Intelligent control method and system for electric energy meter

Abstract

The present invention discloses an intelligent control method and system for an electric energy meter, which relates to the technical field of power systems. It is mainly used to solve the problem of low efficiency of existing electric energy meters. It mainly includes configuring control permissions and detection nodes of different electric energy meters, and the control permissions include the transmission permissions of the electric energy meter; when the operating data of the electric energy meter matches the detection node, the node extreme value that matches the detection node and the control permission is retrieved, and the control object is determined based on the comparison result between the operating data and the node extreme value, and the control object includes a parameter object and an instruction object; the control strategy that matches the control object and the control permission is retrieved, and a control instruction is sent to the electric energy meter based on the control strategy, and the control instruction carries the control operation content obtained by parsing the control strategy. It is mainly used to perform intelligent control on the electric energy meter to improve the efficiency of the electric energy meter.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to an intelligent control method and system for electricity meters. Background Art

[0002] With the rapid development of power electronics technology, electricity meters, as terminal power data acquisition instruments, are used to collect power consumption data from power terminals or transmission nodes, so that the power management platform can accurately analyze the power transmission status of power terminals and transmission nodes.

[0003] Currently, existing electricity meters are typically configured in a normal operating state when collecting electricity data. This means that the meter collects electricity data in real time and transmits it to the power management platform via a wireless transmission module. However, this normal operating state keeps the meter in constant use, especially when no electricity data is being generated. This significantly reduces the meter's lifespan, fails to meet the need for flexible use, and thus reduces the meter's efficiency. Summary of the Invention

[0004] In view of this, the present invention provides an intelligent control method and system for electricity meters, the main purpose of which is to address the problem of low efficiency of existing electricity meters.

[0005] According to one aspect of the present invention, an intelligent control method for an electricity meter is provided, comprising:

[0006] Configure control permissions and detection nodes for different energy meters, wherein the control permissions include the transmission permissions of the energy meters;

[0007] When the operating data of the electricity meter matches the detection node, the extreme value of the node that matches the detection node and the control authority is retrieved, and the control object is determined based on the comparison result between the operating data and the extreme value of the node. The control object includes a parameter object and an instruction object.

[0008] A control strategy matching the controlled object and the control permission is retrieved, and a control command is sent to the energy meter based on the control strategy. The control command carries control operation content parsed from the control strategy.

[0009] Furthermore, the control permissions and detection nodes for configuring different energy meters include:

[0010] Obtain the location information, model information, and associated inspection terminal identification of different electricity meters;

[0011] Based on a preset demand control mapping relationship, the control permissions that match the location information, the model information, and the associated inspection terminal identifier are queried. The preset demand control mapping relationship includes the control permissions pre-configured for different location information, model information, and associated inspection terminal identifiers.

[0012] Based on the model information and the data collection target of the energy meter, a detection coefficient is determined, and the detection node is configured for the energy meter according to the detection coefficient.

[0013] Furthermore, the method also includes:

[0014] The system collects the operating data of the electricity meter and analyzes the time data, data collection volume, equipment runtime, operation and maintenance information, and historical control information in the operating data.

[0015] Determine whether the time data, the data collection volume, the device runtime, the operation and maintenance information, and the historical control information trigger the detection node.

[0016] Furthermore, determining the control object based on the comparison result between the running data and the node extreme values ​​includes:

[0017] When the difference between the operating data and the node extreme value is greater than the difference extreme value of the detection node, a node alarm message is output, and the control object corresponding to the detection node is entered into the power management platform; or,

[0018] When the difference between the running data and the node extreme value is greater than the difference extreme value of the detection node, the control object is queried from the control list based on the ratio between the difference value and the difference extreme value. The control list stores control objects corresponding to different detection nodes and different ratios.

[0019] Furthermore, sending control commands to the energy meter based on the control strategy includes:

[0020] The control strategy is parsed according to the controlled object and the control permissions to determine the time for transmitting and storing the collected power data.

[0021] Determine the instruction sending time that matches the time of transmitting the collected power data and the time of storing the collected power data, and generate the control instruction at the instruction sending time;

[0022] Send the control command to the electricity meter, which carries the time for transmitting the collected electricity data and the time for storing the collected electricity data.

[0023] Furthermore, the method also includes:

[0024] The power management platform collects the transmission time and acquisition time of the electricity meter, and determines the execution result of the control command based on the transmission time and acquisition time.

[0025] If the execution result does not match the control execution degree of the power management platform, a control anomaly alarm message is generated. The control execution degree is used to characterize the effectiveness of the power management platform in controlling the electricity meter.

