Voltage anomaly detection and positioning method based on multiple monitoring point signals and related device

Abstract

The invention discloses a voltage anomaly detection and positioning method based on multiple monitoring point signals and a related device, and relates to the technical field of electric power detection, and the method comprises the following steps: 1, carrying out the statistics of abnormal transformer areas and influence users; 2, analyzing the line position of the abnormal transformer area; 3, analyzing a line head end voltage switch; and step 4, transformer area abnormity reason analysis: in the line position analysis of the transformer area, branch line judgment is carried out firstly, and then pole number judgment is carried out, so that the query efficiency is greatly improved; after the branch line and the pole number are determined, the head end switch can be quickly queried in a static topology mode, and the query efficiency is improved. In the step 1, all abnormal transformer areas can be quickly counted, so that the detection and positioning efficiency is improved; moreover, a user abnormal frequency coefficient is added into the transformer area abnormal scoring model, the proportion of abnormal users is considered, high-frequency anomalies are punished, rapid statistics can be carried out, and high-frequency abnormal users can be monitored.

Description

Technical Field

[0001] The present invention belongs to the technical field of power detection, and particularly relates to a voltage anomaly detection and location method based on signals of multiple monitoring points and related devices. Background Art

[0002] With the continuous increase in new energy input, high-volatility new energy represented by wind power and photovoltaic power joins the conventional power grid, and the proportion of new types of loads increases accordingly, which has a great impact on the stability of the power grid. If not processed in a timely and rapid manner, a single fault may expand to the entire regional power grid through a chain reaction, causing serious safety problems and economic losses to the entire power grid. And to process it in a timely and rapid manner, it is necessary to first locate the abnormal location.

[0003] According to the patent number: CN116223965A - A voltage anomaly detection and location method based on analysis of signals of multiple monitoring points, which records that "the voltage anomaly detection and location method first makes a preliminary judgment. When a voltage anomaly occurs, a power grid topological structure and a monitoring point direction discrimination matrix are established, and the two are combined to achieve voltage anomaly section location". From this, those skilled in the art can know that this method calculates through the calculation methods of topology and the discrimination matrix, which increases the calculation process of the system, and the monitoring points are in units of sections, and it still requires staff to conduct inspections, with low efficiency.

[0004] In summary, a voltage anomaly detection and location method based on analysis of signals of multiple monitoring points is designed. Summary of the Invention

[0005] The purpose of the present invention is to provide a voltage anomaly detection and location method based on signals of multiple monitoring points and related devices to solve the technical problem of low efficiency of abnormal location in the prior art.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a voltage anomaly detection and location method based on signals of multiple monitoring points, including:

[0008] Obtain voltage signals of multiple monitoring points of each substation area, count abnormal substation areas with abnormal voltage signals and affected users to obtain a list of abnormal substation areas and abnormal users under the substation areas;

[0009] Adopt a method of first judging the branch line and then judging the pole number to analyze the line position where the abnormal substation area in the list of abnormal substation areas and abnormal users under the substation area is located, and obtain the line position segment where the abnormal substation area is located;

[0010] Based on the line position segment where the abnormal substation area is located, find the head voltage switch corresponding to the line where the abnormal substation area is located.

[0011] Further, the obtaining of voltage signals of multiple monitoring points for each substation area, the statistics of abnormal substation areas with abnormal voltage signals and affected users, and the resulting list of abnormal substation areas and abnormal users under the substation areas include:

[0012] Statistical analysis is performed on all substation areas with voltage abnormalities during the monitoring period;

[0013] Statistical analysis is performed on the voltages of low-voltage users under all substation areas during the monitoring period;

[0014] Filter out abnormal substation areas based on the number of abnormal users;

[0015] Query all time periods when the voltages of all low-voltage users under the substation area are abnormal, and determine whether there is an intersection between the time period of low-voltage user voltage abnormality and the time period of substation area voltage abnormality:

[0016] If there is an intersection, add the low-voltage user and the abnormality to the list of abnormal substation areas and abnormal users under the substation area;

[0017] If there is no intersection, do not include it in the list of abnormal substation areas and abnormal users under the substation area.

