A cloud edge fusion-based distributed energy equipment intelligent operation and maintenance management method

Abstract

The application discloses a kind of based on cloud edge fusion's distributed energy equipment intelligent operation and maintenance management method, including, the general-purpose model dictionary facing mass distributed energy equipment is established, is uniformly preset in cloud and edge end simultaneously;Combining edge end is carried out equipment ontology identification and scanning, and equipment basic information is structured entry according to preset template, completes local registration and is uploaded to cloud and obtains initialization configuration table;According to equipment initialization configuration table, operation data acquisition storage and uploading rule configuration are carried out;Rely on internet of things transmission protocol, the remote operation of business application and the transceiving of energy equipment control instruction are realized.This method can meet the demand of large-scale grid-connected of large amount of distributed energy, realizes the remote maintenance of distributed energy equipment.

Description

Technical Field

[0001] This invention relates to the field of power technology regulation, and in particular to an intelligent operation and maintenance management method for distributed energy equipment based on cloud-edge fusion. Background Technology

[0002] The current power grid has a large number of distributed energy sources and a vast amount of information. Manually maintaining each device on-site is labor-intensive and difficult to sustain given the current shortage of human resources. With the accelerated pace of electricity marketization, the integration of numerous market participants, such as distributed power sources and charging piles, into the grid has not been effectively monitored in real time, posing significant potential risks. The difficulty in integrating distributed energy sources has created data silos, hindering the company's transformation into a smart grid operator, energy industry value chain integrator, and energy ecosystem service provider. The distributed energy information access technology involves significant technical bottlenecks in areas such as high-precision acquisition of operational data, local processing and analysis based on edge computing, cloud-edge-device grid equipment modeling and universal information interaction, and plug-and-play edge terminal access. Summary of the Invention

[0003] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides an intelligent operation and maintenance management method for distributed energy devices based on cloud-edge convergence, which can solve the problems of difficult access and heavy operation and maintenance management of distributed energy devices.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a method for intelligent operation and maintenance management of distributed energy devices based on cloud-edge convergence, comprising:

[0007] Establish a general-purpose model dictionary for massive distributed energy devices and pre-configure it simultaneously in the cloud and at the edge.

[0008] Combined with edge computing, the device body is identified and scanned, and the basic information of the device is entered in a structured manner according to the preset template. The local registration is completed and uploaded to the cloud to obtain the initial configuration table.

[0009] Configure the rules for data collection, storage, and transmission according to the device initialization configuration table;

[0010] Based on the Internet of Things (IoT) transmission protocol, remote operation of business applications and the sending and receiving of control commands for energy equipment can be realized.

[0011] As a preferred embodiment of the intelligent operation and maintenance management method for distributed energy devices based on cloud-edge fusion described in this invention, the unified pre-setting includes standardizing the data structure of distributed energy devices and defining the main attributes of each type of device.

[0012] As a preferred embodiment of the intelligent operation and maintenance management method for distributed energy equipment based on cloud-edge fusion described in this invention, the general-purpose model dictionary includes detailed definitions of attribute fields for each type of equipment, setting field types, lengths, and non-null requirements, defining primary key constraints, and forming a standard general-purpose model dictionary.

[0013] As a preferred embodiment of the intelligent operation and maintenance management method for distributed energy equipment based on cloud-edge convergence described in this invention, the synchronization includes: the cloud application platform and the intelligent terminal at the edge synchronously configuring a general model dictionary, updating the dictionary to meet forward adaptation, and subsequent additions of device attributes or changes to the configuration of attributes do not affect previous versions;

[0014] The cloud refers to the application system used by the monitoring side, which is deployed on a cloud computing platform or monitoring master station.

[0015] The edge device is a smart terminal device that has local processing capabilities for edge computing, wireless communication capabilities, local acquisition and communication protocol parsing capabilities, and supports the Internet of Things MQTT protocol.

[0016] The communication between the cloud and the edge is secure and encrypted.

[0017] As a preferred embodiment of the intelligent operation and maintenance management method for distributed energy equipment based on cloud-edge fusion described in this invention, the step of combining the edge terminal for equipment identification and scanning includes: wiring the distributed energy equipment and the edge terminal intelligent terminal equipment and powering them on for self-testing, automatically confirming the equipment category, and autonomously querying the general model dictionary to obtain the data structure required for establishing the equipment ledger.

