A method, apparatus, equipment, medium, and product for troubleshooting abnormal line loss.

Abstract

This invention discloses a method, apparatus, equipment, medium, and product for investigating abnormal line losses. The method includes: acquiring first power data and second power data collected at each sampling time within a preset investigation period; the first power data is the power data of the transformer equipment, and the second power data is the power data of all users associated with the transformer equipment; calculating the line resistance at each sampling time based on the first power data and the second power data; and determining the line loss anomaly investigation result for the investigation period based on the line resistance at each sampling time. This technical solution solves the problem of difficult line loss anomaly investigation in low-voltage distribution areas. By using the power data of the transformer equipment and the power data of each user in the power supply area, time stability analysis of the line resistance is performed. Based on the stability analysis results, line loss anomalies can be located, which helps improve the reliability and scenario adaptability of line loss anomaly investigation.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, and in particular to a method, apparatus, equipment, medium, and product for investigating abnormal line loss. Background Technology

[0002] Currently, in the power system, reducing line loss mainly relies on three methods: (1) Inspectors carry infrared thermometers to check the operation of the lines, find hot spots, and observe whether there is any illegal connection; (2) Verify the electricity meters of users with large electricity consumption in the power supply area, determine the accuracy of the electricity meters, and check whether the electricity meters have been illegally modified; (3) Install metering devices at important power line nodes, calculate the management line loss of the power supply area after the metering device, and assess whether there is any abnormal line loss in the power supply area.

[0003] However, all three methods have obvious limitations. Method (1) infrared temperature measuring equipment cannot complete temperature measurement during the day, and patrol personnel work during the day and cannot enter the premises for inspection at night. Method (2) is of little effect on low-voltage distribution areas with small power consumption and a large number of units, making it difficult to locate abnormal line losses. Method (3) after installing branch metering devices, it is necessary to record the power consumption changes of all metering devices in the branch power supply area one by one, which is cumbersome and difficult to operate. Summary of the Invention

[0004] This invention provides a method, apparatus, equipment, medium, and product for investigating abnormal line losses, in order to solve the problem of difficulty in investigating abnormal line losses in low-voltage distribution areas. By using power data from transformer equipment and power data from each user in the power supply area, time stability analysis is performed on the line resistance. Based on the stability analysis results, abnormal line losses can be located, which helps to improve the reliability and adaptability of abnormal line loss investigation.

[0005] According to one aspect of the present invention, a method for investigating abnormal line loss is provided, the method comprising:

[0006] Acquire the first power data and the second power data collected at each sampling time within a preset investigation period; wherein, the first power data is the power data of the transformer equipment, and the second power data is the power data of all users associated with the transformer equipment;

[0007] Calculate the line resistance at each sampling time based on the first power data and the second power data;

[0008] Based on the line resistance at each sampling time, the line loss anomaly investigation results for the investigation cycle are determined.

[0009] According to another aspect of the present invention, a device for investigating abnormal line loss is provided, the device comprising:

[0010] The data acquisition module is used to acquire first power data and second power data collected at each sampling time within a preset investigation period; wherein, the first power data is the power data of the transformer equipment, and the second power data is the power data of all users associated with the transformer equipment;

[0011] The resistance calculation module is used to calculate the line resistance at each sampling time based on the first power data and the second power data;

[0012] The investigation result determination module is used to determine the line loss anomaly investigation result of the investigation period based on the line resistance at each sampling time.

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

[0014] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable 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 line loss anomaly investigation method according to any embodiment of the present invention.

[0015] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a processor to execute and implement the line loss anomaly investigation method described in any embodiment of the present invention.

[0016] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method for investigating line loss anomalies as described in any embodiment of the present invention.

[0017] The technical solution of this invention involves acquiring first and second power data collected at various sampling times within a preset investigation period. The first power data refers to the power data of the transformer equipment, and the second power data refers to the power data of all users associated with the transformer equipment. Based on the first and second power data, the line resistance at each sampling time is calculated. Based on the line resistance at each sampling time, the line loss anomaly investigation result for the investigation period is determined. This technical solution solves the problem of difficult line loss anomaly investigation in low-voltage distribution areas. By using the power data of the transformer equipment and the electricity metering data of each user in the power supply area, time stability analysis of the line resistance is performed. Based on the stability analysis results, line loss anomalies are located, which helps improve the reliability and scenario adaptability of line loss anomaly investigation.

