A method, system, device and medium for improving the efficiency of electric meter data collection

Abstract

A method, system, device and medium for improving the efficiency of data collection of electric meters, relating to the field of electric power systems. In this method, in response to receiving an electric meter archive and network configuration parameters from an acquisition terminal, networking is performed according to the network configuration parameters to establish a communication connection with the electric meter; the networking topology information is sent to the acquisition terminal, and the periodic acquisition task generated by the acquisition terminal according to the networking topology information is received; the first round of acquisition is performed according to the periodic acquisition task and the electric meter archive, and a trunk branch is constructed according to the physical phase of each electric meter and the hierarchical relationship in the communication network, and a branch group is generated at the trunk end of the trunk branch according to the phase relationship of the electric meter and the data collection situation of the first round of acquisition; the periodic acquisition task is executed according to the trunk branch and the branch group. The technical solution provided by the present application is implemented to improve the efficiency of data collection of electric meters.

Description

Technical Field

[0001] The present application relates to the technical field of power systems, and in particular to a method, system, device and medium for improving the efficiency of data collection of electric meters. Background Art

[0002] Power data collection is an important part of modern smart grid management. With the continuous development of the power system, power companies need to efficiently and accurately obtain power consumption data of a large number of users in order to conduct data analysis and optimize management.

[0003] Most existing technologies optimize communication quality or improve channel utilization efficiency from the perspective of physical layer channels, but lack a method to improve efficiency at the software service level. Existing technologies cannot fully adapt to the characteristics of various power usage scenarios, and there are compatibility issues with various terminals, resulting in low data collection efficiency.

[0004] Therefore, how to improve the efficiency and reliability of data collection at the software business level has become a key issue that needs to be solved urgently. Summary of the invention

[0005] The present application provides a method, system, device and medium for improving the efficiency of data collection of electric meters, which optimizes the data collection process by constructing trunk branches and tree branch groupings, thereby improving the collection efficiency.

[0006] In a first aspect of the present application, a method for improving the efficiency of electric meter data collection is provided, which is applied to a high-speed power line carrier communication module, and the method comprises:

[0007] In response to receiving an electric meter profile and a network configuration parameter from a collection terminal, the electric meter profile including basic information of the electric meter and collection requirements, networking is performed according to the network configuration parameter to establish a communication connection with the electric meter;

[0008] Sending the network topology information to the collection terminal, and receiving the periodic collection task generated by the collection terminal according to the network topology information, wherein the network topology information includes the product type, physical phase, and networking level of the electric meter, and the periodic collection task includes the collection data items and the collection period;

[0009] Performing a first round of data collection according to the periodic data collection task and the meter archive, and constructing a trunk branch according to the physical phase of each meter and the hierarchical relationship in the communication network, and generating a branch group at the trunk end of the trunk branch according to the phase relationship of the meter and the data collection situation of the first round of data collection;

[0010] The periodic collection task is performed according to the trunk branches and the tree branch groups.

[0011] Optionally, constructing a trunk branch according to the physical phase of each electric meter and the hierarchical relationship in the communication network, and generating branch groups at the trunk end of the trunk branch according to the phase relationship of the electric meter and the data collection situation of the first round of collection includes:

[0012] Identify and connect meters with the same physical phase and at the same communication level to form a primary trunk branch;

[0013] At the proxy node of the primary trunk branch, a branch group connected to the primary trunk branch is generated according to the phase relationship of the subordinate nodes of the proxy node and the success of the first round of data collection.

[0014] Optionally, generating a branch group connected to the primary trunk branch according to the phase relationship of the subordinate nodes of the proxy node and the success of the first round of data collection includes:

[0015] Searching and determining a plurality of first electric meters that are directly connected to the proxy node and meet a preset phase condition, and analyzing and comparing the plurality of first electric meters to determine a grouping feature;

[0016] According to the grouping characteristics, cluster analysis is performed on the plurality of the first electric meters to obtain a plurality of branch groups, and it is determined whether there is a target branch group including the first electric meters of different phases;

[0017] When there is a first electricity meter containing different phases in the target branch group, the target branch group is split into a plurality of sub-meter groups containing only electricity meters of the same phase.

[0018] Optionally, generating a branch group connected to the primary trunk branch according to the phase relationship of the subordinate nodes of the proxy node and the success of the first round of data collection further includes:

[0019] Monitor the voltage data in the power grid, identify the trend and amplitude of the voltage fluctuation in the same direction, and calculate the degree of influence of the electrical characteristics of each meter in the tree branch group according to the trend and amplitude;

[0020] removing a first electric meter whose electrical characteristic influence degree is greater than or equal to a first threshold from the branch group, and assigning a newly added second electric meter whose electrical characteristic influence degree is less than the first threshold to the branch group;

[0021] The first electric meter having a collection success rate less than the second threshold is allocated to a tree branch group having an electrical characteristic similarity greater than or equal to a third threshold and a collection success rate greater than or equal to the second threshold.

[0022] Optionally, the method further includes:

[0023] In each collection cycle, target data of the electric meter is collected multiple times, wherein the target data includes communication delay information, phase information, voltage and power factor values;

[0024] According to the voltage and power factor values ​​in the historical target data, a change trend of each electric meter is calculated, wherein the change trend includes rising, stable or falling, and the electric meters under the same agent node are grouped according to the change trend to obtain a new branch grouping;

[0025] Calculate the average collection delay of the electric meters in the new tree branch group according to the communication delay information, and sort them from low to high according to the average collection delay to obtain a group list;

[0026] The collection task is executed according to the grouping list.

[0027] Optionally, the method further includes:

[0028] Generate grouping information according to the grouping list, and send the grouping information to the collection terminal through a protocol, so that the collection terminal performs interactive collection according to the grouping order in the grouping information when reading data; or

[0029] The grouping list is used to perform local collection according to the configured task cycle, and the data is temporarily stored. When a reporting instruction is received, the collected data is uploaded to the collection terminal.

[0030] Optionally, the method further includes:

[0031] During the collection process, the data collection status of each electric meter is monitored in real time, and the data collection status includes the collection success rate, data integrity and communication stability;

[0032] When it is detected that the data collection state of the target meter is abnormal, the collection strategy is adjusted according to the position of the target meter in the communication network and the relationship with other meters, and the adjustment of the collection strategy includes adjusting the collection cycle, changing the communication path or increasing the number of collection retries;

[0033] When the number of adjustments exceeds the fourth threshold, the data collection state of the target meter is still abnormal, the target meter is marked as an abnormal meter, the abnormal meter is deleted from the group list, and a new group list is generated.