[0018] The identification includes checking whether all the mandatory information in the equipment ledger has been identified. If all the mandatory information in the equipment ledger has been identified, the identified information is confirmed by combining the nameplate and product manual of the distributed energy equipment.

[0019] If some of the mandatory equipment ledger information is successfully identified but others are not, all mandatory equipment ledger information is transcribed to the first analysis and judgment module. The reasons for the unsuccessful identification of the transcribed mandatory equipment ledger information are analyzed, and the third analysis and judgment module traces the mandatory equipment ledger information and obtains the source text of the mandatory equipment ledger information. The obtained source text of the mandatory equipment ledger information is imported from the third analysis and judgment module into the first analysis and judgment module. The first analysis and judgment module verifies the mandatory equipment ledger information and the source text of the mandatory equipment ledger information. After verification, the information is corrected based on the reasons for the unsuccessful identification of some of the mandatory equipment ledger information. The corrected mandatory equipment ledger information is further identified by the recognition units in the first analysis and judgment module. If all identification is successful, the next information confirmation operation is performed on the identified information, and the mandatory equipment ledger information that failed to be identified on the first attempt is supplemented.

[0020] The step of transcribing all mandatory equipment ledger information to the first analysis and judgment module includes: if the transcription of mandatory equipment ledger information fails, the second analysis and judgment module determines the reason for the transcription failure; if the transcription can be successfully completed through information correction after the reason for failure is determined, the second analysis and judgment module performs correction and transcription operations on the mandatory equipment ledger information; if the transcription cannot be successfully completed through information correction, the third analysis and judgment module performs information tracing and executes subsequent operations.

[0021] The verification includes, if the verification is of the equipment ledger mandatory information with problems, it is determined that the information cannot be corrected and the source text of the equipment ledger mandatory information needs to be transferred to the third analysis and judgment module. The third analysis and judgment module traces the source of the information and imports the source text of the equipment ledger mandatory information whose source cannot be determined into the database as passive equipment ledger mandatory information to await the next operation command.

[0022] If the source of the information can be confirmed, the required information for the equipment ledger will be downloaded again from the source of the information and then checked a second time by the third analysis and judgment module. After the second check is successful, the logic unit of the third analysis and judgment module will send the information back to the first analysis and judgment module or the second analysis and judgment module.

[0023] If the second verification is still unsuccessful, the required fields for the equipment ledger that failed the second verification will be discarded and marked in the database.

[0024] As a preferred embodiment of the intelligent operation and maintenance management method for distributed energy equipment based on cloud-edge fusion described in this invention, the further identification includes: if the further identification result is still partially successful and partially unidentified, the information is imported into the second analysis and judgment module, and the identification operation is repeated until all the mandatory information in the equipment ledger is successfully identified and the previously unidentified mandatory information in the equipment ledger is successfully added or the mandatory information in the equipment ledger is determined to need to be discarded.

[0025] If all required field information in the equipment ledger is not recognized, the required field information is transcribed to the third analysis and judgment module. The source text of the required field information is also synchronized to the third analysis and judgment module. The third analysis and judgment module traces the source of the required field information. After confirming the source, it retrieves the source text of the required field information from the source and obtains new required field information through translation. The new required field information is compared with the transcribed required field information. The logic unit of the third analysis and judgment module determines the reason for the failure to recognize all required field information. Based on the reason for the failure, the information is corrected. After successful correction, the corrected information is imported into the first analysis and judgment module. The first analysis and judgment module then performs the next operation on the corrected required field information.

[0026] The comparison includes, if the reason for the failure to identify cannot be determined after comparison, locking the source text of the mandatory field information of the equipment ledger and the information source transmission channel of the mandatory field information of the equipment ledger to respond to the operation, transferring the information abnormality to manual identification, and waiting for the issuance of subsequent operation instructions.

[0027] As a preferred embodiment of the intelligent operation and maintenance management method for distributed energy equipment based on cloud-edge fusion described in this invention, the correction includes: if the mandatory field information of the equipment ledger cannot be corrected according to the reason for failure or the correction is unsuccessful, the reason for failure of the mandatory field information of the equipment ledger, the mandatory field information of the equipment ledger to be corrected, the source text of the mandatory field information of the equipment ledger to be corrected, and the reason for correction failure are uploaded to the first analysis and judgment module or the second analysis and judgment module, which will then perform further correction. If the correction is still unsuccessful, the third analysis and judgment module will trace back and re-acquire the mandatory field information of the equipment ledger and the source text of the mandatory field information of the equipment ledger, and repeat the relevant response operation for all unidentified mandatory field information of the equipment ledger.

