group of measure scores refers to a score matrix about each candidate measure grade determined based on the evaluation values of the first index grades.

[0089] Optionally, a subjective cloud model can be established based on the classic subjective cloud theory according to the evaluation values of the at least two first index grades corresponding to the preset index factor, and the index data can be evaluated by using the subjective cloud model to determine the first group of measure scores of the lightning protection measure under the candidate measure grade.

[0090] Optionally, the first group of measure scores of the lightning protection measures under the candidate measure level are determined according to the evaluation values of the at least two first-type index levels corresponding to the index data and the preset index factor, and the first score matrix of the lightning protection measures under the preset index factor is determined according to the evaluation values of the at least two first-type index levels corresponding to the index data and the preset index factor; and the first group of measure scores of the lightning protection measures under the candidate measure level are determined according to the score weight matrix and the first score matrix.

[0091] The first score matrix refers to a score matrix determined based on the evaluation of the first-type index levels. The score weight matrix refers to a preset constant weight matrix that comprehensively considers the index factors.

[0092] Optionally, a subjective cloud model can be established based on the evaluation values of the at least two first-type index levels corresponding to the preset index factor and the subjective cloud theory, and the index data of each lightning protection measure is calculated to determine the first scores of the index factors of the lightning protection measure under each candidate measure level and generate the first score matrix according to the digital characteristic function of the established subjective cloud model.

[0093] For example, the digital characteristic function of the subjective cloud model can be represented by the following formula:

[0094] y Ⅰ =exp{[-(x-Ex Ⅰ ) 2 / 2(En′ Ⅰ ) 2 ]}

[0095] wherein y Ⅰ is the score under the Ith candidate measure level, x is an index data, Ex Ⅰ is the mean value of the evaluation value of the index factor, for example, referring to Table 2, when the index factor is lightning protection expenses, Ex Ⅰ is the mean value of 10%, 20%, 30%, and 50%. Referring to Table 1, when the lightning protection measure is to erect a lightning arrester and the index factor is lightning protection expenses, x is 15%. En′ Ⅰ is a normal random number generated with En Ⅰ as the mean value and He Ⅰ as the standard deviation. En Ⅰ is the entropy of the index data. He Ⅰ is the hyper-entropy of the index data.

[0096] For example, if the preset index factors include the degree of reduction in tripping rate, lightning protection cost, ease of modification, ease of maintenance, and service life, and the candidate measure levels include recommended lightning protection measure level, good lightning protection measure level, general lightning protection measure level, or not recommended lightning protection measure level, then the first scoring matrix of lightning protection measures under the preset index factors can be represented in the form of the following table:

[0097] Table 6: First Rating Matrix

[0098] ​ <L2> ​ ​ Lightning protection cost 0.5 0.5 0 0 Difficulty of modification 0.5 0.5 0 0 Ease of maintenance 0 0.5 0.5 0 Operating life 0.5 0.5 0 0 Reduction in tripping rate 1 0 0 0

[0099] Where L1 represents the recommended lightning protection level, L2 the good lightning protection level, L3 the general lightning protection level, or L4 the not recommended lightning protection level. For example, when the preset index factor is lightning protection funding and the candidate lightning protection level is L1 (recommended lightning protection level), x can be determined to be 15%, Ex. Ⅰ For the average of 10%, 20%, 30%, and 50%, En Ⅰ ′ is En Ⅰ As the mean, He Ⅰ En is a normally distributed random number generated by the standard deviation. Ⅰ It is the entropy of the indicator data. He Ⅰ To determine the hyperentropy of the indicator data, substituting the above parameters into the digital feature function of the subjective cloud model, the first score y can be determined. Ⅰ The value is 0.5.

[0100] Optionally, a pre-stored scoring weight matrix can be directly obtained; alternatively, the analytic hierarchy process (AHP) can be used to evaluate each indicator factor based on preset rules, determine the weight comparison matrix A, construct a judgment matrix based on the weight comparison matrix A, calculate the optimal transfer matrix L, further determine the quasi-optimal consistency matrix B, and perform normalization processing based on the eigenvector corresponding to the largest eigenvalue of matrix B to obtain the scoring weight matrix.