[0034] In a second aspect of the present application, a system for improving the efficiency of electric meter data collection is provided, comprising a networking module, a task module, a grouping module and a collection module, wherein:

[0035] A networking module configured to respond to receiving an electric meter profile and a network configuration parameter from a collection terminal, wherein the electric meter profile includes basic information of the electric meter and collection requirements, and to perform networking according to the network configuration parameter to establish a communication connection with the electric meter;

[0036] A task module, configured to send the networking topology information to the collection terminal, and receive a periodic collection task generated by the collection terminal according to the networking topology information, wherein the networking topology information includes a product type, a physical phase, and a networking level of the electric meter, and the periodic collection task includes a collection data item and a collection period;

[0037] a grouping module configured to perform a first round of collection according to the periodic collection task and the electric meter archive, and to construct a trunk branch according to the physical phase of each electric meter and the hierarchical relationship in the communication network, and to generate a branch group at the trunk end of the trunk branch according to the phase relationship of the electric meter and the data collection situation of the first round of collection;

[0038] The collection module is configured to perform the periodic collection task according to the trunk branches and the tree branch groups.

[0039] In the third aspect of the present application, an electronic device is provided, including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes any one of the methods described above.

[0040] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any of the methods described above is executed.

[0041] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0042] 1. Networking is performed based on the received meter files and network configuration parameters to ensure a stable and efficient communication connection with the meter, which helps reduce communication delays and errors and improves the reliability and real-time performance of data collection;

[0043] 2. The data collection terminal generates periodic data collection tasks based on the network topology information (including the product type, physical phase, and network level of the meter). This task generation method is more flexible and can customize data collection plans based on the needs and characteristics of different meters;

[0044] 3. Optimize the data collection process by building trunk branches and branch groups. The trunk branches are built based on the physical phase of the meter and the hierarchical relationship in the communication network, while the branch groups are generated based on the phase relationship of the meter and the data collection situation of the first round of collection. This strategy helps to reduce the redundancy and duplication of data collection and improve the collection efficiency;

[0045] 4. Through the above optimized data collection strategy, the meter data can be obtained more accurately, while reducing the resource consumption in the collection process. This helps to improve the accuracy and efficiency of data collection and provide more reliable data support for the monitoring and management of the power system;

[0046] 5. It can be applied to different types of electricity meters and complex power line carrier communication environments. Through flexible network configuration and task generation, the method can cope with data collection needs in different scenarios and show strong adaptability and scalability. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flowchart of a method for improving the efficiency of electric meter data collection disclosed in an embodiment of the present application;

[0048] Figure 2 It is a schematic diagram of the interaction process between the data acquisition terminal and the high-speed power line carrier communication module disclosed in the embodiment of the present application;

[0049] Figure 3 It is a schematic diagram of the overall process of grouping high-speed power line carrier communication modules disclosed in the embodiment of the present application;

[0050] Figure 4 It is a partial flow diagram of high-speed power line carrier communication module grouping disclosed in the embodiment of the present application;

[0051] Figure 5 It is a module schematic diagram of a system for improving the efficiency of electric meter data collection disclosed in an embodiment of the present application;

[0052] Figure 6 It is a structural schematic diagram of an electronic device disclosed in an embodiment of the present application.

[0053] Explanation of the reference numerals: 501, networking module; 502, task module; 503, grouping module; 504, acquisition module; 601, processor; 602, communication bus; 603, user interface; 604, network interface; 605, memory. DETAILED DESCRIPTION

[0054] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0055] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0056] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0057] This embodiment discloses a method for improving the efficiency of electric meter data collection, which is applied to a high-speed power line carrier communication (HPLC) module. Figure 1 is a flow chart of a method for improving the efficiency of data collection of electric meters disclosed in an embodiment of the present application, such as Figure 1 As shown, the method comprises the following steps:

[0058] S110, in response to receiving an electric meter profile and a network configuration parameter from a collection terminal, the electric meter profile including basic information of the electric meter and collection requirements, networking is performed according to the network configuration parameter to establish a communication connection with the electric meter;

[0059] Figure 2 is a schematic diagram of the interaction process between the acquisition terminal and the high-speed power line carrier communication module disclosed in the embodiment of the present application, combined with Figure 2 The embodiments of the present application are described.

[0060] like Figure 2As shown in the figure, the collection terminal will send a series of meter collection file lists to the central coordinator (CCO) of the HPLC module. These file lists contain basic information and collection requirements of the meter. Basic information includes: product type, physical phase, networking level, etc. of the meter. This information helps to identify and manage the meter. Collection requirements include: collection data items and collection cycle, etc., which clarify the data to be collected and the frequency of collection. The collection terminal will also send network configuration parameters to the CCO. These parameters are required to establish a communication connection and are used to guide the CCO on how to network. Network configuration parameters may include network topology information, communication protocol, communication frequency, etc. After receiving the network configuration parameters, the CCO will start to network according to these parameters. The networking process may involve establishing communication links with each meter to ensure that data can be transmitted smoothly. During networking, the collection terminal may query the network completion status to ensure that the networking process is going smoothly. This usually involves checking whether the communication link is stable and whether all meters have successfully joined the network. When the networking is completed, the CCO establishes a communication connection with the meter. This connection allows the CCO to send collection tasks to the meter and receive data sent by the meter. The establishment of communication connection is the basis for subsequent data collection and transmission. After the network is established, in order to ensure the consistency of the running time of CCO and the terminal, the collection terminal will also send clock information to CCO. This helps to ensure the accuracy and consistency of data collection and transmission. The collection terminal will send periodic collection tasks to CCO. These tasks contain specific collection data items, collection cycles and other information. CCO will store these tasks locally, and regularly send collection instructions to the meter according to the task requirements, and receive and store the data returned by the meter.

[0061] S120, sending the network topology information to the collection terminal, and receiving the periodic collection task generated by the collection terminal according to the network topology information, wherein the network topology information includes the product type, physical phase, and networking level of the electric meter, and the periodic collection task includes collection data items and collection period;

[0062] Each electricity meter has its own specific attributes, such as product type (such as single-phase electricity meter, three-phase electricity meter, etc.), physical phase (phase A, phase B, phase C, etc.) and networking level (such as terminal layer, concentrator layer, master station layer, etc.). Product type: describes the type and specifications of the electricity meter, such as single-phase or three-phase electricity meter. Physical phase: indicates the phase of the power grid to which the electricity meter is connected, which is especially important for three-phase power grids. Networking level: describes the hierarchical position of the electricity meter in the power grid, which helps to understand the relationship between the electricity meter and other devices. These attributes together constitute the networking topology information of the electricity meter, which describes the location of the electricity meter in the power grid and its relationship with other devices. In the embodiment of the present application, the high-speed power line carrier communication module will send the networking topology information to the collection terminal. The collection terminal is usually a device responsible for data collection and preliminary processing. It needs to configure and optimize the data collection process based on this information. After receiving the networking topology information, the collection terminal will generate a periodic collection task based on this information and the system requirements. The periodic collection task specifies the data items that need to be collected (such as current, voltage, power, etc.) and the frequency of collection (ie, the collection cycle). Such as Figure 2 As shown, after the acquisition terminal generates periodic acquisition tasks, it will send these tasks back to the high-speed power line carrier communication module. After receiving these tasks, the high-speed power line carrier communication module will store them and use them to guide the subsequent data acquisition process.

