Topological relation identification method, device and system of electric energy meter

Abstract

The invention relates to the technical field of electric energy meters, and provides a topological relation identification method, device and system for electric energy meters, and the method comprises the steps: obtaining the communication signal strength of a plurality of electric energy meters scanned by a target guide rail meter, and determining an electric energy meter candidate set of a to-be-identified topological relation according to the communication signal strength; acquiring a voltage value of each electric energy meter in the electric energy meter candidate set, and dividing the electric energy meter candidate set into subsets corresponding to each score of the target guide rail meter according to the voltage values; respectively combining the electric energy meters in each subset, obtaining the total electricity consumption of each combination and the total electricity consumption of the split phase corresponding to the target guide rail meter, and calculating the relevancy between the total electricity consumption of the split phase corresponding to the target guide rail meter and the total electricity consumption of each combination; the topological relation of the split phases corresponding to the electric energy meter and the target guide rail meter is identified according to the relevancy, the defect of single signal intensity identification can be overcome, and the identification precision is high.

Description

Technical Field

[0001] This application relates to the field of electricity meter technology, specifically to a method, device, and system for identifying the topological relationship of an electricity meter. Background Technology

[0002] In a power distribution room, there may be multiple distribution boxes. Each distribution box is equipped with a rail-mounted meter for reading data from the downstream electricity meters for management and monitoring. The main functions of the rail-mounted meter are: 1) to centrally read data from the downstream electricity meters and upload it to the cloud, improving reading efficiency; 2) to monitor electricity consumption, analyze its own electricity metering data with the metering data from the downstream electricity meters, and determine if there are any anomalies. If an anomaly is detected (such as leakage or electricity theft), it can report the fault and determine whether to cut off the power supply based on the situation.

[0003] In traditional distribution boxes, rail-mounted meters and downstream energy meters are connected via an RS485 bus for data reading. Currently, to reduce the complexity of RS485 bus wiring, Bluetooth wireless technology is used for downstream energy meter reading. However, in situations where multiple distribution boxes are installed adjacent to each other, the signal strength (RSSI) of Bluetooth signals decreases with distance due to its propagation characteristics. Bluetooth signal strength alone cannot accurately distinguish whether an energy meter is in the same distribution box as a rail-mounted meter, easily leading to errors in topology identification and consequently, failure in power load monitoring. Summary of the Invention

[0004] In view of the above problems, embodiments of this application provide a method, apparatus and system for identifying the topology of an electricity meter to solve the above technical problems.

[0005] In a first aspect, embodiments of this application provide a method for identifying the topological relationship of an electricity meter, including: The communication signal strength of multiple energy meters scanned by the target guide rail meter is obtained, and a candidate set of energy meters with topological relationships to be identified is determined based on the communication signal strength. Collect the voltage values ​​of each of the energy meters in the candidate set of energy meters, and divide the candidate set of energy meters into subsets corresponding to each of the target rail meters based on the voltage values; The energy meters in each subset are combined to obtain the total power consumption of each combination and the total power consumption of the target meter rail corresponding to the phase, and the correlation between the total power consumption of the target meter rail corresponding to the phase and the total power consumption of each combination is calculated. The topological relationship between the corresponding phases of the energy meter and the target rail meter is identified based on the correlation.

[0006] Secondly, embodiments of this application also provide a topology identification device for an electricity meter, comprising: The acquisition module is used to acquire the communication signal strength of multiple energy meters scanned by the target guide rail meter, and determine the candidate set of energy meters with topological relationships to be identified based on the communication signal strength. The classification module is used to collect the voltage values ​​of each of the energy meters in the candidate set of energy meters, and divide the candidate set of energy meters into subsets corresponding to each of the target rail meters according to the voltage values. The calculation module is used to combine the energy meters in each subset respectively, obtain the total power consumption of each combination and the total power consumption of the target meter rail meter corresponding to the phase, and calculate the correlation between the total power consumption of the target meter rail meter corresponding to the phase and the total power consumption of each combination. The identification module is used to identify the topological relationship between the corresponding phases of the energy meter and the target rail meter based on the correlation.

[0007] Thirdly, embodiments of this application also provide a topology identification system for electricity meters, including the aforementioned topology identification system for electricity meters.

[0008] The topology identification method for electricity meters provided in this application embodiment obtains the communication signal strength of multiple electricity meters scanned by the target rail meter, and determines a candidate set of electricity meters for topology identification based on the communication signal strength; collects the voltage value of each electricity meter in the candidate set, and divides the candidate set into subsets corresponding to each phase of the target rail meter based on the voltage value; combines the electricity meters in each subset to obtain the total electricity consumption of each combination and the total electricity consumption of the corresponding phase of the target rail meter, and calculates the correlation between the total electricity consumption of the corresponding phase of the target rail meter and the total electricity consumption of each combination; and identifies the topology relationship between the electricity meter and the corresponding phase of the target rail meter based on the correlation. This method effectively overcomes the defects of single signal strength identification, and even in complex environments with severe signal overlap among multiple meter boxes, it can reverse-engineer the topology relationship by intelligently analyzing the electricity data of the electricity meters, achieving high accuracy.