[0018] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of a method for investigating abnormal line loss according to Embodiment 1 of the present invention;

[0021] Figure 2 This is a flowchart of a method for investigating abnormal line loss according to Embodiment 2 of the present invention;

[0022] Figure 3 This is a schematic diagram of a line loss anomaly detection device provided according to Embodiment 3 of the present invention;

[0023] Figure 4 This is a schematic diagram of the structure of an electronic device that implements the line loss anomaly investigation method of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be used interchangeably where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices. The acquisition, storage, use, and processing of data in the technical solutions of this application all comply with the relevant provisions of national laws and regulations.

[0026] Example 1

[0027] Figure 1 This is a flowchart illustrating a method for investigating abnormal line losses according to Embodiment 1 of the present invention. This embodiment is applicable to scenarios involving investigating abnormal line losses in power systems, particularly in cases of electricity theft. This method can be executed by a device for investigating abnormal line losses, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the method includes:

[0028] S110. Obtain the first power data and the second power data collected at each sampling time within the preset investigation period; wherein, the first power data is the power data of the transformer equipment, and the second power data is the power data of all users associated with the transformer equipment.

[0029] This solution can be executed by a line management platform, which can acquire first and second power data within the target power grid according to a preset sampling interval. The sampling interval can be 10 minutes, 1 hour, or other time intervals, and the investigation period can be an integer multiple of the sampling interval; for example, if the sampling interval is 10 minutes, the investigation period is one day. Therefore, one investigation period can include multiple sampling times.

[0030] The first power data can be power data collected by metering equipment installed on the transformer. All users associated with the transformer can be all users within the transformer's power supply area. The second power data can be power data collected by metering equipment on the user lines within the transformer's power supply area. The metering equipment can be an electricity meter, and the power data can include voltage, current, and energy data. Energy data can be obtained through meter readings.

[0031] S120. Calculate the line resistance at each sampling time based on the first power data and the second power data.

[0032] Understandably, after obtaining the first and second power data, the line management platform can calculate the line resistance at each sampling time based on these data. For example, for power data at the same sampling time, the line management platform can sum the current data of each user within the transformer's power supply area to obtain the total user current, and then subtract the transformer current from the total user current to obtain the current difference. Similarly, the line management platform can sum the energy data of each user within the transformer's power supply area to obtain the total user energy, and then subtract the transformer energy from the total user energy to obtain the energy difference. Based on Joule's law, the line management platform can use the energy difference and current difference to calculate the line resistance at each sampling time.

[0033] S130. Based on the line resistance at each sampling time, determine the line loss anomaly investigation results for the investigation cycle.

[0034] The line management platform can perform statistical analysis on the line resistance at each sampling time to determine whether the distribution of line resistance is stable over time, thereby determining the results of the line loss anomaly investigation during the investigation cycle. For example, the line management platform can calculate statistical indicators such as the average, variance, and standard deviation of the line resistance based on the line resistance at each sampling time, and determine whether the distribution of line resistance is stable over time based on these statistical indicators.

[0035] The technical solution of this invention involves acquiring first and second power data collected at various sampling times within a preset investigation period. The first power data represents the power data of the transformer equipment, and the second power data represents the power data of all users associated with the transformer equipment. Based on the first and second power data, the line resistance at each sampling time is calculated. Based on the line resistance at each sampling time, the line loss anomaly investigation result for the investigation period is determined. This technical solution solves the problem of difficult line loss anomaly investigation in low-voltage distribution areas. By using the power data of the transformer equipment and the power data of each user in the power supply area, time stability analysis of the line resistance is performed. Based on the stability analysis results, line loss anomalies are located, which helps improve the reliability and scenario adaptability of line loss anomaly investigation.

[0036] Example 2

[0037] Figure 2 This is a flowchart of a method for investigating abnormal line loss according to Embodiment 2 of the present invention. This embodiment is a refinement based on the above embodiment. Figure 2 As shown, the method includes:

[0038] S210. Obtain first power data and second power data collected at each sampling time within a preset investigation period; wherein, the first power data is the power data of the transformer equipment, and the second power data is the power data of all users associated with the transformer equipment; the power data includes current data and energy data.

[0039] S220. Calculate the current difference at each sampling time based on the first current data and the second current data, and calculate the energy difference at each sampling time based on the first energy data and the second energy data.

