An Internet of Things edge management platform for a substation

Abstract

An Internet of Things (IoT) edge management platform for a substation, comprising an edge IoT agent module and an intelligent operation and maintenance business application module. The device access layer of the edge IoT agent module realizes data interaction of various devices and modules through various IoT protocols and specifications; the core service layer provides basic services for the entire module, the support service layer provides module support services, and at the same time, as the API access layer through cloud-edge collaboration services, provides API access services for applications, the IoT management platform, and the intelligent operation and inspection control platform; the intelligent operation and maintenance business application module deeply organizes and analyzes various data accessed by the edge IoT agent module to achieve panoramic perception of device status, intelligent identification of device faults, intelligent early warning of device defects, intelligent linkage of main and auxiliary devices, intelligent inspection, and operation and maintenance management. The advantages of the present invention are: realizing the collection of all business data of substation operation and inspection, and improving the digital and intelligent levels of substation operation and maintenance.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent operation and maintenance of substations, and more specifically to an Internet of Things edge management platform at the substation terminal. Background Art

[0002] Among the six links of power generation, power transmission, power transformation, power distribution, power consumption and dispatching in the smart grid, the core of the power transformation part is the construction of intelligent substations. As an important node of the smart grid, intelligent substations are the continuation and development of digital substations. The main features of intelligent substations are "intelligent primary equipment, digitalized substation-wide information, standardized information sharing, and interactive advanced applications". On this basis, a series of standards and specifications such as the "Technical Guidelines for Intelligent Substations" and the "Technical Specifications for Substation Intelligent Transformation" issued by the State Grid Corporation aim to achieve intensive hardware, integrated functions, general interchangeability and controllable performance in intelligent substations. At present, the substation control layer auxiliary systems in substations include on-line monitoring systems and intelligent auxiliary systems. The on-line monitoring devices of main equipment and intelligent auxiliary control devices are respectively connected to the corresponding terminal systems to realize the monitoring of equipment status and the monitoring function of auxiliary equipment. In addition, in recent years, the State Grid has also piloted the deployment of on-line inspection systems to replace manual labor with machines and reduce the work intensity of operating personnel.

[0003] For example, the patent document with the application number 201310519518.1 discloses a structure of an integrated intelligent substation information platform, including a Zone I data server, a Zone II integrated application server, a forward isolation device, a Zone III data modeling and data processing device, and a master station server. It also includes an SDCD-2000 substation data acquisition terminal as a point-to-point data receiving device for the forward isolation device. The forward isolation device is interconnected with the integrated data application server in Zone II and the SDCD-2000 substation data acquisition terminal in Zone III to form a data transmission channel through the isolation device; the basic data is summarized at the SDCD-2000 substation data acquisition terminal, and the data is processed once through data identification, data classification, data modeling, etc., and a DBLink data channel is established with the master station end to upload the data to the master station database regularly. The data of each substation is uniformly collected by the SDCD-2000 terminal and uploaded to the master station, effectively reducing redundant access and alleviating the access pressure on the substation data server.

[0004] At the present stage, certain achievements have been made in the goals achieved by intelligent substations, but there is still room for further improvement.

[0005] In terms of the online monitoring system, there are two problems with the traditional online monitoring system. First, the deployment of front-end sensing devices is incomplete. In conventional stations, only monitoring devices such as oil chromatographs, iron cores, and lightning arresters are deployed, lacking the application of multi-dimensional monitoring data and corresponding monitoring means (such as equipment sound pattern data and heating conditions that are obvious under abnormal working conditions), so that some status information cannot be collected. Second, the collected data lacks advanced analysis functions and fails to conduct comprehensive analysis by correlating integrated automation information and other online monitoring data, resulting in low data utilization rate and only being able to issue out-of-limit alarms for single status quantities, which is not conducive to the operation personnel to comprehensively grasp the equipment operation status.

[0006] In terms of the intelligent auxiliary system and the remote inspection system, the functions of the traditional intelligent auxiliary system and the remote online intelligent inspection system are relatively complete. However, the intelligent auxiliary system is deployed in Zone II, and the remote online intelligent inspection system is deployed in Zone IV. In some cases, it is difficult to link the auxiliary control equipment with the abnormal defects found by the video camera, resulting in serious data "island" problems and difficult to achieve data integration between the two systems, failing to make full use of existing resources and causing a certain degree of resource waste.

[0007] The independent operation of the monitoring system in Zone I, the auxiliary control system in Zone II, and the inspection system in Zone IV also has the following deficiencies for the operation personnel: When the operation personnel routinely view data, they need to switch between different systems. The equipment status data is significantly fragmented, and the data existing in different systems has no secondary processing and analysis capabilities, and can only rely on the experience of the operation personnel to judge. The accumulation of a large amount of invalid data further increases the workload of the operation personnel, which is not conducive to clearly understanding the current status of the equipment.

[0008] Currently, the Equipment Department of the State Grid is actively promoting the top-level design of the new generation of equipment intelligent control system and the centralized control station, proposing unified collection of primary and secondary information, on-site intelligent judgment, and classifying and sending the judgment results to the centralized control station as needed to achieve black screen monitoring and remote centralized control.

[0009] The patent document with the application number 202010463062.1 discloses a method for accessing perception terminal information, which includes the following steps: An edge Internet of Things gateway is used to receive real-time data of various substation perception terminals in an energy storage monitoring system and a data center monitoring system, generate an instantiated file from the real-time data, and send the instantiated file to a data communication network gateway; The data communication network gateway is used to establish a service for monitoring services according to the received instantiated file; A client that follows the general service protocol of the power system is deployed on the front-end machine of the dispatching master station to generate a model and a data access interface corresponding to the substation side, and obtain data by accessing the service of the substation server; And based on the general service protocol of the power system, a remote service communication system is established to realize the plug-and-play of data between the main plant stations. The present invention provides a method for accessing the information of "three stations in one" substations and perception terminals, which solves the problem of difficult monitoring caused by a large number of access devices, security zone isolation restrictions, and complex uplink information in the "three stations in one" mode, and improves the remote monitoring level of equipment and the emergency handling ability of power grid accidents. This document solves the problem of accessing perception terminal information, but does not realize the real-time remote centralized control of substation equipment.

