Metering box electricity stealing detection method, system and equipment under carrier communication and medium

Abstract

The invention provides a metering box electricity larceny detection method, system, equipment and medium under carrier communication, and relates to the field of metering box electricity larceny prevention, and the method comprises the following steps: collecting the three-phase current ICCO, voltage UCCO and freezing electric quantity QCCO of a split-phase protection intelligent circuit breaker, and the current Ij, voltage Uj and freezing electric quantity Qj of an electric energy meter in real time; calculating a correlation coefficient and an average distance between the voltage sequence {Uj} of the electric energy meter and the three-phase voltage sequence {UA, UB, UC} of the circuit breaker, and determining a connection phase of each electric energy meter; the deviation value delta I of the sum of the current ICCO of the circuit breaker and the current Ij of the connected electric energy meter under the same phase is calculated, a line loss model is constructed by combining the freezing electric quantity Qj and the QCCO, and the line loss rate p is solved; and performing three-level electricity stealing judgment, positioning an electricity stealing point and generating an electricity stealing probability Ptheft. Through multi-source data fusion, edge-side autonomous efficient electricity stealing closed-loop judgment and split-phase protection and electricity stealing prevention collaborative optimization, the accuracy of electricity stealing identification and the reliability of power supply are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of electricity theft prevention in metering boxes, and more specifically to a method, system, device, and medium for detecting electricity theft in metering boxes under carrier communication. Background Technology

[0002] In the field of preventing electricity theft in household electricity meter boxes, especially in high-incidence scenarios such as commercial areas and old residential communities, accurately identifying covert behaviors such as bypassing meter wiring and cross-phase electricity theft is crucial to protecting the interests of power supply companies and maintaining the order of power supply and consumption.

[0003] Traditional data acquisition methods rely on wireless communication or narrowband carrier waves, which are susceptible to radio frequency interference attacks that can cause communication interruptions. Furthermore, older residential areas have noisy lines and severely attenuated carrier signals, making it difficult to reliably obtain key parameters such as the frozen electricity meter readings, resulting in a lack of basic data for electricity theft analysis.

[0004] Furthermore, current methods mostly rely on single current deviation detection, but cannot distinguish between normal fluctuations during equipment start-up and shutdown and electricity theft; line loss calculation often ignores meter error rate and fixed losses, resulting in unreasonable threshold settings; at the same time, there is a lack of auxiliary verification of the cabinet door status, making it impossible to correlate with physical intrusion behavior.

[0005] In addition, existing cloud analytics solutions require the transmission of massive amounts of data, resulting in high latency and reliance on high-performance processors, which significantly increases the cost of upgrading older areas; while local edge devices typically lack phase protection mechanisms, causing full-phase power outages in the event of a fault, which cannot meet the continuous power supply needs of commercial users.

[0006] Therefore, how to design a method for detecting electricity theft in metering boxes under carrier communication, which can achieve high-precision electricity theft location and rapid response, while ensuring continuous power supply to non-faulty phases, is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0007] In view of this, the present invention provides a method for detecting electricity theft in meter boxes under carrier communication. Through localized multi-dimensional electricity theft analysis, it can accurately locate complex electricity theft behaviors such as pre-meter wiring and meter tampering. It relies on phase-protected smart circuit breakers to realize edge computing, reducing system costs and response delays. It also integrates IoT lock status monitoring and phase-protected power supply protection to prevent electricity theft while minimizing the impact of power outages and ensuring the stability of power supply and consumption.

