Method and system for identifying user-box relation based on HPLC interception analysis technology

Abstract

The invention relates to the technical field of low-voltage power line carrier communication and intelligent measurement switch application of an intelligent power grid, and discloses a method and a system for identifying a user-box relationship based on an HPLC (High Performance Liquid Chromatography) interception analysis technology. According to the method, a service communication message on a power line is monitored through an HPLC node, and the user-box relationship between an intelligent measurement switch and other HPLC node equipment is identified in combination with logic analysis. According to the method, the difficulty in user-box relation identification is effectively solved by utilizing the approximately equal relation of the forward active total electric energy increment, a split-phase iterative comparison algorithm and a carrier signal compensation gain value K-Means clustering analysis algorithm, and the identification accuracy and efficiency are improved. The system comprises a low-voltage concentrator, an intelligent measurement switch and other components, is suitable for a full-carrier meter table area, and reduces the equipment cost and the maintenance cost.

Description

Technical Field

[0001] This invention relates to the field of low-voltage power line carrier communication and intelligent measurement switch application technology in smart grids, and discloses a method and system for identifying customer box relationships based on HPLC listening analysis technology. Background Technology

[0002] With the bidding and widespread application of HPLC modules and smart metering switches, the demand for the physical topology connections between smart metering switches and smart carrier meters connected to their A, B, and C phase output terminals in low-voltage power information collection areas is increasing. This demand for the smart metering switch-to-box relationship is crucial for the accurate location of faults and the calculation of line losses within the distribution boxes in low-voltage power information collection areas.

[0003] The main current methods for identifying the relationship between the user box and the intelligent metering switch are the RS485 meter search method and the characteristic current analysis method.

[0004] RS485 table lookup method self-identification method: In a scenario where the smart metering switch and the meters connected to its A, B, and C phase output terminals are all connected via RS485, the smart metering switch, upon initial power-on, actively searches for all connected meters sequentially using RS485 abbreviated meter search, thereby achieving self-identification of the relationship between the smart metering switch and the meters.

[0005] Characteristic current analysis and identification method: The concentrator sequentially controls each carrier device connected to the intelligent measurement switch in the control area to actively emit pulse-width modulated characteristic currents. The characteristic current processing unit in the intelligent measurement switch receives the characteristic current, demodulates and identifies it, and reports the characteristic current identification result. Ultimately, the concentrator can then identify the customer-box relationship between the intelligent measurement switch and other carrier node devices in the control area.

[0006] The existing RS485 meter search methods, such as self-identification and characteristic current analysis, for identifying the customer box relationship of smart meter switches have at least the following drawbacks: (1) The RS485 meter search method relies too much on the connection between the smart metering switch and the RS485 communication line of the node device connected to it. However, in reality, most node devices in the transformer area generally use power line carrier communication and no longer connect to the smart metering switch through RS485 communication line. Therefore, this method is not widely applicable.

[0007] (2) The characteristic current analysis and identification method requires that the intelligent measurement switch and its downstream node equipment must have a characteristic current hardware transmission circuit unit, and the intelligent measurement switch must also have a characteristic current receiving and processing circuit unit, which increases the hardware cost of the equipment in the distribution area. In addition, it cannot be applied to equipment distribution areas that do not have a characteristic current transmission and receiving processing circuit unit, that is, the applicable scope is small.

[0008] (3) The characteristic current analysis and identification method requires the concentrator to send characteristic current signals to each device node in the control area one by one. Finally, the relationship between the user box is identified by logical analysis based on the identification result event reported by the intelligent measurement switch. The time for each round of control to send characteristic current and the identification process is relatively long, resulting in low efficiency.

[0009] (4) The characteristic current analysis and identification method has certain side effects because the characteristic current sent in each round of control and the identification process lasts for a long time, which will affect the routine data collection tasks of the low-voltage power consumption information collection station and result in missing some data.

[0010] (5) The characteristic current sending circuit unit in the characteristic current analysis and identification method will cause the board to be briefly and continuously hot each time it sends a characteristic current. Long-term and frequent use will easily damage the characteristic current sending circuit unit, causing the identification of the customer box relationship of the intelligent measurement switch in the transformer area to fail. Therefore, the stability and long-term performance of this method are poor. Summary of the Invention

[0011] To address the aforementioned technical shortcomings, the purpose of this invention is to provide a method and system for identifying customer-box relationships based on HPLC listening analysis technology. This solves the problems of the existing RS485 meter search method, which involves complex wiring and is not applicable to all-carrier meter stations. It also solves the problems of the characteristic current analysis identification method, which suffers from high equipment costs, long time consumption per round of customer-box relationship identification, impact on curve data acquisition, and poor stability due to the additional characteristic current transmission and reception processing board.

[0012] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for identifying customer-cell relationships based on HPLC listening analysis technology, comprising: Step 1: By listening to the service communication messages of all nodes in the power line carrier network that it communicates with through the HPLC node, perform logical analysis to identify the customer box relationship between the intelligent measurement switch and other HPLC node devices; Step 2: The HPLC module on the intelligent measurement switch continuously listens to and analyzes the total positive active power of the HPLC node equipment over multiple cycles on the power line. The response message compares the total positive active power increment of the smart metering switch over multiple cycles. Total positive active power increment compared to other HPLC node devices The sum under different combination scenarios If the approximate equivalence relationship is satisfied, then all HPLC node devices included in the combination belong to the direct-connection devices of the power line at the output terminal of the intelligent measurement switch, that is, the node devices inside the box. Step 3: The HPLC module on the intelligent measurement switch continuously listens for the discovery list messages of HPLC nodes on the power line, parses the phase information of the nodes, records and saves the phase of all detected nodes, and compares the node phase information with the total positive active power increment of the node within the period T calculated by the listening. By combining these factors, the total positive active power increment at different phase nodes can be obtained. ,in Represents phase information; Step 4: Introduce a phase-by-phase positive active total energy increment iterative comparison algorithm to distinguish cases where the difference between the positive active total energy increment of the equipment inside and outside the smart measurement switch box is less than a set threshold. Step 5: Introduce the K-Means clustering analysis algorithm for the carrier signal compensation gain value of HPLC node equipment to handle the case where the positive active total power increment value of the intelligent measurement switch connected to the HPLC node equipment and the non-connected HPLC node equipment is the same or the difference is less than the set threshold. Step 6: The HPLC module on the intelligent measurement switch continuously listens to and parses the response messages of the power line reading device voltage in each statistical cycle, and compares the node device voltages listened to in the previous two statistical cycles with the three phase voltages of the intelligent measurement switch itself. , , Comparative analysis is conducted to help determine whether a node is an in-box node device that is a non-intelligent measuring switch; Step 7: The HPLC module on the smart metering switch continuously listens to the discovery list messages of nodes on the power line, parses out the MAC address, level, and CCO MAC information of the node and saves them accordingly. By sequentially analyzing and comparing the relationship between the level and CCO MAC address of the smart metering switch HPLC module and the level and CCO MAC address information of other node devices detected in the previous two statistical periods, it is determined whether the node is an in-box node device of a non-smart metering switch.

[0013] Preferably, in one possible implementation of the first aspect, step 1 includes: Step 1-1: HPLC sniffing technology sniffs the service communication messages of all nodes in the power line carrier network that are associated with the sniffing node. The nodes associated with the communication include the proxy nodes of the HPLC sniffing node, multi-level proxy nodes, and all lower-level nodes on the same network topology link. Steps 1-2: The HPLC module of the intelligent measurement switch listens to and parses the echo messages of the nodes on the power line, and identifies the customer box relationship between the intelligent measurement switch carrier node and other carrier device nodes through logical analysis.