[0101] For example, when the preset index factors are the degree of reduction in tripping rate, lightning protection cost, ease of retrofitting, ease of maintenance, and service life, the weight comparison matrix A can be represented as:

[0102]

[0103] For example, based on the weight comparison matrix A above, the rating weight matrix can be determined as follows: [0.57 0.16 0.16 0.0546 0.0546]

[0105] Optionally, after the score weight matrix and the first score matrix are determined, the score weight matrix and the first score matrix can be multiplied, and the product matrix is taken as the first group of measure score matrix, i.e. the first group of measure score of the lightning protection measure under the candidate measure level is determined.

[0106] For example, if the lightning protection measure is to erect a lightning arrester, the first group of measure score of the lightning protection measure under each candidate measure level can be represented as:

[0107] [L1 L2 L3 L4]=[0.7573 0.2146 0.0273 0]

[0108] Wherein, L1 is the recommended lightning protection measure level, L2 is the good lightning protection measure level, L3 is the general lightning protection measure level, or L4 is the non-recommended lightning protection measure level.

[0109] S303, according to the evaluation value of the at least two second type index levels corresponding to the index data and the preset index factor, determine the second group of measure score of the lightning protection measure under the candidate measure level.

[0110] Wherein, the second group of measure score refers to the score matrix of each candidate measure level determined based on the evaluation value of the second type index level.

[0111] Optionally, according to the evaluation value of the at least two second type index levels corresponding to the preset index factor, an objective cloud model can be established based on the classical objective cloud theory, and the index data can be evaluated by using the objective cloud model to determine the second group of measure score of the lightning protection measure under the candidate measure level.

[0112] For example, the second group of measure score can be represented as:

[0113] [L1 L2 L3 L4]=[0.6449 0.3231 0.0289 0]

[0114] Wherein, L1 is the recommended lightning protection measure level, L2 is the good lightning protection measure level, L3 is the general lightning protection measure level, or L4 is the non-recommended lightning protection measure level.

[0115] S304, according to the first group of measure score and the second group of measure score, determine the target measure level of the lightning protection measure.

[0116] Optionally, the first group of measure score and the second group of measure score can be calculated based on the pre-designed calculation rule of the DS (Dempster / Shafer) evidence fusion theory, and the candidate measure level to which the lightning protection measure belongs is determined, i.e. the target measure level of the lightning protection measure is determined.

[0117] Optionally, the target measure level of lightning protection measures is determined based on the scores of the first group of measures and the second group of measures, including: determining a normalization constant based on the scores of the first group of measures and the second group of measures; determining the correlation between lightning protection measures and candidate measure levels based on the normalization constant, the scores of the first group of measures and the second group of measures; and determining the target measure level of lightning protection measures based on the correlation between lightning protection measures and candidate measure levels.

[0118] The normalization constant is a constant that can be used to determine the correlation between lightning protection measures and the levels of candidate measures. The correlation between lightning protection measures and the levels of each candidate measure can be determined based on the combination function of evidence fusion theory.

[0119] For example, if the identification framework of the evidence fusion theory is determined as (L1 L2 L3 L4) based on the lightning protection measure level (L1 is the recommended lightning protection measure level, L2 is the good lightning protection measure level, L3 is the general lightning protection measure level, or L4 is the not recommended lightning protection measure level), and the identification model is Θ={L1,L2,L3,...,L... n Let m{L1}, m{L2}, m{L3}, and m{L4} be the probability allocation functions corresponding to each lightning protection measure level. Then, the scores for the first group of measures and the scores for the second group of measures can be expressed in the form shown in Table 7 below:

[0120] Table 7: Scoring Tables for Measures in Group 1 and Measures in Group 2

[0121] m{L1} m{L2} m{L3} m{L4} First group of measures score 0.7573 0.2146 0.0273 0 Second group of measures score 0.6449 0.3231 0.0289 0

[0122] For example, the normalization constant K can be determined based on the following formula:

[0123]

[0124] Where m1 is the feasibility calculation function for the first set of measures, m2 is the feasibility calculation function for the second set of measures, B1 and B2 are both subsets of the identification framework Θ, and K is a coefficient that measures the degree of conflict between different pieces of evidence, i.e., the normalization constant.