[0008] To achieve the above objectives, the present invention adopts the following technical solution:

[0009] In a first aspect, the present invention provides a method for detecting electricity theft from a metering box under carrier communication, comprising the following steps:

[0010] S1. Real-time acquisition of the three-phase current I of the phase-separation protection intelligent circuit breaker. CCO Voltage U CCOFrozen power Q CCO and the current I of the electricity meter j Voltage U j Frozen power Q j ;

[0011] S2. Calculate the voltage sequence of the electricity meter {U} j} and the three-phase voltage sequence of the circuit breaker {U A U B U C The correlation coefficient and average distance are used to determine the connection phase of each energy meter;

[0012] S3. Calculate the circuit breaker current I under the same phase. CCO With the current I of the connected power meter j The total deviation value ΔI, combined with the frozen charge Q j and Q CCO Construct a line loss model and solve for the line loss rate p;

[0013] S4. Based on the deviation value ΔI, line loss rate p, and box door status, perform multi-level electricity theft detection, locate the electricity theft point, and generate the electricity theft probability P. theft .

[0014] Preferably, in step S1, data acquisition is achieved through an HPLC carrier communication network; wherein, the phase-separation protection intelligent circuit breaker is the master node, and the communication module in the energy meter is the slave node;

[0015] The master node periodically sends meter reading commands to the slave nodes, and the slave nodes feed back real-time data through the carrier channel.

[0016] Preferably, S2 includes:

[0017] S21, using the voltage sequence of the electricity meter {U j Let} be the dataset D, and the circuit breaker three-phase voltage sequence {U} A U B U C} are datasets A, B, and C, respectively;

[0018] S22. Calculate the correlation coefficient P between dataset D and datasets A, B, and C. D,X ;

[0019] S23. If there exists a unique P D,X If the value is ≥0.95, then the electricity meter is connected to phase X. If there are multiple P... D,X If the difference is less than 0.05, then calculate the average distance d. avg And select the smallest phase as the connection phase.

[0020] Preferably, in step S3, the deviation value ΔI is expressed as:

[0021]

[0022] Where k represents the total number of energy meters connected under the same phase.

[0023] Preferably, in step S3, solving for the line loss rate p includes:

[0024] A system of linear equations is established based on the principle of energy conservation:

[0025]

[0026] Where m is the total number of electricity meters in the metering box, w j Let be the error rate of the j-th energy meter, p be the line loss rate, and C be the fixed loss constant.

[0027] Write t equations using frozen power data at t time points, and solve the overdetermined system of equations to obtain the line loss rate p.

[0028] Preferably, in step S4, the multi-level electricity theft detection includes:

[0029] Level 1 judgment: When the deviation value ΔI is greater than the preset current threshold I th And the line loss rate p is greater than the preset line loss rate threshold p th At that time, it was determined that there was suspicion of electricity theft;

[0030] Secondary judgment: Traverse the current data of the energy meter under the suspected phase, if I exists j A power meter with a current value of 0 is marked as a power theft node; if there is no zero-current power meter, the current change value |I is filtered. j,t -I j,t-1 |Greater than the historical change threshold I hist The electricity meter was used as a point of electricity theft;

[0031] Level 3 judgment: If the level 2 judgment shows no abnormality, then the electricity theft point is determined to be located in front of the meter box.

[0032] Preferably, in S4, the probability of electricity theft P theft Represented as:

[0033]

[0034] Where α, β, and γ represent weighting coefficients, and S door Indicates the door status, S door =1 indicates the box door is open, S door =0 indicates the box door is closed.

[0035] Secondly, the present invention provides a meter box electricity theft detection system under carrier communication, comprising:

[0036] Acquisition module: Real-time acquisition of the three-phase current I of the phase-separated protection intelligent circuit breaker. CCO Voltage U CCO Frozen power Q CCO and the current I of the electricity meter j Voltage U j Frozen power Q j ;

[0037] Phase determination module: Calculates the voltage sequence of the energy meter {U} j} and the three-phase voltage sequence of the circuit breaker {U A U B U C The correlation coefficient and average distance are used to determine the connection phase of each energy meter;

[0038] Calculation module: Calculates circuit breaker current I under the same phase. CCO With the current I of the connected power meter j The total deviation value ΔI, combined with the frozen charge Q j and Q CCO Construct a line loss model and solve for the line loss rate p;

[0039] Electricity theft detection module: Based on the deviation value ΔI, line loss rate p, and door status, it performs multi-level electricity theft detection, locates the electricity theft point, and generates the electricity theft probability P. theft .