[0040] In this scheme, the first current data within a screening cycle can be represented by vector I1, and the second current data within a screening cycle can be represented by matrix I2. The expressions for I1 and I2 are as follows:

[0041]

[0042] In I1, each element represents the first current value at a sampling time, each column of I2 represents the second current data of a user, and each element represents the second current value of a user at a sampling time. m represents the number of users, and n represents the number of sampling times.

[0043] The current difference at each sampling time within a screening cycle can be represented by the vector ΔI:

[0044] Where k represents the user identifier index.

[0045] The first energy data within a screening period can be represented by vector W1, and the second energy data within a screening period can be represented by matrix W2. The expressions for W1 and W2 are as follows:

[0046]

[0047] In W1, each element represents the first energy value at a sampling time, each column in W2 represents the second energy data of a user, and each element represents the second energy value of a user at a sampling time. m represents the number of users, and n represents the number of sampling times.

[0048] The current difference at each sampling time within a screening cycle can be represented by the vector ΔW:

[0049] Where k represents the user identifier index.

[0050] S230. Calculate the line resistance at each sampling time based on the current difference and energy difference at each sampling time.

[0051] Based on the above scheme, the step of calculating the line resistance at each sampling time according to the current difference and the energy difference at each sampling time includes:

[0052] Based on the current difference and energy difference at each sampling time, and using Joule's law, the line resistance at each sampling time is calculated.

[0053] After obtaining the current difference and energy difference at each sampling time, the line management platform can calculate the line resistance at each sampling time based on Joule's law. Specifically, Joule's law can be expressed as: Where r represents resistance, W represents the heat generated by the current flowing through the resistor, I represents the current flowing through the resistor, and t represents the duration of the current flowing through the resistor. Therefore, the line resistance at each sampling time within a troubleshooting cycle can be expressed as:

[0054]

[0055] In R, each element represents the line resistance value at a sampling time.

[0056] S240. Perform a T-test based on the line resistance at each sampling time to determine the line loss anomaly investigation results for the investigation period.

[0057] It's easy to understand that illegal electricity thieves don't steal electricity around the clock to avoid detection by power company inspectors; they usually steal electricity at night by tampering with lines. Therefore, performing a T-test on the line resistance at multiple sampling times can help identify electricity theft and pinpoint abnormal line losses. The T-test is a statistical method used to compare whether there is a significant difference between the means of two sets of data. It is mainly used for normally distributed data with a small sample size (e.g., less than 30 samples) and an unknown population standard deviation.

[0058] The steps for calculating the T-test are as follows:

[0059] (1) Propose hypotheses: For example, H0: There is an abnormality in line loss; H1: There is no abnormality in line loss.

[0060] (2) Collect sample data: Ensure that the sample data is independent and check for homogeneity of variance.

[0061] (3) Calculate the statistic: Calculate using the formula. X1 and X2 represent the means of the two groups of samples, respectively, and SE represents the standard error.

[0062] (4) Look up the t-distribution table: get the p value. If the p value is less than the significance level (e.g., 0.05), then reject the null hypothesis.

[0063] In this scheme, the line management platform can divide the line resistance at multiple sampling times within a troubleshooting cycle into two groups, such as G1 and G2. The expressions for G1 and G2 are as follows:

[0064]

[0065] Based on G1 and G2, the line management platform can calculate the difference d between G1 and G2, and then calculate the sample mean. and standard error s d d、 and s d The expression is as follows:

[0066]

[0067] Based on the sample mean and standard error s d The line management platform can calculate the statistic t, and the formula for calculating t can be expressed as:

[0068]

[0069] Based on the value of the statistic t, the line management platform can determine the results of the line loss anomaly investigation during the investigation period by querying the t-distribution table, i.e., whether there is a line loss anomaly or not.

[0070] In one feasible solution, the result of the line loss anomaly investigation is either that a line loss anomaly exists or that a line loss anomaly does not exist;

[0071] After determining the results of the line loss anomaly investigation during the investigation period, the method further includes:

[0072] If the line loss anomaly investigation result is that there is no line loss anomaly, then the transformer equipment is taken as the target transformer equipment, the set of transformer equipment associated with the target transformer equipment is obtained, and the risk equipment set is determined based on the line resistance data of each transformer equipment in the transformer equipment set.

[0073] If the target transformer is in the set of risky devices and the power factor of the target transformer is higher than the preset power factor threshold, then the line loss anomaly investigation result will be modified to indicate that a line loss anomaly exists.