[0010] The patent document with the application number 202110998325.3 applied by the present applicant discloses a bionic substation based on digitalization and intelligence, including an integrated operation and maintenance management and control platform. The integrated operation and maintenance management and control platform includes business applications, an NARI-AI algorithm application unit, and data collection. The business applications include edge business applications and edge IoT agents. The edge business applications include intelligent inspection, alarm setting, operation and maintenance management, personnel management, comprehensive monitoring, and permission management. The edge IoT agents include edge analysis, cloud-edge collaboration, protocol adaptation, security authentication, resource monitoring, and container management. This patent discloses the idea of an overall substation, but does not give the implementation method of specific business applications. Summary of the Invention

[0011] The technical problem to be solved by the present invention is how to solve the problems of inability to perform real-time remote centralized control and low intelligent level of existing substations.

[0012] The present invention realizes the solution of the above technical problems through the following technical means: An IoT edge management platform for a substation includes: an edge IoT agent module and an intelligent operation and maintenance business application module. The edge IoT agent module is divided into three layers: a device access layer, a core service layer, and a support service layer, and also includes a security service unit and a system service unit as supports;

[0013] Among them:

[0014] The device access layer realizes the data interaction between various devices and the edge IoT agent module of the substation IoT edge management platform through various IoT protocols and specifications;

[0015] The core service layer provides basic services for the edge IoT agent module of the entire substation IoT edge management platform, including a discovery and registration unit, a device model management unit, a security authentication unit, a container engine unit, a metadata management unit, a control service unit, and a device data unit, and provides corresponding basic services. Among them, the discovery and registration unit provides the configuration required for microservice startup, the device model management unit provides device model management functions, the security authentication unit has the functions of trusted computing, protecting the confidentiality and integrity of stored data, the container engine unit uses container technology to provide a consistent operating environment and an isolation mechanism for each application, the metadata management unit obtains and stores relevant information of the device when the sub-device is accessed, the control service unit is used to develop and encapsulate the common service modules such as the message bus, time service, log, and process monitoring, and control the common services, and the device data unit stores device data locally and provides information for data interaction with other units through protocols;

[0016] The support service layer provides support services for the edge IoT agent module. At the same time, as the API access layer through the cloud-edge collaboration service, it provides API access services for applications, the IoT management platform, and the intelligent operation and maintenance control platform;

[0017] The intelligent operation and maintenance business application module deeply sorts and analyzes various data accessed by the edge IoT agent module to realize panoramic perception of device status, intelligent identification of device faults, intelligent early warning of device defects, intelligent linkage of main and auxiliary devices, intelligent inspection, and operation and maintenance management.

[0018] As a further optimized technical solution, the device access layer, as a data aggregation center, has an IoT protocol adaptation module that provides flexible external interfaces, including accessing sensor data, aggregation node data, and video data using any one or more of the IEC 104, IEC 61850, rtsp, and MQTT protocols; accessing inspection robots using a protocol that meets the interface requirements.

[0019] As a further optimized technical solution, the specific external interface method of the device access layer is as follows:

[0020] 1) The online monitoring inventory system accesses the aggregation node through a wired network and then accesses the edge IoT agent module, which is compatible with the IEC61850, IEC104, manufacturer SDK, and MQTT access specifications;

[0021] 2) The on-line monitoring devices of main equipment such as partial discharge of transformers, partial discharge of GIS, mechanical characteristics of GIS, and temperature measurement of switch cabinets are connected to the acquisition terminal by means of Wifi and ZigBee. The acquisition terminal communicates with the aggregation node through IEC 104 and IEC 61850 protocols, and then accesses the edge Internet of Things proxy module through IEC 104 and IEC 61850 protocols;

[0022] 3) The environmental perception terminals for security, micro-meteorology, lighting, temperature and humidity monitoring are connected to the on-site environment unit by RS485 wiring method, and then communicate with the edge Internet of Things proxy module through IEC 104 and IEC 61850 protocols;

[0023] 4) High-definition cameras and infrared camera devices are connected to the video aggregation node by wired network, and then access the edge Internet of Things proxy module by wired network;

[0024] 5) The inspection robot is connected to the robot aggregation node through Wifi via a micro safety platform device, and the indoor robot is connected to the robot aggregation node through a network port, and then accesses the edge Internet of Things proxy module through IEC 104 and IEC 61850 protocols;

[0025] 6) An https or MQTT protocol is used to establish a data upload interface to upload data to the upper-level platform.

[0026] As a further optimized technical solution, the device model management unit of the core service layer is used to describe device attributes, services, and event information. Among them,

[0027] ① Set the device model attribute information, including attribute ID, attribute name, attribute type, and data format information;

[0028] ② Set the device model service information, including service ID, service name, call method, call method, input parameter information, and output parameter information;

[0029] ③ Set the device model event information, including event ID, event name, event keyword, and output parameter information;

[0030] The data accessed by the edge Internet of Things proxy module is converted into the corresponding device model data format for storage.

[0031] As a further optimized technical solution, the security authentication unit of the core service layer is divided into two aspects: secure call of edge services and secure transmission of device data;

[0032] The secure invocation of edge services mainly authenticates the invoker when invoking the interface of the edge IoT agent module. Its main processes include authorization management, access authorization, and information encryption. Authorization management refers to configuring the users who can access the service interface of the edge IoT agent module and the verification method. Access authorization and information encryption mean that when the invoker calls the internal interface of the edge IoT agent module, an authentication token is obtained through parameters such as passwords or keys, and the service interface of the edge IoT agent module is accessed through the token. The edge IoT agent module verifies the validity of the token when the user accesses it.