[0018] Further, the filtering out of abnormal substation areas based on the number of abnormal users includes:

[0019] Calculate the abnormality score based on the substation area abnormality scoring model, and the substation area abnormality scoring model is:

[0020]

[0021] Among them,

[0022] The S(t i ) is the abnormality score of substation area t i ; is the proportion of time-related abnormal users, is the user abnormality frequency coefficient; U i is the set of all voltage-abnormal users under substation area t i , A u is the set of voltage-abnormal time periods of user u; f(u, t i ) is the abnormal user judgment function; [s u , e u represents the user abnormal time period; [s t , e t represents the substation area abnormal time period; A t represents the set of voltage-abnormal time periods of substation area t;

[0023] Determine whether the power distribution area is an abnormal power distribution area according to the screening decision function, and the screening decision function g(t i ) is as follows:

[0024]

[0025] where α is the screening threshold; k is the threshold of the minimum number of users.

[0026] Furthermore, α is 0.2 and k is 3.

[0027] Furthermore, the method of first judging the branch line and then judging the pole number is adopted to analyze the line position of the abnormal power distribution area in the abnormal power distribution area and the list of abnormal users under the power distribution area, and the line position segment where the abnormal power distribution area is located is obtained, including:

[0028] S21. Judge whether there is a large branch line in each line under all monitoring points: if not, record the maximum pole number of the line; if so, record the main pole number corresponding to the large branch line and the maximum pole number of each large branch line;

[0029] S22. According to the abnormal power distribution area, find the line to which the abnormal power distribution area belongs, and confirm whether there is a large branch line in the line to which the abnormal power distribution area belongs according to the judgment result of the large branch line in all lines:

[0030] If there is no large branch line, query the corresponding pole of the abnormal power distribution area, and the line position segment of the abnormal power distribution area = the main pole number of the pole corresponding to the abnormal power distribution area / the maximum pole number of the line;

[0031] If there is a large branch line, query the corresponding pole of the abnormal power distribution area and enter step S23;

[0032] S23. Judge whether the main pole number of the pole corresponding to the abnormal power distribution area is the main pole number of the large branch line:

[0033] If not, the line position segment of the abnormal power distribution area = the main pole number of the pole corresponding to the abnormal power distribution area / the maximum value of all main pole numbers in the line; if so, the line position segment of the abnormal power distribution area = the secondary pole number of the pole corresponding to the abnormal power distribution area / the maximum pole number of the large branch line.

[0034] Furthermore, finding the first-end voltage switch corresponding to the line where the abnormal power distribution area is located based on the line where the abnormal power distribution area is located includes:

[0035] S31. Conduct topological analysis on all lines in the monitored area and count the first-end switches of all line position segments;

[0036] S32. According to the line to which the abnormal power distribution area belongs and the first-end switches of each line position segment, find the first-end switch of the line to which the abnormal power distribution area belongs;

[0037] S33. Obtain the voltage value of the head switch of the line to which the abnormal substation area belongs during the monitoring period.

[0038] Further, in the step S31, a general network model is established by using static topology, with the line switches as nodes and the feeders as connections, forming a two-way linked list structure of equipment - nodes, and query all head switches of the line position segments based on the general network model.

[0039] In a second aspect, the present invention provides a voltage anomaly detection and location system based on signals of multiple monitoring points, including:

[0040] A screening module for obtaining voltage signals of multiple monitoring points of each substation area, and statistically analyzing abnormal substation areas with abnormal voltage signals and the affected users to obtain a list of abnormal substation areas and abnormal users under the substation areas;

[0041] An abnormal substation area location module for analyzing the line position where the abnormal substation area is located in the list of abnormal substation areas and abnormal users under the substation areas by first judging the branch line and then judging the pole number to obtain the line position segment where the abnormal substation area is located;

[0042] A head voltage switch determination module for finding the head voltage switch corresponding to the line where the abnormal substation area is located based on the line position segment where the abnormal substation area is located.

[0043] In a third aspect, the present invention provides an electronic device, including:

[0044] At least one processor; and,

[0045] A memory communicatively connected to the at least one processor; wherein,

[0046] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the voltage anomaly detection and location method based on signals of multiple monitoring points according to any one of the first aspects of the present invention.

[0047] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, it implements the voltage anomaly detection and location method based on signals of multiple monitoring points according to any one of the first aspects of the present invention.