[0074] Understandably, for electricity theft activities that are constantly linked to the line, the line resistance remains stable, making it difficult to detect such abnormal line losses through line resistance alone. To overcome this problem, the line management platform can cluster all transformers within the target power grid based on their power supply, resulting in multiple transformer sets. The power supply of the transformers in each set is the same or similar.

[0075] The line management platform can use the line resistance of each transformer in the same transformer set at the same sampling time as sample data to perform a T-test and locate risky transformers. It should be noted that abnormal line resistance in the same transformer set could be caused by electricity theft or by line design flaws, such as excessively long or thin lines. Therefore, to rule out abnormal line resistance caused by line design flaws, the line management platform can construct a risky transformer set from the selected risky transformers within the target power grid and obtain the reactive power of each risky transformer in the risky transformer set.

[0076] As is easily understood, during power transmission, electrical energy is converted into magnetic field energy, and reactive energy can be used to represent the magnitude of this conversion. Based on reactive and active energy, the line management platform can calculate the power factor of each risk transformer. If the power factor of a risk transformer is less than a preset power factor threshold, it indicates that the abnormal line resistance of the risk transformer is caused by a line design defect, not by electricity theft, and therefore the risk transformer can be removed from the risk equipment set. If the power factor of a risk transformer is greater than or equal to the preset power factor threshold, it indicates that the abnormal line resistance of the risk transformer is caused by electricity theft. After determining the power factor of all risk transformers in the risk equipment set, the remaining risk transformers in the set are those with abnormal line losses.

[0077] For the line loss anomaly investigation results obtained in S240, if the line loss anomaly investigation result indicates that there is no line loss anomaly, then this transformer is designated as the target transformer, the set of transformers associated with the target transformer is obtained, and the risk equipment set is determined based on the line resistance data of each transformer in the transformer equipment set. If the target transformer is in the risk equipment set, and the power factor of the target transformer is higher than the preset power factor threshold, then the line loss anomaly investigation result corresponding to the target transformer is modified to indicate that there is a line loss anomaly.

[0078] In another feasible solution, the result of the line loss anomaly investigation is either that a line loss anomaly exists or that a line loss anomaly does not exist;

[0079] After determining the results of the line loss anomaly investigation during the investigation period, the method further includes:

[0080] If the line loss anomaly investigation result is that there is no line loss anomaly, then the transformer equipment is taken as the target transformer equipment, the set of transformer equipment associated with the target transformer equipment is obtained, and the risk equipment set is determined based on the line resistance data of each transformer equipment in the transformer equipment set.

[0081] If the target transformer is in the set of risky devices and the voltage of the target transformer is lower than a preset voltage threshold, then the line loss anomaly investigation result will be modified to indicate that a line loss anomaly exists.

[0082] To rule out abnormal line resistance in transformers caused by line design flaws, the line management platform can also obtain the voltage of each risk transformer in the risk equipment set. If the voltage of a risk transformer is greater than or equal to a preset voltage threshold, it indicates that the abnormal line resistance is caused by a line design flaw, not by electricity theft, and therefore the risk transformer can be removed from the risk equipment set. If the voltage of a risk transformer is less than the preset voltage threshold, it indicates that the abnormal line resistance is caused by electricity theft. After completing the voltage determination for all risk transformers in the risk equipment set, the remaining risk transformers in the set are those with abnormal line losses.

[0083] For the line loss anomaly investigation results obtained in S240, if the line loss anomaly investigation result indicates that there is no line loss anomaly, then this transformer is designated as the target transformer, the set of transformers associated with the target transformer is obtained, and the risk equipment set is determined based on the line resistance data of each transformer in the transformer equipment set. If the target transformer is in the risk equipment set, and the voltage of the target transformer is lower than a preset voltage threshold, then the line loss anomaly investigation result corresponding to the target transformer is modified to indicate that there is a line loss anomaly.

[0084] The technical solution of this invention involves acquiring first and second power data collected at various sampling times within a preset investigation period. The first power data represents the power data of the transformer equipment, and the second power data represents the power data of all users associated with the transformer equipment. Based on the first and second power data, the line resistance at each sampling time is calculated. Based on the line resistance at each sampling time, the line loss anomaly investigation result for the investigation period is determined. This technical solution solves the problem of difficult line loss anomaly investigation in low-voltage distribution areas. By using the power data of the transformer equipment and the power data of each user in the power supply area, time stability analysis of the line resistance is performed. Based on the stability analysis results, line loss anomalies are located, which helps improve the reliability and scenario adaptability of line loss anomaly investigation.

