Method for constructing a dispatching operation data base

Abstract

The present application relates to the field of power system automation technology, in particular to a method for constructing a dispatch operation data base, and constructing a cross-dispatch mechanism, which is composed of one leading node and N collaborative nodes, two sites are deployed in different places on the same node, and high-speed synchronization of data between the two sites is realized, and the two sites are balancedly configured; information of schedulable public resources is obtained from the ubiquitous power internet of things through an interface; a data middle platform is constructed, which includes a model data platform, an operation data platform, a dispatch data exchange platform and a power grid address navigation platform; a business middle platform is constructed, which provides a service information interaction mechanism for applications in the form of interface functions, and realizes interconnection and intercommunication of wide-area services between control cloud sites; and problems such as low utilization rate of hardware resources in the field of power grid control, information islands, weak data correlation, repeated construction of applications, value discovery and the like are solved.

Description

Technical Field

[0001] This invention relates to the field of power system automation technology, and more specifically to a method for constructing a dispatch and operation data base. Background Technology

[0002] In accordance with the requirements of the State Grid's "Outline for the Construction of the Power Internet of Things," and fully utilizing advanced cloud computing technologies and concepts, a business middle platform and data middle platform (model data platform and operation data platform) will be developed for the power control field using the "IaaS, PaaS, SaaS" cloud platform model. This will create an enterprise-level shared service platform for the power control field and comprehensively build a ubiquitous Internet of Things control cloud platform software. A control technology support system based on "resource virtualization, data standardization, and application service" will be formed, providing storage, computing, and application capabilities to solve problems such as low utilization of hardware resources, information silos, weak data correlation, redundant application construction, and value discovery in the existing power grid control field. Summary of the Invention

[0003] To address the aforementioned issues, this invention proposes a method for constructing a scheduling and operation data base.

[0004] The technical solution adopted by this invention to solve its technical problem is:

[0005] This invention provides a method for constructing a scheduling and execution data foundation, including the following steps:

[0006] Building across scheduling agencies:

[0007] It consists of one master node and N cooperating nodes, with two sites deployed in different locations on the same node, achieving high-speed data synchronization between the two sites and balanced configuration between the two sites;

[0008] Information on dispatchable public resources can be obtained from the ubiquitous power Internet of Things via an interface;

[0009] A data platform is constructed, which includes a model data platform, an operational data platform, a scheduling data exchange platform, and a power grid address navigation platform.

[0010] The model data platform obtains model data parameters from surrounding business systems to form a model data center, and conducts model verification. It also provides reliable model data to the operation data platform and scheduling data exchange platform by sharing models on demand through model subscription.

[0011] The operation data platform extracts power grid operation data through access services and transforms it into an object-oriented organization based on a general structured design to form power grid operation data. It then provides power grid operation data and model data to the application layer through a service bus.

[0012] The scheduling data exchange platform facilitates interaction between the source data end, the data exchange platform, and the target data end. Data interaction is performed using Kafka message messages, and message serialization is implemented using protobuf technology, providing data access / sending capabilities.

[0013] The power grid geographic information navigation platform uses the human-computer interaction method of Internet maps to build a geographic information platform, so as to realize the automatic hierarchical and graded integrated display of power grid and environment on geographic information map;

[0014] Building a business middle platform:

[0015] The system architecture developed using SOA is used to realize the service functions of common components of the PaaS platform and to enable high-performance and transparent RPC remote service calls between applications on different sites.

[0016] It provides a service information interaction mechanism for applications in the form of interface functions, and realizes the interconnection and interoperability of wide-area services between control cloud sites;

[0017] Building a cluster of micro-applications:

[0018] The process of extracting, transforming, analyzing, and modeling large amounts of business data using data mining techniques to extract key data to support decision-making includes business understanding, indicator design, data extraction, data exploration, algorithm selection, model evaluation, model deployment, and model optimization.

[0019] The schedulable public resources include the application manager, which consists of a server and a client. The server is built in the cloud on the leading node, and the client is built in the cloud on each collaborating node.

[0020] Store application deployment packages uploaded by users through the cloud platform;

[0021] Users upload application deployment packages and list them on the control cloud platform so that subsequent users can delete or download the deployment packages;

[0022] Obtain the application deployment package and remotely deploy the application to the host;

[0023] Management access methods for the host;

[0024] When the model data in the collaborative node cloud changes, the incremental data capture method provided by the vertical data synchronization tool is used to send the changed model data to the cloud through the message middleware deployed on the master node cloud. The cloud receives the message and updates the model data in the cloud.