[0040] Thirdly, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for detecting electricity theft from a metering box.

[0041] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for detecting electricity theft from a metering box.

[0042] The descriptions of the second to fourth aspects of this invention can be referred to the detailed description of the first aspect; and the beneficial effects described in the second to fourth aspects can be referred to the analysis of the beneficial effects of the first aspect, which will not be repeated here.

[0043] As can be seen from the above technical solution, compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. This method combines topological phase identification, current deviation analysis, and box door status monitoring data. By utilizing voltage sequence correlation analysis, it can accurately locate the phase of the meter, effectively solving the problem of concealment in cross-phase electricity theft. At the same time, through joint verification of current deviation and line loss models, it can identify complex electricity theft methods such as front-end wiring and meter tampering. Combined with dynamic correction of box door status, it helps reduce misjudgments caused by operation and maintenance interference, further improving the accuracy of electricity theft identification.

[0045] 2. The star-shaped HPLC network ensures real-time data acquisition without relying on cloud computing power; the solution of the overdetermined equation system for line loss rate and the three-level electricity theft judgment are completed at the edge side, significantly improving the response speed; in addition, the system directly outputs the probability of electricity theft and the location results, such as marking zero current meters and the electricity theft path before the meter, thereby guiding the rapid on-site verification and greatly improving the efficiency and accuracy of electricity theft prevention.

[0046] 3. In the event of a single-phase fault, only the faulty phase is disconnected, rather than the entire power supply, reducing power outage losses. The electricity theft detection process simultaneously monitors line anomalies, such as overload current, embedding electricity theft analysis into the protection system to achieve integrated management of "anti-theft and power supply protection." This is particularly suitable for high-incidence scenarios such as commercial areas and industrial parks, effectively ensuring normal power supply and consumption. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0048] Figure 1 A flowchart of a method for detecting electricity theft from a metering box under carrier communication provided in an embodiment of the present invention;

[0049] Figure 2 This is a schematic diagram illustrating the implementation process of electricity theft detection using metering boxes under commercial area electricity management, provided in an embodiment of the present invention.

[0050] Figure 3 A framework diagram of a meter box electricity theft detection system under carrier communication provided in an embodiment of the present invention;

[0051] Figure 4 A schematic diagram of the electronic device structure is provided for an embodiment of the present invention. Detailed Implementation

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0053] The electricity theft detection method provided in this application can be applied to an electricity theft detection server, which can be either hardware or software. When the electricity theft detection server is hardware, it can be implemented as a distributed server cluster providing electricity theft detection services, or it can be implemented as a single server. When the electricity theft detection server is software, it can be installed on the servers listed above. It can be implemented as multiple software programs or software modules, or it can be implemented as a single software program or software module; no specific limitations are made here.

[0054] Example 1;

[0055] like Figure 1 As shown, this embodiment provides a method for detecting electricity theft in a metering box under carrier communication, including the following steps:

[0056] S1. Real-time acquisition of the three-phase current I of the phase-separation protection intelligent circuit breaker. CCO Voltage U CCO Frozen power Q CCO and the current I of the electricity meter j Voltage U j Frozen power Q j ;

[0057] S2. Calculate the voltage sequence of the electricity meter {U} j} and the three-phase voltage sequence of the circuit breaker {U A U B U C The correlation coefficient and average distance are used to determine the connection phase of each energy meter;

[0058] S3. Calculate the circuit breaker current I under the same phase. CCO With the current I of the connected power meter j The total deviation value ΔI, combined with the frozen charge Q j and Q CCO Construct a line loss model and solve for the line loss rate p;

[0059] S4. Based on the deviation value ΔI, line loss rate p, and box door status, perform multi-level electricity theft detection, locate the electricity theft point, and generate the electricity theft probability P. theft .