[0009] These or other aspects of this application will become more apparent in the following description of the embodiments. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application, 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 this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1This application illustrates a topology identification system for electricity meters provided in an embodiment of the present application.

[0012] Figure 2 This application illustrates a method for identifying the topology of an energy meter according to an embodiment of the present application.

[0013] Figure 3 This application illustrates a method for identifying the topology of an electricity meter according to another embodiment.

[0014] Figure 4 This application illustrates a method for identifying the topology of an electricity meter according to another embodiment.

[0015] Figure 5 This application illustrates a method for identifying the topology of an electricity meter according to another embodiment.

[0016] Figure 6 This application illustrates a method for identifying the topology of an electricity meter according to another embodiment.

[0017] Figure 7 This application illustrates a method for identifying the topology of an electricity meter according to another embodiment.

[0018] Figure 8 This application illustrates a topology identification device for an electricity meter according to an embodiment of the present application. Detailed Implementation

[0019] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0020] To enable those skilled in the art to better understand the solutions of this application, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0021] In the embodiments of this application, it should be noted that, in this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0022] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0023] In the description of the embodiments of this application, the words "example" or "for example" are used to indicate exemplification, illustration, or description. Any embodiment or design described as "example" or "for example" in the embodiments of this application is not to be construed as being more preferred or having more advantages than another embodiment or design. The use of the words "example" or "for example" is intended to present relative concepts in a clear manner.

[0024] Furthermore, in the embodiments of this application, "multiple" refers to two or more. Therefore, in the embodiments of this application, "multiple" can also be understood as "at least two". "At least one" can be understood as one or more, such as one, two, or more. For example, including at least one means including one, two, or more, and is not limited to which ones are included. For example, including at least one of A, B, and C, then it could include A, B, C, A and B, A and C, B and C, or A and B and C.

[0025] It should be noted that in the embodiments of this application, "and / or" describes the relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. In addition, the character " / ", unless otherwise specified, generally indicates that the associated objects before and after it are in an "or" relationship.

[0026] In power distribution room applications, multiple distribution boxes are often closely arranged with very little spacing between them. Due to the propagation characteristics of Bluetooth signals, their signal strength (RSSI) attenuates with increasing distance. However, this attenuation is easily affected by various environmental factors such as shielding and reflection from the metal casing of the meter box, interference from other electronic devices operating on the same frequency, and human presence obstructing the view. Therefore, relying solely on the detected Bluetooth signal strength, rail-mounted meters cannot accurately determine whether a scanned energy meter is located in its own distribution box or in a neighboring box. If the rail-mounted meter incorrectly identifies energy meters in adjacent distribution boxes as devices in its own box and performs readings and management accordingly, it will cause confusion in its managed energy meter list. Furthermore, when performing load monitoring and anomaly analysis, the rail-mounted meter may perform calculations based on incorrect electrical topology (e.g., including a load that should belong to a neighboring distribution box in the total load of its own distribution box). This will directly lead to the failure of power balance analysis, a fundamental deviation in the judgment logic of leakage current and electricity theft, and thus trigger false alarms or missed alarms, causing the load monitoring and safety management functions of the power system to fail completely and failing to achieve the expected design goals.

[0027] Therefore, although Bluetooth technology simplifies wiring complexity in power distribution room applications, overcoming the challenge of topology identification caused by signal crosstalk in environments with densely deployed multiple power distribution boxes, and ensuring that the rail-mounted meter can accurately manage the electricity meters within its jurisdiction, is a technical bottleneck that urgently needs to be solved in this field.

[0028] like Figure 1 As shown, Figure 1 The diagram schematically illustrates a topology identification system for electricity meters provided in an embodiment of this application. The topology identification system 100 includes one or more rail meters 10 and multiple electricity meters 20. Each rail meter 10 is deployed within a distribution box, and each electricity meter 20 is electrically connected to one rail meter 10. This means that within a distribution box, one rail meter 10 can be electrically connected to multiple electricity meters 20.

[0029] In one embodiment, the electricity meter 20 includes a first communication module and an electricity metering module. The rail-mounted meter 10 includes a second communication module, a data acquisition module, and a data processing module. The rail-mounted meter 10 and the electricity meter 20 are connected via the first communication module and the second communication module. The electricity metering module provides power data and electricity consumption data; the data acquisition module collects operating data from the electricity meter, such as power data and electricity consumption data; and the data processing module processes the data collected by the data acquisition module.