[0033] The secure transmission of device data controls the security of the accessed data by configuring and managing the device, as well as setting the device object model and device access. When the data is uploaded to the edge IoT agent module, the national cryptography algorithm can be used for data decryption.

[0034] As a further optimized technical solution, the support service layer includes a resource monitoring unit, a cloud-edge collaboration unit, an alarm notification unit, a client registration unit, an edge analysis unit, a rule engine unit, a log service unit, and a stream processing unit;

[0035] The resource monitoring unit provides process monitoring services;

[0036] The cloud-edge collaboration unit monitors and obtains the operating system model, version, architecture, cpu parameters, memory parameters, disk, and network information of the edge IoT agent module; obtains the CPU load, memory usage, and disk usage information during the operation of the edge IoT agent module; obtains the device function exception information of the operating system and the edge IoT agent module;

[0037] The alarm notification unit processes the alarm tasks of the entire platform and real-time notifies each system in the platform of the alarm messages through the message bus;

[0038] The client registration unit allows the client to register as a data receiver and filters the transferred data as needed;

[0039] The edge analysis unit has edge computing and analysis capabilities, is equipped with a variety of image recognition algorithms and data analysis algorithms, provides algorithm call interfaces, identifies the incoming data, and returns the recognition results;

[0040] The rule engine unit provides a message bus service and sends or receives messages through the message bus;

[0041] The log service unit provides log services;

[0042] The stream processing unit completes the acquisition, caching, scheduling, and transmission and playback of streaming media data.

[0043] As a further optimized technical solution, the intelligent operation and maintenance business application module is divided into a comprehensive monitoring unit, an autonomous inspection unit, a judgment and early warning unit, and an auxiliary decision-making unit;

[0044] The comprehensive monitoring unit is used to achieve comprehensive monitoring of multiple services through one system;

[0045] The autonomous inspection unit combines in-station automatic inspections with multi-source data from inspection robots, video monitoring, infrared thermal imaging temperature measurement, and on-line monitoring systems to complement each other and achieve coverage of most equipment inspection points in the station;

[0046] The judgment and early warning unit conducts hierarchical and classified early warnings on the equipment operation status and production safety environment through the over-limit early warning of a single status quantity and the comprehensive judgment of multiple status quantities;

[0047] The auxiliary decision-making unit establishes a fault intelligent analysis model and an intelligent decision-making database to achieve rapid matching of fault information with the intelligent decision-making database.

[0048] As a further optimized technical solution, the comprehensive monitoring unit accesses high-definition videos, inspection robots, infrared temperature measurement, on-line monitoring of various equipment, access control, and environmental service data, independently monitors the area information, status, and operation information of the in-station main equipment on-line monitoring system, independently monitors the monitoring information of auxiliary equipment such as fire protection, security, and environment, independently monitors visible light and infrared video data, independently monitors the running sound pattern information of the main equipment, and integrates all business data of substation operation and maintenance.

[0049] As a further optimized technical solution, the autonomous inspection unit customizes the configuration of the plan according to the plan type, carries out inspection tasks according to different execution methods configured in the plan, the inspection tasks are issued through the task scheduling service, conducts data interaction with robots, sound patterns, videos, and infrared services, automatically generates inspection results through comprehensive judgment and comparative analysis of the inspection tasks and the data interaction result data, and at the same time, the inspection results are judged by the logical threshold through the preset diagnosis rules, the abnormal results are actively pushed for alarm, the inspection results are reviewed and the abnormal point positions are tracked after confirmation to generate abnormal point inspection tasks. At the same time, the results obtained from the inspection tasks can form an inspection result report.

[0050] As a further optimized technical solution, the specific process of the judgment and early warning unit is as follows:

[0051] 1) Integrate on-line monitoring data, test data, operation data, historical maintenance data, and twin model simulation data of substation equipment, and extract characteristic parameters representing the equipment status as the input for comprehensive status analysis;

[0052] 2) Evaluate the current health status of the transformer based on the state characteristic quantities of the power transformation equipment. When the state evaluation result is normal, the entire analysis process is completed. If the state evaluation result is abnormal, a more in-depth analysis is carried out;

[0053] 3) When the equipment is in an abnormal state, carry out fault diagnosis work. If the diagnosis result shows that there is a fault in the transformer, use intelligent algorithms to determine the fault type and cause. If the diagnosis result shows that there is no obvious fault in the equipment, carry out state characteristic parameter prediction and fault warning work;

[0054] 4) Prediction and warning: Analyze the health status of the equipment at future times and the fault development trend of the faulty equipment. According to the state evaluation and warning results, determine the proposed tests, maintenance contents, maintenance time, and maintenance category contents, and consider the influence of external factors to give suggestions for the maintenance plan.

[0055] The advantages of the present invention are as follows: The present invention generally takes exploring "intelligent operation and maintenance" as the core, strengthens the deployment of intelligent perception terminals, constructs a "substation Internet of Things edge management platform" at the station end, realizes the collection of all operation and maintenance data of substation integrated automation, online monitoring, auxiliary, fire protection, video, robots, etc., applies artificial intelligence technology, realizes on-site data analysis and black screen monitoring, and at the same time meets the requirements of remote centralized control, achieves the efficient operation and maintenance goals of "intelligent inspection, intelligent linkage, intelligent warning, and intelligent decision-making", transforms from on-site manual operation and maintenance to remote background digital operation and maintenance, improves the digital and intelligent level of substation operation and maintenance, and improves the quality and efficiency of operation and maintenance work. Brief Description of the Drawings

[0056] Figure 1 It is a schematic diagram of the system architecture of an Internet of Things edge management platform for a substation proposed by the present invention;

[0057] Figure 2 It is a schematic diagram of the architecture of the edge Internet of Things agent module proposed by the present invention;