[0060] It collects circuit breaker and meter data in real time through a star-shaped HPLC network, accurately identifies meter phase assignment by combining voltage sequence correlation analysis, and locates electricity theft nodes based on joint verification of current deviation and line loss models. At the same time, it integrates the door status to dynamically correct the probability of electricity theft, realizing efficient edge-side analysis without cloud reliance, significantly improving the accuracy and response speed of electricity theft identification. Combined with a phase fault protection mechanism, it ensures the reliability of power supply to non-faulty phases during the electricity theft determination process, forming a synergistic closed loop of electricity theft prevention and power supply optimization.

[0061] The following provides a further detailed explanation of each step of the above method;

[0062] This implementation S1 involves real-time acquisition of the three-phase current I of the phase-separation protection intelligent circuit breaker. CCO Voltage U CCO Frozen power Q CCO and the current I of the electricity meter j Voltage U j Frozen power Q j ;

[0063] Data acquisition is achieved through an HPLC carrier communication network; the phase-separation protection intelligent circuit breaker is the master node, and the communication module in the energy meter is the slave node; the master node broadcasts meter reading instructions to the slave node according to a preset cycle, and the slave node transmits real-time current, voltage and frozen power data back to the master node through the power line carrier channel.

[0064] The core of carrier communication lies in utilizing existing power cables as the physical medium for data transmission. It achieves bidirectional data communication between circuit breakers and electricity meters by superimposing a high-frequency carrier signal onto the inherent power frequency current signal of the power lines. No additional communication cables need to be laid, allowing direct use of the power infrastructure. This makes it particularly suitable for environments where meters are scattered, wiring is difficult, or wireless signals are susceptible to interference. Compared to traditional PLCs, HPLC offers higher transmission rates, stronger anti-interference capabilities, and lower latency. It can reliably and in real-time transmit critical data such as current, voltage, and frozen electricity required by the scheme, laying a solid communication foundation for rapid electricity theft analysis at the edge.

[0065] This step employs a star-shaped HPLC network architecture, with the phase-protected intelligent circuit breaker (CCO) acting as the master node, responsible for initiating communication (broadcasting meter reading commands) and aggregating data. All connected electricity meters act as slave nodes, responding to the master node's commands and transmitting their own data back to the master node via the power line carrier channel. This effectively avoids signal conflicts and routing complexities that may occur in traditional PLC networks, significantly improving the timeliness and reliability of data transmission, and ensuring a stable data foundation for the electricity theft detection algorithm.

[0066] In this implementation S2, the voltage sequence of the electricity meter {U} is calculated. j} and the three-phase voltage sequence of the circuit breaker {U A U B U C The correlation coefficient and average distance are used to determine the connection phase of each electricity meter; including:

[0067] S21, using the voltage sequence of the electricity meter {U j Let} be the dataset D, and the circuit breaker three-phase voltage sequence {U} A U B U C} are datasets A, B, and C, respectively;

[0068] S22. Calculate the correlation coefficient P between dataset D and datasets A, B, and C. D,X ;

[0069] S23. If there exists a unique P D,X If the value is ≥0.95, then the electricity meter is connected to phase X. If there are multiple P... D,X If the difference is less than 0.05, then calculate the average distance d. avg And select the smallest phase as the connection phase.

[0070] Specifically, the correlation coefficient P D,X and average distance d avg Represented as:

[0071]

[0072] Among them, D i This represents the i-th voltage value in the voltage sequence of the electricity meter. X represents the average value of the voltage sequence of the electricity meter. i This represents the i-th voltage value in a phase voltage sequence of a circuit breaker. It represents the average value of a phase voltage sequence of a circuit breaker;

[0073] The correlation coefficient measures the degree of linear correlation between two sequences, with values ​​ranging from -1 to 1. A value close to 1 indicates a positive correlation, close to -1 indicates a negative correlation, and close to 0 indicates no correlation. The mean distance, on the other hand, measures the similarity between two sequences; a smaller value indicates greater similarity.

[0074] It breaks through the limitations of manual investigation or simple threshold comparison, accurately identifies hidden wiring such as cross-phase electricity theft through dual mathematical verification, and tracks voltage fluctuation trends with dynamic datasets to avoid misjudgment caused by instantaneous interference, improves the accuracy of phase recognition, and provides reliable topological basis for subsequent electricity theft location.