[0026] Furthermore, the detection node includes at least one of the following: time detection node, data acquisition detection node, device detection node, and platform management detection node.

[0027] According to another aspect of the present invention, an intelligent control system for an electricity meter is provided, comprising:

[0028] A configuration module is used to configure the control permissions and detection nodes of different energy meters, wherein the control permissions include the transmission permissions of the energy meters;

[0029] The determination module is used to retrieve the node extreme value that matches the detection node and the control authority when the operating data of the electricity meter matches the detection node, and determine the control object based on the comparison result between the operating data and the node extreme value. The control object includes a parameter object and an instruction object.

[0030] The sending module is used to retrieve a control strategy that matches the controlled object and the control permission, and send a control command to the energy meter based on the control strategy. The control command carries control operation content parsed from the control strategy.

[0031] Furthermore, the configuration module includes:

[0032] The acquisition unit is used to acquire the location information, model information, and associated inspection terminal identification of different energy meters;

[0033] The first query unit is used to query the control permissions that match the location information, the model information and the associated inspection terminal identifier based on the preset demand control mapping relationship. The preset demand control mapping relationship includes the control permissions pre-configured for different location information, model information and associated inspection terminal identifier.

[0034] The first determining unit is used to determine the detection coefficient based on the model information and the data collection object of the energy meter, and to configure the detection node for the energy meter according to the detection coefficient.

[0035] Furthermore, the system also includes:

[0036] The parsing module is used to collect the operating data of the electricity meter and parse the time data, data collection volume, equipment running time, operation and maintenance information and historical control information in the operating data;

[0037] The judgment module is used to determine whether the time data, the data collection volume, the device runtime, the operation and maintenance information, and the historical control information trigger the detection node.

[0038] Furthermore, the determining module includes:

[0039] The output unit is configured to output a node alarm message when the difference between the running data and the node extreme value is greater than the difference extreme value of the detection node, and to input the control object corresponding to the detection node into the power management platform; or,

[0040] The second query unit is used to query the control object from the control list based on the ratio between the difference value and the extreme value of the node when the difference value between the running data and the extreme value of the node is greater than the extreme value of the difference of the detection node. The control list stores control objects corresponding to different detection nodes and different ratios.

[0041] Furthermore, the sending module includes:

[0042] The parsing unit is used to parse the time for transmitting and collecting power data and the time for storing power data in the control strategy according to the controlled object and the control authority.

[0043] The second determining unit is used to determine the instruction sending time that matches the time of transmitting the collected power data and the time of storing the collected power data, and to generate the control instruction at the instruction sending time;

[0044] The transmitting unit is used to send the control command to the electricity meter, which carries the time of transmitting the collected electricity data and the time of storing the collected electricity data.

[0045] Furthermore, the system also includes:

[0046] The determining module is further configured to collect the transmission time and collection time of the electricity meter through the power management platform, and determine the execution result of the control command based on the transmission time and the collection time;

[0047] The generation module is used to generate control anomaly alarm information if the execution result does not match the control execution degree of the power management platform. The control execution degree is used to characterize the effectiveness of the power management platform in controlling the electricity meter.

[0048] Furthermore, in specific application scenarios, the detection node includes at least one of the following: time detection node, data acquisition detection node, device detection node, and platform management detection node.

[0049] According to another aspect of the present invention, a storage medium is provided, wherein at least one executable instruction is stored therein, the executable instruction causing a processor to perform an operation corresponding to the intelligent control method of the above-described energy meter.

[0050] According to another aspect of the present invention, a terminal is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus;

[0051] The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the intelligent control method of the above-mentioned energy meter.

[0052] By employing the above-described technical solutions, the technical solutions provided by the embodiments of the present invention have at least the following advantages:

[0053] This invention provides an intelligent control method and system for electricity meters. Compared with existing technologies, this invention configures control permissions and detection nodes for different electricity meters. Control permissions include the electricity meter's transmission permissions. When the electricity meter's operating data matches a detection node, the extreme value of the node matching the detection node and control permissions is retrieved. Based on the comparison between the operating data and the node extreme value, a control object is determined. The control object includes parameter objects and instruction objects. A control strategy matching the control object and control permissions is retrieved, and control instructions are sent to the electricity meter based on the control strategy. The control instructions carry control operation content parsed from the control strategy. This avoids real-time power data transmission between the electricity meter and the power management platform, reducing the electricity meter's data transmission resource consumption. Furthermore, by using the detection node as the trigger node for electricity meter transmission control, it ensures timely and accurate detection of electricity meter anomalies even in the case of intermittent data transmission, thereby improving the electricity meter's utilization efficiency.