[0048] Compared with the prior art, the present invention has at least the following beneficial technical effects:

[0049] 1) In the analysis of the line position in the substation area, first judge from the branch line, and then enter the pole number judgment to query the abnormal position, which greatly improves the query efficiency. After determining the branch line and the pole number, the static topology analysis method can be used to quickly query the position of the head switch, thereby further improving the query efficiency. The operation and maintenance personnel can quickly take actions to repair the faults, improving the reliability and stability of the power system.

[0050] 2) The present invention can quickly count all abnormal substations, improving the efficiency of detection and positioning. Considering the proportion of abnormal users and the frequency of user abnormalities comprehensively, a substation area abnormality scoring model is established. The user abnormality frequency coefficient is added to the substation area abnormality scoring model to punish high-frequency abnormalities. It not only considers the proportion of abnormal users but also punishes high-frequency abnormalities, and can not only perform quick statistics but also monitor high-frequency abnormal users. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a flowchart of a voltage abnormality detection and positioning method based on the analysis of signals from multiple monitoring points provided by the present invention;

[0052] Figure 2 It is a structural block diagram of a voltage abnormality detection and positioning device based on the analysis of signals from multiple monitoring points provided by an embodiment of the present invention;

[0053] Figure 3 It is a block diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0054] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0055] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of the present invention 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 used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product or equipment that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or equipment.

[0056] The present invention will be further described in detail below with reference to the accompanying drawings:

[0057] Embodiment 1

[0058] Refer to Figure 1 , this embodiment provides a voltage abnormality detection and location method based on the analysis of signals from multiple monitoring points. By setting multiple monitoring points in each substation area, the voltage data of the substation area is collected in real time, and the substation area with voltage abnormality, as well as the line where the abnormal substation area is located and the voltage switch at the head end of the line, are quickly located according to the abnormal voltage situation. The specific steps are as follows:

[0059] Step 1: Count the abnormal substation areas and affected users. Through the analysis of the voltage signals of multiple monitoring points in each substation area, count the abnormal substation areas with abnormal voltage signals and the affected users to obtain a list of abnormal substation areas and abnormal users under the substation areas.

[0060] Step 2: Analysis of the line position of the abnormal substation area: According to the list of abnormal substation areas and abnormal users under the substation areas obtained in Step 1, analyze the line position where the abnormal substation area in the list is located to obtain the line position segment where the abnormal substation area is located.

[0061] Step 3: Analysis of the voltage switch at the head end of the line: Through the line where the abnormal substation area is located obtained in Step 2, find the voltage switch at the head end corresponding to the line where the abnormal substation area is located, and obtain the voltage value of the head end voltage switch on the day when the substation area is abnormal.

[0062] Step 4: Analyze the voltage value of the head end voltage switch at the current time of the substation area abnormality in Step 3, so as to analyze the cause of the substation area abnormality;

[0063] Among them, Step 1 includes the following steps:

[0064] S11. Select a specified day, and count all the abnormal substation areas with abnormal voltage signals through the analysis of the signals of multiple monitoring points in each substation area;

[0065] S12. Statistically analyze the voltage of low-voltage users on the same day in all substations to facilitate the screening of abnormal substations.

[0066] S13. Calculate the abnormal score based on the substation abnormal scoring model, and screen out abnormal substations according to the abnormal score.

[0067] S14. Query for missing abnormal users, query all time periods when the voltage of all low-voltage users under the substation is abnormal, and determine whether there is an intersection between all time periods of the statistically abnormal voltage of low-voltage users and the voltage abnormal time periods of the abnormal substation: If there is an intersection, output the abnormal substation and the list of abnormal users under the substation; If there is no intersection, do not include it in the list of abnormal substations and abnormal users under the substation.

[0068] Among them, step 2 includes the following steps:

[0069] S21. Determine whether each line under all monitoring points has a large branch line. If not, record the maximum pole number of the line. If so, record the main pole number corresponding to the large branch line and the maximum pole number of each large branch line for use in querying the line to which the abnormal substation belongs in the next step.