[0030] For example, the electricity meter 20 and the rail meter 10 are connected wirelessly. This means that a rail meter 10 can wirelessly communicate with the electricity meter 20 within its own distribution box, and also with the electricity meter 20 in an adjacent distribution box. Wireless communication methods include, but are not limited to, Bluetooth, Wi-Fi, and NFC. In this embodiment, Bluetooth is used as an example, meaning that both the first and second communication modules are Bluetooth modules. The rail meter 10 transmits data with the electricity meter 20 via Bluetooth. For example, the electricity meter 20 can respond to the reading command from the rail meter 10 via Bluetooth and return data. Multi-channel Bluetooth communication supports at least 20 concurrent Bluetooth connection links, enabling the rail meter 10 to simultaneously collect operating data from multiple electricity meters 20, thus improving data collection efficiency.

[0031] like Figure 2 As shown, Figure 2 The illustration schematically depicts a topology identification method for electricity meters provided in an embodiment of this application. This topology identification method is suitable for identifying electricity meters with slow changes in power consumption. The method includes: Step S10: Obtain the communication signal strength of multiple energy meters scanned by the target guide rail meter, and determine the candidate set of energy meters with topological relationships to be identified based on the communication signal strength.

[0032] In this step, the target rail meter continuously performs a broadcast scan via Bluetooth module, receiving Bluetooth broadcast signals from surrounding electricity meters and parsing the communication signal strength (such as RSSI value). Based on a preset signal strength threshold, remote electricity meters with communication signal strength below the threshold are filtered out, thus forming a candidate set of electricity meters with the topological relationship to be identified. For example, suppose a power distribution room has three distribution boxes (A, B, C), each equipped with rail meters DTU_A, DTU_B, and DTU_C, with 10 electricity meters connected to each rail meter. Each rail meter's Bluetooth module enters broadcast scanning mode, enabling it to scan the Bluetooth broadcast signals of multiple electricity meters in its own distribution box and adjacent distribution boxes. For example, the rail-mounted meter DTU_A scans broadcast signals from 10 electricity meters in this distribution box and 30 electricity meters in adjacent distribution boxes B and C, and obtains the communication signal strength. The rail-mounted meter DTU_A compares the communication signal strength of each electricity meter with a signal strength threshold, filters out electricity meters whose communication signal strength is lower than the signal strength threshold, and forms a candidate set of electricity meters (e.g., 15 electricity meters) for identifying the topological relationship.

[0033] This step can initially screen the electricity meters whose topological relationships need to be identified, effectively reducing the data range for subsequent analysis and improving identification efficiency and accuracy.

[0034] Step S20: Collect the voltage value of each energy meter in the candidate energy meter set, and divide the candidate energy meter set into subsets corresponding to each subset of the target guide rail meter based on each voltage value.

[0035] In this step, within a three-phase power system, due to varying loads, complete three-phase voltage balance cannot be achieved, resulting in a certain deviation in the voltage value of each phase. The target rail meter utilizes a Bluetooth module to support at least 20 concurrent Bluetooth connection links, simultaneously initiating connection and data requests to each energy meter in the candidate energy meter set to obtain the voltage values ​​of each meter. Then, the voltage values ​​of each energy meter are classified, using either threshold classification or clustering methods, to obtain subsets corresponding to each phase of the target rail meter.

[0036] As one embodiment, the voltage values ​​of each energy meter in the candidate energy meter set are collected; the voltage values ​​are classified according to the different phases of the target rail meter; and the candidate energy meter set is divided into subsets corresponding to each phase of the target rail meter based on the classification results.

[0037] Different phases of the target guide rail meter, such as phases A, B, and C, are assigned to each energy meter in the candidate set of energy meters, generating subsets corresponding to each phase of the target guide rail meter.

[0038] In one embodiment, classifying the voltage values ​​of each energy meter according to the three phases of the target rail meter in a three-phase power system can be done using a K-means clustering algorithm. For example, the K-means clustering is set to 3 clusters. Three cluster centers are automatically found based on the distance between voltage data points (e.g., Euclidean distance), and the energy meters in the candidate set are assigned to the nearest cluster center, thus forming three subsets: A1, A2, and A3. The user or system can manually or through phase identification mapping rules assign the three subsets to the three phases of the target rail meter, respectively, and label them as phase A, phase B, and phase C, based on the actual voltage amplitude of the cluster centers (e.g., cluster center 1 is ~230V, cluster center 2 is ~228V, and cluster center 3 is ~225V).