[0125] Substituting the scores of the first and second groups of measures in Table 7 above into the formula for determining the normalization constant, we can obtain a normalization constant of 0.558.

[0126] Optionally, after determining the normalization constant, the scores of the first group of measures and the scores of the second group of measures, the normalization constant, the scores of the first group of measures and the scores of the second group of measures can be input into a preset correlation determination function, such as the mass function in evidence fusion theory, to determine the correlation between lightning protection measures and the levels of each candidate measure.

[0127] For example, the combination function for the recommended lightning protection level L1 can be expressed as:

[0128]

[0129] Where m is the combination function, B1 and B2 are both subsets of the identification frame Θ, ψ is the non-empty subset where B1 and B2 intersect, K is the normalization constant, m1 is the feasibility calculation function for the first set of measures, and m2 is the feasibility calculation function for the second set of measures.

[0130] For example, by substituting the first set of measure scores m1(B1), i.e. 0.7573, the second set of measure scores m2(B2), i.e. 0.6449, and the normalization constant given in Table 7 above into the above combination function, we can calculate that the correlation value between the lightning protection measure (installing a surge arrester) and the candidate measure level (recommended lightning protection measure level L1) is 0.8752. The specific calculation process is: 0.7573*0.6449 / 0.558=0.8752.

[0131] By analogy, the correlation values ​​between lightning protection measures (installing surge arresters) and other candidate measure levels (except for the recommended lightning protection measure level L1) can be determined. Specifically, the correlation between lightning protection measures (installing surge arresters) and each candidate measure level can be summarized as follows:

[0132] {P{L1}, P{L2}, P{L3}, P{L4}}={0.8752, 0.124,0,0}

[0133] Optionally, the correlation values ​​between the lightning protection measure and each candidate measure level can be compared. Based on the correlation, the candidate measure level corresponding to the highest correlation value is taken as the target measure level to which the lightning protection measure belongs. For example, if the correlation value between the lightning protection measure (installing a surge arrester) and each candidate measure level is as shown in the above formula, then the target measure level of the lightning protection measure (installing a surge arrester) can be determined as the recommended lightning protection measure level L1.

[0134] S305. Determine the implementation strategy of lightning protection measures based on the target level of the lightning protection measures.

[0135] The technical scheme of the embodiment of the present application is that after the index data is acquired, the first group of measure scores of the lightning protection measures under the candidate measure level is determined according to the evaluation values of the at least two first-type index levels corresponding to the index data and the preset index factor, the second group of measure scores of the lightning protection measures under the candidate measure level is determined according to the evaluation values of the at least two second-type index levels corresponding to the index data and the preset index factor, and the target measure level of the lightning protection measures is determined according to the first group of measure scores and the second group of measure scores, so as to determine the execution strategy of the lightning protection measures. In this way, an implementable manner for determining the target measure level of the lightning protection measures is given, the measure level to which the lightning protection measures belong can be more effectively determined, the appropriate execution strategy of the lightning protection measures can be determined subsequently, and thus the loss caused by the lightning hazard problem can be reduced to the greatest extent.

[0136] Embodiment Four

[0137] Figure 4 is a flowchart of a lightning protection strategy determination method provided by Embodiment Four of the present application. Based on the above-mentioned embodiments, the embodiment further explains and describes in detail the "determination of the second group of measure scores of the lightning protection measures under the candidate measure level according to the evaluation values of the at least two second-type index levels corresponding to the index data and the preset index factor", as shown in Figure 4 The method comprises the following steps.