[0075] In this implementation S3, the circuit breaker current I under the same phase is calculated. CCO With the current I of the connected power meter jThe total deviation value ΔI, combined with the frozen charge Q j and Q CCO Construct a line loss model and solve for the line loss rate p;

[0076] The deviation value ΔI is expressed as:

[0077]

[0078] Where k represents the total number of energy meters connected under the same phase.

[0079] Furthermore, solving for the line loss rate p includes:

[0080] A system of linear equations is established based on the principle of energy conservation:

[0081]

[0082] Where m is the total number of electricity meters in the metering box, w j Let be the error rate of the j-th energy meter, p be the line loss rate, and C be the fixed loss constant.

[0083] Write t equations using frozen power data at t time points, and solve the overdetermined system of equations to obtain the line loss rate p.

[0084] Based on the law of conservation of energy, it constructs a multivariate equation that includes meter error rate, line loss rate, and fixed loss, which can cover all electricity meters in the meter box. It also writes redundant equations by freezing electricity data at multiple time points and uses optimization algorithms such as least squares to solve for the optimal solution of line loss rate. It achieves decoupling of loss factors at the edge and accurately identifies hidden electricity loss caused by chronic data tampering.

[0085] In this implementation S4, based on the deviation value ΔI, the line loss rate p, and the box door status, a multi-level electricity theft detection is performed to locate the electricity theft point and generate the electricity theft probability P. theft ;

[0086] The multi-level electricity theft detection process includes:

[0087] Level 1 judgment: When the deviation value ΔI is greater than the preset current threshold I th And the line loss rate p is greater than the preset line loss rate threshold p th At that time, it was determined that there was suspicion of electricity theft;

[0088] Secondary judgment: Traverse the current data of the energy meter under the suspected phase, if I exists j A power meter with a current value of 0 is marked as a power theft node; if there is no zero-current power meter, the current change value |I is filtered. j,t -I j,t-1 |Greater than the historical change threshold I hist The electricity meter was used as a point of electricity theft;

[0089] Level 3 judgment: If the level 2 judgment shows no abnormality, then the electricity theft point is determined to be located in front of the meter box.

[0090] This step reduces the false positive rate through a layered filtering mechanism: the first level eliminates interference from equipment start-up and shutdown, the second level identifies the specific electricity theft meter, and the third level covers the electricity theft blind spot before the meter; forming a progressive positioning logic from phase to meter to line, solving the problem of complex scenario analysis in collective electricity theft involving multiple points.

[0091] Furthermore, the probability P of electricity theft theft Represented as:

[0092]

[0093] Where α, β, and γ represent weighting coefficients, and S door Indicates the door status, S door =1 indicates the box door is open, S door =0 indicates the box door is closed.

[0094] Specifically, current deviation rate Real-time detection of phase imbalance directly reflects electricity theft activities such as wiring tampering; line loss exceeding standard rate. Identify long-term hidden losses and resolve line loss anomalies caused by chronic data tampering; Cabin door status S door The physical intrusion time window is associated to provide behavioral evidence; further, the evidence priority is dynamically allocated by combining the weight coefficient α+β+γ=1 to ensure the judgment logic of current-driven, line loss-enhanced, and physical-assisted.

[0095] It compresses complex electricity theft characteristics into quantifiable indicators, achieving anti-false alarm, tiered response, and full-scenario coverage. Normal current fluctuations are filtered out due to normal line loss rates and box door status, avoiding false alarms; the system automatically dispatches orders and locks boxes, forming a tiered response mechanism; in addition, this method supports the linkage analysis of electricity theft after the meter, electricity theft in the cable before the meter, and abnormal box door conditions, reducing the false alarm rate of a single current detection model, thereby achieving comprehensive closed-loop decision-making for electricity theft prevention.