[0058] Figure 3 It is a schematic diagram of the system architecture of the intelligent operation and maintenance service application module proposed by the present invention;

[0059] Figure 4 It is the specific flowchart of the comprehensive monitoring unit of the intelligent operation and maintenance service application module proposed by the present invention;

[0060] Figure 5 It is the specific flowchart of the autonomous inspection unit of the intelligent operation and maintenance service application module proposed by the present invention;

[0061] Figure 6 It is the specific flowchart of the analysis and warning unit of the intelligent operation and maintenance service application module proposed by the present invention;

[0062] Figure 7Flow chart of data trend analysis and processing for the judgment and early warning unit of the intelligent operation and maintenance business application module proposed by the present invention;

[0063] Figure 8 Flow chart of multi-source data fusion analysis for the judgment and early warning unit of the intelligent operation and maintenance business application module proposed by the present invention;

[0064] Figure 9 Specific flow chart of the auxiliary decision-making unit of the intelligent operation and maintenance business application module proposed by the present invention;

[0065] Figure 10 Flow chart of a specific application of the auxiliary decision-making unit of the intelligent operation and maintenance business application module proposed by the present invention. Detailed implementation manners

[0066] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0067] The present invention is positioned as a set of substation edge proxy nodes at the station end, which is an important part of the distributed centralized control station and intelligent IoT system. As the station-end node of the substation centralized control station and digital overall architecture, the platform provides information support for the centralized control station and the provincial edge IoT management platform. The platform plans communication interfaces with the municipal centralized control station and the provincial "IoT management platform".

[0068] See Figures 1 to 3 , Figure 1 is a schematic diagram of the system architecture of the IoT edge management platform for a substation proposed by the present invention; Figure 2 is a schematic diagram of the architecture of the edge IoT proxy module proposed by the present invention; Figure 3 is a schematic diagram of the architecture of the business application system proposed by the present invention.

[0069] As Figure 1 shown, an IoT edge management platform for a substation includes:

[0070] The edge IoT proxy module, based on software-defined terminals and container technology, completes the aggregation access, edge processing, and forwarding and uploading of multi-class system data in the station through technical means such as communication protocol adaptation, unified data model, and security control, and solves the unified access, data sharing, and service collaboration of intelligent terminals and sensing terminals;

[0071] The intelligent operation and maintenance business application module conducts in-depth sorting and analysis based on various types of data accessed by the edge IoT agent module, realizing panoramic perception of device status, intelligent identification of device failures, intelligent early warning of device defects, intelligent linkage of main and auxiliary devices, intelligent inspection, operation and maintenance management, and three-dimensional panoramic visualization, etc., so as to promote autonomous inspection of devices, on-site judgment of status, proactive early warning of risks, and auxiliary decision-making in management.

[0072] As Figure 2 shown, the edge IoT agent module is divided into three layers: the device access layer, the core service layer, and the support service layer. At the same time, there are also a security service unit and a system service unit as supports.

[0073] The device access layer realizes data interaction between various devices and the edge IoT agent module of the substation IoT edge management platform through various IoT protocols and specifications.

[0074] The core service layer, as the core of the edge IoT agent module of the substation IoT edge management platform, provides basic services for the edge IoT agent module of the entire substation IoT edge management platform by receiving, processing, and forwarding device data, using metadata management, and discovering and registering devices, etc.

[0075] The support service layer provides support services for the edge IoT agent module of the substation IoT edge management platform, such as logs, alarms, rule engines, stream processing, etc. At the same time, through the cloud-edge collaboration service as the access layer of the northbound API, it provides API access services for applications, IoT management platforms, and intelligent operation and maintenance control platforms.

[0076] Furthermore, the device access layer, as a data aggregation center, has an IoT protocol adaptation module, providing flexible external interfaces. It includes accessing sensor data, aggregation node data, and video data using multiple types of protocols such as IEC 104, IEC 61850, rtsp, and MQTT; accessing inspection robots using an interface that meets the protocol of "Technical Requirements for Substation Intelligent Robot Inspection System in the Pilot Project of Smart Substations (Trial)".

[0077] 1) The online monitoring inventory system accesses the aggregation node through a wired network method and then accesses the edge IoT agent module, being compatible with multiple access specifications such as IEC61850, IEC104, manufacturer SDK, and MQTT.

[0078] 2) New types of on-line monitoring devices for main equipment such as transformer partial discharge, GIS partial discharge, GIS mechanical characteristics, and switch cabinet temperature measurement are connected to the acquisition terminal by means of Wifi and ZigBee. The acquisition terminal communicates with the aggregation node through protocols such as IEC 104 and IEC 61850, and then accesses the edge IoT agent module through protocols such as IEC 104 and IEC 61850.

[0079] 3) Environmental perception terminals such as security, micro-meteorology, lighting, temperature and humidity monitoring are connected to the on-site environment unit by RS485 wiring, and then communicate with the edge IoT agent module through protocols such as IEC 104 and IEC 61850.

[0080] 4) High-definition cameras and infrared camera devices are connected to the video aggregation node by wired network, and then connected to the edge IoT agent module by wired network.

[0081] 5) The inspection robot is connected to the robot aggregation node through Wifi via a micro security platform device, and the indoor robot is connected to the robot aggregation node through a network port, and then connected to the edge IoT agent module through protocols such as IEC 104 and IEC 61850.

[0082] 6) An https or MQTT protocol is used to establish a data upload interface, and data can be uploaded to superior platforms such as the centralized control station system, provincial IoT platform, and data middle platform.

[0083] Furthermore, the core service layer includes a discovery and registration unit, a device model management unit, a security authentication unit, a container engine unit, a metadata management unit, a control service unit, a device data unit, etc., which provide corresponding basic services.