[0070] S22. Based on the abnormal substation, find the line to which the abnormal substation belongs, and according to the judgment result of the large branch lines in all lines in S21, confirm whether the line to which the abnormal substation belongs has a large branch line: If there is no large branch line, query the corresponding pole of the abnormal substation, and the position segment of the abnormal substation in the line = the main pole number of the corresponding pole of the abnormal substation / the maximum value of all main pole numbers in the line; where the maximum value of all main pole numbers in the line is the maximum pole number of the line in S21; If there is a large branch line, query the corresponding pole of the abnormal substation and proceed to step S23.

[0071] S23. Determine whether the main pole number of the pole corresponding to the abnormal substation is the main pole number of the large branch line: If not, the position segment of the abnormal substation in the line = the main pole number of the corresponding pole of the abnormal substation / the maximum value of all main pole numbers in the line; If so, the position segment of the abnormal substation in the line = the secondary pole number of the corresponding pole of the abnormal substation / the maximum value of all main pole numbers in the line.

[0072] As a specific embodiment, step 3 includes the following steps:

[0073] S31. Conduct line topology analysis, perform topology analysis on all lines in the monitored area, and count the head switches of all line position segments.

[0074] S32. Based on the line to which the abnormal substation belongs found in steps S22 and S23, find the head switch corresponding to the line to which the abnormal substation belongs according to S31.

[0075] S33. Obtain the line head switch according to S32, and then obtain the voltage value of the head switch on the day when the substation area is abnormal.

[0076] As a specific embodiment, in the fourth step, the abnormal reasons include unreasonable distribution transformer gears and too long line routing.

[0077] As a specific embodiment, in the S31 step, a general network model is established by using static topology, with the line switch as the node and the feeder as the connection line, forming a two-way linked list structure of equipment - node, supporting fast query and traversal, so as to improve the rapid search for the line head switch.

[0078] As a specific embodiment:

[0079] The core algorithm of step 1 is as follows:

[0080] I. Definition of core parameters

[0081] T = {t1, t2, …, t n} represents the set of all abnormal substations in a certain area, and each ti represents an independent substation area;

[0082] U i = {u i1 , u i2 , …, u im} represents the set of all voltage - abnormal users under the substation area t i , where u i1 is the first voltage - abnormal user of the substation area t i , and u im is the mth voltage - abnormal user of the substation area t i ;

[0083] represents the set of voltage - abnormal time periods of user u, and each interval represents an abnormal event;

[0084] Among them, represents the ith voltage - abnormal time period of user u; is the start time of the ith voltage - abnormal time period of user u, is the end time of the ith voltage - abnormal time period of user u;

[0085] represents the set of voltage - abnormal time periods of the substation area t, and each interval represents an abnormal event, represents the ith voltage - abnormal time period of the substation area t; is the start time of the ith voltage - abnormal time period of the substation area t, is the end time of the ith voltage - abnormal time period of the substation area t;

[0086] α = 0.2 represents the determination threshold for the proportion of abnormal users (20%).

[0087] II. Space-time constraint screening formula:

[0088] 1) Abnormal user determination function, used to determine abnormal users in substation area t. The abnormal user determination function is as follows:

[0089]

[0090] Determine whether there is an intersection between the abnormal time period of user u and the abnormal time period of substation area t, used to screen users associated with the abnormal time of the substation area. f(u, t) = 1 indicates that user u is an abnormal user, and f(u, t) = 0 indicates that user u is a normal user.

[0091] If any abnormal time period [s u , e u of user u overlaps with any abnormal time period [s t , e t of substation area t (i.e., max(s u , s t ) < min(e u , e t ))), then return f(u, t) = 1; otherwise return f(u, t) = 0.

[0092] 2) Substation area abnormal score model S(t i ), used to calculate the ratio of the number of abnormal users in substation area t (here, each user with voltage abnormality is marked as an abnormal user) to the total number of users:

[0093]

[0094] Among them, is the proportion of time-correlated abnormal users, is the user abnormal frequency coefficient, which not only considers the proportion of abnormal users but also punishes high-frequency abnormalities (e.g., multiple abnormalities of a user may reflect serious problems).

[0095] The substation area abnormal score model is used to calculate the comprehensive abnormal score of substation area t i , including two dimensions:

[0096] A. Proportion of abnormal users: That is, the proportion of users associated with the abnormal time period of the substation area;

[0097] B. User abnormal frequency: That is, the logarithmic weighting of the average number of abnormal times of users.