[0063] S130, performing a first round of data collection according to the periodic data collection task and the meter archive, and constructing a trunk branch according to the physical phase of each meter and the hierarchical relationship in the communication network, and generating a branch group at the trunk end of the trunk branch according to the phase relationship of the meter and the data collection situation of the first round of data collection;

[0064] CCO starts the first round of data collection according to the preset periodic data collection tasks and meter files. CCO actively sends data collection instructions to each meter based on the information in the meter files. After receiving the instructions, the meter sends its own data (such as power, voltage, current, etc.) back to CCO. After receiving the data from all meters, CCO identifies the physical phase of each meter and the hierarchical relationship in the communication network. The physical phase refers to the phase of the power system to which the meter is connected, such as phase A, phase B, phase C, etc. The communication level refers to the position of the meter in the communication network, such as first-level agent, second-level agent, terminal node, etc. Based on the identified physical phase and communication level, CCO starts to build trunk branches. Meters with the same phase and the same first-level agent are classified as the same trunk branch. The trunk branch represents the main path in the communication network for data transmission and distribution. At the trunk end of the trunk branch (i.e., the agent node), CCO organizes the meter phase relationship of the subordinate nodes and the data collection status of the first round of data collection. The meter phase relationship refers to the phase connection relationship between the meters. The data collection status refers to the meters that successfully sent back data and the meters that failed to send back data during the first round of collection. According to the phase relationship and data collection status of the sorted meters, CCO generates branch groups at the end of each trunk. The branch group represents a collection of meters with different phases or different data collection situations under the same trunk branch. If it is a three-phase meter, it can be placed in the same branch group because they belong to the same physical phase group. For other phases, different branch groups are generated according to the different phases.

[0065] Optionally, constructing a trunk branch according to the physical phase of each electric meter and the hierarchical relationship in the communication network, and generating branch groups at the trunk end of the trunk branch according to the phase relationship of the electric meter and the data collection situation of the first round of collection includes:

[0066] Identify and connect meters with the same physical phase and at the same communication level to form a primary trunk branch;

[0067] At the proxy node of the primary trunk branch, a branch group connected to the primary trunk branch is generated according to the phase relationship of the subordinate nodes of the proxy node and the success of the first round of data collection.

[0068] Figure 3 The overall process diagram of the high-speed power line carrier communication module grouping disclosed in the embodiment of the present application is combined with Figure 3 The embodiments of the present application are described below. Figure 3As shown, the overall process of high-speed power line carrier communication module grouping includes: step S301, completing the networking according to the configuration meter collection file list CCO issued by the collection terminal, and performing network maintenance. Step S302, periodically updating the networking topology. Step S303, according to the physical phase and communication level of the meter, connecting the meters with the same physical phase and at the same communication level to form a main communication trunk (i.e., a first-level trunk branch). The first-level trunk branch represents the main path in the communication network for data transmission and distribution. In the first-level trunk branch, CCO determines the proxy node, which is usually a key node connecting multiple meters, such as a first-level proxy node. Step S304, at the proxy node, analyze the phase relationship of the subordinate nodes and the success of the first round of data collection. According to the analysis results, in the subordinate nodes of the proxy node, according to the phase relationship and the success of the first round of data collection, determine the branch 1 (i.e., the branch node). Step S305, analyze the same phase and product form STA according to branch 1. Step S306: Generate branch 1 grouping connected to the first-layer trunk branch based on the same and similar features. Step S307: Split the STA groups of different phases. Step S308: Generate branch N (N is a positive integer) grouping using the same method. Step S309: Collect data on branch 1 grouping to obtain branch group 1. Step S310: Adjust branch group 1 based on the voltage fluctuation in the same direction. Step S311: Optimize branch group 1 based on the historical collection success rate. These branch groups represent a collection of meters with different phases or different data collection situations under the same trunk branch. The generation of branch groups helps CCO better manage meter nodes in the communication network and improve the efficiency and accuracy of data collection.

[0069] Assume that a smart grid system includes multiple meters, and these meter nodes are distributed in different physical phases (phase A, phase B, phase C) and communication levels. The task of CCO is to build trunk branches based on the physical phase and communication level relationship of the meter, and generate branch groups based on the trunk branches. The meter node information is as follows:

[0070] The CCO first identifies all meters that are at the first-level proxy level and have the same physical phase, and considers the results of the first round of collection. In this example, both meter 1 and meter 2 are phase A and at the first-level proxy level, and the first round of collection is successful, so they are connected to form the first-level trunk branch of phase A. Although meter 3 is phase B and at the first-level proxy level, the first round of collection failed, so the CCO may not include it in the trunk branch for the time being, or mark it as a node that needs special attention. Meter 5 is phase C and at the first-level proxy level, and the first round of collection is successful, so it can be regarded as a separate trunk branch (phase C first-level trunk branch). At the proxy node of the first-level trunk branch of phase A (meter 1 or meter 2), the CCO analyzes the phase relationship of the subordinate nodes and the success of the first round of data collection. Meter 4 is phase A and at the second-level proxy level, and the first round of collection is successful, so it is regarded as a branch group of the first-level trunk branch of phase A. For phase B, since meter 3 failed to collect in the first round, the CCO may not immediately include it in the branch group. However, if meter 6 (also in phase B but at the secondary agent level on a different path) succeeds in the first round of collection, the CCO may consider grouping meter 6 as an independent branch or wait for meter 3 to return to normal before grouping. For the sake of completeness in this example, it is assumed that meter 6 is grouped as an independent phase B branch (although it is not directly subordinate to meter 3, in actual applications, the CCO may decide how to group it based on the network topology and collection strategy). The phase C trunk branch (meter 5) has no direct subordinate nodes in this example, so it does not generate a branch group. But in actual applications, if there are other phase C meters connected to meter 5, they will be added to the corresponding branch group.

[0071] By identifying and connecting meters with the same physical phase and at the same communication level to form a primary trunk branch, redundant connections in the communication network can be significantly reduced, and the efficiency and speed of data transmission can be improved. This grouping method based on physical phase and communication level makes the flow of data in the communication network more orderly and efficient, which helps to reduce network congestion and delay. At the proxy node of the primary trunk branch, the branch grouping is generated according to the phase relationship of the subordinate nodes and the success of the first round of data collection, which can ensure the accuracy and reliability of data collection. In this way, it is easier to identify which meter nodes have problems during the data collection process, so that timely measures can be taken to repair or adjust them. The network topology can be dynamically adjusted according to the actual connection status of the meter and the data collection results, so that the network is more adapted to the actual operation needs of the power grid system. By continuously optimizing the network topology, the stability and reliability of the entire smart grid system can be improved, and the probability of failure can be reduced. Through reasonable grouping and allocation, resources in the communication network, such as bandwidth and processor power, can be more effectively utilized.