[0084] Among them:

[0085] The discovery and registration unit provides the configurations required for microservice startup, such as port numbers. When each microservice starts, it registers its own information to this unit. When the configuration changes, this unit will notify the corresponding microservice in a timely manner, and the configuration information will overwrite the built-in configuration information of the microservice, which can support dynamic environment switching to meet the dynamic expansion requirements of the microservice architecture. When the configuration registration microservice is unavailable, the microservice can start using its own embedded configuration without this unit.

[0086] The device model management unit provides device model management functions for describing information such as device attributes, services, events, etc., and can create, import, delete, modify, and view product models. Among them,

[0087] ① Set the device model attribute information, including attribute ID, attribute name, attribute type, data format, etc.

[0088] ② Set the device model service information, including service ID, service name, call method, call method, input parameter information, output parameter information.

[0089] ③ Set the device model event information, including event ID, event name, event keyword, output parameter information.

[0090] The data accessed by the edge IoT agent module can be converted into the data format that conforms to the corresponding device model for storage.

[0091] The security authentication unit has the functions of trusted computing, protecting the confidentiality and integrity of stored data. In terms of security, it is mainly divided into two aspects: secure invocation of edge services and secure transmission of device data.

[0092] The secure invocation of edge services mainly authenticates the caller when invoking the interface of the edge IoT agent module. Its main processes include functions such as authorization management, access authorization, and information encryption. Authorization management refers to configuring the users who can access the service interface of the edge IoT agent module and the verification method. Access authorization and information encryption mean that when the caller invokes the internal interface of the edge IoT agent module, it obtains an authentication token through parameters such as passwords or keys, and accesses the service interface of the edge IoT agent module through the token. The edge IoT agent module verifies the validity of the token when the user accesses.

[0093] The secure transmission of device data controls the security of the accessed data by configuring and managing the devices, as well as setting the device model and device access. When the data is uploaded to the edge IoT agent module, the national cryptography algorithm can be used to decrypt the data to ensure the security of the transmitted data.

[0094] The container engine unit uses container technology to provide a consistent running environment and an isolation mechanism for each application. It can view container information, image information, system information, etc., specifically including: viewing container version information, local image information stored in the container, current running container instance information, etc.

[0095] The metadata management unit obtains and stores the relevant information of the device when the sub-device accesses. It provides the storage of the device-reported device status data, supports real-time or periodic update and collection of the status information of the sub-devices, and can effectively group and batch manage the devices by device type, device area, etc., reducing the device management cost. It provides a reporting function to facilitate users to view the device situation.

[0096] The control service unit is used to develop and encapsulate common service modules such as the message bus, time service, log, and process monitoring, and control the common services.

[0097] The device data unit stores device data locally and provides information for data interaction with other units through the REST APIs protocol.

[0098] Furthermore, the support service layer includes a resource monitoring unit, a cloud-edge collaboration unit, an alarm notification unit, a client registration unit, an edge analysis unit, a rule engine unit, a log service unit, and a stream processing unit, which provide support services for the edge IoT agent module, such as logs, alarms, rule engines, stream processing, etc. At the same time, as the access layer of the northbound API through the cloud-edge collaboration service, it provides API access services for applications, IoT management platforms, and intelligent operation and maintenance control platforms.

[0099] The resource monitoring unit provides process monitoring services, mainly monitoring each process of the platform, including monitoring the resource usage of processes, process information, etc.

[0100] The cloud-edge collaboration unit monitors and obtains information such as the operating system model, version, architecture, cpu parameters, memory parameters, disks, networks, etc. of the edge IoT agent module; obtains information such as CPU load, memory usage, disk (storage medium) usage during the operation of the edge IoT agent module; obtains abnormal information about the operating system and the device functions of the edge IoT agent module.

[0101] The alarm notification unit processes the alarm tasks of the entire platform and notifies each system in the platform of the alarm messages in real time through the message bus.

[0102] The client registration unit allows clients to register as data receivers and filter and transfer data as needed. Using local analysis services, event processors, and gateway aggregation, it provides historical data and deeper data analysis capabilities. At the same time, new requests can be created, existing requests can be updated, and requests can be deleted through the RESTAPI.

[0103] The edge analysis unit has edge computing analysis, equipped with a variety of image recognition algorithms and data analysis algorithms, including meter reading recognition, indicator light recognition, bird's nest recognition, etc. It provides algorithm call interfaces to identify the incoming data and return the recognition results. It supports list display and related control of various algorithm analysis libraries, such as enabling and disabling.

[0104] The rule engine unit provides a message bus service and can send or receive messages through the message bus.

[0105] The log service unit provides log services, supporting the writing, storage, and retrieval of the log content of other services. The log service unit includes: log insertion interfaces, log query interfaces, etc.

[0106] The stream processing unit completes the acquisition, caching, scheduling, and transmission and playback of streaming media data. It supports the forwarding of streaming media data and the forwarding of multiple audio and video coding formats. It provides the retrieval and playback functions of video recordings, supporting data retrieval and playback according to time and specified cameras.

[0107] In the embodiments of the present invention, the intelligent operation and maintenance service application module is based on various types of data such as online monitoring, auxiliary equipment, video, infrared, robot, access control, and lock control accessed by the edge Internet of Things agent module. It uses technologies such as artificial intelligence, image recognition, and algorithm analysis for in-depth sorting and analysis to achieve panoramic perception of equipment status, intelligent identification of equipment failures, intelligent early warning of equipment defects, intelligent linkage of main and auxiliary equipment, intelligent patrol, operation and maintenance management, and three-dimensional panoramic visualization, etc., to realize four functions of comprehensive monitoring, autonomous patrol, judgment and early warning, and auxiliary decision-making, and provide a man-machine interaction interface.