[0028] If the correction is successful, the third analysis and judgment module will perform further identification of the mandatory information in the equipment ledger. If the second identification is successful, the identified information will be confirmed by combining the nameplate and product manual of the distributed energy equipment.

[0029] If the second identification result is partially successful and partially unsuccessful, then import it into the second analysis and judgment module to repeat the identification operation until all the mandatory information in the equipment ledger is successfully identified and the previously unsuccessful mandatory information in the equipment ledger is successfully added or it is determined that the mandatory information in the equipment ledger needs to be discarded.

[0030] If the secondary identification result is all unidentified, the logic unit of the third analysis and judgment module will determine whether manual intervention is required. If not, the relevant response operation for all unidentified information in the required fields of the equipment ledger will be repeated. If it is required, the system will wait for the manual intervention instruction to be issued.

[0031] As a preferred embodiment of the intelligent operation and maintenance management method for distributed energy equipment based on cloud-edge fusion described in this invention, the method of combining the edge terminal for equipment identification and scanning further includes, after confirming that the mandatory information in the equipment ledger and the model parameter information are correct, creating a local model, and after the model is created, compiling and encrypting the equipment registration information and sending it to the cloud interface.

[0032] The scanning includes the cloud application platform decoding and compiling device registration information and adding the device to the cloud database;

[0033] The collection and storage refers to the configuration of rules for collecting operating data from distributed energy devices. Configuration items include the type of electrical quantity to be collected, the collection frequency, and the local storage duration.

[0034] The above-upload rule configuration refers to configuring the rules for uploading the operation data of distributed energy devices. The configuration items include the upload path, data sampling frequency, and upload frequency.

[0035] As a preferred embodiment of the intelligent operation and maintenance management method for distributed energy devices based on cloud-edge fusion described in this invention, the business application refers to the remote operation of the distributed energy device management application, including remote downloading, installation, configuration, update, uninstallation, startup, stop, and restart of the business application.

[0036] As a preferred embodiment of the intelligent operation and maintenance management method for distributed energy devices based on cloud-edge fusion described in this invention, the sending and receiving of control commands refers to remote control of distributed energy devices, including sending control commands from the cloud, and receiving and sending the control commands to the distributed energy devices for execution at the edge.

[0037] The beneficial effects of this invention are as follows: This invention meets the large-scale grid connection needs of distributed energy resources, providing reliable and accurate basic power grid data resources and model services for applications such as distributed energy operation monitoring and distributed energy consumption analysis. It enables standardized access for edge nodes of different distributed resource types, solving problems such as the large workload caused by the large number of distributed resource edge nodes, diverse equipment types, and inconsistent data structures. Simultaneously, this invention enables remote maintenance of distributed energy equipment without the need for additional complex debugging and configuration, and without the need for significant investment of manpower and resources. This improves the effectiveness and convenience of monitoring and controlling the operation of distributed energy equipment, allowing for unified management and remote operation and maintenance in the cloud, and facilitating flexible expansion of the power grid's business functions for distributed new energy sources. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0039] Figure 1 This is a schematic diagram of a method for intelligent operation and maintenance management of distributed energy equipment based on cloud-edge convergence, provided as an embodiment of the present invention.

[0040] Figure 2 This is a schematic diagram of a method for intelligent operation and maintenance management of distributed energy devices based on cloud-edge fusion, provided as another embodiment of the present invention. Detailed Implementation

[0041] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0042] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0043] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0044] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0045] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0046] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0047] Example 1

[0048] Reference Figure 1 This is the first embodiment of the present invention, which provides a method for intelligent operation and maintenance management of distributed energy devices based on cloud-edge convergence, including:

[0049] S1: Establish a general-purpose model dictionary for massive distributed energy devices and pre-configure it simultaneously in the cloud and at the edge.

[0050] Furthermore, the unified preset includes standardizing the data structure of distributed energy devices and defining the main attributes of each type of device.

[0051] It should be noted that the general model dictionary also includes a general model dictionary that is synchronously configured on the cloud application platform and the edge smart terminal. Updating the dictionary satisfies forward adaptation and does not affect previous versions.

[0052] It should also be noted that the synchronization includes the synchronized configuration of the general model dictionary on the cloud application platform and the edge smart terminal. The updated dictionary satisfies forward adaptation, and subsequent additions to device attributes or changes to attribute configurations will not affect previous versions.