[0138] S401, acquiring index data of lightning protection measures under a preset index factor.

[0139] S402, determining a first group of measure scores of the lightning protection measures under a candidate measure level according to evaluation values of at least two first-type index levels corresponding to the index data and the preset index factor.

[0140] S403, determining a second score matrix of the lightning protection measures under the preset index factor according to evaluation values of at least two second-type index levels corresponding to the index data and the preset index factor.

[0141] The second score matrix refers to a score matrix determined after evaluation based on the second-type index level.

[0142] Optionally, an objective cloud model can be established based on the evaluation values of the at least two second-type index levels corresponding to the preset index factor and the objective cloud theory, the index data of each lightning protection measure is calculated according to the digital characteristic function of the established objective cloud model, the second scores of each index factor of the lightning protection measure under each candidate measure level are determined, and the second score matrix is generated.

[0143] For example, the digital characteristic function of the objective cloud model can be represented by the following formula:

[0144] y Ⅰ=exp{[-(x-Ex objⅠ ) 2 / 2(En′ objⅠ ) 2 ]}

[0145] Among them, y Ⅰ This refers to the score at the level of the I-th candidate measure. x refers to a single indicator data point. Ex objⅠ It is the mean of the evaluation values ​​corresponding to the indicator factors. For example, see Table 3. When the indicator factor is lightning protection funding, Ex... objⅠ The mean values ​​are 9%, 17%, 28%, and 46%, respectively. objⅠ Therefore, En objⅠ As the mean, He Ⅰ En is a normally distributed random number generated by the standard deviation. objⅠ It is the entropy of the indicator data, He Ⅰ This refers to the hyperentropy of the indicator data.

[0146] For example, if the preset index factors include the degree of reduction in tripping rate, lightning protection cost, ease of retrofitting, ease of maintenance, and service life, and the candidate measure levels include recommended lightning protection measure level, good lightning protection measure level, general lightning protection measure level, or not recommended lightning protection measure level, then the second scoring matrix of lightning protection measures under the preset index factors can be represented in the form of the following table:

[0147] Table 8: Second Scoring Matrix

[0148] ​ <L2> ​ ​ Lightning protection cost 0.25 0.75 0 0 Difficulty of modification 0 1 0 0 Ease of maintenance 0 0.47 0.53 0 Operating life 0.64 0.32 0 0 Reduction in tripping rate 1 0 0 0

[0149] Where L1 represents the recommended lightning protection level, L2 the good lightning protection level, L3 the general lightning protection level, or L4 the not recommended lightning protection level. For example, when the preset index factor is lightning protection funding and the candidate lightning protection level is L1 (recommended lightning protection level), x can be determined to be 15%, Ex. Ⅰ For the mean of 10%, 20%, 30%, and 50%, Ex objⅠ The mean values ​​are 9%, 17%, 28%, and 46%, respectively. objⅠ Therefore, En objⅠ As the mean, He Ⅰ En is a normally distributed random number generated by the standard deviation. objⅠ It is the entropy of the indicator data, He Ⅰ To determine the hyperentropy of the indicator data, substituting the above parameters into the digital feature function of the objective cloud model, the second score y can be determined. Ⅰ The value is 0.25.

[0150] Optionally, the pre-stored scoring weight matrix can be directly obtained; or the analytic hierarchy process can be used to evaluate each index factor based on a pre-set rule to determine a weight comparison matrix A, construct a judgment matrix based on the weight comparison matrix A, calculate an optimal transfer matrix L, further determine a quasi-optimal consistent matrix B, perform normalization processing based on a characteristic vector corresponding to a maximum eigenvalue of the matrix B to obtain the scoring weight matrix. The weight comparison matrix can be specifically in the form provided by the above embodiments of the present aspect.

[0151] It should be noted that the first scoring matrix and the second scoring matrix described in the present embodiment are both scoring matrices for each candidate measure level.