[0025] The collaborative node cloud can subscribe to the model data of the master node cloud. When the model in the master node cloud changes, it is automatically sent to the model data center of the collaborative node cloud.

[0026] Historical measurement data in the cloud model data center of the collaborative nodes are periodically synchronized to the cloud using a timestamp-based scanning method.

[0027] Preferably, the data platform includes a message center, which is event-driven and uses a subscription / publishing message middleware technology to realize message transmission between applications in the control cloud platform system, providing support for information transmission between internal and external applications of the control cloud system.

[0028] Preferably, it also includes building an instant messaging service module, using the network technology provided in the HTML5 standard for full-duplex communication between the client and the server, whereby the client sends a WebSocket connection request and the server responds with a connection.

[0029] Through "one-stop" chat, group chat, and file transfer, messages, notifications, and announcements from different applications and platforms are received, filtered, verified, assembled, encrypted, and stored before being pushed online or offline to third-party application clients.

[0030] Preferably, the model data platform utilizes metadata management and dictionary management to achieve modeling standardization and scheduling terminology normalization, respectively. Through the metadata management table structure, it realizes the standardized design and scalability of data objects, including standardized data objects, data object tables, data object table attributes, and dictionary objects.

[0031] Preferably, the model data platform uses a message bus to achieve vertical synchronization of model data among the source data terminal, collaborative nodes, and leading nodes in the cloud.

[0032] The source-end model synchronization client uses database triggers to periodically detect data changes, encapsulates the data based on a specific message protocol, and sends it to the message bus.

[0033] The cloud-based model synchronization server receives the data protocol packets, parses them, and then stores them in the database.

[0034] Preferably, model synchronization includes:

[0035] Model data sending module:

[0036] Capture database and image file data;

[0037] Extract data from the captured database and image files;

[0038] The extracted data is sent through the message bus;

[0039] Model data receiving module:

[0040] Receive data sent by the message bus;

[0041] Load the received data.

[0042] Preferred model subscription:

[0043] The cloud provides model subscription services, enabling monitoring, perception, analysis, processing, routing, and distribution based on content subscriptions. The source end implements full-process control over model subscription definition, monitoring, invocation, parsing, storage, and receipt.

[0044] Preferably, the operational data platform consists of two parts: a sending client and a receiving server.

[0045] Sending client: Extract relevant data from various business systems, convert the object codes into object codes that can be recognized by the control cloud, and send them to the cloud through the control cloud message bus. For running data that cannot be directly extracted by accessing the business system database, write it into the database at the control cloud source data end.

[0046] Receiving server: The data receiving and storage module is responsible for receiving various types of runtime data messages from the message bus, parsing them, and storing them in the database. The storage of runtime data is designed in accordance with the general data object structure specification.

[0047] Preferably, a business service module is built in the business middle platform, which is divided into four parts: service provider, service consumer, service registration center, and service monitoring.

[0048] The service container is responsible for starting, loading, and running the service provider;

[0049] When a service provider starts up, it registers the services it provides with the service registry.

[0050] When a service consumer starts up, it subscribes to the services it needs from the service registry. The registry then returns a list of service provider addresses to the consumer.

[0051] It also includes building a scenario-based personal cloud desktop, using SPA (Single Page Application) front-end technology, and dynamically rewriting the current page.

[0052] Preferably, it is built in a group of micro-applications:

[0053] The model topic retrieval micro-application group is used to analyze and extract the most important and frequently used information of model objects to form topic profiles, and to design typical scenarios that conform to business characteristics, and to display topics in a graphical and visual way.

[0054] The automated operation and intelligent command micro-application group includes:

[0055] The perception layer is used to acquire perception information and convert it into transmission signals after edge computing.

[0056] The network layer is used to transmit the converted transmission signals;

[0057] Application layer: Used to receive edge computing results and distribute work specifications;

[0058] Platform layer: Provides and shares application layer information;

[0059] A cluster of micro-applications for new energy consumption analysis, used for monitoring, analyzing, and evaluating new energy consumption;

[0060] The equipment status monitoring micro-application group is used for real-time data analysis of substations, historical data analysis of equipment, early warning of equipment time-series status trends, multi-dimensional analysis of power generation equipment, power grid event analysis, and early warning of equipment operating status trends.