[0072] Optionally, generating a branch group connected to the primary trunk branch according to the phase relationship of the subordinate nodes of the proxy node and the success of the first round of data collection includes:

[0073] Searching and determining a plurality of first electric meters that are directly connected to the proxy node and meet a preset phase condition, and analyzing and comparing the plurality of first electric meters to determine a grouping feature;

[0074] According to the grouping characteristics, cluster analysis is performed on the plurality of the first electric meters to obtain a plurality of branch groups, and it is determined whether there is a target branch group including the first electric meters of different phases;

[0075] When there is a first electricity meter containing different phases in the target branch group, the target branch group is split into a plurality of sub-meter groups containing only electricity meters of the same phase.

[0076] Each meter node has its specific physical phase (such as phase A, phase B, phase C, etc.) and communication level. In order to construct the tree branch grouping connected to the first-level trunk branch, it is first necessary to find and determine the meters that are directly connected to the proxy node and meet the preset phase conditions. These meters are called "first meters". The preset phase conditions may include: being in the same physical phase as the proxy node, good communication status, high data collection success rate, etc. By screening these conditions, it can be ensured that the selected first meter is reliable in both physical and communication, and has a direct connection with the proxy node. After determining the first meter directly connected to the proxy node, it is necessary to analyze and compare these meters to determine their grouping characteristics. Grouping characteristics may include:

[0077] Physical phase: Ensure that the meters in the same group have the same physical phase to ensure consistency during data transmission and collection.

[0078] Communication quality: Consider the communication status of the meter and the data collection success rate to ensure that the meters in the group are reliable in communication.

[0079] Geographic location: If possible, the geographic location of the meter can also be taken into account so that factors such as network coverage and transmission distance can be considered when constructing branch groupings.

[0080] By analyzing and comparing these features, it is possible to determine the meters that should be classified into the same branch group. After determining the grouping features, it is necessary to perform cluster analysis on multiple first meters. Cluster analysis is a commonly used data mining technology that can classify similar objects into one category, thereby discovering potential patterns and structures in the data. In this scenario, cluster analysis can divide multiple first meters into multiple branch groups based on the grouping features. The meters in each branch group have similar characteristics such as physical phase, communication quality, and geographical location. After obtaining multiple branch groups, it is necessary to determine whether there is a target branch group containing first meters with different phases. This is because in the smart grid system, meters with different phases may have differences in the data transmission and collection process, so classifying them into the same branch group may cause errors or delays in data transmission. If there is such a target branch group, it needs to be split to ensure that the meters in each branch group have the same physical phase. When it is found that the target branch group contains first meters with different phases, it needs to be split into multiple sub-meter groups that only contain meters with the same phase. This ensures that the meters in each sub-meter group are consistent in physical phase, thereby avoiding errors or delays in data transmission and collection. The splitting process can be performed according to the physical phase of the meter, and the meters with the same phase are classified into the same sub-meter group. The split sub-meter group will be used as the final branch group, connected to the primary trunk branch, and together form the communication network of the smart grid system.

[0081] For example, suppose there is a community with multiple residential buildings, each of which has multiple smart meters installed. These smart meters are used to record the electricity consumption of each household. In order to optimize data collection efficiency, the power company decided to use a high-speed power line carrier communication platform and group management based on information such as the physical phase, product type, and communication layer of the meter. In the power community, a centrally located distribution box is selected as the proxy node of the primary trunk branch. The proxy node starts to find meters that are directly connected to it and meet specific phase conditions. For example, all meters with phase A are selected as preliminary screening results. These meters are classified as candidate meters for branch 1. Product information is collected from the candidate meters of branch 1, including manufacturer, model, communication protocol, electrical parameters, etc. The collected product information is analyzed and compared to identify similarities and differences between the meters. For example, it is found that most of the meters use the same communication protocol and electrical parameters, but there are differences in manufacturers and models. Based on the analysis results, key features for grouping are determined. In this example, communication protocol and electrical parameters can be selected as grouping features. According to the determined grouping characteristics, cluster analysis is performed on the candidate meters of branch 1. Meters with similar communication protocols and electrical parameters are classified into one category, and corresponding group numbers or identifiers are assigned to them. After cluster analysis, multiple meter groups are obtained. The meters in each group have similarities in communication protocols and electrical parameters, and data collection and transmission can be performed more efficiently. In the generated branch 1 group, the phase information of the meters in each group is checked. If it is found that a group contains meters with different phase characteristics (for example, phase A and phase B are mixed. Since the same-phase meters are grouped in one group in the embodiment of the present application, this situation does not exist. However, if the preset phase condition is other conditions, this step may be included), it is necessary to split the phase STA group. Split the group containing meters with different phases into multiple sub-groups containing only meters with the same phase. Ensure that the meters in each sub-group have the same phase characteristics. Verify the split sub-groups to ensure that the meters in each sub-group meet the phase requirements and that the data collection and transmission efficiency is improved.

[0082] By finding and determining the first electric meter that is directly connected to the proxy node and meets the preset phase conditions, the reliability of the selected electric meter in terms of physical phase and communication status can be ensured, thereby optimizing the structure of the communication network, reducing unnecessary communication links and nodes, and improving communication efficiency. Multiple first electric meters are analyzed and compared to determine the grouping characteristics, and reasonable grouping can be performed based on key information such as the physical phase, communication quality, and geographical location of the electric meter. This grouping method helps to ensure that the electric meters in the same group have similar behavioral characteristics during the data collection process, thereby improving the accuracy of data collection. By clustering the electric meters into multiple branch groups and determining whether there is a target branch group containing electric meters with different phases, potential communication problems can be discovered and handled in a timely manner. Once it is found that the target branch group contains electric meters with different phases, it is immediately split to avoid communication interference between electric meters with different phases and enhance the stability of the network.

[0083] Optionally, generating a branch group connected to the primary trunk branch according to the phase relationship of the subordinate nodes of the proxy node and the success of the first round of data collection further includes:

[0084] Monitor the voltage data in the power grid, identify the trend and amplitude of the voltage fluctuation in the same direction, and calculate the degree of influence of the electrical characteristics of each meter in the tree branch group according to the trend and amplitude;

[0085] removing a first electric meter whose electrical characteristic influence degree is greater than or equal to a first threshold from the branch group, and assigning a newly added second electric meter whose electrical characteristic influence degree is less than the first threshold to the branch group;

[0086] The first electric meter having a collection success rate less than the second threshold is allocated to a tree branch group having an electrical characteristic similarity greater than or equal to a third threshold and a collection success rate greater than or equal to the second threshold.