[0098] Numerator: Count the total number of users associated with the abnormal time period of the substation area, denominator: The total number of users in the substation area, used to normalize the ratio, logarithmic term: Represents the total number of abnormal occurrences for all users, is the average number of abnormal occurrences per user, plus 1 to avoid taking the logarithm of zero.

[0099] 3) Screening decision function:

[0100]

[0101] Determine whether the power distribution area is abnormal based on the comprehensive abnormal score and the threshold.

[0102] Scoring threshold: S(t i ) ≥ 0.2 (the proportion of abnormal users ≥ 20% and meet the standard after weighting). The minimum number of abnormal users Avoid misjudgment of small samples. For example, if only 1 - 2 users are abnormal, it may be accidental. If the conditions are met, mark it as an abnormal power distribution area (g(t i ) = 1), otherwise ignore it.

[0103] III. Formula Explanation

[0104] 1. Optimization of spatio-temporal overlap detection

[0105] Adopt an improved interval tree algorithm to accelerate the judgment:

[0106]

[0107] That is, check whether there is an intersection between the abnormal time period of the user and the abnormal time period of the power distribution area.

[0108] 2. Decomposition of abnormal score

[0109]

[0110] Abnormal score = temporal correlation degree × log(abnormal intensity)

[0111] IV. Algorithm Execution Process

[0112]

[0113] Input represents the data input by the system. Spatio-temporal data partitioning means partitioning all monitoring data according to the power distribution area. Through f(u im ,t i ) screen out the users associated with the abnormal time period of the power distribution area; calculate the comprehensive abnormal score of the power distribution area through S(t i ); finally determine the abnormal power distribution area through g(t i ) and output the list.

[0114] V. Optimization of Computational Complexity

[0115] TopoSearch(G, t i) = FindHeadSwitch(t i ).

[0116] Input: Grid topology graph G (nodes are switches, edges are feeders), target substation area t i ;

[0117] Output: List of abnormal substation areas and abnormal users under the substation area

[0118] Model construction: Abstract the power grid as a graph G=(V, E), where V is the switch node and E is the feeder connection relationship, forming a two-way linked list of equipment - nodes. Query process: Starting from the line to which the substation area t i belongs, traverse the linked list in the reverse direction to the head node (i.e., the node with an in-degree of 0).

[0119] Optimization effect:

[0120] The query time complexity is reduced from O(m) to O(1), where m is the number of line nodes, and it is applicable to frequent head switch positioning scenarios.

[0121] VI. Parameter sensitivity analysis

[0122] During the screening process of abnormal substation areas, the threshold parameter α and the minimum number of abnormal users are the key parameters affecting the results.

[0123] Sensitivity analysis of the threshold parameter α

[0124] α = 0.2: Screening threshold, requiring S(t i ) ≥ α (proportion of abnormal users ≥ 20%).

[0125] Sensitivity function:

[0126] Function of the detection rate of abnormal substation areas changing with α:

[0127]

[0128] When α → 0, P(α) → 1 (all substation areas are marked as abnormal);

[0129] When α → 1, P(α) → 0 (only extremely abnormal substation areas are detected);

[0130] By adjusting α, the false alarm rate and the missed detection rate can be balanced. For example, α = 0.2 can filter out occasional anomalies (such as temporary load fluctuations).

[0131] Sensitivity analysis of the minimum number of abnormal users:

[0132] ∑f(u j ,t i ) ≥ 3: Require that each abnormal substation area is associated with at least 3 abnormal users.

[0133] Function showing how the result stability of the sensitivity function varies with the minimum number of users k:

[0134]

[0135] When k = 1, it may contain a large amount of noise (such as a single user device failure);

[0136] When k ≥ 3, the result stability is significantly improved (multiple user anomalies need to occur simultaneously);

[0137] If Stability(k) ≥ 0.95, the parameter k is considered reasonable.