[0014] Preferably, in one possible implementation of the first aspect, step 2 includes: Step 2-1: The HPLC module on the intelligent measurement switch continuously listens for the response messages of the HPLC node devices on the power line, identifies the node to which the response code value belongs based on the device address in the message, and calculates the total positive active power of all listening nodes in each statistical period. The positive active total electrical energy increment within ,in , and They are respectively Time and Total positive active power at any given moment; Step 2-2: Compare the increase in total positive active power of the intelligent measuring switch within period T. Other The total positive active power increment of each HPLC node device Does the equality relationship satisfy the following conditions in a certain combination scenario? ,in Line loss due to power consumption; Steps 2-3: If two consecutive periods T satisfy the above approximate equivalence relationship, then all HPLC node devices included in this combination are considered valid. , , , The power supply lines are all directly connected to one of the phase outputs of the intelligent measurement switch A, B, and C, which belongs to the HPLC node equipment inside the box; Steps 2-4: Compare the current information of all HPLC node devices in the chamber with the information of the node devices in the chamber that was saved last time. If they are the same, the original information is maintained. If they are different, the information is updated and a user-chamber relationship change event is generated. The HPLC module of the intelligent measurement switch actively reports the event to the uplink terminal device. Step 2-5: Repeat step 2-1.

[0015] Preferably, in one possible implementation of the first aspect, step 3 includes: Step 3-1: The HPLC module on the intelligent measurement switch continuously listens for the discovery list messages of HPLC nodes on the power line, parses the communication address and phase information of the HPLC node that sent the message, and records and saves them. Step 3-2: Combine the node phase information with the total positive active power increment of the node calculated within period T. By combining these measurements, the total positive active power increment at different phase nodes detected by the intelligent measurement switch HPLC module was obtained. , , , , , , where A, B, and C represent phases A, B, and C, respectively.

[0016] Preferably, in one possible implementation of the first aspect, step 4 includes: Step 4-1: Within each statistical period T, after receiving the feedback code of the total positive active energy data of the intelligent measurement switch, the HPLC module on the intelligent measurement switch actively reads the total positive active energy data of phases A, B, and C of the intelligent measurement switch, and calculates the increment of the total positive active energy of each phase within period T. ,in Indicates phase, and They are respectively Time and time The total positive active power of the phase; Step 4-2: Compare the increase in total positive active power of each phase of the smart metering switch within each statistical period T. The phase obtained from step 3-2 The total positive active power increment of all node devices The summation under different combinations Does the relationship satisfy the equality requirement? ,in Line loss due to power consumption; Step 4-3: If two consecutive periods T satisfy the above approximate equivalence relationship, then all HPLC node devices included in this combination are considered valid. , , , The power supply lines are all powered by intelligent measurement switches. The phase output line is directly connected, belonging to the in-chamber HPLC node equipment; Step 4-4: Through statistical comparative analysis of steps 4-2 and 4-3, the relationship between the monitored HPLC node device and the intelligent measurement switch in the three phases A, B, and C is obtained; Steps 4-5: Calculate the relationship between the HPLC node equipment and the intelligent measurement switch in the three phases by analyzing the approximate relationship of the total positive active power increment in each phase.

[0017] Preferably, in one possible implementation of the first aspect, step 5 includes: Step 5-1: The carrier signal compensation gain value represents the carrier signal attenuation measure of other HPLC node devices in the low-voltage power line carrier network relative to the listening node device. It indicates the gain value required to maintain stable carrier communication. The smaller the gain value, the smaller the signal attenuation and the stronger the signal. Step 5-2: The carrier signal compensation gain between all networked HPLC node devices and HPLC listening node devices gradually increases with the superposition of physical topology levels, the extension of communication distance, or the relay of intelligent measurement switches. Step 5-3: Due to the influence of physical topology and communication distance, the carrier signal compensation gain value between the HPLC node device directly powered by the same intelligent measurement switch output terminal and the intelligent measurement switch HPLC device is smaller compared with the carrier signal compensation gain value between node devices under other physical topology levels. Step 5-4: HPLC listening technology can listen to the carrier signal compensation gain value between the listening node itself and surrounding nodes and the listening node device, where the gain value of the listening node itself is... =0; Step 5-5: The intelligent measurement switch compensates for the carrier signal gain value of all monitored HPLC node devices. Introducing the K-Means clustering algorithm, iteratively classifying all node devices into gain values. near and away Two major clusters; Steps 5-6: For HPLC node devices where the total positive active power increment is 0, equal, or the difference is less than a set threshold within certain statistical periods, determine their gain value. Does it fall under the category of being far away? Cluster members are used to exclude nodes belonging to the same bin; if a node belongs to a cluster far away, it is determined to be a node not belonging to the same bin.

[0018] Preferably, in one possible implementation of the first aspect, step 5-5 includes: Step 5-5-1: Using the K-Means clustering algorithm, the carrier signal compensation gain value of the intelligent measurement switch's own HPLC node device is calculated. As the initial cluster center of cluster 1 ; Step 5-5-2: Calculate the gain values ​​of all listening HPLC node devices. and absolute value of the difference ,in ; Step 5-5-3: Use bubble sort to sort... Sort and take the maximum value. ,Will As the initial cluster center of cluster 2 ; Step 5-5-4: Calculate each and and absolute value of the difference and Compare the sizes, if Smaller Classified to If it belongs to the same cluster, otherwise it is classified as... Cluster; Step 5-5-5: Calculate the average value of all members in cluster 1 and cluster 2 respectively. and ; Step 5-5-6: If or Then replace , replace Repeat steps 5-5-4 to 5-5-6, otherwise proceed to step 5-5-7; Step 5-5-7: If and This yields two stable clusters of data, with the first cluster having gain values ​​close to... The category set, the second cluster is the one where the gain value is far away A collection of categories.

[0019] Preferably, in one possible implementation of the first aspect, steps 5-6 include: Step 5-6-1: For HPLC node equipment where the total positive active power increment is 0, determine its gain value. The relationship between a user and a box is determined by whether the user belongs to the first cluster. If the user belongs to the first cluster, the user is considered an internal node; otherwise, the user is considered an external node. Step 5-6-2: For cases where the total positive active power increments of multiple node devices are equal or the difference is less than a set threshold, determine their gain values. The relationship between a user and a box is determined by whether the user belongs to the first cluster. If the user belongs to the first cluster, the user is considered an internal node; otherwise, the user is considered an external node.

[0020] Preferably, in one possible implementation of the first aspect, step 6 includes: Step 6-1: The HPLC module on the intelligent measurement switch continuously listens to the power line to read the response messages of the HPLC node device voltage during each statistical cycle, parses the device address and voltage value, and saves them accordingly. The voltage of the intelligent measurement switch itself includes the A-phase voltage. Phase B voltage C-phase voltage ; Step 6-2: Compare the voltage information corresponding to each device address. and , , absolute value of the difference , , Are they all greater than , The default value is 3V, and the comparison results are saved. Step 6-3: Based on the comparison results of Step 6-2 in the previous two statistical periods, if the difference condition is met, it is determined that the node device does not belong to the node in the intelligent measurement switch box.