[0087] Voltage fluctuation in the same direction refers to the common change trend of voltage in the power grid within a certain period of time. This trend is usually related to factors such as load changes in the power grid and line impedance changes. In order to accurately identify the trend and amplitude of voltage fluctuation in the same direction, it is necessary to collect voltage data in the power grid in real time and conduct in-depth analysis and processing.

[0088] By analyzing the voltage data, a voltage change trend graph can be drawn, so that the voltage fluctuation can be observed intuitively. At the same time, the amplitude of the voltage fluctuation, that is, the difference between the maximum and minimum voltage values, can also be calculated to quantify the degree of voltage fluctuation. After identifying the trend and amplitude of the voltage fluctuation in the same direction, it is necessary to calculate the degree of influence of the electrical characteristics of each meter in the branch group. The degree of influence of electrical characteristics is a comprehensive indicator that reflects the degree of influence of changes in electrical parameters such as voltage and current on the meter in the power grid. In order to calculate this indicator, factors such as the location of the meter, line impedance, and load conditions can be considered comprehensively. Specifically, the electrical parameters such as voltage and current at the meter can be calculated according to the power grid model, and these parameters can be compared with the standard values ​​to obtain the degree of influence of the electrical characteristics on the meter. When it is found that the degree of influence of the electrical characteristics of a meter is greater than or equal to the preset first threshold, it means that the performance of the meter in the power grid may be unstable, or its measurement data may be subject to greater interference. In order to ensure the accuracy and reliability of data acquisition, the meter needs to be removed from the current branch group. After removing some meters, new meters may need to be added to the branch group. In order to ensure that the newly added electric meter can coordinate with other electric meters, it is necessary to evaluate the degree of influence of its electrical characteristics. Only when the degree of influence of the electrical characteristics of the new electric meter is less than the first threshold, it will be assigned to the corresponding tree branch group. In the smart grid system, the collection success rate of the electric meter is an important performance indicator. When it is found that the collection success rate of a certain electric meter is less than the preset second threshold, it means that there may be problems in the data collection process of the electric meter. In order to improve the reliability and integrity of data collection, the electric meter needs to be assigned to the tree branch group whose electrical characteristic similarity is greater than or equal to the third threshold and whose collection success rate is greater than or equal to the second threshold. This can ensure that the electric meter can obtain a better working environment and a higher collection success rate in the new group.

[0089] By monitoring the voltage data in the power grid, the trend and amplitude of the voltage fluctuation in the same direction can be identified, which is a key indicator for evaluating the state of the power grid. According to these trends and amplitudes, the degree of influence of the electrical characteristics of each meter in the branch group is calculated, and the operating state of each meter in the power grid can be accurately understood, providing data support for subsequent optimization and adjustment. According to the degree of influence of the electrical characteristics, the first meter with an influence greater than or equal to the first threshold is removed from the branch group, and the second meter with an electrical characteristic influence less than the first threshold is assigned to the branch group. This dynamic adjustment mechanism can ensure that the meters in the branch group are consistent in electrical characteristics and improve the efficiency and accuracy of group management. By assigning the first meter with a collection success rate less than the second threshold to a branch group with an electrical characteristic similarity greater than or equal to the third threshold and a collection success rate greater than or equal to the second threshold, the existing resources can be fully utilized to optimize the data collection success rate. This allocation method can ensure the continuity and stability of data collection and reduce the cost of data loss and repeated collection caused by collection failure. The comprehensive application of the above technical effects can improve the overall operation efficiency of the smart grid system. By accurately evaluating the impact of electrical characteristics, dynamically adjusting meter grouping and optimizing data collection success rate, real-time monitoring and rapid response to the power grid status can be achieved, thereby improving the stability and reliability of the power grid.

[0090] S140: Execute the periodic collection task according to the trunk branches and the tree branch groups.

[0091] Data is collected from the meters in the trunk branches and branch groups according to a predetermined cycle. The data collection process usually includes reading the current, voltage, power and other parameters in the meter and converting them into digital signals for transmission. The collected data will be transmitted to a higher-level node or data center through the communication network in the trunk branches and branch groups. During the transmission process, the data may be compressed, encrypted and other processes to ensure the integrity and security of the data. The received data will be further processed and analyzed in the data center. This includes steps such as data cleaning, data verification, and data analysis to ensure the accuracy and reliability of the data. At the same time, based on the analysis results, the operation status of the power grid can be monitored and warned in real time.

[0092] Optionally, the method further includes:

[0093] In each collection cycle, target data of the electric meter is collected multiple times, wherein the target data includes communication delay information, phase information, voltage and power factor values;

[0094] According to the voltage and power factor values ​​in the historical target data, a change trend of each electric meter is calculated, wherein the change trend includes rising, stable or falling, and the electric meters under the same agent node are grouped according to the change trend to obtain a new branch grouping;

[0095] Calculate the average collection delay of the electric meters in the new tree branch group according to the communication delay information, and sort them from low to high according to the average collection delay to obtain a group list;

[0096] The collection task is executed according to the grouping list.

[0097] Figure 4 1 is a partial flow chart of the high-speed power line carrier communication module grouping disclosed in the embodiment of the present application, such as Figure 4 As shown, part of the process of high-speed power line carrier communication module grouping is the formation process of branch grouping 2-N, which specifically includes: S401, the remaining nodes at the end of the trunk except branch group 1 are grouped according to the ABC phase framework. S402, high-frequency acquisition of voltage and power factor. S403, according to the voltage and power factor, the same direction of fluctuation trend is found to subdivide the group members. S405, the subdivided group members are sorted according to groups 1-N.

[0098] Assume that there is a large power system with thousands of meters distributed in different geographical locations and connected to different grid phases (Phase A, Phase B, Phase C). CCO sets a fixed collection cycle, such as data collection once a day at 1 a.m. This cycle can be adjusted according to actual conditions to ensure the accuracy and timeliness of the data. In each collection cycle, CCO will collect meter data multiple times (for example, 3 times or more), including communication delay information, phase information, voltage and power factor values. These data will be used for subsequent analysis and grouping. CCO will count the communication delay and phase information of each meter and record this information. For meters with the same phase, CCO will mark them as the same group and calculate the average communication delay of these meters. CCO will calculate the change trend of each meter based on the most recent (for example, the last 5) voltage and power factor values. These trends may include rising (+1, +2, +3), stable (0) or falling (-1, -2, -3). CCO also calculates the probability of these trends to understand the stability and variability of meter data. Based on the trend analysis of voltage and power factor values, CCO will sort the electricity meters on the same tree branch (or the same proxy node). Electric meters with similar trends will be grouped together to form a detailed grouping with similar characteristics of the same proxy node and power grid. Based on the detailed grouping, CCO will also vote and sort according to the acquisition delay. Specifically, CCO will calculate the average acquisition delay of the electricity meters in each detailed grouping and sort these delays. Groups with lower average acquisition delays will be processed first. CCO will generate acquisition archive branch grouping relationships based on the results of detailed grouping. These relationships will record the main branch, phase information, proxy node, and meter member list to which each group belongs. CCO will form multiple branch information based on the information of different phases and main branches. These branch information will be reorganized and sorted in the order of ABC phases to form a traversal grouping list of different phases and different proxy paths. This list will serve as the basis for subsequent data collection and transmission. Execute the corresponding collection tasks according to the grouping list.