[0108] As Figure 3 shown, the intelligent operation and maintenance service application module is divided into a comprehensive monitoring unit, an autonomous patrol unit, a judgment and early warning unit, and an auxiliary decision-making unit. It integrates multi-dimensional data such as substation monitoring, auxiliary monitoring, on-line monitoring of primary and secondary equipment, video monitoring, infrared thermal imaging, and robot monitoring in the substation, and can realize business function applications such as panoramic perception monitoring, intelligent patrol, and operation and maintenance management of equipment. It uses artificial intelligence technology and edge computing analysis for comprehensive analysis and processing to realize the situation prediction of equipment status, intelligent early warning of equipment failures, and intelligent decision-making.

[0109] As Figure 4 shown, the comprehensive monitoring unit accesses business data such as high-definition video, patrol robots, infrared temperature measurement, on-line monitoring of various equipment, access control, and environment. It independently monitors the area information, status, and operation information of the on-line monitoring system of the main equipment in the station, independently monitors the monitoring information of auxiliary equipment such as fire protection, security, and environment, independently monitors video data such as visible light and infrared, and independently monitors the running sound pattern information of the main equipment. It integrates all business data of substation operation and maintenance, and realizes the comprehensive monitoring of multiple services through one system, solving the situation of substation operation and maintenance personnel facing various complicated systems; provides an application for the control of in-station operation and maintenance services, and improves the operation and maintenance personnel's control ability of equipment status.

[0110] The autonomous patrol unit combines multi-source data such as automatic patrol robots, video monitoring, infrared thermal imaging temperature measurement, and on-line monitoring systems in the station to complement each other, and can cover most of the equipment patrol points in the station. With the assistance of analysis means such as image recognition, it can replace the daily patrol tasks (routine patrol, comprehensive patrol, light-off patrol, special patrol, etc.). It can actively give early warning of abnormal patrol results, automatically generate reports for patrol results, and can conduct horizontal analysis on different patrol methods for the same patrol point, and can conduct vertical comparison analysis according to different phases, realizing multi-dimensional intelligent judgment and providing effective reference for operation and maintenance personnel.

[0111] As Figure 5As shown in the figure, the autonomous inspection unit can customize the configuration of the plan according to the plan type, carry out the inspection tasks according to different execution methods configured in the plan, and the inspection tasks are sent through the task scheduling service, and data interaction is carried out with the robot, voiceprint, video, and infrared services. Through comprehensive judgment and comparative analysis of the inspection tasks and the data interaction result data, the inspection results are automatically generated. At the same time, the inspection results are judged by the preset diagnostic rules for logical threshold, and the abnormal results are actively pushed for warning. After the inspection results are confirmed, they can be rechecked (manual video confirmation) and the abnormal points can be tracked, and the inspection tasks for the abnormal points can be generated. At the same time, the inspection result report can be generated for the results obtained from the inspection tasks.

[0112] The research and judgment and early warning unit conducts hierarchical and classified early warning on the equipment operation status and production safety environment through the over-limit early warning of a single state quantity and the comprehensive research and judgment of multiple state quantities. As Figure 6 The specific process is as follows:

[0113] 1) Integrate the on-line monitoring data, test data, operation data, historical maintenance data and twin model simulation data of substation equipment, and extract the characteristic parameters representing the equipment status as the input for comprehensive status analysis.

[0114] 2) Evaluate the current health status of the transformer according to the state characteristic quantities of the substation equipment. When the state evaluation result is normal, the entire analysis process is completed; if the state evaluation result is abnormal, a more in-depth analysis is carried out.

[0115] 3) When the equipment has an abnormal state, carry out fault diagnosis work. If the diagnosis result shows that there is a fault in the transformer, intelligent algorithms such as deep learning are used to determine the fault type and fault cause; if the diagnosis result shows that there is no obvious fault in the equipment, the prediction of state characteristic parameters and fault early warning work are carried out.

[0116] 4) Prediction and early warning: Analyze the health status of the equipment at future times and the fault development trend of the faulty equipment. According to the state evaluation and early warning results, determine the test, maintenance content, maintenance time, maintenance category, etc. that are recommended to be carried out, and consider the influence of external factors such as simultaneous maintenance restrictions, mutually exclusive maintenance restrictions, maintenance resources and power grid operation, and give suggestions for the maintenance plan.

[0117] As Figure 7 shown, based on the continuous monitoring of the operation status of various equipment, through means such as "daily comparison and weekly analysis", combined with monitoring data such as dissolved gases in transformer oil, core clamp current, SF6 gas pressure, and arrester monitoring, set the thresholds for different early warning stages, realize data trend analysis, and help the operation and maintenance personnel to pre-check the possible faults in advance and reduce the probability of faults occurring.

[0118] As Figure 8As shown in the figure, a multi-dimensional and multi-physical dynamic data model is established to simulate the attributes, behaviors, rules, etc. of physical entities in the real environment. The multi-parameter physical monitoring data includes data such as temperature, load status, oil chromatography, and acoustic fingerprint vibration (including historical data). Obtain the temperature value of a certain part corresponding to the on-site sensor of the transformer, the value of dissolved characteristic gases in the oil corresponding to the transformer, and the load status. Using the established multi-physical field twin model, simulate and obtain the global temperature field, load status, and distribution of dissolved gases in the oil of the equipment. Collect data through monitoring sensors and establish a fusion data analysis model based on multi-source monitoring data. Through the panoramic hierarchical perception system, collect the monitoring data of multi-parameters of the transformer, and perform fusion processing on the multi-parameter data of the multi-parameter transformer, so as to establish an accurate and efficient method for quickly detecting abnormal states and a state differential evaluation model.

[0119] As Figure 9 shown in the figure, the auxiliary decision-making unit focuses on studying the fault characteristics and treatment strategies of various equipment, establishing a fault intelligent analysis model and an intelligent decision-making library, developing fault key information screening and filtering technologies, realizing the rapid matching of fault information with the intelligent decision-making library, automatically judging the fault type, and automatically pushing the treatment strategy, so as to improve the accuracy of fault treatment and reduce the fault treatment time.