[0039] In another embodiment, the K-means clustering cluster is set to 3. The three phase voltage values ​​of the target rail meter are used as centroids for clustering. The electricity meters in the candidate set of electricity meters are assigned to the nearest cluster center, thereby forming three subsets A1, A2, and A3, which correspond to the three phases A, B, and C, respectively.

[0040] This step, through voltage value clustering analysis, can further reduce the data range for subsequent analysis, thereby improving recognition efficiency and accuracy.

[0041] Step S30: Combine the energy meters in each subset to obtain the total power consumption of each combination and the total power consumption of the corresponding phase of the target meter guide rail meter, and calculate the correlation between the total power consumption of the corresponding phase of the target guide rail meter and the total power consumption of each combination.

[0042] In this step, the electricity consumption of each energy meter in each subset and the total electricity consumption of the corresponding phase of the target guide rail meter are obtained respectively; the energy meters in each subset are combined; for each combination, the total electricity consumption of the corresponding combination is calculated based on the electricity consumption of the energy meters in the combination.

[0043] For example, suppose there are three electricity meters in subset A1, namely S1, S2, and S3. The electricity consumption of electricity meter S1 is denoted as Q_S1, the electricity consumption of electricity meter S2 is denoted as Q_S2, and the electricity consumption of electricity meter S3 is denoted as Q_S3. The total electricity consumption of the corresponding phase of the target guide rail meter is denoted as Q_A. All possible non-empty combinations of electricity meters S1, S2, and S3 are performed, resulting in combinations including [S1], [S2], [S3], [S1+S2], [S1+S3], [S2+S3], and [S1+S2+S3]. The total electricity consumption of each of these combinations is calculated. For the combination [S1+S2], the total electricity consumption is Q[S1+S2] = Q_S1 + Q_S2. The calculation of the total electricity consumption of other combinations follows the same principle. The subsequent steps involve calculating the correlation between Q_A and Q[S1], Q[S2], Q[S3], Q[S1+S2], Q[S1+S3], Q[S2+S3], and Q[S1+S2+S3].

[0044] As one embodiment, the electricity consumption sequence of each energy meter in each subset and the total electricity consumption sequence of the corresponding phase of the target rail meter are obtained within a preset period. The energy meters in each subset are combined. For each combination, the total electricity consumption sequence of the combination is calculated based on the electricity consumption sequence of the energy meters in the combination. The total electricity consumption sequence is the sum of the electricity consumption sequences of the energy meters in the combination. This embodiment can use a polling method to read the electricity consumption of each energy meter in each subset and the total electricity consumption of the corresponding phase of the target rail meter. The reading can be done once at a preset time interval within a preset period, and continuously read for a preset number of times, such as once every 15 seconds, for 10 consecutive times, thereby obtaining the electricity consumption sequence of each energy meter and the total electricity consumption sequence of the corresponding phase of the target rail meter.

[0045] For example, suppose there are three electricity meters in subset A1, namely S1, S2 and S3. The target guide rail meter retrieves the total electricity consumption sequence of phase A at 10 15-minute intervals, denoted as Q_A = [Q1, Q2, ..., Q10]. The electricity consumption sequence of electricity meter S1 at 10 15-minute intervals is denoted as Q_S1 = [q11, q12, ..., q110], the electricity consumption sequence of electricity meter S2 at 10 15-minute intervals is denoted as Q_S2 = [q21, q22, ..., q210], and the electricity consumption sequence of electricity meter S3 at 10 15-minute intervals is denoted as Q_S3 = [q31, q32, ..., q310]. For electricity meters S1, S2, and S3, perform all possible non-empty combinations, resulting in combinations including [S1], [S2], [S3], [S1+S2], [S1+S3], [S2+S3], and [S1+S2+S3]. Calculate the total electricity consumption sequence for each of these combinations. For the combination [S1+S2], the total electricity consumption sequence Q[S1+S2] = [(q11+q21), (q12+q22), ..., (q110+q210)]. The calculation of the total electricity consumption for other combinations follows the same principle. Subsequently, it is necessary to calculate the correlation between Q_A and Q[S1], Q[S2], Q[S3], Q[S1+S2], Q[S1+S3], Q[S2+S3], and Q[S1+S2+S3].

[0046] As one embodiment, the correlation can be reflected by the Pearson correlation coefficient. This requires calculating the Pearson correlation coefficient between the total power consumption sequence of the corresponding phase of the target guide rail and the total power consumption sequence of each combination. Specifically, this involves calculating the Pearson correlation coefficients between Q_A and Q[S1], Q[S2], Q[S3], Q[S1+S2], Q[S1+S3], Q[S2+S3], and Q[S1+S2+S3]. The formula for calculating the Pearson correlation coefficient is as follows: ,in, The total electrical quantity sequence of the target guide rail i within a preset period. Let be the total electricity consumption sequence of combination j within a preset period, cov be the covariance, and D be the variance.