[0054] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. Attached Figure Description

[0055] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0056] Figure 1 A flowchart of an intelligent control method for an electricity meter according to an embodiment of the present invention is shown;

[0057] Figure 2 A flowchart of another intelligent control method for an electricity meter provided by an embodiment of the present invention is shown;

[0058] Figure 3 A block diagram of an intelligent control system for an electricity meter provided in an embodiment of the present invention is shown.

[0059] Figure 4 A schematic diagram of the structure of a terminal provided in an embodiment of the present invention is shown. Detailed Implementation

[0060] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0061] This invention provides an intelligent control method for electricity meters, such as... Figure 1 As shown, the method includes:

[0062] 101. Configure control permissions and detection nodes for different electricity meters.

[0063] In this embodiment of the invention, the electricity meter is a smart meter, which transmits data with the power management platform via wired or wireless network. The start and end times of this data transmission process are controlled by the power management platform. The current executing entity is the server of the power management platform, which can be a local server or a cloud server. To achieve intelligent control of the electricity meter, different electricity meters are configured with their own corresponding control permissions and detection nodes. The control permissions include the electricity meter's transmission permissions, meaning the electricity meter is always running and continuously collecting the user's electricity data. However, the data transmission process from the collected electricity data to the power management platform is under the control of the current executing entity. A detection node is a detection point triggered by a specific value of a certain data item in the electricity meter's operating data. For example, when the electricity meter's operating time reaches 2 hours, the detection node is triggered, and the electricity meter's operating data needs to be detected.

[0064] It should be noted that the control permissions and detection node configurations for different electricity meters can be determined based on at least one of the following: the electricity meter's device model, the type of electricity-consuming enterprise corresponding to the meter, the meter's location information, and the inspection terminal identifier corresponding to the meter. Furthermore, the control permissions and detection nodes corresponding to different electricity meters can be completely identical, partially identical, or completely different. The configuration strategies and specific content for the control permissions and detection nodes of different electricity meters can be customized according to the needs of the application scenario; this embodiment of the invention does not impose specific limitations.

[0065] It should be noted that when the electricity meter collects power data from a single power user, i.e., when the power data collection object is an independent electrical device, such as large electrical equipment or assembly lines, and the electricity meter collects zero data when the electrical device is not running, the control permissions can also include the start and stop control permissions of the electricity meter.

[0066] 102. When the operating data of the electricity meter matches the detection node, retrieve the extreme value of the node that matches the detection node and the control authority, and determine the control object based on the comparison result between the operating data and the extreme value of the node.

[0067] In this embodiment of the invention, when the operating data of the electricity meter matches the detection node, the node extreme values ​​of the detection node and the control authority are retrieved. The node extreme values ​​are used to compare the operating data to determine whether the electricity meter's operating state, as represented by the current operating data, requires control, and how to control it, including maximum and minimum values. Specifically, the node extreme values ​​can be retrieved based on a pre-built mapping relationship between different detection nodes and control authorities and their corresponding node extreme values. The control object is the means of controlling the electricity meter's data transmission process, including parameter objects and instruction objects. That is, based on the comparison result between the operating data and the node extreme values, it is determined whether to control the relevant parameters of the data transmission process or the relevant instructions of the data transmission process.

[0068] It should be noted that node extreme values ​​are the extreme values ​​of specified data items that match the detection node and control authority. When the operating data of the electricity meter matches different detection nodes, the power data that needs to be focused on also differs. For example, if the control authority is transmission authority and the detection node is the power consumption node, the corresponding node extreme values ​​could be current extreme values, voltage extreme values, and power extreme values. Furthermore, different comparison results between the operating data and the node extreme values ​​also characterize different operating states of the electricity meter, requiring different objects to be controlled accordingly. Determining the control object by comparing the node extreme values ​​with the operating data can cover a more comprehensive range of the electricity meter's operating states and specifically identify the control object, thereby ensuring the accuracy of the electricity meter control measures.

[0069] 103. Retrieve a control strategy that matches the controlled object and the control authority, and send a control command to the electricity meter based on the control strategy.

[0070] In this embodiment of the invention, the control command carries control operation content obtained from the parsing of the control strategy. Under different transmission permissions, different control objects correspond to different control strategies. After determining the control object, the control strategy corresponding to the current control object is matched from the data list of the correspondence between control objects, control permissions, and control strategies. After determining the control strategy, the control strategy is parsed to obtain the control operation content. The control operation content is packaged and sent to the electricity meter so that the electricity meter can execute according to the control operation content, thereby realizing the control of the electricity meter.