[0021] Preferably, in one possible implementation of the first aspect, step 7 includes: Step 7-1: The HPLC module on the intelligent measurement switch and the downstream node devices at the output terminals of each phase line are isolated and attenuated in the carrier communication. The level of the downstream node device in the carrier network is higher than or equal to the node level of the intelligent measurement switch HPLC module. If the node level is more than one level lower than the intelligent measurement switch level or more than two levels higher, it is determined to be a non-in-box node device. Step 7-2: The HPLC module on the intelligent measurement switch continuously listens for the node discovery list messages on the power line and records the MAC address, level, and CCO MAC address correspondence of the nodes; Step 7-3: By analyzing and comparing the relationship between the hierarchy of the intelligent measurement switch HPLC module, the MAC address of the CCO and the hierarchy of other node devices, and the MAC address information of the CCO in the first two statistical periods, determine whether the node is a non-in-box node device.

[0022] Preferably, in one possible implementation of the first aspect, step 7-3 includes: Step 7-3-1: Analyze and compare the hierarchical level of the intelligent measurement switch HPLC module, the MAC address of the CCO, and the hierarchical level and MAC address information of the CCO with other node devices in the first two statistical periods. Step 7-3-2: If the MAC address of the CCO of a certain node device is different from the MAC address of the CCO of the intelligent measurement switch HPLC module in both statistical periods, it is determined to be a non-in-box node device. Step 7-3-3: If the level of a certain node device is more than one level lower than the level of the intelligent measurement switch HPLC module in both statistical periods, it is determined to be a non-in-box node device. Step 7-3-4: If the level of a certain node device is more than 2 levels higher than the level of the intelligent measurement switch HPLC module in both statistical periods, it is determined to be a non-in-box node device.

[0023] Secondly, the present invention provides an intelligent measuring switch, which integrates a circuit breaker switch, a carrier communication unit board, a power supply board, and a main control metering board, and has the functions of switching on and off, carrier communication, metering, and intelligent control, and is used to implement the method described in the first aspect.

[0024] Thirdly, the present invention provides a system for identifying customer-cell relationships based on HPLC listening analysis technology, used to implement the method described in the first aspect, including: The low-voltage concentrator is used to periodically collect 15-minute curve data from smart metering switches and carrier energy meters according to the tasks and schemes configured by the main station, and to receive and parse the customer box relationship identification result event and customer box relationship change event reported by the smart metering switch. The CCO master node module is plugged into the low-pressure concentrator and is used for HPLC networking and communication. The STA slave node module is plugged into a smart measurement switch or carrier energy meter and is used for HPLC networking and communication. The intelligent measurement switch includes the main body of the intelligent measurement switch and the STA slave node module. The STA slave node module realizes HPLC networking, listens and analyzes data acquisition business messages on the power line and performs algorithm analysis to calculate the relationship between the customer box and the power supply box. The main body of the intelligent measurement switch realizes the intelligent control and metering functions related to the circuit breaker. Carrier energy meters include carrier energy meters connected to the three-phase output terminals A, B, and C of the smart measurement switch and carrier energy meters connected to the bypass of the smart measurement switch. Electrical load devices are connected to the outgoing line of the carrier energy meter to generate energy consumption, providing power consumption data support for identifying the relationship between the household and the meter.

[0025] Fourthly, the present invention provides a terminal, wherein the storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the method described in the first aspect.

[0026] Fifthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described in the first aspect.

[0027] The beneficial effects of this invention are as follows: The method and system for identifying customer-cell relationships based on HPLC listening analysis technology proposed in this invention creatively introduces HPLC listening technology combined with logic analysis to realize the function of identifying customer-cell relationships. It cleverly bypasses the disadvantage of conventional RS485 self-identification methods that require an additional connection of an intelligent measurement switch to an RS485 line. At the same time, it avoids the disadvantage of characteristic current identification methods that require the integration of characteristic current modulation transmitter boards in both the intelligent measurement switch and the downstream carrier node equipment, which greatly reduces the cost of application equipment and on-site maintenance costs.

[0028] The introduced HPLC eavesdropping technology listens to and parses service interaction messages on the power line carrier channel and identifies the relationship between the customer and the transformer substation through logical analysis. It cleverly uses low-voltage electricity consumption information collection service messages for analysis directly, without the need to send additional special command messages, which greatly reduces the impact of transformer substation customer relationship identification on the routine electricity consumption information collection service in the transformer substation area.

[0029] The introduced method for identifying the relationship between households and distribution boxes based on HPLC listening analysis technology can complete the algorithm identification in as little as two rounds of electricity consumption information data collection (the concentrator typically collects one round of electricity consumption information data from the node equipment every 15 minutes), which greatly improves the efficiency of household-distributor relationship identification in the distribution area.

[0030] The algorithm iterates in real time by analyzing the data collected every two electricity consumption data collection cycles, which can promptly identify scenarios where the relationship between the household and the distribution box changes midway, greatly ensuring the real-time performance and accuracy of the household-distribution box relationship identification.

[0031] The K-Means clustering analysis algorithm for carrier signal compensation gain of HPLC node equipment is introduced to solve the problem that the incremental value of positive active power of HPLC node equipment connected to the smart metering switch and non-HPLC node equipment is the same or similar in certain cycles, which makes it difficult to determine the relationship between node equipment and smart metering switch customer box. This greatly improves the universality of this technical method for various scenarios and substations. Attached Figure Description

[0032] 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 some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 This application provides a flowchart of a method for identifying customer-cell relationships based on HPLC listening analysis technology.

[0034] Figure 2This application provides an increment of the total positive active power based on intelligent measurement switches over multiple cycles. E(k) and the increment of total positive active power of other HPLC node devices E( ) Flowchart of the algorithm for relationship analysis to identify user-box relationships.

[0035] Figure 3 This application provides a flowchart for analyzing the relationship between HPLC node equipment and intelligent measurement switches using a carrier signal compensation gain K-Means clustering algorithm.

[0036] Figure 4 This application provides a schematic diagram of the framework structure of a test system for identifying the relationship between users and boxes based on HPLC listening analysis technology. Detailed Implementation

[0037] 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.

[0038] Example 1: As Figure 1 As shown, this invention proposes a method for identifying customer-box relationships based on HPLC eavesdropping analysis technology. It uses power line carrier eavesdropping technology to listen to the read data packets of intelligent measuring switches and other HPLC node devices in the low-voltage power consumption information collection area, and realizes the function of customer-box relationship identification through logical algorithm analysis.

[0039] The method includes the following steps: Step 1: By listening to the service communication messages of all nodes in the power line carrier network that it communicates with through the HPLC node, logical analysis is performed to identify the customer box relationship between the intelligent measurement switch and other HPLC node devices.

[0040] Specifically, in step 1-1, HPLC sniffing technology can detect the business communication messages of all nodes in the power line carrier network that are associated with it. The nodes associated with the communication include the proxy nodes of the HPLC sniffing node, multi-level proxy nodes, and all lower-level nodes on the same network topology link.

[0041] Steps 1-2: The HPLC module of the intelligent measurement switch listens to and parses the echo messages from the nodes on the power line. Through subsequent logical analysis, it identifies the customer-box relationship between the carrier node of the intelligent measurement switch and other carrier device nodes.

[0042] Furthermore, the so-called HPLC eavesdropping technology is achieved through minor modifications to the existing State Grid HPLC interconnection carrier communication technology: When the HPLC application layer monitor receives service messages on the carrier power line, it does not filter them according to their own address, but instead parses and processes the service messages.

[0043] Step 2: The HPLC module on the intelligent measurement switch continuously listens to and analyzes the total positive active power of the HPLC node equipment in multiple cycles on the power line. The response message compares the total positive active power increment of the smart metering switch over multiple cycles. Total positive active power increment compared to other HPLC node devices The sum under different combination scenarios If the approximate equivalence relationship is satisfied, then all HPLC node devices included in the combination belong to the direct-connection devices of the power line at the output terminal of the intelligent measurement switch, that is, the node devices inside the box.