[0138] Example 2

[0139] Please refer to Figure 2 , in this example, a voltage anomaly detection and location device based on the analysis of signals from multiple monitoring points is provided, including:

[0140] A screening module for obtaining the voltage signals of multiple monitoring points in each substation area, counting the abnormal substation areas and the affected users with abnormal voltage signals, and obtaining a list of abnormal substation areas and abnormal users under the substation areas;

[0141] An abnormal substation area location module for analyzing the line position where the abnormal substation area is located in the list of abnormal substation areas and abnormal users under the substation area by first judging the branch line and then judging the pole number, and obtaining the line position segment where the abnormal substation area is located;

[0142] A first-end voltage switch determination module for finding the first-end voltage switch corresponding to the line where the abnormal substation area is located based on the line position segment where the abnormal substation area is located.

[0143] All relevant contents of each step involved in the example of the foregoing voltage anomaly detection and location method based on the analysis of signals from multiple monitoring points can be cited in the function description of the corresponding functional modules of a voltage anomaly detection and location device based on the analysis of signals from multiple monitoring points in the embodiments of the present invention, and will not be elaborated herein.

[0144] Example 3

[0145] Refer to Figure 3, this embodiment provides an electronic device, which includes a processor and a memory, and the processor is connected to the memory through a bus; the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of a voltage anomaly detection and location method based on the analysis of signals at multiple monitoring points. The bus may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 3 only one line is shown in [the figure], but it does not mean that there is only one bus or one type of bus.

[0146] Embodiment 4

[0147] This embodiment provides a storage medium, specifically a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in an electronic device, used to store programs and data. It can be understood that the computer-readable storage medium here can include both the built-in storage medium in the electronic device and, of course, the extended storage medium supported by the electronic device. The computer-readable storage medium provides storage space, and this storage space stores the operating system of the terminal. Moreover, one or more instructions suitable for being loaded and executed by the processor are stored in this storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. One or more instructions stored in the computer-readable storage medium can be loaded and executed by the processor to implement the corresponding steps of the voltage anomaly detection and location method based on the analysis of signals at multiple monitoring points in the above embodiment.

[0148] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a device, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0149] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (apparatus), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, 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 generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0150] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions in Figure 1 one flow or multiple flows and / or blocks Figure 1The functions specified in one or more boxes.

[0151] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide for implementing the steps for the functions specified in Figure 1 one process or more processes and / or boxes Figure 1 the functions specified in one box or more boxes.

[0152] Embodiment 5

[0153] This embodiment provides a computer program product, including a non-volatile computer-readable storage medium. The non-volatile computer-readable storage medium stores a computer program product. When the computer program is executed by a processor, the steps of the methods described in various embodiments of the present application are implemented.

[0154] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or fully authorized by all parties. And the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions.

[0155] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0156] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: It is still possible to modify the specific implementation manners of the present invention or make equivalent replacements. Any modification or equivalent replacement that does not deviate from the spirit and scope of the present invention should be covered by the protection scope of the claims of the present invention.

Claims

1. A method for detecting and locating voltage anomalies based on signals from multiple monitoring points, characterized in that Including: Obtain the voltage signals of multiple monitoring points in each substation area, count the abnormal substation areas with abnormal voltage signals and the affected users, and obtain a list of abnormal substation areas and abnormal users under the substation areas; Adopt a method of first judging the branch line and then judging the pole number to analyze the line position where the abnormal substation area in the list of abnormal substation areas and abnormal users under the substation area is located, and obtain the line position segment where the abnormal substation area is located; Based on the line position segment where the abnormal substation area is located, find the first-end voltage switch corresponding to the line where the abnormal substation area is located.

2. The voltage abnormality detection and location method based on signals of multiple monitoring points according to claim 1, characterized in that The obtaining the voltage signals of multiple monitoring points in each substation area, counting the abnormal substation areas with abnormal voltage signals and the affected users, and obtaining a list of abnormal substation areas and abnormal users under the substation area includes: Count all substation areas with voltage abnormalities during the monitoring period; Count the voltages of low-voltage users under all substation areas during the monitoring period; Screen out abnormal substation areas based on the number of abnormal users; Query all time periods when the voltages of all low-voltage users under the substation area are abnormal, and judge whether there is an intersection between the time period of low-voltage user voltage abnormality and the time period of substation area voltage abnormality: If there is an intersection, add the low-voltage user and the abnormal substation area to the list of abnormal substation areas and abnormal users under the substation area; If there is no intersection, do not include it in the list of abnormal substation areas and abnormal users under the substation area.