[0152] S404, determining a second group of measure scores of the lightning protection measure at the candidate measure level according to the scoring weight matrix and the second scoring matrix.

[0153] The scoring weight matrix refers to a pre-set constant weight matrix that comprehensively considers each index factor. The scoring weight matrix used to determine the first group of measure scores and the second group of measure scores is the same.

[0154] Optionally, after the scoring weight matrix and the second scoring matrix are determined, the scoring weight matrix and the second scoring matrix can be multiplied, and the product matrix can be taken as the second group of measure scores matrix, i.e., the second group of measure scores of the lightning protection measure at the candidate measure level is determined.

[0155] For example, if the lightning protection measure is to erect a lightning arrester, the second group of measure scores of the lightning protection measure at each candidate measure level can be represented as: [L1 L2 L3 L4] = [0.6449 0.3231 0.0289 0], wherein L1 is a recommended lightning protection measure level, L2 is a good lightning protection measure level, L3 is a general lightning protection measure level, or L4 is a non-recommended lightning protection measure level.

[0156] S405, determining a target measure level of the lightning protection measure according to the first group of measure scores and the second group of measure scores.

[0157] S406, determining an execution strategy of the lightning protection measure according to the target measure level of the lightning protection measure.

[0158] The technical scheme of the embodiment of the present application, after obtaining the index data and determining the first group of measure scores of the lightning protection measures under the candidate measure level, determines a second score matrix of the lightning protection measures under the preset index factor according to the evaluation values of at least two second-type index levels corresponding to the index data and the preset index factor, determines a second group of measure scores of the lightning protection measures under the candidate measure level according to the score weight matrix and the second score matrix, and further determines the target measure level of the lightning protection measures according to the first group of measure scores and the second group of measure scores, so as to determine the execution strategy of the lightning protection measures. In this way, an implementable manner of determining the second group of measure scores is given, the measure level to which the lightning protection measures belong can be more effectively determined, the suitable execution strategy of the lightning protection measures can be determined subsequently, and thus the loss caused by the lightning hazard problem can be reduced to the greatest extent.

[0159] Embodiment five

[0160] Figure 5 is a flowchart of the lightning protection strategy determination method provided by the embodiment five of the present application. The embodiment is based on the above-mentioned embodiments, and gives an implementable manner of realizing the execution strategy determination of the lightning protection measures by using the subjective cloud model, the objective cloud model and the evidence fusion theory, as shown in Figure 5 , the method comprises the following processes:

[0161] ATP-EMTP is used to simulate and model the distribution network line, various lightning protection measures are set, the lightning tower model is established, the lightning current is designed to calculate the tower trip-out rate (i.e. lightning trip-out rate), and the effect of reducing the lightning trip-out rate (i.e. lightning trip-out rate reduction effect) of various lightning protection measures is evaluated after simulation. The related parameters of the simulation model (35kV) are as follows: the wire type is LGJ-120 / 20, the ground wire type is LGJ-35, the span is set to 50m, the tower is a π-type tower with a height of 20m, the lightning strike is a double exponential wave, the lightning strike amplitude is set to 40kA with negative polarity, the insulator is simulated by using the Flash Mode model, and the lightning arrester is simulated by using the voltage-controlled switch.

[0162] Optionally, five index factors (lightning trip-out rate reduction effect, engineering cost, reconstruction difficulty, maintenance difficulty and operation life) that can comprehensively evaluate the lightning protection reconstruction measures are determined according to the expert opinions, i.e. the index factors are determined.

[0163] Optionally, the implementable manner of establishing the subjective and objective cloud models is that four effect levels (i.e., the first type of index level) are set in each index factor, and the subjective cloud model of different index factors is established according to the experience of experts or the threshold guide. For each index factor, four clustering centers (i.e., the second type of index level) are obtained based on the historical operation data and the FCM clustering algorithm, and the objective cloud model of different index factors is established according to the clustering result. After the subjective and objective weight cloud models are established, the subjective and objective cloud scoring matrices (the first and second scoring matrices) can be generated by using the subjective and objective models to score each lightning protection measure. Specifically, the subjective and objective cloud scoring matrices can be shown in Tables 6 and 8, respectively.