[0044] Specifically, the detailed algorithm flowchart for step 2 is as follows: Figure 2 As shown.

[0045] Step 2-1: The HPLC module on the intelligent measurement switch continuously listens for the response messages of the positive active total power of the HPLC node devices on the power line, and confirms the node to which the response code value belongs based on the device address in the message. Then, it calculates each statistical period T (T can usually be set to 15 minutes) for all the nodes it has detected. The increase in total positive active power before and after , and They are respectively Time and Total positive active power at any given moment; Step 2-2: Repeatedly compare the increment of the total positive active power of the smart metering switch within the cycle T. Increment of total positive active power compared to other HPLC node devices Does the following equality relation hold in a certain combination scenario?

[0046] 'q' refers to the line loss of electricity consumption, which can be set; the default setting is 3Wh.

[0047] Steps 2-3, if two consecutive periods T satisfy the condition... If the relationship is approximately equal, then this combination includes all HPLC node devices. , , , The power supply lines are all directly connected to one of the phase outputs of the intelligent measurement switch A, B, and C, which belongs to the HPLC node equipment inside the box.

[0048] Steps 2-4 compare the information of all HPLC node devices in the chamber with the information of the HPLC node devices in the chamber saved last time. If they are the same, keep the information of the HPLC node devices in the chamber unchanged; if they are different, update the information of the HPLC node devices in the chamber and generate a user-chamber relationship change event, which is actively reported to the uplink terminal device by the HPLC module of the intelligent measurement switch.

[0049] Step 2-5, then return to step 2-1.

[0050] Furthermore, the content format of the account change event mentioned in steps 2-4 is defined as shown in Table 1 below.

[0051] Table 1. Definition of Format for User Box Change Event Content

[0052] Step 3: The HPLC module on the intelligent measurement switch continuously listens for the discovery list messages of HPLC nodes on the power line, parses the phase information of the nodes, records and saves the phase of all detected nodes, and compares the node phase information with the total positive active power increment of the node within the period T calculated by the listening. By combining these factors, the total positive active power increment at different phase nodes can be obtained. ,in Represents phase information; Step 3-1: The HPLC module on the intelligent measurement switch continuously listens for the discovery list messages of HPLC nodes on the power line, parses the communication address and phase information of the HPLC node that sent the discovery list message, and records and saves it.

[0053] Step 3-2: Combine the corresponding node phase information with the increment of the total positive active power of the node within the period T calculated by the monitoring. By combining these measurements, the increment of the total positive active power at different phase nodes detected by the HPLC module of the intelligent measurement switch can be obtained. , , (A, B, and C refer to phases A, B, and C, respectively).

[0054] Furthermore, the discovery list message format of the HPLC node mentioned in step 3-1 follows the definition in Part 4-2 of the Low Voltage Power Line Broadband Carrier Communication Interoperability Technical Specification: Data Link Layer Communication Protocol, as shown in Table 2. The MAC address in the table is the communication address of the HPLC node that sends the discovery list message, and the phase line in the table is the phase to which the HPLC node belongs.

[0055] Table 2 Discovery List Message Format

[0056] Step 4 introduces a phase-by-phase positive active total energy increment iterative comparison algorithm to distinguish cases where the difference between the positive active total energy increment of the equipment inside and outside the smart measurement switch box is less than a set threshold.

[0057] Step 4-1, each statistical period T (T is set to 15 minutes, Within a given period, each time the HPLC module on the intelligent measuring switch receives the feedback code of the total positive active energy data from the intelligent measuring switch, it begins to actively read the total positive active energy data of each phase (A, B, and C) of the intelligent measuring switch, and calculates the increment of the total positive active energy of each phase within period T. ,in Indicates phase, and They are respectively Time and time The total active electrical energy in the positive direction of the phase.

[0058] Step 4-2: Compare the increment of the total positive active power of each phase of the smart measuring switch before and after each statistical period T. (p refers to the phase, which may be one of three phases: A, B, or C) and the total positive active power increment of all node devices before and after the period T obtained in step 3-2 for that phase p. Summation under different combinations Does the relationship satisfy the equality requirement?

[0059] This refers to the line loss of electricity consumption, which can be set; the default setting is 3Wh.

[0060] Step 4-3: If two consecutive periods T satisfy the approximation relationship in step 4-2, then this combination includes all HPLC node devices. , , , The power supply lines are all powered by intelligent measurement switches. The phase output line is directly connected, making it an in-chamber HPLC node device.

[0061] Step 4-4: Following steps 4-2 and 4-3, statistical comparison and analysis are performed to obtain the relationship between the detected HPLC node device and the intelligent measurement switch in the three phases A, B, and C.

[0062] Steps 4-5, and the statistical logic analysis in steps 4-1, 4-2, 4-3, and 4-4, refine the calculation of the relationship between the HPLC node equipment and the intelligent measurement switch in phases A, B, and C by analyzing the approximate relationship of the total positive active energy increment in each phase. This solves the problem of some HPLC node equipment having equal or significantly different total positive active energy increments within the statistical period. The problem is that it is impossible to distinguish which HPLC node device belongs to which category.

[0063] In practice, taking the area around the power wiring of a smart metering switch in a residential radio station area as an example, Table 3 below shows the detection data of 9 carrier meters around a smart metering switch and the calculation results of the algorithm in step 4.

[0064] Table 3. Actual detection data and calculation results of the intelligent measurement switch and its surrounding 9 carrier meters.

[0065] Table 3 (continued) Actual detection data and calculation results of the intelligent measurement switch and its surrounding 9 carrier meters

[0066] In Table 3, the HPLC identification phase is obtained by the HPLC module of the intelligent measurement switch by listening to and parsing the discovery list messages of the node devices on the power line.

[0067] In Table 3, the positive active total energy increment 1 and positive active total energy increment 2 are obtained through the method in step 3 and the formula in step 4-1. It was calculated.

[0068] Try substituting the calculated positive active total electrical energy increment 1 into the approximation relationship in step 2-2:

[0069] available:

[0070]

[0071]

[0072]

[0073] It can be seen that the increase in total positive active power of nodes 3 and 9 within the statistical period T is similar, and the increase in total positive active power of nodes 5 and 10 within the statistical period T is also similar. Therefore, it is difficult to identify the accurate household-box relationship according to the algorithm in step 2.

[0074] Therefore, the approximate relationship of the total positive active power increment of the phase-separated node equipment is adopted in step 4-2. Substituting the increase of 1 in the total positive active power within the previous statistical period T, we can obtain:

[0075]

[0076]

[0077] It can be concluded that node devices 9 and 10 do not belong to the nodes within this intelligent measurement switch box.

[0078] Substituting the increase of the total positive active power in the next statistical period T into the equation, we can obtain:

[0079]

[0080]

[0081] It can be concluded that node devices 9 and 10 do not belong to the nodes within this intelligent measurement switch box.

[0082] Within two consecutive statistical periods, the calculations and analyses determined that nodes 2, 5, 8, 3, 6, 4, and 7 are internal nodes of the smart metering switch, while nodes 9 and 10 are not. This confirms that the calculated customer-box relationship is accurate and reliable. The algorithm in step 4 is then executed again for subsequent statistical periods to analyze the customer-box relationship between the smart metering switch and other carrier node devices.