3. The voltage anomaly detection and location method based on signals from multiple monitoring points according to claim 2, wherein The screening out abnormal substation areas based on the number of abnormal users includes: Calculating an abnormal score based on a substation area abnormal scoring model, and the substation area abnormal scoring model is: Among them, The S(t i ) is the anomaly score of the power distribution area t i ; is the proportion of users with time-related anomalies, is the user anomaly frequency coefficient; U i is the set of all voltage anomaly users under the power distribution area t i , A u is the set of voltage anomaly time periods of user u; f(u, t i ) is the anomaly user judgment function; [s u , e u represents the user anomaly time period; [s t , e t represents the power distribution area anomaly time period; A t represents the set of voltage anomaly time periods of the power distribution area t; Determine whether the power distribution area is an abnormal power distribution area according to the screening decision function, and the screening decision function g(t i ) is as follows: Wherein, α is a screening threshold; k is a minimum number of users threshold.

4. The voltage abnormality detection and location method based on signals of multiple monitoring points according to claim 2, wherein, The α is 0.2 and the k is 3.

5. The voltage abnormality detection and location method based on signals of multiple monitoring points according to claim 1, characterized in that The adopting a method of first judging the branch line and then judging the pole number to analyze the line position where the abnormal substation area in the list of abnormal substation areas and abnormal users under the substation area is located, and obtaining the line position segment where the abnormal substation area is located includes: S21. Judge whether there is a large branch line in each line under all monitoring points: if not, record the maximum pole number of the line; if so, record the main pole number corresponding to the large branch line and the maximum pole number of each large branch line; S22. According to the abnormal substation area, find the line to which the abnormal substation area belongs, and based on the judgment results of the large branch lines in all lines, confirm whether there is a large branch line in the line to which the abnormal substation area belongs: If there is no large branch line, query the corresponding pole tower of the abnormal substation area, and the line position segment of the abnormal substation area = the main pole number of the corresponding pole tower of the abnormal substation area / the maximum pole number of the line; If there is a large branch line, query the corresponding pole tower of the abnormal substation area and enter step S23; S23. Judge whether the main pole number of the pole tower corresponding to the abnormal substation area is the main pole number of the large branch line: If not, the line position segment of the abnormal substation area = the main pole number of the corresponding pole tower of the abnormal substation area / the maximum value of all main pole numbers in the line; if so, the line position segment of the abnormal substation area = the secondary pole number of the corresponding pole tower of the abnormal substation area / the maximum pole number of the large branch line.

6. The voltage abnormality detection and location method based on signals of multiple monitoring points according to claim 1, characterized in that The finding the first-end voltage switch corresponding to the line where the abnormal substation area is located based on the line where the abnormal substation area is located includes: S31. Conduct a topology analysis on all lines in the monitored area and count the first-end switches of all line position segments; S32. According to the line to which the abnormal substation area belongs and the first-end switches of each line position segment, find the first-end switch of the line to which the abnormal substation area belongs. S33. Obtain the voltage value of the head switch of the line to which the abnormal substation belongs during the monitoring period.

7. The voltage abnormality detection and location method based on signals of multiple monitoring points according to claim 6, wherein In step S31, a general network model is established using static topology, where line switches are nodes and feeders are connections, forming a two-way linked list structure of devices - nodes. Based on the general network model, query the head switches of all line position segments.

8. A voltage anomaly detection and location system based on signals from multiple monitoring points, characterized in that, It includes: A screening module for obtaining voltage signals of multiple monitoring points for each substation, statistically analyzing abnormal substations with abnormal voltage signals and the affected users, and obtaining a list of abnormal substations and abnormal users under the substations. An abnormal substation positioning module for analyzing the line positions where the abnormal substations in the list of abnormal substations and abnormal users under the substations are located by first judging the branch lines and then judging the pole numbers, and obtaining the line position segments where the abnormal substations are located. A head voltage switch determination module for finding the head voltage switch corresponding to the line where the abnormal substation is located based on the line position segment where the abnormal substation is located.

9. An electronic device, characterized in that, It includes: At least one processor; And, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the voltage anomaly detection and positioning method based on multiple monitoring point signals as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the voltage anomaly detection and positioning method based on multiple monitoring point signals as described in any one of claims 1 to 7.

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