[0047] Compared to simple absolute or relative errors, the Pearson correlation coefficient is more resistant to interference and can improve recognition accuracy.

[0048] Step S40: Identify the topological relationship between the corresponding phases of the energy meter and the target rail meter based on the correlation.

[0049] In this step, when the correlation is reflected by the Pearson correlation coefficient, the Pearson correlation coefficient between the total power consumption sequence of each combination and the total power consumption sequence of the corresponding phase of the target rail meter is compared. The combination with the largest Pearson correlation coefficient is selected as the target combination that has a topological relationship with the corresponding phase of the target rail meter. The energy meters in the target combination are the energy meters that have a topological relationship with the corresponding phase of the target rail meter.

[0050] The topology identification method of the electricity meter in this embodiment effectively overcomes the defects of single signal strength identification by static power traversal matching. Even in complex environments where signals from multiple meter boxes overlap significantly, it can achieve accurate and reliable identification of the topology relationship of the electricity meter.

[0051] Figure 2 The illustrated method for identifying the topology of electricity meters can identify the topology of meters with slow power consumption changes, but it cannot identify the topology of meters with rapid power consumption changes. As an example, please refer to [link to example]. Figure 3 Before step S30, the topology identification method for the electricity meter further includes: Step S50: Collect the real-time power data of each energy meter in each subset and the total power data of each phase of the target rail meter. Calculate the real-time power change of each energy meter based on the real-time power data and the total power change of each phase of the target rail meter based on the total power data.

[0052] In this step, real-time power data includes active power and reactive power, and total power data includes active power and reactive power.

[0053] As one embodiment, real-time power data of each energy meter in each subset and total power data of each phase of the target rail meter are collected at preset time intervals. The real-time power change of each energy meter and the total power change of each phase of the target rail meter are then calculated based on a differential algorithm. The preset time can be set by the user or the system according to actual needs. For example, a preset time of 200 milliseconds means that the real-time power of each energy meter and the total power of each phase of the target rail meter are collected at 200-millisecond intervals as a single sampling point. This continuous collection for a preset duration results in multiple sampling points within that duration.

[0054] The differential algorithm is a two-point differential calculation, which can be understood as taking the real-time power difference between two adjacent sampling points of the same energy meter as the real-time power change of the energy meter, and taking the total power difference between two adjacent sampling points of the same phase of the target rail meter as the total power change of the corresponding phase of the target rail meter; the interval between two adjacent sampling points is a preset time.

[0055] In one application scenario, when an energy meter connects to or disconnects from the communication of a target rail meter, it causes a step change in the total power of the target rail meter. By continuously collecting the total power data of each phase of the target rail meter at preset intervals, it is possible to monitor the change in the total power of the target rail meter when a single energy meter is connected or disconnected.

[0056] In one embodiment, after continuously collecting the real-time power of each energy meter in each subset and the total power of each phase of the target rail meter at preset time intervals, and before calculating the real-time power change of each energy meter and the total power change of each phase of the target rail meter based on a differential algorithm, the method further includes: storing the real-time power of each energy meter and the total power of each phase of the target rail meter in a preset buffer, and performing digital filtering on the data in the buffer. The buffer is a circular first-in-first-out queue with a buffer length of 64 points. This means that when the buffer is full, new data will overwrite the oldest data, always maintaining the latest 64 collection points. Digital filtering, for example, uses a digital infinite impulse response filter with a filter cutoff frequency fc = 1Hz and an order of 5. By performing digital infinite impulse response filtering on the data, high-frequency interference can be eliminated, improving the reliability and accuracy of the data.

[0057] Step S60: By comparing the matching degree between the real-time power change and the total power change when a single energy meter is connected to or disconnected from the target rail meter, the topological relationship between the corresponding phases of the energy meter and the target rail meter is identified.

[0058] In this step, since active power and reactive power satisfy the law of conservation of energy, they can be superimposed. If the energy meters in the topology generate changes in active power and / or reactive power, the corresponding rail meters will also generate corresponding changes in active power and / or reactive power. By comparing the changes in active power and / or reactive power, the topological relationship of the corresponding energy meters can be determined.

[0059] In this step, the matching degree is judged by the fact that the real-time power change of the electricity meter and the negative value of the total power change of the corresponding phase of the target rail meter are matched within a preset error threshold.

[0060] Through the above methods, the embodiments of this application can identify the topological relationship of electricity meters with high power consumption, effectively overcoming the defects of single signal strength identification. Even in complex environments where signals from multiple meter boxes severely overlap, the topological relationship can be deduced in real time by analyzing the real-time operating data of the electricity meters, thereby achieving dynamic identification of the topological relationship of the electricity meters with high accuracy.