[0099] In each collection cycle, multiple data collections are performed on the electric meter, which can effectively reduce the misjudgment caused by single collection errors or abnormal data, and improve the accuracy and reliability of the data. By collecting target data such as communication delay information, phase information, voltage and power factor values, the operation status of the electric meter in the power grid can be fully reflected, providing a rich information basis for subsequent analysis and processing. According to the voltage and power factor values ​​in the historical target data, the change trend of each electric meter is calculated, and the electric meters are grouped according to the change trend. This grouping method can ensure that the electric meters in the same group have similar operating status and characteristics, which is conducive to the optimization of subsequent collection tasks. According to the communication delay information, the average collection delay of the electric meters in the new branch group is calculated and sorted. This sorting method can reflect the differences in communication efficiency of each group and provide a basis for the priority arrangement of subsequent collection tasks. When executing the collection task according to the group list, the data of the electric meter with a lower average collection delay can be collected first. This method can reduce waiting time and improve the execution efficiency of the collection task. In the process of executing the collection task, the grouping and sorting can be dynamically adjusted according to the actual situation. This flexibility can cope with the real-time changes in the power grid status and ensure the continuous optimization of the collection task.

[0100] Optionally, the method further includes:

[0101] Generate grouping information according to the grouping list, and send the grouping information to the collection terminal through a protocol, so that the collection terminal performs interactive collection according to the grouping order in the grouping information when reading data; or

[0102] The grouping list is used to perform local collection according to the configured task cycle, and the data is temporarily stored. When a reporting instruction is received, the collected data is uploaded to the collection terminal.

[0103] The first method: send group information to the collection terminal through the protocol. According to the previously calculated group list (based on the changing trend of the meter, average collection delay and other factors), CCO will generate corresponding group information. The group information contains the meter identification (such as meter ID) in each group and the order of the groups. The group information is sent to the collection terminal through a specific communication protocol (which may be a custom or standard communication protocol). This process may involve the expansion of the local interface protocol to adapt to the new group information transmission requirements. After receiving the group information, the collection terminal will arrange the meter reading order according to the group order. In this way, the collection terminal can interactively collect data according to the group order in the group information when reading data, thereby improving the collection efficiency and data real-time performance.

[0104] The second method: Use the group list to collect data locally and temporarily store data. CCO will collect data locally based on the group list and the configured task cycle (such as 5 minutes, 15 minutes, 30 minutes, 60 minutes, etc.). In each task cycle, the system will collect data from the meters in the group list. The collected data will be temporarily stored in the storage medium of the HPLC module STA (station). These data will not be uploaded immediately while waiting for the reporting instruction from the collection terminal. When the collection terminal issues a reporting instruction, STA will upload the temporarily stored data to the collection terminal. In this way, the collection terminal can obtain the latest meter data for subsequent analysis and processing.

[0105] In the first method, although the collection terminal performs interactive collection in the order of grouping, the system can still design a concurrent meter reading mechanism, that is, send collection instructions to multiple meters at the same time to further improve the collection efficiency. In the second method, the system can also use the characteristics of concurrent meter reading when performing local collection to collect data from multiple meters at the same time. Through the above two methods, the system can obtain meter data more quickly, thereby improving the real-time nature of the data. In particular, in the first method, the collection terminal performs interactive collection in the order of grouping, which can reduce waiting time and obtain the required data faster. Since the system groups the meters and sorts them according to factors such as average collection delay, it can arrange collection tasks more reasonably. This helps to reduce collection failures and data loss caused by factors such as communication delay and meter failure, thereby improving data stability.

[0106] The collection terminal performs interactive collection according to the grouping order in the grouping information, which can reduce unnecessary waiting time and communication overhead and optimize the collection process. The order arrangement in the grouping information usually takes into account factors such as communication delay and change trend between meters, so it can ensure the efficient execution of the collection task and improve the collection efficiency. By optimizing the collection process and improving the collection efficiency, the collection terminal can obtain meter data more quickly, thereby enhancing the real-time nature of the data. Reasonable grouping and order arrangement can reduce the communication frequency between the collection terminal and the meter, reduce the system load, and improve the stability and reliability of the system.

[0107] The system can configure different task cycles (such as 5 minutes, 15 minutes, 30 minutes, 60 minutes, etc.) according to actual needs to adapt to different application scenarios and collection needs. By locally collecting and temporarily storing data, the frequency of real-time communication between the collection terminal and the meter can be reduced, reducing communication overhead. Temporarily stored data can be uploaded in time when the collection terminal issues a reporting instruction to ensure the integrity and accuracy of the data. The system can reasonably allocate collection resources and storage resources according to the grouping list and collection cycle to avoid resource waste and improve resource utilization efficiency.

[0108] Optionally, the method further includes:

[0109] During the collection process, the data collection status of each electric meter is monitored in real time, and the data collection status includes the collection success rate, data integrity and communication stability;

[0110] When it is detected that the data collection state of the target meter is abnormal, the collection strategy is adjusted according to the position of the target meter in the communication network and the relationship with other meters, and the adjustment of the collection strategy includes adjusting the collection cycle, changing the communication path or increasing the number of collection retries;

[0111] When the number of adjustments exceeds the fourth threshold, the data collection state of the target meter is still abnormal, the target meter is marked as an abnormal meter, the abnormal meter is deleted from the group list, and a new group list is generated.

[0112] Real-time monitoring of the data collection status of each meter. This includes three key indicators:

[0113] Collection success rate: measures the proportion of meter data that is successfully collected. A high collection success rate means that the system can obtain meter data stably and reliably.

[0114] Data integrity: Evaluate whether the collected meter data is complete and without missing data. A complete data set is crucial for subsequent analysis and processing.

[0115] Communication stability: reflects the communication quality between the meter and the data collection system. Stable communication is the basis for ensuring the continuity and accuracy of data collection.