[0071] It should be noted that controlling the electricity meter based on a control strategy that matches the control permissions and the controlled object avoids real-time data transmission between the electricity meter and the power management platform, reducing resource consumption during data transmission. At the same time, it ensures the comprehensiveness and accuracy of the monitoring of the electricity meter's operating data, thereby greatly improving the accuracy of the monitoring of the electricity meter.

[0072] In one embodiment of the present invention, for further illustration and limitation, such as Figure 2 As shown, step 101, configuring the control permissions and detection nodes for different energy meters, includes:

[0073] 201. Obtain the location information, model information, and associated inspection terminal identification of different electricity meters.

[0074] 202. Based on preset requirements, control the mapping relationship to query control permissions that match the location information, the model information, and the associated inspection terminal identifier.

[0075] 203. Determine the detection coefficient based on the model information and the data collection object of the energy meter, and configure the detection node for the energy meter according to the detection coefficient.

[0076] In this embodiment of the invention, control permissions are configured based on the location information, model information, and associated inspection terminal of the electricity meter. The control permissions are matched according to a preset demand control mapping relationship, which includes pre-configured control permissions for different location information, model information, and associated inspection terminal identifiers. That is, electricity meters of different models, located in different locations, and associated with different inspection terminals each correspond to different control permissions. These control permissions include transmission permissions that control multiple parameters involved in the power data transmission process. For example, permissions to control transmission duration, transmission data type, and transmission start frequency. The location information refers to the installation location of the electricity meter, such as equipment cabinet No. 2 in factory a of company A, or the meter box on the 13th floor of unit 2 in building 13 of a residential complex. The model information refers to the equipment model of the electricity meter, used to characterize the meter's performance, power data acquisition specifications, and power data acquisition items. The associated inspection terminal identifier is the unique identifier of the portable terminal device equipped by the inspection personnel who have the inspection authority of the current electricity meter. The identifier is also used to represent the authority level of the inspection personnel corresponding to the associated inspection terminal. For example, the inspection terminal identifier of ordinary employees is 1001~1020, and the inspection terminal identifier of the person in charge of inspection is 1000.

[0077] It should be noted that by pre-establishing the correspondence between different location information, model information, and associated inspection terminal identifiers and control permissions, the size of the control permissions can be matched with the electricity consumption characteristics of the electricity meter users, the performance and data acquisition capabilities of the electricity meter, and the inspection permissions. This avoids control operations that exceed the performance of the electricity meter or the inspection permissions, and also avoids the generation of control permissions that do not meet the electricity consumption characteristics of users, thereby ensuring the compatibility of control permissions with the electricity meter.

[0078] In this invention application, a pre-established correspondence between different detection coefficients and different detection nodes is constructed. The detection coefficients are determined based on the model information of the electricity meter and the data collection object. Specifically, the model information of the electricity meter is numerically represented. The larger the specification range and storage capacity of the electricity meter represented by the model information, the smaller the corresponding numerical value. For example, the numerical representation of a 1G memory electricity meter is greater than that of a 2G memory electricity meter. The higher the importance of the data collection object, the larger the corresponding numerical representation. For example, the importance of a residential user is lower than that of a factory equipment, so the numerical representation of a residential user is smaller than that of a factory equipment. The product of the numerical representation of the model information and the numerical representation of the data collection object is used as the detection coefficient. The larger the detection coefficient, the higher the level of attention required for detection; the smaller the detection coefficient, the lower the level of attention required for detection. Detection nodes are configured according to the detection coefficients. The larger the detection coefficient, the smaller the time span of each node in the corresponding detection node, the smaller the data volume, the lower the fault tolerance, and the higher the frequency of triggering detection at the corresponding detection node. For example, the larger the detection coefficient, the shorter the duration of the detection node corresponding to the device's runtime, the smaller the value of the detection node corresponding to the data collection volume, and the fewer the number of times the detection node is triggered corresponding to the number of maintenance operations.

[0079] It should be noted that by determining the detection node based on the model information of the electricity meter and the data collection object, the triggering frequency of the detection node can be adjusted according to the storage capacity of the electricity meter and the importance of the data collection object. This achieves matching between the detection trigger and the electricity meter and the data collection environment, improving the precise matching of detection accuracy, and thus ensuring the timeliness and intelligence of electricity meter detection.

[0080] In one embodiment of the present invention, for further explanation and limitation, the method further includes:

[0081] The system collects the operating data of the electricity meter and analyzes the time data, data collection volume, equipment runtime, operation and maintenance information, and historical control information in the operating data.

[0082] Determine whether the time data, the data collection volume, the device runtime, the operation and maintenance information, and the historical control information trigger the detection node.