[0061] The above-described technical solution of the present invention has the following beneficial technical effects:

[0062] Data and Business Platform: Adapting to the requirements of power Internet of Things construction, it evolves towards platform-based support, creating a control cloud data platform. It employs metadata management, message bus, model synchronization, model subscription, data integration, and data verification to aggregate and manage model and operational data. Through service bus, automatic deployment, and other applications, it provides a unified service association and application management framework for upper-layer SaaS applications.

[0063] Content-based on-demand data sharing: A content-based publish-subscribe mechanism matches message content according to rules that meet certain conditions and routes messages, enabling efficient and accurate subscription and distribution of model data between the cloud and the source.

[0064] Card-based object profiling query: In terms of displaying power grid containers and equipment objects, the most important and frequently used information of the objects is analyzed and extracted to create object profiles. Typical scenarios that conform to business characteristics are designed and displayed in a graphical and visual way using cards. Visual recognition is used to make information display both convenient and fast, as well as rich in form, achieving a perfect combination of aesthetics and practicality.

[0065] Scenario-based personal cloud desktop: By combining the operation and interaction advantages of mainstream PC and mobile operating systems through single-page rich application (SPA) front-end technology, a scenario-based personal cloud desktop for control cloud is formed. Application studios can be defined according to different professional departments, different departments of the power grid, different power generation companies, and different users. This realizes the framework of the power Internet of Things customer display service platform, providing users with one-stop application integration, display and access capabilities in the form of a desktop. Attached Figure Description

[0066] Figure 1 This is a diagram illustrating the overall architecture of a power Internet of Things (IoT) control cloud in one embodiment of the present invention.

[0067] Figure 2 This is a schematic diagram illustrating the overall principle of the present invention;

[0068] Figure 3 This is a schematic diagram of the butler structure used in this invention;

[0069] Figure 4 This is a diagram illustrating the dominant node and collaborating nodes of this invention;

[0070] Figure 5 This is a structural block diagram of the instant messaging service module of the present invention;

[0071] Figure 6 This is a flowchart illustrating the entire process management of the model data platform of this invention.

[0072] Figure 7 This is a block diagram of the model synchronization of the present invention;

[0073] Figure 8 A schematic diagram of the invention model subscription;

[0074] Figure 9 A flowchart for verifying and evaluating the invention model;

[0075] Figure 10 An overall block diagram of the invention's operational data platform;

[0076] Figure 11 Block diagram of the scheduling data exchange platform;

[0077] Figure 12 This is a map displayed for the power grid geographic information navigation platform.

[0078] Figure 13 The micro-application group can only command the block diagram. Detailed Implementation

[0079] To make the technical means, creative features, achieved objectives, and effects of this invention readily understandable, the invention is further described below with reference to specific embodiments and accompanying drawings. However, the following embodiments are merely preferred embodiments of this invention and not all embodiments. Other embodiments obtained by those skilled in the art based on the embodiments described herein without creative effort are all within the protection scope of this invention. Furthermore, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily obscuring the concept of this invention.

[0080] refer to Figure 1-13 .

[0081] This invention provides a method for constructing a scheduling and execution data foundation, including the following steps:

[0082] Building across scheduling agencies:

[0083] refer to Figure 1 It consists of a master node and N cooperating nodes. Two sites are deployed in different locations on the same node, and high-speed data synchronization between the two sites is achieved, with balanced configuration between the two sites.

[0084] To ensure the reliability and continuity of the control cloud, each node of the control cloud is built using a dual-site model, that is, two sites, A and B, are deployed in different locations on the same node, and high-speed data synchronization is achieved between the sites. The two sites are balanced in configuration, and both can provide services to the outside world simultaneously at the business level, realizing active-active operation of cross-site applications.

[0085] Information on dispatchable public resources can be obtained from the ubiquitous power Internet of Things via an interface;

[0086] A data platform is constructed, which includes a model data platform, an operational data platform, a scheduling data exchange platform, and a power grid address navigation platform.