[0083] Step 5 introduces the K-Means clustering analysis algorithm for the carrier signal compensation gain value of HPLC node equipment, which is used to handle the cases where the total positive active power increment value of the HPLC node equipment connected to the intelligent measurement switch and the non-HPLC node equipment connected to the intelligent measurement switch is the same or the difference is less than the set threshold.

[0084] Step 5-1: The carrier signal compensation gain value refers to a measure of the carrier signal attenuation of other HPLC node devices relative to the HPLC listening node device in a low-voltage power line carrier network. It indicates the magnitude of the gain required to maintain stable carrier communication between the HPLC node device and the HPLC listening node device. A smaller carrier signal compensation gain value indicates less signal attenuation, a stronger signal, and a smaller required compensation gain value; conversely, a larger value indicates greater signal attenuation, a weaker signal, and a larger required compensation gain value.

[0085] Step 5-2: The carrier signal compensation gain value between all networked HPLC node devices and HPLC listening node devices will gradually increase as the physical topology layers are superimposed, the communication distance is extended, and the relay of intelligent measurement switches is used.

[0086] Step 5-3: The carrier signal compensation gain values ​​between HPLC node devices directly powered by the same intelligent measurement switch output terminal and HPLC devices with intelligent measurement switches are similar due to similar physical topology levels, communication distances, and relay conditions of the intelligent measurement switches. However, the carrier signal compensation gain values ​​between HPLC node devices at other physical topology levels are significantly different.

[0087] Step 5-4: HPLC eavesdropping technology can detect the carrier signal compensation gain value between the node itself and surrounding nodes and the HPLC eavesdropping node device. Specifically, it detects the carrier signal compensation gain value between the HPLC eavesdropping node and itself. The value is 0, meaning the carrier signal compensation gain of the intelligent measurement switch node is 0. It is 0.

[0088] Step 5-5: The intelligent measurement switch compensates for the carrier signal gain of all HPLC node devices detected by its HPLC. The K-Means clustering algorithm was introduced and repeatedly iterated to classify all HPLC node devices into carrier signal compensation gain values. It belongs to the carrier signal compensation gain value of intelligent measurement switching node. and the carrier signal compensation gain value far from the intelligent measurement switch node The two major clusters.

[0089] Steps 5-6: For some HPLC node devices where the increase in total positive active power is 0, equal, or very similar within certain statistical periods, determine whether it belongs to the carrier signal compensation gain value of the remote intelligent measurement switch node analyzed by the K-Means clustering algorithm in step 5-5. The cluster members are used to exclude the box household affiliation. If it belongs to a cluster member, it is determined that it is not a box node.

[0090] Furthermore, such as Figure 3 As shown, step 5-5 specifically includes: Step 5-5-1: Introduce the K-Means clustering algorithm to compensate for the carrier signal gain of the intelligent measurement switch's own HPLC node device. As the initial cluster center of cluster 1 .

[0091] Step 5-5-2: Adjust the carrier signal compensation gain value of all HPLC node devices detected by the intelligent measurement switch itself. , in turn and Calculate the difference and take its absolute value ,in .

[0092] Step 5-5-3, introduce the bubble sort method, for Perform a sorting operation to find the maximum value. ,but As the initial cluster center of the second cluster .

[0093] Step 5-5-4: Using the K-Means clustering algorithm, the carrier signal compensation gain values ​​of all HPLC node devices detected by the intelligent measurement switch itself are calculated. Cluster centers of the two clusters respectively and Find the difference and take its absolute value: , , and compare and The size, if Smaller Classified to If it belongs to the same cluster, otherwise it is classified as... The cluster in which it is located.

[0094] Step 5-5-5: Calculate the average value of all members within each node of clusters 1 and 2, respectively. , .

[0095] Step 5-5-6, if or ,but replace , replace If the condition is met, proceed to steps 5-5-4, 5-5-5, and 5-5-6; otherwise, proceed to step 5-5-7.

[0096] Step 5-5-7, if and This yields two stable data clusters. The first cluster belongs to the category where the carrier signal compensation gain value of the HPLC node is close to that of the intelligent measurement switch node, while the second cluster belongs to the category where the carrier signal compensation gain value of the HPLC node is far from that of the intelligent measurement switch node.

[0097] Furthermore, steps 5-6 specifically include: Step 5-6-1 addresses the issue that some HPLC node devices have a zero increase in total positive active power during certain statistical periods, making it difficult to determine their customer / container relationship. This is addressed by determining the carrier signal compensation gain value of the HPLC node device. This can be resolved by determining whether the device belongs to a cluster of members whose carrier signal compensation gain value is close to that of the intelligent measurement switch node. If the data belongs to the first cluster calculated in step 5-5-7, then the HPLC node device is determined to be an internal node of the intelligent measurement switch box; otherwise, it is an external node of the intelligent measurement switch box.

[0098] Step 5-6-2 addresses the problem of multiple HPLC node devices having equal or extremely similar increases in total positive active power over certain statistical periods, making it difficult to determine their customer-cell relationship. This is addressed by determining the carrier signal compensation gain value of the HPLC node device. This can be resolved by determining whether the device belongs to a cluster of members whose carrier signal compensation gain value is close to that of the intelligent measurement switch node. If the data belongs to the first cluster calculated in step 5-5-7, then the HPLC node device is determined to be an internal node of the intelligent measurement switch box; otherwise, it is an external node of the intelligent measurement switch box.

[0099] The following example scenario will be used to describe the implementation process and effect of step 5.

[0100] For example in practical applications: Some residential users have been unoccupied for a period of time, resulting in a zero increase in electricity consumption; Some residential users have similar or equal increases in electricity consumption over a period of time, and these increases happen to be in the same phase. In this scenario, the algorithms in steps 2, 3, and 4 will make it difficult to identify the user-box relationship of these users' carrier table nodes.

[0101] At this point, the K-Means clustering analysis algorithm with carrier signal compensation value of HPLC node equipment is introduced.

[0102] The carrier signal compensation gain of the intelligent measurement switch HPLC node is [value missing]. The value is 0, representing the carrier signal compensation gain value of other HPLC node devices detected by the intelligent measurement switch HPLC node. Not 0, In real-world environments, the carrier signal compensation gain values ​​between HPLC node devices directly powered by the same intelligent measurement switch output terminal and HPLC devices powered by intelligent measurement switches tend to be similar due to similar physical topology levels, communication distances, and relay conditions of the intelligent measurement switch. However, this differs significantly from the carrier signal compensation gain values ​​between HPLC node devices at other physical topology levels. Consider the following scenario as an example: Table 4 Actual operational detection data of the intelligent measurement switch and its eight surrounding carrier meters

[0103] As shown in the table, within a statistical period of T=60min, the electricity consumption increments of meters 2 and 3 are both 0, while the electricity consumption increments of meters 4 and 8 are 502Wh and 504Wh, respectively.

[0104] Substitute the incremental relationship of electricity consumption of the above electricity meters and measuring switches into the approximation relationship in step 2-2.

[0105] Discover:

[0106]

[0107] and or None of these factors affect the validity of the inequality.

[0108] Since the algorithm in step 2 is insufficient to accurately identify the relationship between users and boxes, the K-Means clustering analysis algorithm based on the carrier signal compensation gain value of the HPLC node equipment needs to be introduced to further identify the relationship between users and boxes.

[0109] Follow the specific steps in step 5-5: 1) Execute step 5-5-1 to adjust the carrier signal compensation gain value of the intelligent measurement switch's own HPLC node device. The initial cluster center of the first cluster is 0.

[0110] 2) Execute step 5-5-2 to calculate the absolute value of the difference between the member data and the cluster center of the first cluster: ,in .