[0083] In this embodiment of the invention, to determine whether the current detection node is met, the operating data of the electricity meter is parsed to extract time data, data collection volume, device runtime, maintenance information, and historical control information. Time data refers to the time point at which data is collected. Data collection volume is the cumulative amount of data collected by the electricity meter within a preset time period. Device runtime is the cumulative runtime of the electricity meter from its last startup to the current time point. Maintenance information refers to the inspection and maintenance information of the electricity meter, specifically including maintenance content, maintenance time point, inspection time point, and inspection status entered through the inspection terminal. Historical control information includes the execution time of the electricity meter's startup control, shutdown control, data transmission startup control, and data transmission shutdown control within a historical time period. Detection nodes include trigger thresholds corresponding to the data collection volume, device runtime, maintenance information, and historical control information, respectively. For example, the trigger threshold corresponding to device runtime is 10 hours; if the device runtime meets 10 hours, the detection node is triggered. For example, the trigger threshold for historical control information is 3 abnormal controls. If, in the historical control information, data transmission start control is executed 3 times consecutively without executing data transmission stop control, then the detection node is triggered.

[0084] It should be noted that by identifying detection nodes, the operating data of electricity meters can be comprehensively monitored from multiple dimensions such as time, control anomaly, and operation and maintenance. This improves the accuracy of electricity meter data monitoring and the timeliness of anomaly detection, thereby ensuring the timeliness of subsequent electricity meter control.

[0085] In one embodiment of the present invention, for further explanation and limitation, the step of determining the control object based on the comparison result between the running data and the node extreme value includes:

[0086] When the difference between the operating data and the node extreme value is greater than the difference extreme value of the detection node, a node alarm message is output, and the control object corresponding to the detection node is entered into the power management platform; or,

[0087] If the difference between the running data and the node extreme value is greater than the difference extreme value of the detection node, then the control object is queried from the control list based on the ratio between the difference value and the difference extreme value.

[0088] In this embodiment of the invention, the detection node is also configured with a difference extreme value. When the difference between the operating data and the node extreme value is greater than this difference extreme value, it indicates that there is an anomaly in the current operating data, and control adjustments to the energy meter are required, i.e., the control object needs to be determined. The difference value is the difference between the node extreme value of the corresponding data item of the detection node and the value of the corresponding operating data. The determination of the control object can be achieved through two methods: manual input and automatic query. Manual input involves outputting node alarm information through the interactive interface of the power management platform when control adjustments are required, allowing managers to determine the control object based on the node alarm information and specify the control object through input on the power management platform. Automatic query matches the control object by searching a control list. The control list stores control objects corresponding to different detection nodes and different ratios. When the difference between the operating data and the node extreme value is greater than the difference extreme value of the detection node, the multiple relationship between the difference value and the difference extreme value, i.e., the ratio, is calculated. A group whose ratio and detection node both match the current ratio and detection node is identified from the control list, and its corresponding control object is used as the query result.

[0089] It should be noted that the two methods for determining the controlled object can be configured according to specific application requirements. Determining the controlled object through both manual input and automatic query can meet the needs of both automated control and scenarios requiring manual intervention, thus improving the flexibility of controlled object selection.

[0090] In one embodiment of the present invention, for further explanation and limitation, the step of sending control commands to the energy meter based on the control strategy includes:

[0091] The control strategy is parsed according to the controlled object and the control permissions to determine the time for transmitting and storing the collected power data.

[0092] Determine the instruction sending time that matches the time of transmitting the collected power data and the time of storing the collected power data, and generate the control instruction at the instruction sending time;

[0093] Send the control command to the electricity meter, which carries the time for transmitting the collected electricity data and the time for storing the collected electricity data.

[0094] In this embodiment of the invention, the control command is not issued immediately after the controlled object is determined, but rather executed based on the command sending time determined by the transmission and storage times of the collected power data. The control strategy includes the transmission and storage times of the collected power data corresponding to different controlled objects under different control permissions. The corresponding transmission and storage times of the collected power data need to be determined according to the control permissions and the controlled object, and in accordance with the control strategy. Then, based on the preset correspondence between the transmission and storage times of the collected power data and the command sending time, the command sending time is matched to generate and send the control command according to the command sending time. The control command carries the transmission and storage times of the collected power data, instructing the energy meter to send the collected power data to the power management platform according to the transmission time, and to collect and store the collected power data according to the storage time.

[0095] It should be noted that by configuring different transmission and storage times for power data acquisition and storage for control objects under different control permissions through control strategies, it is possible to separate different data transmission volumes, avoid excessively large or small data transmission volumes between the electricity meter and the power management platform, and ensure the utilization rate of resource consumption and the efficiency of data transmission.