[0053] Furthermore, the cloud refers to the application system used by the monitoring side, which is deployed on a cloud computing platform or monitoring master station.

[0054] Furthermore, the edge device is a smart terminal device that has local processing capabilities for edge computing, wireless communication capabilities, local acquisition and communication protocol parsing capabilities, and supports the Internet of Things MQTT protocol.

[0055] It should be noted that the communication between the cloud and the edge is secure and encrypted.

[0056] S2: Combine the edge terminal to identify and scan the device itself, enter the basic information of the device in a structured manner according to the preset template, complete the local registration, upload it to the cloud, and obtain the initial configuration table.

[0057] Furthermore, the device identification and scanning combined with the edge terminal includes wiring and powering on distributed energy devices and edge terminal smart terminal devices for self-testing, automatically confirming the device category, and autonomously querying a general model dictionary to obtain the data structure required for establishing the device ledger.

[0058] Furthermore, the identification includes verifying whether all the mandatory information in the equipment ledger has been identified. If all the mandatory information in the equipment ledger has been identified, the identified information is confirmed by combining the nameplate and product manual of the distributed energy equipment.

[0059] It should be noted that if some of the mandatory equipment ledger information is successfully identified but others are not, all mandatory equipment ledger information will be transcribed to the first analysis and judgment module. The reasons for the unsuccessful identification of the transcribed mandatory equipment ledger information will be analyzed, and the third analysis and judgment module will trace back the mandatory equipment ledger information and obtain the source text of the mandatory equipment ledger information. The obtained source text of the mandatory equipment ledger information will be imported from the third analysis and judgment module into the first analysis and judgment module. The first analysis and judgment module will verify the mandatory equipment ledger information and the source text of the mandatory equipment ledger information. If the verification is correct, the information will be corrected according to the reasons for the unsuccessful identification of some of the mandatory equipment ledger information. The corrected mandatory equipment ledger information will be further identified by the recognition units in the first analysis and judgment module. If all identification is successful, the next information confirmation operation will be performed on the identified information, and the mandatory equipment ledger information that failed to be identified on the first attempt will be supplemented.

[0060] Furthermore, the step of transcribing all mandatory equipment ledger information to the first analysis and judgment module includes the following: if the transcription of mandatory equipment ledger information fails, the second analysis and judgment module determines the reason for the transcription failure. If the transcription can be successfully completed through information correction after determining the reason for the failure, the second analysis and judgment module performs correction and transcription operations on the mandatory equipment ledger information. If the transcription cannot be successfully completed through information correction, the third analysis and judgment module performs information tracing and executes subsequent operations.

[0061] It should be noted that the verification includes, if the verification of the required field information of the equipment ledger has problems, it is determined that the information cannot be corrected. The source text of the required field information of the equipment ledger needs to be transferred to the third analysis and judgment module. The third analysis and judgment module traces the source of the information. The source text of the required field information of the equipment ledger whose source cannot be determined is imported into the database and is regarded as the passive equipment ledger required field information to await the next operation command.

[0062] Furthermore, if the source of the information can be confirmed, the mandatory information for the equipment ledger will be downloaded again from the source and verified a second time by the third analysis and judgment module. After the second verification is successful, the logic unit of the third analysis and judgment module will send the information back to the first analysis and judgment module or the second analysis and judgment module.

[0063] It should be noted that if the second verification is still unsuccessful, the required information in the equipment ledger for the failed second verification will be discarded and marked in the database.

[0064] Furthermore, the further identification includes, if the further identification result is still partially successful and partially unidentified, then the information is imported into the second analysis and judgment module, and the identification operation is repeated until all the mandatory field information of the equipment ledger is successfully identified and the previously unidentified mandatory field information of the equipment ledger is successfully added or it is determined that the mandatory field information of the equipment ledger needs to be discarded.

[0065] It should be noted that if all required field information in the equipment ledger is not recognized, the required field information is transcribed to the third analysis and judgment module. The source text of the required field information is also synchronized to the third analysis and judgment module. The third analysis and judgment module traces the source of the required field information. After confirming the source, it retrieves the source text of the required field information from the source and obtains new required field information through translation. The new required field information is compared with the transcribed required field information. The logic unit of the third analysis and judgment module determines the reason for the failure to recognize all required field information. Based on the reason for the failure, the information is corrected. After successful correction, the corrected information is imported into the first analysis and judgment module, which then performs the next operation on the corrected required field information.