[0116] When an abnormal data collection status of a target meter is detected, a series of measures will be taken immediately to adjust the collection strategy in an attempt to restore normal data collection. These adjustment measures include:

[0117] Adjust the collection cycle: Depending on the abnormal status of the meter, the system may shorten or extend the collection cycle to monitor the meter data more frequently or flexibly.

[0118] Changing the communication path: If there is a problem with communication stability, the system may try to establish a connection with the meter through a different communication path to bypass possible communication obstacles.

[0119] Increase the number of collection retries: When collection fails, the system will increase the number of retries to improve the collection success rate.

[0120] If the data collection status of the target meter is still abnormal after multiple adjustments to the collection strategy (the number of adjustments exceeds the fourth threshold), the system will mark the meter as an abnormal meter. This means that the meter may have hardware failures, communication problems, or other reasons that lead to data collection failure. In order to ensure the smooth progress of the collection task and the accuracy of the data, the system will delete the abnormal meter from the current grouping list. After deleting the abnormal meter, the system will regenerate the grouping list based on the status and characteristics of the remaining meters. This helps to optimize the collection process and improve collection efficiency.

[0121] By real-time monitoring of data collection status and adjusting collection strategies, the system can promptly discover and solve problems in the data collection process, thereby improving the reliability and accuracy of data collection. The system can flexibly adjust the collection strategy according to the abnormal status of the meter to adapt to different application scenarios and collection requirements. By deleting abnormal meters and regenerating the grouping list, the system can optimize resource allocation and avoid wasting resources on meters that cannot collect valid data. It can improve the overall performance of the smart grid system in data collection, processing and analysis, and provide strong support for the further development of smart grids.

[0122] This embodiment also discloses a system for improving the efficiency of electric meter data collection. Figure 5 is a module schematic diagram of a system for improving the efficiency of electric meter data collection disclosed in an embodiment of the present application, such as Figure 5 As shown, the system includes a networking module 501, a task module 502, a grouping module 503 and a collection module 504, wherein:

[0123] The networking module 501 is configured to respond to receiving an electric meter file and a network configuration parameter from a collection terminal, wherein the electric meter file includes basic information of the electric meter and collection requirements, and to perform networking according to the network configuration parameter to establish a communication connection with the electric meter;

[0124] The task module 502 is configured to send the network topology information to the collection terminal, and receive the periodic collection task generated by the collection terminal according to the network topology information, wherein the network topology information includes the product type, physical phase, and networking level of the electric meter, and the periodic collection task includes collection data items and collection period;

[0125] The grouping module 503 is configured to perform a first round of collection according to the periodic collection task and the meter archive, and to construct a trunk branch according to the physical phase of each meter and the hierarchical relationship in the communication network, and to generate a branch group at the trunk end of the trunk branch according to the phase relationship of the meter and the data collection situation of the first round of collection;

[0126] The collection module 504 is configured to perform the periodic collection task according to the trunk branches and the tree branch groups.

[0127] Optionally, the grouping module 503 is configured to:

[0128] Identify and connect meters with the same physical phase and at the same communication level to form a primary trunk branch;

[0129] At the proxy node of the primary trunk branch, a branch group connected to the primary trunk branch is generated according to the phase relationship of the subordinate nodes of the proxy node and the success of the first round of data collection.

[0130] Optionally, the grouping module 503 is configured to:

[0131] Searching and determining a plurality of first electric meters that are directly connected to the proxy node and meet a preset phase condition, and analyzing and comparing the plurality of first electric meters to determine a grouping feature;

[0132] According to the grouping characteristics, cluster analysis is performed on the plurality of the first electric meters to obtain a plurality of branch groups, and it is determined whether there is a target branch group including the first electric meters of different phases;

[0133] When there is a first electricity meter containing different phases in the target branch group, the target branch group is split into a plurality of sub-meter groups containing only electricity meters of the same phase.

[0134] Optionally, the grouping module 503 is further configured to:

[0135] Monitor the voltage data in the power grid, identify the trend and amplitude of the voltage fluctuation in the same direction, and calculate the degree of influence of the electrical characteristics of each meter in the tree branch group according to the trend and amplitude;

[0136] removing a first electric meter whose electrical characteristic influence degree is greater than or equal to a first threshold from the branch group, and assigning a newly added second electric meter whose electrical characteristic influence degree is less than the first threshold to the branch group;

[0137] The first electric meter having a collection success rate less than the second threshold is allocated to a tree branch group having an electrical characteristic similarity greater than or equal to a third threshold and a collection success rate greater than or equal to the second threshold.

[0138] Optionally, the system further comprises a list module, wherein the list module is configured to:

[0139] In each collection cycle, target data of the electric meter is collected multiple times, wherein the target data includes communication delay information, phase information, voltage and power factor values;

[0140] According to the voltage and power factor values ​​in the historical target data, a change trend of each electric meter is calculated, wherein the change trend includes rising, stable or falling, and the electric meters under the same agent node are grouped according to the change trend to obtain a new branch grouping;

[0141] Calculate the average collection delay of the electric meters in the new tree branch group according to the communication delay information, and sort them from low to high according to the average collection delay to obtain a group list;

[0142] The collection task is executed according to the grouping list.

[0143] Optionally, the system further includes an execution module, wherein the execution module is configured to:

[0144] Generate grouping information according to the grouping list, and send the grouping information to the collection terminal through a protocol, so that the collection terminal performs interactive collection according to the grouping order in the grouping information when reading data; or

[0145] The grouping list is used to perform local collection according to the configured task cycle, and the data is temporarily stored. When a reporting instruction is received, the collected data is uploaded to the collection terminal.

[0146] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0147] This embodiment also discloses an electronic device, referring to Figure 6 The electronic device may include: at least one processor 601 , at least one communication bus 602 , a user interface 603 , a network interface 604 , and at least one memory 605 .

[0148] The communication bus 602 is used to realize the connection and communication between these components.

[0149] The user interface 603 may include a display screen (Display) and a camera (Camera). The optional user interface 603 may also include a standard wired interface and a wireless interface.

[0150] The network interface 604 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0151] Among them, the processor 601 may include one or more processing cores. The processor 601 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 605, and calling data stored in the memory 605. Optionally, the processor 601 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 601 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 601, and it can be implemented separately through a chip.

[0152] Among them, the memory 605 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 605 includes a non-transitory computer-readable storage medium. The memory 605 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 605 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory 605 may optionally be at least one storage device located away from the aforementioned processor 601. As Figure 6 As shown, the memory 605 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program of the system for improving the efficiency of electric meter data collection.

[0153] exist Figure 6In the electronic device shown, the user interface 603 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 601 can be used to call the application of the system for improving the efficiency of meter data collection stored in the memory 605. When executed by one or more processors 601, the electronic device executes one or more methods in the above embodiments.

[0154] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0155] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0156] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0157] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0158] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0159] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory 605 and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned memory 605 includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk.