[0061] In one embodiment, please refer to Figure 4 Step S60 further includes the following steps: Step S601: When a single energy meter is connected to or disconnected from the target rail meter, calculate the matching degree between the real-time power change of the energy meter and the total power change of the corresponding phase of the target rail meter.

[0062] In this step, the matching degree is compared with a preset error threshold to determine whether the matching degree is within the preset error threshold range.

[0063] Step S602: If the matching degree is within the preset error threshold range, it is determined that there is a topological relationship between the corresponding phases of the energy meter and the target guide rail meter.

[0064] In this step, the preset error threshold range can be adjusted by the user or the system according to actual needs.

[0065] Step S603: If the matching degree is not within the preset error threshold range, it is determined that there is no topological relationship between the corresponding phases of the energy meter and the target guide rail meter.

[0066] For example, using DTU_A as the target rail meter, the current total power P0 of the target rail meter DTU_A and the real-time power P_M of the energy meter M in subset A1 are obtained. Then, the connection between DTU_A and the energy meter M in subset A1 is briefly interrupted, and the total power P1 of DTU_A is obtained again after a preset interval. The total power change ΔP = P1 - P0 is calculated. According to the law of conservation of energy, ideally, the total power change ΔP_expected of the target rail meter caused by disconnecting the energy meter M should be approximately equal to -P_M. When the difference between ΔP and ΔP_expected is within a preset error threshold range (e.g., 5%), it proves that the real-time power change of the energy meter M matches the total power change of DTU_A, and it is determined that there is a topological relationship between the energy meter M and DTU_A.

[0067] In one embodiment, please refer to Figure 5 After step S603, the following steps are also included: Step S604: Accumulate the length of the preset time and determine whether the accumulated result has reached the preset duration.

[0068] In this step, the preset time is the interval for data collection, which can be set by the user or the system according to actual needs. For example, the preset time is 200 milliseconds, and the preset duration can be set by the user or the system according to actual needs. For example, the preset duration is 5 minutes.

[0069] In one embodiment, if the topological relationship of the energy meter is not determined in step S603 and the length of the accumulated preset time reaches the preset duration, it indicates that there is no topological relationship between the energy meter and the target guide rail meter. Then, the topological relationship of the next energy meter is identified, i.e., step S605 is executed.

[0070] Step S605: If yes, continue polling to identify the next energy meter until all energy meters in each subset have been polled.

[0071] In this step, polling to identify the next electricity meter can be understood as performing steps S50 and S60 on the next electricity meter.

[0072] In another embodiment, if the topological relationship of the electricity meter has been determined in step S602, step S605 is executed directly, without waiting for a preset time before polling to identify the next electricity meter, which can save time and computing resources.

[0073] Figure 2 and Figure 3 The illustrated method for identifying the topology of electricity meters can identify the topology of electricity meters that are using electricity, but it cannot identify the topology of electricity meters that are not using electricity. As an example, please refer to... Figure 6 After step S60, the method for identifying the topology of the energy meter further includes: Step S70: When there is an energy meter to be identified in the subset, collect the voltage value of the energy meter to be identified.

[0074] In this step, the energy meter to be identified is an energy meter that is not using electricity. This can be understood as the energy meter to be identified being processed... Figure 2 and Figure 3 The electricity meter topology identification method shown failed to identify the electricity meter. This is because the conductor has impedance, and 1 meter has a cross-sectional area of ​​2.5 mm². 2 The impedance of the copper conductor is approximately 6.7 mΩ. Therefore, when the phase currents of two rail meters differ significantly, the voltages measured by the rail meters will show a noticeable difference. For example, a current difference of 50 A will result in a voltage difference of 0.335 V. Meanwhile, the voltage value of an unused energy meter, having no current flowing through it, will be essentially the same as the phase voltage value of its corresponding rail meter.

[0075] Step S80: Classify the voltage values ​​of the energy meters to be identified.

[0076] In this step, the inherent distribution pattern of voltage characteristics is explored through classification analysis. This can be done using threshold classification or clustering classification, thereby identifying the possible phase assignment of the second energy meter.

[0077] As one embodiment, K-means clustering is performed on the voltage value of the second energy meter to be identified. For example, the number of clusters in the K-means clustering is set to 3. R, where R is the number of adjacent rail meters, with the three phase voltage values ​​of the target rail meter as the centroid.

[0078] Step S90: Determine the topological relationship between the phases of the energy meter to be identified and the target rail meter based on the clustering results.

[0079] In this step, the energy meters whose voltage values ​​are clustered together with the phase voltages of the target rail meter are determined to have a topological relationship with the phase corresponding to the target rail meter.