[0066] Furthermore, the comparison includes, if the reason for the failure to identify cannot be determined after comparison, locking the source text of the mandatory field information of the equipment ledger and the information source transmission channel of the mandatory field information of the equipment ledger to respond to the operation, transferring the information abnormality to manual identification, and waiting for the issuance of subsequent operation instructions.

[0067] It should be noted that the correction includes, if the required field information of the equipment ledger cannot be corrected according to the reason for failure or the correction is unsuccessful, the reason for the failure of the required field information of the equipment ledger, the required field information of the equipment ledger to be corrected, the source text of the required field information of the equipment ledger to be corrected, and the reason for the correction failure are uploaded to the first analysis and judgment module or the second analysis and judgment module, which will then perform further correction. If the correction is still unsuccessful, the third analysis and judgment module will trace back and re-acquire the required field information of the equipment ledger and the source text of the required field information of the equipment ledger, and repeat the relevant response operation for all unidentified required field information of the equipment ledger.

[0068] Furthermore, if the correction is successful, the third analysis and judgment module will perform further identification of the mandatory information in the equipment ledger. If the secondary identification is successful, the identified information will be confirmed by combining the nameplate and product manual of the distributed energy equipment.

[0069] It should be noted that if the secondary recognition result is partially successful and partially unsuccessful, the recognition operation will be repeated in the second analysis and judgment module until all the mandatory information in the equipment ledger is successfully recognized and the previously unrecognized mandatory information in the equipment ledger is successfully added or the mandatory information in the equipment ledger needs to be discarded.

[0070] It should also be noted that if the secondary identification result is all unidentified, the logic unit of the third analysis and judgment module will determine whether manual intervention is required. If not, the relevant response operation for all unidentified information in the required fields of the equipment ledger will be repeated. If it is required, the system will wait for the manual intervention instruction to be issued.

[0071] Furthermore, the device identification and scanning combined with the edge terminal also includes creating a local model after confirming that the required information in the device ledger and the model parameter information are correct, and then compiling and encrypting the device registration information and sending it to the cloud interface after the model is created.

[0072] It should be noted that the scanning includes the cloud application platform decoding and compiling the device registration information and adding the device to the cloud database.

[0073] S3: Configure the rules for data collection, storage, and uploading according to the device initialization configuration table.

[0074] Furthermore, the collection and storage refers to configuring rules for collecting operating data from distributed energy devices. Configuration items include the type of electrical quantity to be collected, the collection frequency, and the local storage duration.

[0075] It should be noted that the above-upload rule configuration refers to configuring the rules for uploading the operation data of distributed energy devices. The configuration items include the upload path, data sampling frequency, and upload frequency.

[0076] S4: Based on the Internet of Things transmission protocol, it enables remote operation of business applications and the sending and receiving of control commands for energy equipment.

[0077] Furthermore, the business application refers to the remote operation of the distributed energy equipment management application, including the remote download, installation, configuration, update, uninstallation, startup, stop, and restart of the business application.

[0078] It should be noted that the sending and receiving of control commands refers to the remote control of distributed energy devices, including sending control commands from the cloud, and receiving them at the edge and sending them to the distributed energy devices for execution.

[0079] Example 2

[0080] Reference Figure 2 In another embodiment of the present invention, a method for intelligent operation and maintenance management of distributed energy equipment based on cloud-edge fusion is provided. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through experiments.

[0081] Figure 2 The specific steps and methods for realizing intelligent operation and maintenance management of distributed energy equipment based on cloud-edge convergence.

[0082] Step 1: Establish a general-purpose model dictionary for massive distributed energy devices, and pre-configure it uniformly on both the cloud and edge:

[0083] Standardize the data structure of distributed energy equipment and define the main attributes of each type of equipment. For example, firstly, distributed energy is classified into containers such as distributed photovoltaic stations, energy storage stations, charging stations, and wind power stations. Then, typical equipment within each container is defined and classified into secondary categories according to equipment type. For example, the equipment in a distributed photovoltaic station includes at least grid connection point switches, inverters, combiner boxes, and collector lines. Taking the inverter, a core equipment of distributed photovoltaic systems, as an example, the model involves ontology parameters, measurement point models, and control point models. The main attributes of the ontology parameters include the inverter's maximum DC input power, maximum DC input voltage, and maximum DC input current. The main attributes of the measurement points include the inverter's DC start-up voltage, inverter operating status, inverter DC input power, inverter DC input voltage, inverter DC input current, inverter output power, inverter output voltage, inverter output current, and inverter output voltage frequency. The main attributes of the control points include control type and command parsing protocol type.