[0096] like Figure 2 As shown below, the specific implementation steps of the above-mentioned meter box electricity theft detection method will be explained in detail in conjunction with the specific electricity management of commercial areas:

[0097] 1) Real-time data acquisition;

[0098] In this commercial street metering system, a phase-protection intelligent circuit breaker (CCO) is installed and connected to four electricity meters (STA1 to STA4). Every 15 minutes, the CCO sends meter reading commands to each electricity meter via an HPLC carrier network, obtaining data including the three-phase current I0. A =50A, IB =30A, I C =40A, voltage U A =220V, U B =219V, UI C =221V and frozen charge Q CCO Key data includes 1200kWh; meanwhile, data collected from the electricity meters shows that STA1 has a current of I1 = 20A, voltage U1 = 219.5V, and energy Q1 = 400kWh; STA2 has a current of I2 = 15A, voltage U2 = 219.3V, and energy Q2 = 300kWh; STA3 has a current of I3 = 25A, voltage U3 = 220.8V, and energy Q3 = 350kWh; and STA4 has a current of I4 = 18A, voltage U4 = 220.5V, and energy Q4 = 300kWh.

[0099] During data acquisition, the CCO (Content Control Operator) acts as the master node, coordinating the entire communication network to ensure the reliability and timeliness of data transmission. All electricity meters act as slave nodes, feeding back real-time data according to the instructions issued by the CCO. This communication method significantly improves the success rate of data acquisition and reduces data loss due to signal interference or transmission failure. Furthermore, regular data acquisition helps to promptly detect potential anomalies, such as sudden current surges or abnormal fluctuations in electricity consumption, thus providing strong support for subsequent electricity theft analysis.

[0100] 2) Phase topology identification;

[0101] To determine the specific phase connected to each energy meter, taking STA1 as an example, its voltage sequence D = {219.5, 219.6, 219.4, ...} is compared with the three-phase voltage sequences A = {220.0, 220.1, ...}, B = {219.0, 219.2, ...}, and C = {221.0, 220.9, ...} of CCO. The correlation coefficient P is obtained by calculating the correlation coefficient. D,A =0.98, P D,B =0.65, P D,C =0.62. Because P D,A The value is significantly higher than the other two phases and exceeds the standard of 0.95, indicating that STA1 is connected to phase A.

[0102] In some cases, the correlation coefficients of multiple phases may be very close, in which case it is necessary to further calculate the average distance to distinguish them. For example, if P D,A and P D,B If all values ​​exceed 0.95 and the difference is less than 0.05, then the average distance d needs to be calculated. avgIf the calculation results show that the distance between STA1 and phase A is minimized, then it can be confirmed that STA1 is indeed connected to phase A. This method can effectively solve the problem of phase identification in complex environments and improve the overall reliability of the system.

[0103] 3) Calculation of current deviation and line loss;

[0104] If suspected electricity theft is detected in phase A, the current I in phase CCO-A is... A =50A, while the total current of STA1 and STA2 is 35A, thus the current deviation ΔI = 15A. A line loss model is established based on the principle of energy conservation, and a system of equations is constructed using electricity data from four time points to solve for the line loss rate p. The simplified example shows that at one time point, 1200kWh = (400(1+w1) + 300(1+w1)) + p·1200 + C. By solving the overdetermined system of equations, the final line loss rate is p = 5%, exceeding the preset threshold pth = 4%, which further confirms the possibility of electricity theft.

[0105] Furthermore, by analyzing the frozen electricity data at different time points, the system's energy consumption can be assessed more comprehensively. For example, by using the electricity difference data over four consecutive days to formulate a system of equations, the error rate of each meter and the line loss rate can be determined. If the line loss rate is found to be significantly higher than normal within a certain time period and exceeds a set threshold, it can be inferred that electricity theft may have occurred during that period.