[0080] The topology identification method for electricity meters in this embodiment, based on dynamic power matching and static power traversal matching, achieves topology identification for installed but not powered electricity meters through zero-power voltage identification, thereby realizing topology identification for all types (dynamic, static, and zero-power) electricity meters within the jurisdiction of the rail-mounted meter, with high identification accuracy.

[0081] As one example, please refer to Figure 7 Step S70 includes: Step S701: When there is an energy meter to be identified in the subset, establish communication between the target rail meter and the adjacent rail meters.

[0082] In this step, the communication method is wireless, such as Bluetooth.

[0083] Step S702: Obtain the voltage and power values ​​of the adjacent rail meters, and calculate the current value of the adjacent rail meters based on the voltage and power values.

[0084] Step S703: Obtain the current value of the target rail meter and calculate the current difference between the target rail meter and the adjacent rail meter.

[0085] Step S704: When the current difference exceeds the preset threshold, collect the voltage value of the energy meter to be identified.

[0086] In this step, "current difference exceeding the preset threshold" means that the current difference is greater than the preset threshold, for example, the preset threshold is 50A.

[0087] For example, assuming that energy meter S1 in subset A1 is an unused energy meter, then at any time, the A-phase voltage of the target rail meter DTU_A is U_A. The target rail meter DTU_A obtains the A-phase voltage of the adjacent rail meter DTU_B, which is U_B, via Bluetooth communication. Due to the different loads of the two meter boxes, if the A-phase current of the target rail meter DTU_A is much greater than that of the adjacent rail meter DTU_B, then U_A will be slightly lower than U_B due to line impedance (e.g., U_A = 229.5V, U_B = 229.8V, a difference of 0.3V, corresponding to a current difference of approximately 45A). At this time, the target rail meter DTU_A reads the voltage value of energy meter S1. If the voltage value of energy meter S1 is 229.5V, it is consistent with U_A, but significantly different from U_B. Therefore, by using K-means clustering, the electricity meter S1 is identified as having a topological relationship with phase A of the target rail meter DTU_A.

[0088] like Figure 8As shown in the figure, this application embodiment also provides a topology identification device for an electricity meter. The device 80 includes an acquisition module 81, a classification module 82, a calculation module 83, and an identification module 84.

[0089] The acquisition module 81 is used to acquire the communication signal strength of multiple energy meters scanned by the target guide rail meter, and determine the candidate set of energy meters with topological relationship to be identified based on the communication signal strength. The classification module 82 is used to collect the voltage values ​​of each energy meter in the candidate set of energy meters, and divide the candidate set of energy meters into subsets corresponding to each subset of the target guide rail meter according to each voltage value; The calculation module 83 is used to combine the energy meters in each subset respectively, obtain the total power consumption of each combination and the total power consumption of the target meter rail meter corresponding to the phase, and calculate the correlation between the total power consumption of the target rail meter corresponding to the phase and the total power consumption of each combination. The identification module 84 is used to identify the topological relationship between the corresponding phases of the energy meter and the target rail meter based on the correlation.

[0090] The topology identification device for this electricity meter uses intelligent analysis of the electricity meter's power data to infer the topology relationship. It has high identification accuracy and can effectively overcome the shortcomings of identification using a single signal strength in complex environments with severe signal overlap among multiple meter boxes.

[0091] The above are merely preferred embodiments of this application and are not intended to limit this application in any way. Although this application has disclosed preferred embodiments as above, it is not intended to limit this application. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the technical solution of this application. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of this application without departing from the scope of the technical solution of this application shall still fall within the scope of the technical solution of this application.

Claims

1. A method for identifying the topological relationship of an electricity meter, characterized in that, include: The communication signal strength of multiple energy meters scanned by the target guide rail meter is obtained, and a candidate set of energy meters with topological relationships to be identified is determined based on the communication signal strength. Collect the voltage values ​​of each of the energy meters in the candidate set of energy meters, and divide the candidate set of energy meters into subsets corresponding to each of the target rail meters based on the voltage values; The energy meters in each subset are combined to obtain the total power consumption of each combination and the total power consumption of the target meter rail corresponding to the phase, and the correlation between the total power consumption of the target meter rail corresponding to the phase and the total power consumption of each combination is calculated. The topological relationship between the corresponding phases of the energy meter and the target rail meter is identified based on the correlation.