[0084] The attribute fields for each type of device are defined in detail, including setting field type, length, and non-null requirements, defining primary key constraints, and forming a standard general-purpose model dictionary. The following table illustrates this using the inverter's intrinsic parameter model as an example:

[0085]

[0086]

[0087] The general model dictionary is configured synchronously on the cloud application platform and the edge smart terminal. The dictionary is updated to meet the requirements of forward adaptation, that is, the device attributes added later or the configuration changes made to the attributes will not affect the previous version, ensuring the consistency of the device ledger information created based on the general model dictionary. For example, when the model attributes are changed, the expansion mode should be adopted to supplement the missing attributes. If there is a need to change the type or length, the model field conversion requirements must be met.

[0088] Step 2: Combine edge computing to identify and scan the device itself, input the basic device information in a structured manner according to the preset template, complete the local registration, upload it to the cloud, and obtain the initial configuration table.

[0089] Wiring of distributed energy equipment and edge-end intelligent terminal equipment, taking distributed photovoltaic equipment inverters as an example, can be carried out by qualified personnel on site in accordance with the requirements of on-site safety construction guidelines. The high-voltage connectors and low-voltage connection lines between the edge-end intelligent terminal equipment and the photovoltaic inverter are connected one by one.

[0090] The device performs a power-on self-test and identifies the device itself, automatically confirms the device category, and autonomously queries the general model dictionary to obtain the data structure required for establishing the device ledger. For example, for inverter devices adapted to distributed photovoltaics, after being identified as inverter types, the device queries the general model dictionary to obtain the data structure of the inverter's body parameter SE_DG_GFP_B.

[0091] Verify that all required fields in the equipment ledger have been identified. Confirm the identified information by referring to the nameplate and product manual of the distributed energy equipment, and supplement any unidentified information. For example, the equipment grid connection serial number can be generated by the terminal, and the nameplate parameters can be manually supplemented.

[0092] After confirming that the model parameters are correct, create the local model. Once created, compile and encrypt the device registration information and send it to the cloud interface.

[0093] The cloud application platform decodes and compiles the device registration information and adds the device to the cloud database.

[0094] Step 3: Configure the rules for data acquisition, storage, and upload according to the device initialization configuration table:

[0095] Configure the rules for collecting operation data of distributed energy equipment. The configuration items include the type of electrical quantity to be collected, the collection frequency, and the local storage duration. For example, the electrical quantity types for data collection of distributed photovoltaic inverters include real-time power generation, voltage and current, and daily power generation. Taking the power generation as an example, the collection frequency cycle can be set to once per second, and the local storage is 30 days, which is 2,592,000 seconds.

[0096] Configure the rules for sampling and uploading operation data of distributed energy devices. The configuration items include the upload path, data sampling frequency, and upload frequency. For example, the real-time power generation sampling frequency of distributed photovoltaic inverters is one point every 5 seconds, and it is uploaded once per minute, with 12 sampling points uploaded each time.

[0097] Step 4: Relying on the Internet of Things (IoT) transmission protocol, realize remote operation of business applications and the sending and receiving of control commands for energy equipment:

[0098] Remote operation of distributed energy equipment management applications includes remote downloading, installation, configuration, updating, uninstallation, startup, shutdown, and restart of business applications. Messages are encapsulated and published using the MQTT protocol, enabling remote APP operation and control.

[0099] Remote control of distributed energy devices involves sending control commands from the cloud to the edge device, which then receives and sends the commands to the distributed energy device for execution. The process involves sending control commands from the cloud using MQTT and 104 protocols, receiving and parsing them at the edge smart terminal, converting the commands into recognizable ones for the distributed energy device, and then sending them to the device via the downlink channel to achieve remote control.

[0100] This invention is an intelligent operation and maintenance management technology for distributed energy devices based on cloud-edge convergence. It is primarily used to meet the large-scale grid connection needs of distributed energy resources and enable remote maintenance of distributed energy devices. The method first establishes a general-purpose model dictionary for a massive number of distributed energy devices, simultaneously pre-configured on both the cloud and edge. Combined with edge device identification and scanning, basic device information is structured and entered according to a pre-configured template. Local registration is completed, the data is uploaded to the cloud, and an initial configuration table is obtained. Then, based on the device initial configuration table, operational data is collected, stored, and uploaded according to the configuration rules. Relying on IoT transmission protocols, remote operation of business applications and the sending and receiving of control commands for energy devices are realized.