[0096] In one embodiment of the present invention, for further explanation and limitation, the method further includes:

[0097] The power management platform collects the transmission time and acquisition time of the electricity meter, and determines the execution result of the control command based on the transmission time and acquisition time.

[0098] If the execution result does not match the control execution degree of the power management platform, a control anomaly alarm message will be generated.

[0099] In this embodiment of the invention, after the control command is issued, the execution status of the control command needs to be monitored periodically to determine the execution result of the power management platform's control over the electricity meter. The execution result can be determined by comparing the actual data transmission time of the electricity meter (transmission time) with the time for transmitting and collecting electricity data carried in the control command, and the actual data collection time (collection time) with the time for storing and collecting electricity data carried in the control command. For example, the transmission time and collection time of the electricity meter can be collected over a month. The time deviation value between the transmission and collection time of the corresponding control command and the time deviation value between the storage and collection time of the corresponding control command are calculated, and the sum of the ratios of the two deviation values ​​to the total control time is determined as the execution result. The deviation value is the sum of the deviation value at the start time, the deviation value at the end time, and the deviation value of the control time. If the execution result is less than the control execution degree, a control anomaly alarm message is generated to remind the power management platform to troubleshoot the control of the corresponding electricity meter. The control execution degree is used to characterize the effectiveness of the power management platform's control over the electricity meter and can be determined based on statistical data of historical execution results.

[0100] It should be noted that by monitoring the control execution of the power management platform, abnormal situations in the execution of control commands by the electricity meter can be detected in a timely manner, thereby ensuring the effective execution of the smart control of the electricity meter.

[0101] In one embodiment of the present invention, for further explanation and limitation, the detection node includes at least one of a time detection node, a data acquisition detection node, a device detection node, and a platform management detection node.

[0102] In this embodiment of the invention, the time detection node is the trigger node for detecting time data in the corresponding running data. The data acquisition detection node is the trigger node for detecting the amount of data acquired in the corresponding running data. The device detection node is the trigger node for detecting the running time of the device in the corresponding running data. The platform management detection node is the trigger node for detecting maintenance information and historical control information in the corresponding running data. Detection nodes may include one, more, or all of the above detection nodes, and can be customized according to the needs of the actual application scenario. This embodiment of the invention does not impose specific limitations. For example, when the electricity meter is a key monitored plant power meter, the detection node may include all of the above detection nodes; when the electricity meter is a general residential power meter, the detection node may include either a device detection node or a time detection node. By configuring the detection nodes, the control requirements of electricity meters in different application scenarios can be met, thereby improving the multi-scenario applicability of electricity meter control.

[0103] This invention provides an intelligent control method for electricity meters. Compared with existing technologies, this invention configures control permissions and detection nodes for different electricity meters. Control permissions include the electricity meter's transmission permissions. When the electricity meter's operating data matches a detection node, the extreme value of the node matching the detection node and control permissions is retrieved. Based on the comparison between the operating data and the node extreme value, a control object is determined. The control object includes parameter objects and instruction objects. A control strategy matching the control object and control permissions is retrieved, and control instructions are sent to the electricity meter based on the control strategy. The control instructions carry control operation content parsed from the control strategy. This avoids real-time power data transmission between the electricity meter and the power management platform, reducing the electricity meter's data transmission resource consumption. Furthermore, by using the detection node as the trigger node for electricity meter transmission control, it ensures timely and accurate detection of electricity meter anomalies even in the case of intermittent data transmission, thereby improving the electricity meter's utilization efficiency.

[0104] Furthermore, as a response to the above Figure 1 The implementation of the method shown in this invention provides an intelligent control system for an electricity meter, such as... Figure 3 As shown, the system includes:

[0105] Configuration module 31 is used to configure the control permissions and detection nodes of different energy meters, wherein the control permissions include the transmission permissions of the energy meters;

[0106] The determination module 32 is used to retrieve the node extreme value that matches the detection node and the control authority when the operating data of the energy meter matches the detection node, and determine the control object based on the comparison result between the operating data and the node extreme value. The control object includes a parameter object and an instruction object.

[0107] The sending module 33 is used to retrieve a control strategy that matches the controlled object and the control permission, and send a control command to the energy meter based on the control strategy. The control command carries control operation content parsed based on the control strategy.

[0108] Furthermore, the configuration module 31 includes:

[0109] The acquisition unit is used to acquire the location information, model information, and associated inspection terminal identification of different energy meters;

[0110] The first query unit is used to query the control permissions that match the location information, the model information and the associated inspection terminal identifier based on the preset demand control mapping relationship. The preset demand control mapping relationship includes the control permissions pre-configured for different location information, model information and associated inspection terminal identifier.