[0164] Optionally, the weights of various characteristics of the lightning protection measures are defined, i.e., the scoring weight matrix is determined, the subjective and objective cloud measure scores (i.e., the first and second groups of measure scores) are determined according to the subjective and objective cloud scoring matrices and the scoring weight matrix, and specifically, the subjective and objective cloud measure scores can be represented in the form provided by the above-mentioned embodiments of the present application, as shown in Table 7.

[0165] Optionally, the subjective and objective cloud measure scores are fused by using the D-S evidence theory, i.e., the fusion judgment is performed, the measure levels of each lightning protection measure are evaluated in sequence, and the lightning protection execution strategy actually adopted is decided (i.e., the execution strategy of the lightning protection measure is determined) based on each lightning protection measure and the corresponding measure level.

[0166] The technical solution of the embodiments of the present application provides an optimal way of determining the execution strategy of the lightning protection measure by using the subjective and objective cloud models and the evidence fusion theory, and the optimal execution strategy of the lightning protection measure can be determined, thereby minimizing the loss caused by the lightning hazard problem.

[0167] Embodiment six

[0168] Figure 6 is a structural diagram of a lightning protection strategy determination device provided by the sixth embodiment of the present application. The lightning protection strategy determination device provided by the embodiments of the present application can execute the lightning protection strategy determination method provided by any of the embodiments of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0169] As Figure 6 shown, the device includes:

[0170] The acquisition module 601 is configured to acquire index data of the lightning protection measure under the preset index factor.

[0171] The grade determination module 602 is configured to determine the target measure grade of the lightning protection measure according to the index data, evaluation values of at least two first-type index grades corresponding to the preset index factor, and evaluation values of at least two second-type index grades corresponding to the preset index factor.

[0172] The strategy determination module 603 is configured to determine the execution strategy of the lightning protection measure according to the target measure grade of the lightning protection measure.

[0173] The technical scheme of the embodiment of the present application acquires the index data of the lightning protection measure under the preset index factor, determines the target measure grade of the lightning protection measure according to the index data, evaluation values of at least two first-type index grades corresponding to the preset index factor, and evaluation values of at least two second-type index grades corresponding to the preset index factor, and finally determines the execution strategy of the lightning protection measure according to the target measure grade of the lightning protection measure. By evaluating the index data according to the index data of the lightning protection measure, determining the target measure grade of the lightning protection measure and then determining the execution strategy, an effective execution strategy of the lightning protection measure can be determined, and the loss caused by the lightning hazard problem can be reduced to the greatest extent.

[0174] Further, the acquisition module 601 is specifically configured to:

[0175] acquire first data of the lightning protection measure under a first-type index factor in the preset index factor according to a simulation modeling result of the distribution network line;

[0176] acquire second data of the lightning protection measure under a second-type index factor in the preset index factor according to historical operation data of the distribution network line;

[0177] determine the index data of the lightning protection measure under the preset index factor according to the first data and the second data.

[0178] Further, the grade determination module 602 can include:

[0179] a first determination unit configured to determine a first group of measure scores of the lightning protection measure under a candidate measure grade according to the index data and evaluation values of at least two first-type index grades corresponding to the preset index factor;

[0180] a second determination unit configured to determine a second group of measure scores of the lightning protection measure under the candidate measure grade according to the index data and evaluation values of at least two second-type index grades corresponding to the preset index factor;

[0181] a third determination unit configured to determine the target measure grade of the lightning protection measure according to the first group of measure scores and the second group of measure scores.