[0111] The above 9 node devices and The absolute value of the calculated difference is the same as its original value, that is: , , , , , , , , .

[0112] 3) Execute step 5-5-3 to sort and find the initial cluster centers of the second cluster. The sorting result using the bubble sort algorithm is as follows: , , , , , , , , .

[0113] Therefore, the maximum value is... Then It serves as the initial cluster center for the second cluster of data.

[0114] 4) Perform step 5-5-4 to reclassify the data based on the distance to the cluster centers of the two clusters.

[0115] The intelligent measurement switch itself compensates for the carrier signal gain of all HPLC node devices detected by the HPLC. Cluster centers of the two clusters respectively and Find the difference and take its absolute value: and and compare and The size, if Smaller Classified to If it belongs to the cluster, otherwise it is classified as... The cluster in which it belongs. The clustering results are shown in Table 5.

[0116] Table 5. Intelligent Measurement Switch and Carrier Signal Compensation Gain Values ​​of 8 Carrier Meters Clustering results

[0117] 5) Execute step 5-5-5 to calculate the average value of the two clusters of data.

[0118] From 4), we can derive the data for the first cluster as follows: , , , , , .

[0119] The data for cluster 2 is as follows: , , .

[0120] The average value of all members in cluster 1 is: .

[0121] The average value of all members in cluster 2 is: .

[0122] 6) Execute step 5-5-6 to determine the new cluster centers for the two clusters of data.

[0123] , and , They are all unequal, therefore... , As the new cluster centers for clusters 1 and 2, i.e. , .

[0124] 7) Repeat step 5-5-4 to reclassify the data based on the distances from the data to the cluster centers of the two clusters. The clustering results are shown in Table 6.

[0125] Table 6. Intelligent Measurement Switch and Carrier Signal Compensation Gain Values ​​of 8 Carrier Meters Clustering results

[0126] 8) Execute step 5-5-5 to calculate the average value of the two clusters of data.

[0127] From 7), we can derive the data for the first cluster as follows: , , , , , .

[0128] The data for cluster 2 is as follows: , , .

[0129] The average value of all members in cluster 1 is: .

[0130] The average value of all members in cluster 2 is: .

[0131] 9) Perform step 5-5-7.

[0132] and equal, and If they are equal, then two stable data clusters are obtained. The first data cluster belongs to the category set in which the carrier signal compensation gain value of the HPLC node device is close to that of the carrier signal compensation gain value of the intelligent measurement switch node, and the second data cluster belongs to the category set in which the carrier signal compensation gain value of the HPLC node device is far away from that of the intelligent measurement switch node.

[0133] Therefore, node devices 3, 7, and 8 can be classified as data members of the second cluster, which are non-in-box device nodes.

[0134] Step 6: The HPLC module on the intelligent measurement switch continuously listens to and parses the response messages of the voltage reading devices on the power line during each statistical cycle, and compares the node device voltages listened to in the first two statistical cycles with the three phase voltages of the intelligent measurement switch itself. , , Comparative analysis is conducted to help determine whether a node is an in-box node device that is not a smart measuring switch.

[0135] Step 6-1: The HPLC module on the smart metering switch continuously listens for response messages from the power line during each statistical cycle, reading the voltage of the HPLC node devices (including the voltage of the smart metering switch itself). It parses the device address information and voltage values ​​in the response messages and saves them accordingly. The voltage values ​​parsed from the smart metering switch itself include phase A, phase B, and phase C voltages. In a real-world environment, during a certain normal operating period, the voltage of a phase of the smart metering switch and the voltage value of the meter connected to that phase's output terminal are similar and will not deviate significantly.

[0136] Step 6-2: The HPLC module on the intelligent measurement switch compares the voltage information corresponding to each device address monitored and analyzed in the previous period within each statistical period. The voltage of phase A of the intelligent measuring switch itself Phase B voltage C-phase voltage The size relationship, comparing the absolute values ​​of the differences. , , Are they all greater than (Default is set to 3V), and save the relationship between whether it is satisfied or not.

[0137] Step 6-3: The HPLC module on the intelligent measurement switch compares the magnitudes calculated in step 6-2 for each detected node device in the previous two cycles within each statistical period. If the relationship is satisfied, the node device is determined not to belong to the node in the intelligent measurement switch box. This can help determine whether the node device is a non-intelligent measurement switch box node.

[0138] Step 7: The HPLC module on the smart metering switch continuously listens to the discovery list messages of nodes on the power line, parses out the MAC address, level, and CCO MAC information of the node and saves them accordingly. By sequentially analyzing and comparing the relationship between the level and CCO MAC address of the smart metering switch HPLC module and the level and CCO MAC address information of other node devices detected in the previous two statistical periods, it is determined whether the node is an in-box node device of a non-smart metering switch.

[0139] Step 7-1: The HPLC module on the smart metering switch and the node devices connected to the output terminals of each phase line of the smart metering switch are typically at a higher or the same network level in the carrier network due to the isolation and attenuation relationship in carrier communication. If the network level of a certain node device is more than one level lower or more than two levels higher than the network level of the HPLC module node of the smart metering switch, it can be determined that it is not an internal node device of the smart metering switch.

[0140] Step 7-2: The HPLC module on the smart metering switch continuously listens to the node hierarchy information in the node discovery list messages on the power line (including the discovery list messages of the smart metering switch's own HPLC module) during each statistical period, and records and saves the corresponding relationships of node MAC address, hierarchy, and CCO MAC address in the discovery list messages.

[0141] Step 7-3: The HPLC module on the intelligent measurement switch determines whether a node is a non-intelligent measurement switch's internal node device by sequentially analyzing and comparing the relationship between the hierarchy of the intelligent measurement switch's HPLC module, the MAC address of the CCO, and the hierarchy and MAC address information of other node devices that it listens to and stores in the previous two statistical periods.

[0142] Furthermore, step 7-3 specifically includes: Step 7-3-1: The HPLC module on the intelligent measurement switch sequentially analyzes and compares the relationship between the hierarchy of the intelligent measurement switch HPLC module, the MAC address of the CCO, and the hierarchy and MAC address information of other node devices that it listens to and saves during the first two statistical periods.

[0143] Step 7-3-2: If the MAC address of the CCO of a certain node device is different from the MAC address of the CCO of the intelligent measurement switch HPLC module in both statistical periods, then it is determined that the node device is not an in-box node device of the intelligent measurement switch.

[0144] Step 7-3-3: If, within both statistical periods, the level of a certain node device is more than one level lower than the level of the intelligent measurement switch HPLC module, then the node device is determined not to be an in-box node device of the intelligent measurement switch.

[0145] Step 7-3-4: If, within both statistical periods, the level of a certain node device is more than two levels higher than the level of the intelligent measurement switch HPLC module, then the node device is determined not to be an in-box node device of the intelligent measurement switch.

[0146] Furthermore, the levels mentioned in step 7 all refer to the carrier network level where the carrier node device is located.

[0147] As shown in Table 2, the HPLC module of the smart measurement switch detects the discovery list message sent by the carrier node. Parsing this message reveals the carrier node's level, MAC address, associated phase line, and the MAC address of its CCO. Furthermore, steps 7-1 to 7-3 and 7-3-1 to 7-3-4 can be used to analyze the relationship between the corresponding carrier node device and the smart measurement switch's customer housing.