[0101] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

[0102] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0103] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0104] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0105] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0106] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0107] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for intelligent operation and maintenance management of distributed energy equipment based on cloud-edge convergence, characterized in that: include, Establish a general-purpose model dictionary for massive distributed energy devices and pre-configure it simultaneously in the cloud and at the edge. Combined with edge computing, the device body is identified and scanned, and the basic information of the device is entered in a structured manner according to the preset template. The local registration is completed and uploaded to the cloud to obtain the initial configuration table. Configure the rules for data collection, storage, and transmission according to the device initialization configuration table; Based on the Internet of Things (IoT) transmission protocol, remote operation of business applications and the sending and receiving of control commands for energy equipment can be realized; The unified pre-configuration includes standardizing the data structure of distributed energy devices and defining the main attributes of each type of device; The general-purpose model dictionary includes detailed definitions of attribute fields for each type of device, setting field types, lengths, non-null requirements, defining primary key constraints, and forming a standard general-purpose model dictionary; The process of combining edge devices for device identification and scanning includes connecting distributed energy devices and edge smart terminal devices and powering them on for self-testing, automatically confirming the device category, and autonomously querying a general model dictionary to obtain the data structure required for establishing the device ledger. The identification includes checking whether all the mandatory information in the equipment ledger has been identified. If all the mandatory information in the equipment ledger has been identified, the identified information is confirmed by combining the nameplate and product manual of the distributed energy equipment. If some of the mandatory equipment ledger information is successfully identified but others are not, all mandatory equipment ledger information is transcribed to the first analysis and judgment module. The reasons for the unsuccessful identification of the transcribed mandatory equipment ledger information are analyzed, and the third analysis and judgment module traces the mandatory equipment ledger information and obtains the source text of the mandatory equipment ledger information. The obtained source text of the mandatory equipment ledger information is imported from the third analysis and judgment module into the first analysis and judgment module. The first analysis and judgment module verifies the mandatory equipment ledger information and the source text of the mandatory equipment ledger information. After verification, the information is corrected based on the reasons for the unsuccessful identification of some of the mandatory equipment ledger information. The corrected mandatory equipment ledger information is further identified by the recognition units in the first analysis and judgment module. If all identification is successful, the next information confirmation operation is performed on the identified information, and the mandatory equipment ledger information that failed to be identified on the first attempt is supplemented. The step of transcribing all mandatory equipment ledger information to the first analysis and judgment module includes: if the transcription of mandatory equipment ledger information fails, the second analysis and judgment module determines the reason for the transcription failure; if the transcription can be successfully completed through information correction after the reason for failure is determined, the second analysis and judgment module performs correction and transcription operations on the mandatory equipment ledger information; if the transcription cannot be successfully completed through information correction, the third analysis and judgment module performs information tracing and executes subsequent operations. The verification includes, if the verification is of the equipment ledger mandatory information with problems, it is determined that the information cannot be corrected and the source text of the equipment ledger mandatory information needs to be transferred to the third analysis and judgment module. The third analysis and judgment module traces the source of the information and imports the source text of the equipment ledger mandatory information whose source cannot be determined into the database as passive equipment ledger mandatory information to await the next operation command. If the source of the information can be confirmed, the required information for the equipment ledger will be downloaded again from the source of the information and then checked a second time by the third analysis and judgment module. After the second check is successful, the logic unit of the third analysis and judgment module will send the information back to the first analysis and judgment module or the second analysis and judgment module. If the second verification is still unsuccessful, the required fields for the equipment ledger that failed the second verification will be discarded and marked in the database.

2. The intelligent operation and maintenance management method for distributed energy equipment based on cloud-edge fusion as described in claim 1, characterized in that: The synchronization includes the synchronized configuration of a general model dictionary on the cloud application platform and the smart terminal at the edge. The dictionary is updated to meet the requirements of forward adaptation, and subsequent additions of device attributes or changes to the configuration of attributes will not affect previous versions. The cloud refers to the application system used by the monitoring side, which is deployed on a cloud computing platform or monitoring master station. The edge device is a smart terminal device that has local processing capabilities for edge computing, wireless communication capabilities, local acquisition and communication protocol parsing capabilities, and supports the Internet of Things MQTT protocol. The communication between the cloud and the edge is secure and encrypted.