[0085] Example 3

[0086] Figure 3 This is a schematic diagram of a line loss anomaly detection device provided in Embodiment 3 of the present invention. Figure 3 As shown, the device includes:

[0087] The data acquisition module 310 is used to acquire first power data and second power data collected at each sampling time within a preset investigation period; wherein, the first power data is the power data of the transformer equipment, and the second power data is the power data of all users associated with the transformer equipment;

[0088] The resistance calculation module 320 is used to calculate the line resistance at each sampling time based on the first power data and the second power data;

[0089] The investigation result determination module 330 is used to determine the line loss anomaly investigation result of the investigation period based on the line resistance at each sampling time.

[0090] In this scheme, optionally, the power data includes current data and electrical energy data;

[0091] The resistance calculation module 320 is specifically used for:

[0092] Based on the first current data and the second current data, calculate the current difference at each sampling time, and based on the first energy data and the second energy data, calculate the energy difference at each sampling time.

[0093] Calculate the line resistance at each sampling time based on the current difference and energy difference at each sampling time.

[0094] Based on the above scheme, the step of calculating the line resistance at each sampling time according to the current difference and the energy difference at each sampling time includes:

[0095] Based on the current difference and energy difference at each sampling time, and using Joule's law, the line resistance at each sampling time is calculated.

[0096] In this embodiment, the investigation result determination module 330 is specifically used for:

[0097] A T-test is performed based on the line resistance at each sampling time to determine the line loss anomaly investigation results for the investigation period.

[0098] In one feasible solution, the result of the line loss anomaly investigation is either that a line loss anomaly exists or that a line loss anomaly does not exist;

[0099] The device further includes:

[0100] The first investigation result correction module is used to determine the line loss anomaly investigation result of the investigation period. If the line loss anomaly investigation result is that there is no line loss anomaly, the transformer equipment is used as the target transformer equipment, the set of transformer equipment associated with the target transformer equipment is obtained, and the risk equipment set is determined according to the line resistance data of each transformer equipment in the transformer equipment set.

[0101] If the target transformer is in the set of risky devices and the power factor of the target transformer is higher than the preset power factor threshold, then the line loss anomaly investigation result will be modified to indicate that a line loss anomaly exists.

[0102] In another feasible solution, the result of the line loss anomaly investigation is either that a line loss anomaly exists or that a line loss anomaly does not exist;

[0103] The device further includes:

[0104] The second investigation result correction module is used to determine the line loss anomaly investigation result of the investigation period. If the line loss anomaly investigation result is that there is no line loss anomaly, the transformer equipment is used as the target transformer equipment, the set of transformer equipment associated with the target transformer equipment is obtained, and the risk equipment set is determined according to the line resistance data of each transformer equipment in the transformer equipment set.

[0105] If the target transformer is in the set of risky devices and the voltage of the target transformer is lower than a preset voltage threshold, then the line loss anomaly investigation result will be modified to indicate that a line loss anomaly exists.

[0106] The line loss anomaly investigation device provided in this embodiment of the invention can execute the line loss anomaly investigation method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0107] Example 4

[0108] Figure 4 A schematic diagram of an electronic device 410 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.

[0109] like Figure 4As shown, the electronic device 410 includes at least one processor 411 and a memory, such as a read-only memory (ROM) 412 or a random access memory (RAM) 413, communicatively connected to the at least one processor 411. The memory stores computer programs executable by the at least one processor. The processor 411 can perform various appropriate actions and processes based on the computer program stored in the ROM 412 or loaded from storage unit 418 into the RAM 413. The RAM 413 may also store various programs and data required for the operation of the electronic device 410. The processor 411, ROM 412, and RAM 413 are interconnected via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0110] Multiple components in electronic device 410 are connected to I / O interface 415, including: input unit 416, such as keyboard, mouse, etc.; output unit 417, such as various types of displays, speakers, etc.; storage unit 418, such as disk, optical disk, etc.; and communication unit 419, such as network card, modem, wireless transceiver, etc. Communication unit 419 allows electronic device 410 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0111] Processor 411 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 411 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 411 performs the various methods and processes described above, such as methods for troubleshooting line loss anomalies.