[0148] like Figure 4 As shown, the present invention also proposes a system for identifying the relationship between customers and boxes based on HPLC listening analysis technology, which is used to implement the above-mentioned method for identifying the relationship between customers and boxes based on HPLC listening analysis technology. The system includes: a low-voltage concentrator, a CCO carrier master node module, a carrier energy meter, a STA carrier slave node module, an intelligent measurement switch, and an electrical load. Among them, the low-voltage concentrator is used to periodically collect power consumption information data from carrier energy meters and smart metering switches according to a pre-configured acquisition scheme; One CCO carrier master node module and multiple STA carrier slave node modules are used for HPLC networking and communication; Intelligent metering switches are typically installed in the distribution box of a transformer substation, with their three-phase output lines (A, B, and C) connected to carrier energy meters for different users.

[0149] The STA carrier slave node module in the smart metering switch not only has HPLC networking and communication functions, but also has the HPLC listening technology described in this patent and the customer box identification and analysis algorithm pointed out in steps 2 to 7. Through multiple cycles of continuous analysis and iteration, the customer box relationship identification function of the smart metering switch and its downloaded wave energy meter equipment is realized.

[0150] The electrical load includes all kinds of electrical appliances in ordinary households, which are connected to the output wires of the carrier energy meter. This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0151] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media include, but are not limited to, electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0152] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0153] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0154] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for identifying customer-cell relationships based on HPLC listening analysis technology, characterized in that, include: Step 1: By listening to the service communication messages of all nodes in the power line carrier network that it communicates with through the HPLC node, perform logical analysis to identify the customer box relationship between the intelligent measurement switch and other HPLC node devices; Step 2: The HPLC module on the intelligent measurement switch continuously listens to and analyzes the total positive active power of the HPLC node equipment over multiple cycles on the power line. The response message compares the total positive active power increment of the smart metering switch over multiple cycles. Total positive active power increment compared to other HPLC node devices The sum under different combined scenarios If the approximate equivalence relationship is satisfied, then all HPLC node devices included in the combination belong to the direct-connection devices of the power line at the output terminal of the intelligent measurement switch, that is, the node devices inside the box. Step 3: The HPLC module on the intelligent measurement switch continuously listens for the discovery list messages of HPLC nodes on the power line, parses the phase information of the nodes, records and saves the phase of all detected nodes, and compares the node phase information with the total positive active power increment of the node within the period T calculated by the listening. By combining these factors, the total positive active power increment at different phase nodes can be obtained. ,in Represents phase information; Step 4: Introduce a phase-by-phase positive active total energy increment iterative comparison algorithm to distinguish cases where the difference between the positive active total energy increment of the equipment inside and outside the smart measurement switch box is less than a set threshold. Step 5: Introduce the K-Means clustering analysis algorithm for the carrier signal compensation gain value of HPLC node equipment to handle the situation where the positive active total energy increment value of the intelligent measurement switch connected to the HPLC node equipment and the non-connected HPLC node equipment is the same or the difference is less than the set threshold. Step 6: The HPLC module on the intelligent measurement switch continuously listens for and parses the response messages of the voltage reading devices on the power line during each statistical cycle, and compares the node device voltages listened for in the previous two statistical cycles with the three phase voltages of the intelligent measurement switch itself. , , Comparative analysis is conducted to help determine whether a node is an in-box node device that is a non-intelligent measuring switch; Step 7: The HPLC module on the smart metering switch continuously listens to the discovery list messages of nodes on the power line, parses out the MAC address, level, and CCO MAC information of the node and saves them accordingly. By sequentially analyzing and comparing the relationship between the level and CCO MAC address of the smart metering switch HPLC module and the level and CCO MAC address information of other node devices detected in the previous two statistical periods, it is determined whether the node is an in-box node device of a non-smart metering switch.

2. The method for identifying household-box relationships based on HPLC listening analysis technology according to claim 1, characterized in that, Step 1 includes: Step 1-1: HPLC sniffing technology sniffs the service communication messages of all nodes in the power line carrier network that are associated with the sniffing node. The nodes associated with the communication include the proxy nodes of the HPLC sniffing node, multi-level proxy nodes, and all lower-level nodes on the same network topology link. Steps 1-2: The HPLC module of the intelligent measurement switch listens to and parses the echo messages of the nodes on the power line, and identifies the customer box relationship between the intelligent measurement switch carrier node and other carrier device nodes through logical analysis.

3. The method for identifying household-box relationships based on HPLC listening analysis technology according to claim 1, characterized in that, Step 2 includes: Step 2-1: The HPLC module on the intelligent measurement switch continuously listens for the response messages of the HPLC node devices on the power line, identifies the node to which the response code value belongs based on the device address in the message, and calculates the total positive active power of all listening nodes in each statistical period. The positive active total electrical energy increment within ,in , and They are respectively Time and Total positive active power at any given moment; Step 2-2: Compare the increase in total positive active power of the intelligent measuring switch within period T. Other The total positive active power increment of each HPLC node device Does the equality relationship satisfy the following conditions in a certain combination scenario? ,in Line loss due to power consumption; Steps 2-3: If two consecutive periods T satisfy the above approximate equivalence relationship, then all HPLC node devices included in this combination are considered valid. , , , The power supply lines are all directly connected to one of the phase outputs of the intelligent measurement switch A, B, and C, which belongs to the HPLC node equipment inside the box; Steps 2-4: Compare the current information of all HPLC node devices in the chamber with the information of the node devices in the chamber that was saved last time. If they are the same, the original information is maintained. If they are different, the information is updated and a user-chamber relationship change event is generated. The HPLC module of the intelligent measurement switch actively reports the event to the uplink terminal device. Step 2-5: Repeat step 2-1.

4. The method for identifying household-box relationships based on HPLC listening analysis technology according to claim 1, characterized in that, Step 3 includes: Step 3-1: The HPLC module on the intelligent measurement switch continuously listens for the discovery list messages of HPLC nodes on the power line, parses the communication address and phase information of the HPLC node that sent the message, and records and saves them. Step 3-2: Combine the node phase information with the total positive active power increment of the node calculated within period T. By combining these measurements, the total positive active power increment at different phase nodes detected by the intelligent measurement switch HPLC module was obtained. , , , , , , where A, B, and C represent phases A, B, and C, respectively.

5. The method for identifying customer-box relationships based on HPLC listening analysis technology according to claim 1, characterized in that, Step 4 includes: Step 4-1: Within each statistical period T, after receiving the feedback code of the total positive active energy data of the intelligent measurement switch, the HPLC module on the intelligent measurement switch actively reads the total positive active energy data of phases A, B, and C of the intelligent measurement switch, and calculates the increment of the total positive active energy of each phase within period T. ,in Indicates phase, and They are respectively Time and time The total positive active power of the phase; Step 4-2: Compare the increase in total positive active power of each phase of the smart metering switch within each statistical period T. The phase obtained from step 3-2 The total positive active power increment of all node devices The summation under different combinations Does the relationship satisfy the equality requirement? ,in Line loss due to power consumption; Step 4-3: If two consecutive periods T satisfy the above approximate equivalence relationship, then all HPLC node devices included in this combination are considered valid. , , , The power supply lines are all powered by intelligent measurement switches. The phase output line is directly connected, belonging to the in-chamber HPLC node equipment; Step 4-4: Through statistical comparative analysis of steps 4-2 and 4-3, the relationship between the monitored HPLC node device and the intelligent measurement switch in the three phases A, B, and C is obtained; Steps 4-5: Calculate the relationship between the HPLC node equipment and the intelligent measurement switch in the three phases by analyzing the approximate relationship of the total positive active power increment in each phase.