[0111] The first determining unit is used to determine the detection coefficient based on the model information and the data collection object of the energy meter, and to configure the detection node for the energy meter according to the detection coefficient.

[0112] Furthermore, the system also includes:

[0113] The parsing module is used to collect the operating data of the electricity meter and parse the time data, data collection volume, equipment running time, operation and maintenance information and historical control information in the operating data;

[0114] The judgment module is used to determine whether the time data, the data collection volume, the device runtime, the operation and maintenance information, and the historical control information trigger the detection node.

[0115] Furthermore, the determining module includes:

[0116] The output unit is configured to output a node alarm message when the difference between the running data and the node extreme value is greater than the difference extreme value of the detection node, and to input the control object corresponding to the detection node into the power management platform; or,

[0117] The second query unit is used to query the control object from the control list based on the ratio between the difference value and the extreme value of the node when the difference value between the running data and the extreme value of the node is greater than the extreme value of the difference of the detection node. The control list stores control objects corresponding to different detection nodes and different ratios.

[0118] Furthermore, the sending module 33 includes:

[0119] The parsing unit is used to parse the time for transmitting and collecting power data and the time for storing power data in the control strategy according to the controlled object and the control authority.

[0120] The second determining unit is used to determine the instruction sending time that matches the time of transmitting the collected power data and the time of storing the collected power data, and to generate the control instruction at the instruction sending time;

[0121] The transmitting unit is used to send the control command to the electricity meter, which carries the time of transmitting the collected electricity data and the time of storing the collected electricity data.

[0122] Furthermore, the system also includes:

[0123] The determining module 32 is further configured to collect the transmission time and collection time of the electricity meter through the power management platform, and determine the execution result of the control command based on the transmission time and the collection time;

[0124] The generation module is used to generate control anomaly alarm information if the execution result does not match the control execution degree of the power management platform. The control execution degree is used to characterize the effectiveness of the power management platform in controlling the electricity meter.

[0125] Furthermore, in specific application scenarios, the detection node includes at least one of the following: time detection node, data acquisition detection node, device detection node, and platform management detection node.

[0126] This invention provides an intelligent control system for electricity meters. Compared with existing technologies, this invention configures control permissions and detection nodes for different electricity meters. Control permissions include the electricity meter's transmission permissions. When the electricity meter's operating data matches a detection node, the system retrieves the extreme value of the node matching the detection node and control permissions. Based on the comparison between the operating data and the node extreme value, a control object is determined. The control object includes parameter objects and instruction objects. A control strategy matching the control object and control permissions is retrieved, and control commands are sent to the electricity meter based on the control strategy. The control commands carry control operation content parsed from the control strategy. This avoids real-time power data transmission between the electricity meter and the power management platform, reducing the electricity meter's data transmission resource consumption. Furthermore, by using the detection node as the trigger node for electricity meter transmission control, it ensures timely and accurate detection of electricity meter anomalies even in the event of intermittent data transmission, thereby improving the electricity meter's utilization efficiency.

[0127] According to one embodiment of the present invention, a storage medium is provided, the storage medium storing at least one executable instruction, which can execute the intelligent control method of the electricity meter in any of the above method embodiments.

[0128] Figure 4 The diagram shows a structural schematic of a terminal according to an embodiment of the present invention. The specific implementation of the terminal is not limited by the specific embodiments of the present invention.

[0129] like Figure 4 As shown, the terminal may include: a processor 402, a communications interface 404, a memory 406, and a communications bus 408.

[0130] The processor 402, communication interface 404, and memory 406 communicate with each other via communication bus 408.

[0131] Communication interface 404 is used for network communication with other devices such as clients or other servers.

[0132] The processor 402 is used to execute program 410, specifically the relevant steps in the above-described embodiment of the intelligent control method for electricity meters.

[0133] Specifically, program 410 may include program code that includes computer operation instructions.

[0134] Processor 402 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The terminal may include one or more processors of the same type, such as one or more CPUs; or it may include processors of different types, such as one or more CPUs and one or more ASICs.

[0135] Memory 406 is used to store program 410. Memory 406 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0136] Specifically, program 410 can be used to cause processor 402 to perform the following operations:

[0137] Configure control permissions and detection nodes for different energy meters, wherein the control permissions include the transmission permissions of the energy meters;

[0138] When the operating data of the electricity meter matches the detection node, the extreme value of the node that matches the detection node and the control authority is retrieved, and the control object is determined based on the comparison result between the operating data and the extreme value of the node. The control object includes a parameter object and an instruction object.