[0112] In some embodiments, the method for troubleshooting line loss anomalies may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 418. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 410 via ROM 412 and / or communication unit 419. When the computer program is loaded into RAM 413 and executed by processor 411, one or more steps of the method for troubleshooting line loss anomalies described above may be performed. Alternatively, in other embodiments, processor 411 may be configured to perform the method for troubleshooting line loss anomalies by any other suitable means (e.g., by means of firmware).

[0113] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0114] Computer programs used to implement the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable line loss anomaly detection device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0115] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0116] To provide interaction with a user, the systems and techniques described herein 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 pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; 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 sound input, voice input, or tactile input).

[0117] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0118] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0119] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0120] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. 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 substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for investigating abnormal line losses, applicable to scenarios involving electricity theft through wiring in power systems, characterized in that, The method includes: Acquire the first power data and the second power data collected at each sampling time within a preset investigation period; wherein, the first power data is the power data of the transformer equipment, and the second power data is the power data of all users associated with the transformer equipment; Calculate the line resistance at each sampling time based on the first power data and the second power data; Based on the line resistance at each sampling time, determine the line loss anomaly investigation results for the investigation cycle; The power data includes current data and electrical energy data; The step of calculating the line resistance at each sampling time based on the first power data and the second power data includes: Based on the first current data and the second current data, calculate the current difference at each sampling time, and based on the first energy data and the second energy data, calculate the energy difference at each sampling time. Calculate the line resistance at each sampling time based on the current difference and energy difference at each sampling time.

2. The method according to claim 1, characterized in that, The calculation of the line resistance at each sampling time based on the current difference and energy difference at each sampling time includes: Based on the current difference and energy difference at each sampling time, and using Joule's law, the line resistance at each sampling time is calculated.

3. The method according to claim 1, characterized in that, The determination of the line loss anomaly investigation results for the investigation period based on the line resistance at each sampling time includes: A T-test is performed based on the line resistance at each sampling time to determine the line loss anomaly investigation results for the investigation period.

4. The method according to claim 1, characterized in that, The result of the line loss anomaly investigation is either that a line loss anomaly exists or that a line loss anomaly does not exist; After determining the results of the line loss anomaly investigation during the investigation period, the method further includes: If the line loss anomaly investigation result is that there is no line loss anomaly, then the transformer equipment is taken as the target transformer equipment, the set of transformer equipment associated with the target transformer equipment is obtained, and the risk equipment set is determined based on the line resistance data of each transformer equipment in the transformer equipment set. If the target transformer is in the set of risky devices and the power factor of the target transformer is higher than the preset power factor threshold, then the line loss anomaly investigation result will be modified to indicate that a line loss anomaly exists.

5. The method according to claim 1, characterized in that, The result of the line loss anomaly investigation is either that a line loss anomaly exists or that a line loss anomaly does not exist; After determining the results of the line loss anomaly investigation during the investigation period, the method further includes: If the line loss anomaly investigation result is that there is no line loss anomaly, then the transformer equipment is taken as the target transformer equipment, the set of transformer equipment associated with the target transformer equipment is obtained, and the risk equipment set is determined based on the line resistance data of each transformer equipment in the transformer equipment set. If the target transformer is in the set of risky devices and the voltage of the target transformer is lower than a preset voltage threshold, then the line loss anomaly investigation result will be modified to indicate that a line loss anomaly exists.

6. A device for detecting abnormal line loss, configured in a scenario for detecting electricity theft through wiring in a power system, characterized in that, The device includes: The data acquisition module is used to acquire first power data and second power data collected at each sampling time within a preset investigation period; wherein, the first power data is the power data of the transformer equipment, and the second power data is the power data of all users associated with the transformer equipment; The resistance calculation module is used to calculate the line resistance at each sampling time based on the first power data and the second power data; The investigation result determination module is used to determine the line loss anomaly investigation result of the investigation period based on the line resistance at each sampling time. The power data includes current data and electrical energy data; The resistance calculation module is specifically used for: Based on the first current data and the second current data, calculate the current difference at each sampling time, and based on the first energy data and the second energy data, calculate the energy difference at each sampling time. Calculate the line resistance at each sampling time based on the current difference and energy difference at each sampling time.

7. 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 executable 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 line loss anomaly investigation method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method for troubleshooting line loss anomalies as described in any one of claims 1-5.

9. A computer program product comprising a computer program that, when executed by a processor, implements a method for investigating abnormal line loss according to any one of claims 1-5.

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