[0120] The intelligent decision-making library includes a regular decision-making library and an emergency plan decision-making library, providing decision-making basis for rapid response under different on-site conditions, thus improving the effectiveness and correctness of decision-making.

[0121] Push the fault judgment result and the fault treatment strategy to relevant personnel, which can be pushed in the form of content such as text, sound, pictures, and videos; the relevant push personnel include maintenance personnel and management personnel. The former pushes the fault judgment result and the fault treatment strategy, and the latter pushes the fault judgment result. The auxiliary decision-making unit performs real-time message pushing on decision-making information. As Figure 10 shown in the figure, perform periodic pushing on the 104 general call according to the pre-module, perform real-time pushing on the patrol task change information and periodic pushing on the patrol task progress information according to the patrol module, and perform periodic pushing on the equipment status information such as the system server, hard disk video recorder, high-definition camera, and inspection robot.

[0122] The auxiliary decision-making unit can automatically push multi-source data such as pictures, historical curves, and sounds, as well as decision-making opinions, to assist maintenance personnel in judging and disposing of equipment faults. It can automatically generate task plan reports, production reports, statistical reports, data analysis reports, etc., to assist maintenance personnel in the management and statistics of equipment.

[0123] The present invention generally focuses on exploring "intelligent operation and maintenance inspection", strengthens the deployment of intelligent perception terminals, and constructs a "substation Internet of Things edge management platform" at the station end. By accessing the integrated data of the edge Internet of Things proxy module, integrating subsystems such as in-station high-definition videos, inspection robots, infrared temperature measurement, online monitoring of various equipment, security, fire protection, access control, and environment, a unified Internet of Things model is established, the levels are streamlined, the "information islands" are broken, and the situation of maintenance personnel facing various complex systems is solved; means for controlling in-station operation and maintenance inspection services are provided, and the control ability of maintenance personnel over the equipment status is improved. At the same time, by combining multi-source data of in-station operation and maintenance inspection services, which complement each other, the replacement of daily manual inspection tasks is realized through means such as image recognition and intelligent analysis, providing a basis for multi-dimensional intelligent judgment, realizing in-situ judgment of data, and on this basis, realizing data interaction and sharing and intelligent linkage among multiple auxiliary subsystems such as online monitoring, environment monitoring, intelligent lighting control, and videos. Thus, the efficient operation and maintenance inspection goals of "intelligent inspection, intelligent linkage, intelligent early warning, and intelligent decision-making" are achieved, the on-site manual operation and maintenance are transformed into remote background digital operation and maintenance, and the digital and intelligent levels of substation operation and maintenance are improved, as well as the quality and efficiency of operation and maintenance work.

[0124] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An Internet of Things edge management platform for a substation, comprising: an edge Internet of Things agent module and an intelligent operation and maintenance business application module, characterized in that: the edge Internet of Things agent module is divided into three layers: a device access layer, a core service layer, and a support service layer, and also includes a security service unit and a system service unit as supports, wherein: The device access layer realizes data interaction between various devices and the edge Internet of Things agent module of the substation Internet of Things edge management platform through various Internet of Things protocols and specifications; The core service layer provides basic services for the edge Internet of Things agent module of the entire substation Internet of Things edge management platform, including a discovery and registration unit, a device model management unit, a security authentication unit, a container engine unit, a metadata management unit, a control service unit, and a device data unit, and provides corresponding basic services. Among them, the discovery and registration unit provides the configuration required for microservice startup, the device model management unit provides device model management functions, the security authentication unit has the functions of trusted computing, protecting the confidentiality and integrity of stored data, the container engine unit uses container technology to provide a consistent operating environment and mutual isolation mechanism for each application, the metadata management unit obtains relevant information of the device when the sub-device is accessed and stores it, the control service unit is used to develop and encapsulate the common service modules such as the message bus, time service, log, and process monitoring, and control the common services, and the device data unit stores device data locally and provides information for data interaction with other units through protocols; The support service layer provides support services for the edge Internet of Things agent module, and at the same time, as the API access layer through cloud-edge collaboration services, provides API access services for applications, the Internet of Things management platform, and the intelligent operation and inspection control platform; The intelligent operation and maintenance business application module deeply sorts and analyzes various data accessed by the edge Internet of Things agent module to achieve panoramic perception of device status, intelligent identification of device faults, intelligent early warning of device defects, intelligent linkage of main and auxiliary devices, intelligent inspection, and operation and maintenance management; The intelligent operation and maintenance business application module is divided into a comprehensive monitoring unit, an autonomous inspection unit, a research and judgment and early warning unit, and an auxiliary decision-making unit; The comprehensive monitoring unit is used to achieve comprehensive monitoring of multiple services through one system; The autonomous inspection unit combines in-station automatic inspections with multi-source data from inspection robots, video monitoring, infrared thermal imaging temperature measurement, and online monitoring systems to complement each other and achieve coverage of most device inspection points in the station; The research and judgment and early warning unit conducts hierarchical and classified early warnings on the device operation status and production safety environment through the over-limit early warning of a single status quantity and the comprehensive research and judgment of multiple status quantities; The auxiliary decision-making unit establishes an intelligent fault analysis model and an intelligent decision-making library to achieve rapid matching of fault information with the intelligent decision-making library; The comprehensive monitoring unit accesses high-definition video, inspection robots, infrared temperature measurement, online monitoring of various devices, access control, and environmental service data, independently monitors the area information, status, and operation information of the in-station main equipment online monitoring system, independently monitors the monitoring information of auxiliary equipment such as fire protection, security, and environment, independently monitors visible light and infrared video data, independently monitors the operation sound pattern information of the main equipment, and integrates all business data of substation operation and inspection; The autonomous inspection unit customizes and configures the plan according to the plan type, and carries out the inspection task according to different execution methods configured in the plan. The inspection task is sent down through the task scheduling service, and data interaction is carried out with the robot, voiceprint, video, and infrared services. Through comprehensive judgment and comparative analysis of the inspection task and the data interaction result data, the inspection result is automatically generated. At the same time, the inspection result is judged by the preset diagnosis rule for the logical threshold. The abnormal result is actively pushed for alarm. After the inspection result is confirmed, it is rechecked and the abnormal point is tracked to generate the inspection task for the abnormal point. At the same time, the result obtained from the inspection task can be formed into an inspection result report; The specific process of the judgment and early warning unit is as follows: 1) Integrate the on-line monitoring data, test data, operation data, historical maintenance data and twin model simulation data of substation equipment, and extract the characteristic parameters representing the equipment state as the input of comprehensive state analysis; 2) Evaluate the current health status of the transformer according to the state characteristic quantity of the substation equipment. When the state evaluation result is normal, the entire analysis process is completed. If the state evaluation result is abnormal, a more in-depth analysis is carried out; 3) When the equipment is in an abnormal state, carry out fault diagnosis work. If the diagnosis result shows that there is a fault in the transformer, use intelligent algorithms to determine the fault type and cause. If the diagnosis result shows that there is no obvious fault in the equipment, carry out state characteristic parameter prediction and fault early warning work; 4) Prediction and early warning: Analyze the health status of the equipment at future moments and the fault development trend of the faulty equipment. According to the state evaluation and early warning results, determine the test, maintenance content, maintenance time and maintenance category content that are recommended to be carried out, and consider the influence of external factors to give suggestions for the maintenance plan.