[0106] 4) Multi-level electricity theft detection;

[0107] Because the current deviation ΔI of phase A is 15A, which is greater than the threshold I... th =10A, and the line loss rate p = 5% is greater than p th =4%, triggering a Level 1 suspicion of electricity theft. Next, a Level 2 assessment is performed, checking the current of the electricity meters under phase A. If the current of STA2 is found to be 0A, this is clearly abnormal, therefore STA2 is marked as a suspected electricity theft node. If no obvious zero-current electricity meter is found, electricity meters with significant current changes will be selected as suspicious based on historical current variation values.

[0108] Furthermore, in the third-level judgment, if no abnormalities are found in the second-level judgment, a further investigation will be conducted to determine whether electricity theft may be occurring at the meter box. For example, by comparing the historical current data of STA2, suspected electricity theft nodes will be marked. In addition, based on the abnormal door opening status information reported by the IoT lock, the probability of electricity theft will be calculated using a formula. If it exceeds the preset electricity theft probability threshold, on-site verification and confirmation are required.

[0109] By implementing the above steps, accurate detection and location of electricity theft at metering boxes in commercial areas can be achieved. This method not only improves the accuracy and efficiency of detection but also effectively reduces power loss caused by the inadequacy of traditional detection methods. Furthermore, the application of smart IoT locks further enhances the monitoring capabilities for electricity theft, realizing a comprehensive anti-theft solution at the metering box level. In the future, with continuous technological advancements and the expansion of application scenarios, this method is expected to play a significant role in more fields, contributing to the healthy development of the power industry.

[0110] Example 2;

[0111] like Figure 3 As shown, this embodiment provides a meter box electricity theft detection system under carrier communication, including:

[0112] Acquisition module: Real-time acquisition of the three-phase current I of the phase-separated protection intelligent circuit breaker. CCO Voltage U CCO Frozen power Q CCO and the current I of the electricity meter j Voltage U j Frozen power Q j ;

[0113] Phase determination module: Calculates the voltage sequence of the energy meter {U} j} and the three-phase voltage sequence of the circuit breaker {U A U B U C The correlation coefficient and average distance are used to determine the connection phase of each energy meter;

[0114] Calculation module: Calculates circuit breaker current I under the same phase. CCO With the current I of the connected power meter j The total deviation value ΔI, combined with the frozen charge Q j and Q CCO Construct a line loss model and solve for the line loss rate p;

[0115] Electricity theft detection module: Based on the deviation value ΔI, line loss rate p, and door status, it performs multi-level electricity theft detection, locates the electricity theft point, and generates the electricity theft probability P. theft .

[0116] The system collects relevant data from the phase-separated protection smart circuit breaker and the electricity meter in real time through the acquisition module, determines the connection phase of the electricity meter using the phase determination module, calculates the current deviation and line loss rate using the calculation module, and finally performs multi-level electricity theft judgment through the electricity theft judgment module to locate the electricity theft point and generate the electricity theft probability, thereby realizing the effective detection of electricity theft behavior in the metering box.

[0117] Example 3;

[0118] like Figure 4 As shown, this embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described method for detecting electricity theft from a metering box.

[0119] Example 4;

[0120] This embodiment provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the aforementioned method for detecting electricity theft from a metering box. It should be understood that the disclosed methods, systems, devices, and media in the embodiments provided in this application can be implemented in other ways. The methods, systems, devices, and media embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and other division methods may exist in actual implementation. Each functional unit can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0121] The units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0122] Computer programs include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. Computer-readable media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory, random access memory, electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0123] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for detecting electricity theft from a metering box under carrier communication, characterized in that, Includes the following steps: S1. Real-time acquisition of the three-phase current I of the phase-separation protection intelligent circuit breaker. CCO Voltage U CCO Frozen power Q CCO and the current I of the electricity meter j Voltage U j Frozen power Q j ; S2. Calculate the voltage sequence of the electricity meter {U} j } and the three-phase voltage sequence of the circuit breaker {U A U B U C The correlation coefficient and average distance are used to determine the connection phase of each energy meter; S3. Calculate the circuit breaker current I under the same phase. CCO With the current I of the connected power meter j The total deviation value ΔI, combined with the frozen charge Q j and Q CCO Construct a line loss model and solve for the line loss rate p; S4. Based on the deviation value ΔI, line loss rate p, and box door status, perform multi-level electricity theft detection, locate the electricity theft point, and generate the electricity theft probability P. theft .