[0087] The model data platform obtains model data parameters from surrounding business systems to form a model data center, and conducts model verification. It also provides reliable model data to the operation data platform and scheduling data exchange platform by sharing models on demand through model subscription.

[0088] The operation data platform extracts power grid operation data through access services and transforms it into an object-oriented organization based on a general structured design to form power grid operation data. It then provides power grid operation data and model data to the application layer through a service bus.

[0089] refer to Figure 2 In accordance with the requirements for the construction of the power Internet of Things (IoT) and combined with the needs of power dispatching operations, this system constructs a power IoT dispatching cloud based on the enterprise middle platform of dispatching agencies. Based on a data middle platform model data platform, it utilizes a distributed message transmission mechanism to acquire model data parameters from surrounding business systems, forming a model data center and conducting model verification. This provides reliable model data for the operation data platform and dispatching data exchange platform, and allows for on-demand model sharing through model subscription. The operation data exchange platform extracts power grid operation data from D5000, OMS2.0, and other sources through access services, converting it into object-oriented organization based on a general structured design to form power grid operation data. Unified data services are provided externally through a service bus. Power grid operation data and model data are provided for various applications such as application-layer data statistics and display, comprehensive evaluation, and comprehensive display.

[0090] The scheduling data exchange platform facilitates interaction between the source data end, the data exchange platform, and the target data end. Data interaction is performed using Kafka message messages, and message serialization is implemented using protobuf technology, providing data access / sending capabilities.

[0091] The power grid geographic information navigation platform uses the human-computer interaction method of Internet maps to build a geographic information platform, so as to realize the automatic hierarchical and graded integrated display of power grid and environment on geographic information map;

[0092] Building a business middle platform:

[0093] The system architecture developed using SOA is used to realize the service functions of common components of the PaaS platform and to enable high-performance and transparent RPC remote service calls between applications on different sites.

[0094] It provides a service information interaction mechanism for applications in the form of interface functions, and realizes the interconnection and interoperability of wide-area services between control cloud sites;

[0095] Building a cluster of micro-applications:

[0096] The process of extracting, transforming, analyzing, and modeling large amounts of business data using data mining techniques to extract key data to support decision-making includes business understanding, indicator design, data extraction, data exploration, algorithm selection, model evaluation, model deployment, and model optimization.

[0097] refer to Figure 3 The schedulable public resources include the application manager, which consists of a server and a client. The server is built on the cloud of the leading node, and the client is built on the cloud of each collaborating node.

[0098] A server is built on the national cloud platform to manage the entire process of application package uploading, review, listing, and release. Update information is pushed to provincial clouds via a message bus for installation and deployment. Clients are built on each provincial cloud platform to detect newly released or updated applications on the national cloud platform, providing download, installation, and update functions for rapid and automatic application deployment. The status of deployed applications is monitored, allowing for operations such as stopping, uninstalling, and updating applications.

[0099] Store application deployment packages uploaded by users through the cloud platform;

[0100] Users upload application deployment packages and list them on the control cloud platform so that subsequent users can delete or download the deployment packages;

[0101] Users upload and manage deployment packages, including JAR and WAR files, through the platform. Local or remote files can be uploaded, and the platform manages the storage of these packages in the backend. Uploaded deployment packages are listed on the platform, and users can deploy, delete, and download them.

[0102] Obtain the application deployment package and remotely deploy the application to the host;

[0103] Management access methods for the host;

[0104] refer to Figure 4 When the model data in the collaborative node cloud changes, the incremental data capture method provided by the vertical data synchronization tool is used to send the changed model data to the cloud through the message middleware deployed on the master node cloud. The cloud receives the message and updates the model data in the cloud.

[0105] The collaborative node cloud can subscribe to the model data of the master node cloud. When the model in the master node cloud changes, it is automatically sent to the model data center of the collaborative node cloud.

[0106] Historical measurement data in the cloud model data center of the collaborative nodes are periodically synchronized to the cloud using a timestamp-based scanning method.

[0107] The data platform includes a message center, which is event-driven and uses subscription / publishing message middleware technology to realize message transmission between applications in the control cloud platform system, providing support for information transmission between internal and external applications of the control cloud system.

[0108] refer to Figure 5 It also includes building an instant messaging service module, using the network technology provided in the HTML5 standard for full-duplex communication between the client and the server. The client sends a WebSocket connection request, and the server responds with a connection.