[0182] Further, the first determination unit is specifically configured to:

[0183] determine a first score matrix of the lightning protection measure under the preset index factor according to the index data and evaluation values of at least two first-type index levels corresponding to the preset index factor;

[0184] determine a first group of measure scores of the lightning protection measure under the candidate measure level according to the score weight matrix and the first score matrix.

[0185] Further, the second determining unit is specifically configured to:

[0186] determine a second score matrix of the lightning protection measure under the preset index factor according to the index data and evaluation values of at least two second-type index levels corresponding to the preset index factor;

[0187] determine a second group of measure scores of the lightning protection measure under the candidate measure level according to the score weight matrix and the second score matrix.

[0188] Further, the third determining unit is specifically configured to:

[0189] determine a normalization constant according to the first group of measure scores and the second group of measure scores;

[0190] determine the correlation between the lightning protection measure and the candidate measure level according to the normalization constant, the first group of measure scores and the second group of measure scores;

[0191] determine the target measure level of the lightning protection measure according to the correlation between the lightning protection measure and the candidate measure level.

[0192] Further, the above device is further configured to:

[0193] perform clustering processing on the historical operation data based on the preset index factor to obtain at least two clustering centers corresponding to the preset index factor;

[0194] determine evaluation values of at least two second-type index levels corresponding to the preset index factor according to the at least two clustering centers corresponding to the preset index factor.

[0195] Embodiment Seven

[0196] Figure 7 is a structural schematic diagram of an electronic device provided by Embodiment Seven of the present application. Figure 7A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0197] like Figure 7 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0198] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0199] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the lightning protection strategy determination method.

[0200] In some embodiments, the lightning protection strategy determination method can be implemented as a computer program tangibly embodied in a computer readable storage medium, e.g., storage unit 18. In some embodiments, parts or all of the computer program can be loaded and / or installed onto electronic device 10 via, e.g., ROM 12 and / or communication unit 19. When the computer program is loaded onto RAM 13 and executed by processor 11, one or more steps of the lightning protection strategy determination method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the lightning protection strategy determination method by other any suitable means, e.g., by way of firmware.

[0201] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (PLD), a computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0202] Computer programs used to implement the processes of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the computer program, when executed by the processor of the machine, implements the functions / acts specified in the flowcharts and / or block diagrams. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0203] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0204] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0205] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0206] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0207] It should be understood that the various forms of flow shown above can be reordered, added to, or have steps deleted. For example, the steps described in the present application can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions of the present application can be achieved, which are not limited herein.

[0208] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for determining lightning protection strategies, characterized in that, include: Obtaining indicator data for lightning protection measures under preset indicator factors includes: obtaining first data for lightning protection measures under the first type of indicator factors in the preset indicator factors based on the simulation modeling results of the distribution network lines; filtering historical operating data of the distribution lines according to preset filtering rules, and selecting second data for each lightning protection measure under the second type of indicator factors in the preset indicator factors from the historical operating data; and determining the indicator data for lightning protection measures under the preset indicator factors based on the first data and the second data. Determining the target measure level of the lightning protection measure based on the indicator data, the evaluation values ​​of at least two first-type indicator levels corresponding to the preset indicator factors, and the evaluation values ​​of at least two second-type indicator levels corresponding to the preset indicator factors includes: determining a first set of measure scores for the lightning protection measure under the candidate measure level based on the indicator data and the evaluation values ​​of at least two first-type indicator levels corresponding to the preset indicator factors; determining a second set of measure scores for the lightning protection measure under the candidate measure level based on the indicator data and the evaluation values ​​of at least two second-type indicator levels corresponding to the preset indicator factors; and determining the target measure level of the lightning protection measure based on the first set of measure scores and the second set of measure scores; wherein, the first-type indicator levels are determined empirically; and the second-type indicator levels are determined using a clustering algorithm. Based on the target level of the lightning protection measures, the implementation strategy of the lightning protection measures is determined; the implementation strategy includes the number of lightning protection measures adopted and the execution order of each adopted lightning protection measure; This also includes: performing clustering processing on the historical operating data based on preset indicator factors to obtain at least two cluster centers corresponding to the preset indicator factors; and determining the evaluation values ​​of at least two second-class indicator levels corresponding to the preset indicator factors based on the at least two cluster centers corresponding to the preset indicator factors.