[0160] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for improving the efficiency of electric meter data collection, characterized in that: Applied to a high-speed power line carrier communication module, the method comprises: In response to receiving an electric meter profile and a network configuration parameter from a collection terminal, the electric meter profile including basic information of the electric meter and collection requirements, networking is performed according to the network configuration parameter to establish a communication connection with the electric meter; Sending the network topology information to the collection terminal, and receiving the periodic collection task generated by the collection terminal according to the network topology information, wherein the network topology information includes the product type, physical phase, and networking level of the electric meter, and the periodic collection task includes the collection data items and the collection period; Performing a first round of data collection according to the periodic data collection task and the meter archive, and constructing a trunk branch according to the physical phase of each meter and the hierarchical relationship in the communication network, and generating a branch group at the trunk end of the trunk branch according to the phase relationship of the meter and the data collection situation of the first round of data collection; Execute the periodic collection task according to the trunk branches and the tree branch groups, The step of constructing a trunk branch according to the physical phase of each electric meter and the hierarchical relationship in the communication network, and generating a branch group at the trunk end of the trunk branch according to the phase relationship of the electric meter and the data collection situation of the first round of collection includes: Identify and connect meters with the same physical phase and at the same communication level to form a primary trunk branch; At the proxy node of the primary trunk branch, a branch group connected to the primary trunk branch is generated according to the phase relationship of the subordinate nodes of the proxy node and the success of the first round of data collection, The step of generating a branch group connected to the primary trunk branch according to the phase relationship of the subordinate nodes of the proxy node and the success of the first round of data collection includes: Searching and determining a plurality of first electric meters that are directly connected to the proxy node and meet a preset phase condition, and analyzing and comparing the plurality of first electric meters to determine a grouping feature; According to the grouping characteristics, cluster analysis is performed on the plurality of the first electric meters to obtain a plurality of branch groups, and it is determined whether there is a target branch group including the first electric meters of different phases; When there is a first electricity meter containing different phases in the target branch group, the target branch group is split into a plurality of sub-meter groups containing only electricity meters of the same phase.

2. The method for improving the efficiency of electric meter data collection according to claim 1, characterized in that: The step of generating a branch group connected to the primary trunk branch according to the phase relationship of the subordinate nodes of the proxy node and the success of the first round of data collection further comprises: Monitor the voltage data in the power grid, identify the trend and amplitude of the voltage fluctuation in the same direction, and calculate the degree of influence of the electrical characteristics of each meter in the tree branch group according to the trend and amplitude; removing a first electric meter whose electrical characteristic influence degree is greater than or equal to a first threshold from the branch group, and assigning a newly added second electric meter whose electrical characteristic influence degree is less than the first threshold to the branch group; The first electric meter having a collection success rate less than the second threshold is allocated to a tree branch group having an electrical characteristic similarity greater than or equal to a third threshold and a collection success rate greater than or equal to the second threshold.

3. The method for improving the efficiency of electric meter data collection according to claim 1, characterized in that: The method further comprises: In each collection cycle, target data of the electric meter is collected multiple times, wherein the target data includes communication delay information, phase information, voltage and power factor values; According to the voltage and power factor values ​​in the historical target data, a change trend of each electric meter is calculated, wherein the change trend includes rising, stable or falling, and the electric meters under the same agent node are grouped according to the change trend to obtain a new branch grouping; Calculate the average collection delay of the electric meters in the new tree branch group according to the communication delay information, and sort them from low to high according to the average collection delay to obtain a group list; The collection task is executed according to the grouping list.

4. The method for improving the efficiency of electric meter data collection according to claim 3, characterized in that: The method further comprises: Generate grouping information according to the grouping list, and send the grouping information to the collection terminal through a protocol, so that the collection terminal performs interactive collection according to the grouping order in the grouping information when reading data; or The grouping list is used to perform local collection according to the configured task cycle, and the data is temporarily stored. When a reporting instruction is received, the collected data is uploaded to the collection terminal.

5. The method for improving the efficiency of electric meter data collection according to claim 4, characterized in that: The method further comprises: During the collection process, the data collection status of each electric meter is monitored in real time, and the data collection status includes the collection success rate, data integrity and communication stability; When it is detected that the data collection state of the target meter is abnormal, the collection strategy is adjusted according to the position of the target meter in the communication network and the relationship with other meters, and the adjustment of the collection strategy includes adjusting the collection cycle, changing the communication path or increasing the number of collection retries; When the number of adjustments exceeds the fourth threshold, the data collection state of the target meter is still abnormal, the target meter is marked as an abnormal meter, the abnormal meter is deleted from the grouping list, and a new grouping list is generated.

6. A system for improving the efficiency of electric meter data collection, characterized in that: It includes networking module, task module, grouping module and collection module, among which: A networking module configured to respond to receiving an electric meter profile and a network configuration parameter from a collection terminal, wherein the electric meter profile includes basic information of the electric meter and collection requirements, and to perform networking according to the network configuration parameter to establish a communication connection with the electric meter; A task module, configured to send the networking topology information to the collection terminal, and receive a periodic collection task generated by the collection terminal according to the networking topology information, wherein the networking topology information includes a product type, a physical phase, and a networking level of the electric meter, and the periodic collection task includes a collection data item and a collection period; a grouping module configured to perform a first round of collection according to the periodic collection task and the electric meter archive, and to construct a trunk branch according to the physical phase of each electric meter and the hierarchical relationship in the communication network, and to generate a branch group at the trunk end of the trunk branch according to the phase relationship of the electric meter and the data collection situation of the first round of collection; A collection module is configured to perform the periodic collection task according to the trunk branches and the tree branches. The step of constructing a trunk branch according to the physical phase of each electric meter and the hierarchical relationship in the communication network, and generating a branch group at the trunk end of the trunk branch according to the phase relationship of the electric meter and the data collection situation of the first round of collection includes: Identify and connect meters with the same physical phase and at the same communication level to form a primary trunk branch; At the proxy node of the primary trunk branch, a branch group connected to the primary trunk branch is generated according to the phase relationship of the subordinate nodes of the proxy node and the success of the first round of data collection, The step of generating a branch group connected to the primary trunk branch according to the phase relationship of the subordinate nodes of the proxy node and the success of the first round of data collection includes: Searching and determining a plurality of first electric meters that are directly connected to the proxy node and meet a preset phase condition, and analyzing and comparing the plurality of first electric meters to determine a grouping feature; According to the grouping characteristics, cluster analysis is performed on the plurality of the first electric meters to obtain a plurality of branch groups, and it is determined whether there is a target branch group including the first electric meters of different phases; When there is a first electricity meter containing different phases in the target branch group, the target branch group is split into a plurality of sub-meter groups containing only electricity meters of the same phase.

7. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 5 is performed.

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