2. The IoT edge management platform of the substation according to claim 1, characterized in that: The equipment access layer, as a data aggregation center, has an IoT protocol adaptation module, providing flexible external interfaces, including accessing sensor data, aggregation node data and video data using any one or more of the IEC 104, IEC 61850, rtsp, and MQTT protocols; accessing the inspection robot using a protocol that meets the interface requirements.

3. The IoT edge management platform of the substation according to claim 2, characterized in that: The external interface method of the equipment access layer is specifically as follows: 1) The on-line monitoring inventory system is connected to the aggregation node through a wired network and then connected to the edge IoT agent module, which is compatible with the IEC61850, IEC104, manufacturer SDK, and MQTT access specifications; 2) The on-line monitoring equipment of the main equipment such as transformer partial discharge, GIS partial discharge, GIS mechanical characteristics, and switch cabinet temperature measurement adopts the Wifi and ZigBee methods to be connected to the acquisition terminal. The acquisition terminal communicates with the aggregation node through the IEC 104 and IEC 61850 protocols, and then is connected to the edge IoT agent module through the IEC 104 and IEC 61850 protocols; 3) The environmental perception terminals for security, micro-meteorology, lighting, temperature and humidity monitoring are connected to the on-site environment unit through the RS485 wiring method, and then communicate with the edge IoT agent module through the IEC 104 and IEC 61850 protocols; 4) The high-definition camera and infrared camera devices are connected to the video aggregation node through the wired network method, and then connected to the edge IoT agent module through the wired network method; 5) The inspection robot is connected to the robot aggregation node through Wifi via the micro security platform device, and the indoor robot is connected to the robot aggregation node through the network port, and then connected to the edge IoT agent module through the IEC 104 and IEC 61850 protocols; 6) The data upload interface is established using the https or MQTT protocol to upload data to the upper-level platform.

4. The IoT edge management platform of the substation according to claim 1, characterized in that: The device model management unit of the core service layer is used to describe device attributes, services, and event information, where, ① Set the device model attribute information, including attribute ID, attribute name, attribute type, and data format information; ② Set the device model service information, including service ID, service name, call method, call method, input parameter information, and output parameter information; ③ Set the device model event information, including event ID, event name, event keyword, and output parameter information; The data accessed by the edge IoT agent module is converted into the corresponding device model data format for storage.

5. The IoT edge management platform of the substation according to claim 1, characterized in that: The security authentication unit of the core service layer is divided into two aspects: secure call of edge services and secure transmission of device data; The secure call of edge services is to authenticate the caller when calling the interface of the edge IoT agent module. The process includes: authorization management, access authorization, and information encryption. Authorization management refers to configuring the users who can access the service interface of the edge IoT agent module and the verification method. Access authorization and information encryption mean that when the caller calls the internal interface of the edge IoT agent module, an authentication token is obtained through the password or key parameter, and the edge IoT agent module service interface is accessed through the token. The edge IoT agent module verifies the validity of the token when the user accesses; The secure transmission of device data controls the security of the accessed data by configuring and managing the device, as well as setting the device model and device access of the device. The national secret algorithm can be used to decrypt the data when the data is uploaded to the edge IoT agent module.

6. The IoT edge management platform of the substation according to claim 1, characterized in that: The support service layer includes a resource monitoring unit, a cloud-edge collaboration unit, an alarm notification unit, a client registration unit, an edge analysis unit, a rule engine unit, a log service unit, and a stream processing unit; The resource monitoring unit provides process monitoring services; The cloud-edge collaboration unit monitors and obtains the operating system model, version, architecture, cpu parameters, memory parameters, disk, and network information of the edge IoT agent module; Obtain CPU load, memory usage, and disk usage information during the operation of the edge IoT agent module; obtain operating system and device function exception information of the edge IoT agent module; The alarm notification unit processes the alarm tasks of the entire platform and notifies each system within the platform of the alarm messages in real time through the message bus; The client registration unit allows the client to register as a data receiver and filters the flowing data as needed; The edge analysis unit has edge computing analysis, is equipped with a variety of image recognition algorithms and data analysis algorithms, provides an algorithm call interface, recognizes the incoming data, and returns the recognition results; The rule engine unit provides a message bus service and sends or receives messages through the message bus; The log service unit provides log services; The stream processing unit completes the acquisition, caching, scheduling, and transmission and playback of streaming media data.

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