3. The intelligent operation and maintenance management method for distributed energy equipment based on cloud-edge convergence as described in claim 2, characterized in that: The further identification includes, if the further identification result is still that some identification is successful and some is not, then the information is imported into the second analysis and judgment module, and the identification operation is repeated until all the mandatory information in the equipment ledger is successfully identified and the previously unidentified mandatory information in the equipment ledger is successfully added or the mandatory information in the equipment ledger is determined to be discarded. If all required field information in the equipment ledger is not recognized, the required field information is transcribed to the third analysis and judgment module. The source text of the required field information is also synchronized to the third analysis and judgment module. The third analysis and judgment module traces the source of the required field information. After confirming the source, it retrieves the source text of the required field information from the source and obtains new required field information through translation. The new required field information is compared with the transcribed required field information. The logic unit of the third analysis and judgment module determines the reason for the failure to recognize all required field information. Based on the reason for the failure, the information is corrected. After successful correction, the corrected information is imported into the first analysis and judgment module. The first analysis and judgment module then performs the next operation on the corrected required field information. The comparison includes, if the reason for the failure to identify cannot be determined after comparison, locking the source text of the mandatory field information of the equipment ledger and the information source transmission channel of the mandatory field information of the equipment ledger to respond to the operation, transferring the information abnormality to manual identification, and waiting for the issuance of subsequent operation instructions.

4. The intelligent operation and maintenance management method for distributed energy equipment based on cloud-edge convergence as described in claim 3, characterized in that: The correction includes, if the required field information of the equipment ledger cannot be corrected according to the reason for failure or the correction is unsuccessful, the reason for the failure of the required field information of the equipment ledger, the required field information of the equipment ledger to be corrected, the source text of the required field information of the equipment ledger to be corrected, and the reason for the correction failure are uploaded to the first analysis and judgment module or the second analysis and judgment module, which will then perform further correction. If the correction is still unsuccessful, the third analysis and judgment module will trace back and re-acquire the required field information of the equipment ledger and the source text of the required field information of the equipment ledger, and repeat the relevant response operation for all unidentified required field information of the equipment ledger. If the correction is successful, the third analysis and judgment module will perform further identification of the mandatory information in the equipment ledger. If the second identification is successful, the identified information will be confirmed by combining the nameplate and product manual of the distributed energy equipment. If the second identification result is partially successful and partially unsuccessful, then import it into the second analysis and judgment module to repeat the identification operation until all the mandatory information in the equipment ledger is successfully identified and the previously unsuccessful mandatory information in the equipment ledger is successfully added or it is determined that the mandatory information in the equipment ledger needs to be discarded. If the secondary identification result is all unidentified, the logic unit of the third analysis and judgment module will determine whether manual intervention is required. If not, the relevant response operation for all unidentified information in the required fields of the equipment ledger will be repeated. If it is required, the system will wait for the manual intervention instruction to be issued.

5. The intelligent operation and maintenance management method for distributed energy equipment based on cloud-edge convergence as described in claim 4, characterized in that: The method of combining edge devices for device identification and scanning also includes creating a local model after confirming that the required information in the device ledger and the model parameter information are correct, and then compiling and encrypting the device registration information and sending it to the cloud interface after the model is created. The scanning includes the cloud application platform decoding and compiling device registration information and adding the device to the cloud database; The collection and storage refers to configuring the rules for collecting operating data from distributed energy devices. The configuration items include the type of electrical quantity to be collected, the collection frequency, and the local storage duration. The above-upload rule configuration refers to configuring the rules for uploading the operation data of distributed energy devices. The configuration items include the upload path, data sampling frequency, and upload frequency.

6. The intelligent operation and maintenance management method for distributed energy equipment based on cloud-edge convergence as described in claim 5, characterized in that: The business application refers to the remote operation of the distributed energy equipment management application, including the remote download, installation, configuration, update, uninstallation, start, stop, and restart of the business application.

7. The intelligent operation and maintenance management method for distributed energy equipment based on cloud-edge convergence as described in claim 6, characterized in that: The sending and receiving of control commands refers to the remote control of distributed energy devices, including sending control commands from the cloud, receiving them at the edge, and sending them back to the distributed energy devices for execution.

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