[0139] A control strategy matching the controlled object and the control permission is retrieved, and a control command is sent to the energy meter based on the control strategy. The control command carries control operation content parsed from the control strategy.

[0140] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing systems. They can be centralized on a single computing system or distributed across a network of multiple computing systems. Optionally, they can be implemented using program code executable by a computing system, thereby storing them in a storage system for execution by the computing system. In some cases, the steps shown or described can be performed in a different order than those presented herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0141] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An intelligent control method for an electricity meter, characterized in that, include: Configure control permissions and detection nodes for different energy meters, wherein the control permissions include the transmission permissions of the energy meters; wherein configuring control permissions and detection nodes for different energy meters includes: acquiring location information, model information, and associated inspection terminal identifiers of different energy meters; querying control permissions that match the location information, model information, and associated inspection terminal identifiers based on a preset demand control mapping relationship, wherein the preset demand control mapping relationship includes the control permissions pre-configured for different location information, model information, and associated inspection terminal identifiers; determining detection coefficients based on the model information and the data collection object of the energy meter, and configuring the detection nodes for the energy meters according to the detection coefficients; When the operating data of the electricity meter matches the detection node, the extreme value of the node that matches the detection node and the control authority is retrieved, and the control object is determined based on the comparison result between the operating data and the extreme value of the node. The control object includes a parameter object and an instruction object. A control strategy matching the controlled object and the control permission is retrieved, and a control command is sent to the energy meter based on the control strategy. The control command carries the control operation content parsed based on the control strategy.

2. The method according to claim 1, characterized in that, The method further includes: The system collects the operating data of the electricity meter and analyzes the time data, data collection volume, equipment runtime, operation and maintenance information, and historical control information in the operating data. Determine whether the time data, the data collection volume, the device runtime, the operation and maintenance information, and the historical control information trigger the detection node.

3. The method according to claim 2, characterized in that, The determination of the control object based on the comparison result between the operating data and the node extreme value includes: When the difference between the operating data and the node extreme value is greater than the difference extreme value of the detection node, a node alarm message is output, and the control object corresponding to the detection node is entered into the power management platform; or, When the difference between the running data and the node extreme value is greater than the difference extreme value of the detection node, the control object is queried from the control list based on the ratio between the difference value and the difference extreme value. The control list stores control objects corresponding to different detection nodes and different ratios.

4. The method according to claim 3, characterized in that, Sending control commands to the energy meter based on the control strategy includes: The control strategy is analyzed according to the controlled object and the control permissions to determine the time for transmitting and storing the collected power data. Determine the instruction sending time that matches the time of transmitting the collected power data and the time of storing the collected power data, and generate the control instruction at the instruction sending time; Send the control command to the electricity meter, which carries the time for transmitting the collected electricity data and the time for storing the collected electricity data.

5. The method according to claim 1, characterized in that, The method further includes: The power management platform collects the transmission time and acquisition time of the electricity meter, and determines the execution result of the control command based on the transmission time and acquisition time. If the execution result does not match the control execution degree of the power management platform, a control anomaly alarm message is generated. The control execution degree is used to characterize the effectiveness of the power management platform in controlling the electricity meter.

6. The method according to claim 1, characterized in that, The detection nodes include at least one of the following: time detection node, data acquisition detection node, device detection node, and platform management detection node.

7. An intelligent control system for an electricity meter, characterized in that, include: A configuration module is used to configure control permissions and detection nodes for different energy meters. The control permissions include the transmission permissions of the energy meters. Configuring control permissions and detection nodes for different energy meters includes: acquiring location information, model information, and associated inspection terminal identifiers for different energy meters; querying control permissions matching the location information, model information, and associated inspection terminal identifiers based on a preset demand control mapping relationship, where the preset demand control mapping relationship includes pre-configured control permissions for different location information, model information, and associated inspection terminal identifiers; determining detection coefficients based on the model information and the data collection object of the energy meter; and configuring the detection nodes for the energy meters according to the detection coefficients. The determination module is used to retrieve the node extreme value that matches the detection node and the control authority when the operating data of the electricity meter matches the detection node, and determine the control object based on the comparison result between the operating data and the node extreme value. The control object includes a parameter object and an instruction object. The sending module is used to retrieve a control strategy that matches the controlled object and the control permission, and send a control command to the energy meter based on the control strategy. The control command carries control operation content parsed from the control strategy.

8. A storage medium storing at least one executable instruction that causes a processor to perform an operation corresponding to the intelligent control method of an energy meter as described in any one of claims 1-6.

9. A terminal, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the intelligent control method of the electricity meter as described in any one of claims 1-6.

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