2. The method for identifying the topological relationship of an electricity meter as described in claim 1, characterized in that, The step of combining the energy meters in each subset to obtain the total electricity consumption of each combination and the total electricity consumption of the corresponding phase of the target meter rail includes: Within a preset period, the electricity consumption sequence of each of the energy meters in each of the subsets and the total electricity consumption sequence of the corresponding phase of the target guide rail meter are obtained respectively; The energy meters within each of the aforementioned subsets are combined; For each combination, the total electricity consumption sequence of the combination is calculated based on the electricity consumption sequence of the electricity meters within the combination; the total electricity consumption sequence is the sum of the electricity consumption sequences of the electricity meters within the combination.

3. The method for identifying the topological relationship of an electricity meter as described in claim 2, characterized in that, The calculation of the correlation between the total power consumption of the corresponding phase of the target guide rail meter and the total power consumption of each combination includes: Calculate the Pearson correlation coefficient between the total power consumption sequence of the corresponding phase of the target rail table and the total power consumption sequence of each combination; The formula for calculating the Pearson correlation coefficient is as follows: , wherein The target guide rail table i represents the total electrical quantity sequence within the preset period. Let be the total electricity consumption sequence of combination j within the preset period, where cov is the covariance and D is the variance.

4. The method for identifying the topological relationship of an electricity meter as described in claim 3, characterized in that, The step of identifying the topological relationship between the corresponding phases of the energy meter and the target rail meter based on the correlation includes: Compare the Pearson correlation coefficients of each; The combination corresponding to the largest Pearson correlation coefficient is selected as the target combination with the topological relationship of the phase corresponding to the target rail meter; the energy meter in the target combination is the energy meter that has a topological relationship with the phase corresponding to the target rail meter.

5. The method for identifying the topological relationship of an electricity meter as described in claim 1, characterized in that, Before combining the energy meters in each subset to obtain the total power consumption of each combination and the total power consumption of the corresponding phase of the target meter rail, and calculating the correlation between the total power consumption of the corresponding phase of the target meter rail and the total power consumption of each combination, the method further includes: Collect real-time power data of each energy meter in each subset and total power data of each phase of the target rail meter; calculate the real-time power change of each energy meter based on the real-time power data and the total power change of each phase of the target rail meter based on the total power data. By comparing the matching degree between the real-time power change and the total power change when a single energy meter is connected to or disconnected from the target rail meter, the topological relationship between the corresponding phases of the energy meter and the target rail meter is identified.

6. The method for identifying the topological relationship of an electricity meter as described in claim 5, characterized in that, The process of collecting real-time power data from each of the energy meters in each of the subsets and total power data from each phase of the target rail meter, and calculating the real-time power change of each of the energy meters based on the real-time power data and the total power change of each phase of the target rail meter based on the total power data, includes: Real-time power data of each energy meter in each subset and total power data of each phase of the target guide rail meter are collected at consecutive preset time intervals. The real-time power change of each of the energy meters and the total power change of each phase of the target rail meter are calculated based on the differential algorithm.

7. The method for identifying the topological relationship of an electricity meter as described in claim 1, characterized in that, After identifying the topological relationship between the corresponding phases of the energy meter and the target rail meter based on the correlation, the method further includes: When the subset contains an energy meter to be identified, the voltage value of the energy meter to be identified is collected; The voltage values ​​of the energy meters to be identified are classified. The topological relationship between the phases of the energy meter to be identified and the target rail meter is determined based on the clustering results.

8. The method for identifying the topological relationship of an electricity meter as described in claim 7, characterized in that, When the subset contains an energy meter to be identified, collecting the voltage value of the energy meter to be identified includes: When the subset contains an energy meter to be identified, communication is established between the target rail meter and the adjacent rail meters. Obtain the voltage and power values ​​of the adjacent rail meters, and calculate the current value of the adjacent rail meters based on the voltage and power values; Obtain the current value of the target rail meter and calculate the current difference between the target rail meter and the adjacent rail meter; When the current difference exceeds a preset threshold, the voltage value of the energy meter to be identified is collected.

9. A topology identification device for an electricity meter, characterized in that, include: The acquisition module is used to acquire the communication signal strength of multiple energy meters scanned by the target guide rail meter, and determine the candidate set of energy meters with topological relationships to be identified based on the communication signal strength. The classification module is used to collect the voltage values ​​of each of the energy meters in the candidate set of energy meters, and divide the candidate set of energy meters into subsets corresponding to each of the target rail meters according to the voltage values. The calculation module is used to combine the energy meters in each subset respectively, obtain the total power consumption of each combination and the total power consumption of the target meter rail meter corresponding to the phase, and calculate the correlation between the total power consumption of the target meter rail meter corresponding to the phase and the total power consumption of each combination. The identification module is used to identify the topological relationship between the corresponding phases of the energy meter and the target rail meter based on the correlation.

10. A topological relationship identification system for an electricity meter, characterized in that, Includes the topology identification device for an electricity meter as described in claim 9.

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