2. The method according to claim 1, characterized in that, Based on the indicator data and the rating values ​​of at least two first-category indicator levels corresponding to the preset indicator factors, the first set of measure scores for the lightning protection measures under the candidate measure levels is determined, including: Based on the indicator data and the rating values ​​of at least two first-class indicator levels corresponding to the preset indicator factors, determine the first scoring matrix of the lightning protection measures under the preset indicator factors; Based on the scoring weight matrix and the first scoring matrix, the first group of measure scores for the lightning protection measures under the candidate measure level is determined.

3. The method according to claim 1, characterized in that, Based on the evaluation values ​​of at least two second-category indicator levels corresponding to the indicator data and the preset indicator factors, the second set of measure scores for the lightning protection measures under the candidate measure levels is determined, including: Based on the indicator data and the rating values ​​of at least two second-category indicator levels corresponding to the preset indicator factors, determine the second scoring matrix of the lightning protection measures under the preset indicator factors; Based on the scoring weight matrix and the second scoring matrix, the second set of measure scores for the lightning protection measures under the candidate measure level is determined.

4. The method according to claim 1, characterized in that, Based on the scores of the first set of measures and the second set of measures, the target measure level of the lightning protection measures is determined, including: Determine the normalization constant based on the scores of the first group of measures and the scores of the second group of measures; The correlation between the lightning protection measures and the candidate measure levels is determined based on the normalization constant, the scores of the first group of measures, and the scores of the second group of measures. The target measure level of the lightning protection measure is determined based on the correlation between the lightning protection measure and the candidate measure level.

5. A lightning protection strategy determination device, characterized in that, include: The acquisition module is used to acquire indicator data of lightning protection measures under preset indicator factors; The acquisition module is also used to acquire the first data of lightning protection measures under the first type of index factor in the preset index factors based on the simulation modeling results of the distribution network line; According to the preset screening rules, the historical operation data of the power distribution line is screened, and the second data of each lightning protection measure under the second type of index factor in the preset index factors are selected from the historical operation data. Based on the first data and the second data, determine the index data of the lightning protection measures under the preset index factor; The level determination module is used to determine the target measure level of the lightning protection measures based on the indicator data, the evaluation values ​​of at least two first-type indicator levels corresponding to the preset indicator factors, and the evaluation values ​​of at least two second-type indicator levels corresponding to the preset indicator factors; wherein, the first-type indicator levels are determined by experience; and the second-type indicator levels are determined by a clustering algorithm. The level determination module includes a first determination unit, a second determination unit, and a third determination unit: The first determining unit is used to determine the first set of measure scores of the lightning protection measures under the candidate measure level based on the evaluation values ​​of at least two first-class indicator levels corresponding to the indicator data and the preset indicator factors; The second determining unit is used to determine the second set of measure scores of the lightning protection measures under the candidate measure level based on the evaluation values ​​of at least two second-category indicator levels corresponding to the indicator data and the preset indicator factors; The third determining unit is used to determine the target measure level of the lightning protection measures based on the first set of measure scores and the second set of measure scores; The strategy determination module is used to determine the execution strategy of the lightning protection measures based on the target measure level of the lightning protection measures; the execution strategy includes the number of lightning protection measures adopted and the execution order of each adopted lightning protection measure; This also includes: performing clustering processing on the historical operating data based on preset indicator factors to obtain at least two cluster centers corresponding to the preset indicator factors; and determining the evaluation values ​​of at least two second-class indicator levels corresponding to the preset indicator factors based on the at least two cluster centers corresponding to the preset indicator factors.

6. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the lightning protection strategy determination method according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that are used to cause a processor to execute the lightning protection strategy determination method according to any one of claims 1-4.

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