6. The method for identifying household-box relationships based on HPLC listening analysis technology according to claim 1, characterized in that, Step 5 includes: Step 5-1: The carrier signal compensation gain value represents the carrier signal attenuation measure of other HPLC node devices in the low-voltage power line carrier network relative to the listening node device. It indicates the gain value required to maintain stable carrier communication. The smaller the gain value, the smaller the signal attenuation and the stronger the signal. Step 5-2: The carrier signal compensation gain between all networked HPLC node devices and HPLC listening node devices gradually increases with the superposition of physical topology levels, the extension of communication distance, or the relay of intelligent measurement switches. Step 5-3: Due to the influence of physical topology and communication distance, the carrier signal compensation gain value between the HPLC node device directly powered by the same intelligent measurement switch output terminal and the intelligent measurement switch HPLC device is smaller compared with the carrier signal compensation gain value between node devices under other physical topology levels. Step 5-4: HPLC listening technology can listen to the carrier signal compensation gain value between the listening node itself and surrounding nodes and the listening node device, where the gain value of the listening node itself is... =0; Step 5-5: The intelligent measurement switch compensates for the carrier signal gain value of all monitored HPLC node devices. Introducing the K-Means clustering algorithm, iteratively classifying all node devices into gain values. near and away Two major clusters; Steps 5-6: For HPLC node devices where the total positive active power increment is 0, equal, or the difference is less than a set threshold within certain statistical periods, determine their gain value. Does it fall under the category of being far away? Cluster members are used to exclude nodes belonging to the same bin; if a node belongs to a cluster far away, it is determined to be a node not belonging to the same bin.

7. The method for identifying household-box relationships based on HPLC listening analysis technology according to claim 6, characterized in that, Step 5-5 includes: Step 5-5-1: Using the K-Means clustering algorithm, the carrier signal compensation gain value of the intelligent measurement switch's own HPLC node device is calculated. As the initial cluster center of cluster 1 ; Step 5-5-2: Calculate the gain values ​​of all listening HPLC node devices. and absolute value of the difference ,in ; Step 5-5-3: Use bubble sort to sort... Sort and take the maximum value. ,Will As the initial cluster center of cluster 2 ; Step 5-5-4: Calculate each and and absolute value of the difference and Compare the sizes, if Smaller Classified to If it belongs to the same cluster, otherwise it is classified as... Cluster; Step 5-5-5: Calculate the average value of all members in cluster 1 and cluster 2 respectively. and ; Step 5-5-6: If or Then replace , replace Repeat steps 5-5-4 to 5-5-6, otherwise proceed to step 5-5-7; Step 5-5-7: If and This yields two stable clusters of data, with the first cluster having gain values ​​close to... The category set, the second cluster is the one where the gain value is far away A collection of categories.

8. The method for identifying customer-cell relationships based on HPLC listening analysis technology according to claim 6, characterized in that, Steps 5-6 include: Step 5-6-1: For HPLC node equipment where the total positive active power increment is 0, determine its gain value. The relationship between a user and a box is determined by whether the user belongs to the first cluster. If the user belongs to the first cluster, the user is considered an internal node; otherwise, the user is considered an external node. Step 5-6-2: For cases where the total positive active power increments of multiple node devices are equal or the difference is less than a set threshold, determine their gain values. The relationship between a user and a box is determined by whether the user belongs to the first cluster. If the user belongs to the first cluster, the user is considered an internal node; otherwise, the user is considered an external node.

9. The method for identifying household-box relationships based on HPLC listening analysis technology according to claim 1, characterized in that, Step 6 includes: Step 6-1: The HPLC module on the intelligent measurement switch continuously listens to the power line to read the response messages of the HPLC node device voltage during each statistical cycle, parses the device address and voltage value, and saves them accordingly. The voltage of the intelligent measurement switch itself includes the A-phase voltage. Phase B voltage C-phase voltage ; Step 6-2: Compare the voltage information corresponding to each device address. and , , absolute value of the difference , , Are they all greater than , The default value is 3V, and the comparison results are saved. Step 6-3: Based on the comparison results of Step 6-2 in the previous two statistical periods, if the difference condition is met, it is determined that the node device does not belong to the node in the intelligent measurement switch box.

10. The method for identifying household-box relationships based on HPLC listening analysis technology according to claim 1, characterized in that, Step 7 includes: Step 7-1: The HPLC module on the intelligent measurement switch and the downstream node devices at the output terminals of each phase line are isolated and attenuated in the carrier communication. The level of the downstream node device in the carrier network is higher than or equal to the node level of the intelligent measurement switch HPLC module. If the node level is more than one level lower than the intelligent measurement switch level or more than two levels higher, it is determined to be a non-in-box node device. Step 7-2: The HPLC module on the intelligent measurement switch continuously listens for the node discovery list messages on the power line and records the MAC address, level, and CCO MAC address correspondence of the nodes; Step 7-3: By analyzing and comparing the relationship between the hierarchical level of the intelligent measurement switch HPLC module, the MAC address of the CCO and the hierarchical level of other node devices, and the MAC address information of the CCO in the first two statistical periods, it is determined whether the node is a non-in-box node device.

11. The method for identifying household-box relationships based on HPLC listening analysis technology according to claim 10, characterized in that, Step 7-3 includes: Step 7-3-1: Analyze and compare the hierarchical level of the intelligent measurement switch HPLC module, the MAC address of the CCO, and the hierarchical level and MAC address information of the CCO with other node devices in the first two statistical periods. Step 7-3-2: If the MAC address of the CCO of a certain node device is different from the MAC address of the CCO of the intelligent measurement switch HPLC module in both statistical periods, it is determined to be a non-in-box node device. Step 7-3-3: If the level of a certain node device is more than one level lower than the level of the intelligent measurement switch HPLC module in both statistical periods, it is determined to be a non-in-box node device. Step 7-3-4: If the level of a certain node device is more than 2 levels higher than the level of the intelligent measurement switch HPLC module in both statistical periods, it is determined to be a non-in-box node device.

12. An intelligent measuring switch, characterized in that, The intelligent measuring switch is a device that integrates a circuit breaker switch, a carrier communication unit board, a power supply board, and a main control metering board. It has functions of switching on and off, carrier communication, metering, and intelligent control, and is used to implement the method described in any one of claims 1-11.

13. A system for identifying customer-cell relationships based on HPLC listening analysis technology, characterized in that, For implementing the method as described in any one of claims 1-11, comprising: The low-voltage concentrator is used to periodically collect 15-minute curve data from smart metering switches and carrier energy meters according to the tasks and schemes configured by the main station, and to receive and parse the customer box relationship identification result event and customer box relationship change event reported by the smart metering switch. The CCO master node module is plugged into the low-pressure concentrator and is used for HPLC networking and communication. The STA slave node module is plugged into a smart measurement switch or carrier energy meter and is used for HPLC networking and communication. The intelligent measurement switch includes the main body of the intelligent measurement switch and the STA slave node module. The STA slave node module realizes HPLC networking, listens and analyzes data acquisition business messages on the power line and performs algorithm analysis to calculate the relationship between the customer box and the power supply box. The main body of the intelligent measurement switch realizes the intelligent control and metering functions related to the circuit breaker. Carrier energy meters include carrier energy meters connected to the three-phase output terminals A, B, and C of the smart measurement switch and carrier energy meters connected to the bypass of the smart measurement switch. Electrical load devices are connected to the outgoing line of the carrier energy meter to generate energy consumption and provide power consumption data support for identifying the relationship between the household and the meter.

14. A terminal, comprising a processor and a storage medium, characterized in that, The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the steps of the method as described in any one of claims 1-11.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-11.

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