2. The method for detecting electricity theft in a metering box under carrier communication according to claim 1, characterized in that, In S1, data acquisition is achieved through an HPLC carrier communication network; wherein, the phase-separation protection intelligent circuit breaker is the master node, and the communication module in the energy meter is the slave node. The master node periodically sends meter reading commands to the slave nodes, and the slave nodes feed back real-time data through the carrier channel.

3. The method for detecting electricity theft in a metering box under carrier communication according to claim 1, characterized in that, S2 includes: S21, using the voltage sequence of the electricity meter {U j Let} be the dataset D, and the circuit breaker three-phase voltage sequence {U} A U B U C } are datasets A, B, and C, respectively; S22. Calculate the correlation coefficient P between dataset D and datasets A, B, and C. D,X ; S23. If there exists a unique P D,X If the value is ≥0.95, then the electricity meter is connected to phase X. If there are multiple P... D,X If the difference is less than 0.05, then calculate the average distance d. avg And select the smallest phase as the connection phase.

4. The method for detecting electricity theft in a metering box under carrier communication according to claim 1, characterized in that, In S3, the deviation value ΔI is expressed as: Where k represents the total number of energy meters connected under the same phase.

5. The method for detecting electricity theft in a metering box under carrier communication according to claim 1, characterized in that, In step S3, solving for the line loss rate p includes: A system of linear equations is established based on the principle of energy conservation: Where m is the total number of electricity meters in the metering box, w j Let be the error rate of the j-th energy meter, p be the line loss rate, and C be the fixed loss constant. Write t equations using frozen power data at t time points, and solve the overdetermined system of equations to obtain the line loss rate p.

6. The method for detecting electricity theft in a metering box under carrier communication according to claim 1, characterized in that, In step S4, the multi-level electricity theft detection includes: Level 1 judgment: When the deviation value ΔI is greater than the preset current threshold I th And the line loss rate p is greater than the preset line loss rate threshold p th At that time, it was determined that there was suspicion of electricity theft; Secondary judgment: Traverse the current data of the energy meter under the suspected phase, if I exists j A power meter with a current value of 0 is marked as a power theft node; if there is no zero-current power meter, the current change value |I is filtered. j,t -I j,t-1 |Greater than the historical change threshold I hist The electricity meter was used as a point of electricity theft; Level 3 judgment: If the level 2 judgment shows no abnormality, then the electricity theft point is determined to be located in front of the meter box.

7. The method for detecting electricity theft in a metering box under carrier communication according to claim 1, characterized in that, In S4, the probability of electricity theft P theft Represented as: Where α, β, and γ represent weighting coefficients, and S door Indicates the door status, S door =1 indicates the box door is open, S door =0 indicates the box door is closed.

8. A meter box electricity theft detection system under carrier communication, characterized in that, include: Acquisition module: Real-time acquisition of the three-phase current I of the phase-separated protection intelligent circuit breaker. CCO Voltage U CCO Frozen power Q CCO and the current I of the electricity meter j Voltage U j Frozen power Q j ; Phase determination module: Calculates the voltage sequence of the energy meter {U} j } and the three-phase voltage sequence of the circuit breaker {U A U B U C The correlation coefficient and average distance are used to determine the connection phase of each energy meter; Calculation module: Calculates circuit breaker current I under the same phase. CCO With the current I of the connected power meter j The total deviation value ΔI, combined with the frozen charge Q j and Q CCO Construct a line loss model and solve for the line loss rate p; Electricity theft detection module: Based on the deviation value ΔI, line loss rate p, and door status, it performs multi-level electricity theft detection, locates the electricity theft point, and generates the electricity theft probability P. theft .

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the meter box electricity theft detection method 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 meter box electricity theft detection method as described in any one of claims 1 to 7.

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