[0109] This achieves a TCP handshake-like action, thus establishing a fast, long-lived HTTP connection between the browser client and the WebSocket server. Subsequent data transfers between the two can then proceed directly without needing to initiate a new connection or respond.

[0110] Through "one-stop" chat, group chat, and file transfer, messages, notifications, and announcements from different applications and platforms are received, filtered, verified, assembled, encrypted, and stored before being pushed online or offline to third-party application clients.

[0111] The model data platform utilizes metadata management and dictionary management to achieve modeling standardization and scheduling terminology normalization, respectively. Through the metadata management table structure, it realizes the standardized design and scalability of data objects, including standardized data objects, data object tables, data object table attributes, and dictionary objects.

[0112] The model data platform is a key component of the PaaS layer of the control cloud's leading and collaborating nodes. It utilizes metadata management and dictionary management to standardize modeling and dispatch terminology, respectively. By standardizing the structure of metadata management tables such as data objects, data object tables, data object table attributes, and dictionary objects, it achieves standardized design and scalability requirements for data objects. With the development of the power Internet of Things (IoT), requirements for cloud-edge-field construction have emerged. Model synchronization and model subscription serve as data transmission and sharing channels between the control cloud and the source end. Through high-concurrency and massive data transmission verification, further improvements to the model synchronization function are needed.

[0113] refer to Figure 6 The model end-to-end management architecture is a complete technical system that enables the full-process management of models, including model maintenance, model synchronization, model subscription, model validation, and model display. Specifically:

[0114] Data maintenance: Model maintenance is mainly divided into two categories: model product model information maintenance and model object data maintenance.

[0115] Data synchronization: Provides high-speed vertical concurrent data synchronization for massive amounts of data.

[0116] Data Subscription: The shuj subscription tool is an easy-to-use, high-volume, real-time, and high-concurrency subscription tool based on content, enabling on-demand data subscription and precise, efficient distribution across different business areas.

[0117] Data verification: Verify the integrity, standardization, rationality, compliance, and redundancy of data to accurately locate dirty data.

[0118] Data evaluation: Based on the verification results, in accordance with the evaluation rules and combined with manual supervision, the data quality evaluation results are automatically generated, providing a basis for the data quality evaluation report.

[0119] Data retrieval and analysis: Analyze and extract the most important and frequently used information from the data to form thematic profiles, and design typical scenarios that conform to business characteristics. Use graphics and visual methods to display the themes, making the information display both convenient and fast, as well as rich in form.

[0120] refer to Figure 7 The model data platform uses a message bus to achieve vertical synchronization of model data among the source data terminal, collaborative nodes, and leading nodes in the cloud.

[0121] The source-end model synchronization client uses database triggers to periodically detect data changes, encapsulates the data based on a specific message protocol, and sends it to the message bus.

[0122] The cloud-based model synchronization server receives the data protocol packets, parses them, and then stores them in the database.

[0123] include:

[0124] Model data sending module:

[0125] Capture database and image file data;

[0126] Extract data from the captured database and image files;

[0127] The extracted data is sent through the message bus;

[0128] Model data receiving module:

[0129] Receive data sent by the message bus;

[0130] Load the received data.

[0131] refer to Figure 8 Model subscription:

[0132] The cloud provides model subscription services, enabling monitoring, perception, analysis, processing, routing, and distribution based on content subscriptions. The source end implements full-process control over model subscription definition, monitoring, invocation, parsing, storage, and receipt.

[0133] The operational data platform consists of two parts: a sending client and a receiving server.

[0134] Sending client: Extract relevant data from various business systems, convert the object codes into object codes that can be recognized by the control cloud, and send them to the cloud through the control cloud message bus. For running data that cannot be directly extracted by accessing the business system database, write it into the database at the control cloud source data end.

[0135] Receiving server: The data receiving and storage module is responsible for receiving various types of runtime data messages from the message bus, parsing them, and storing them in the database. The storage of runtime data is designed in accordance with the general data object structure specification.

[0136] refer to Figure 9 Model validation and evaluation involves verifying the data models, parameters, and graphics collected from public resources, primary and secondary sources in the cloud. Following the requirements of the "Structured Design of General Data Objects for Power Dispatch," the scope of the control cloud model validation includes: rationality verification, compliance verification, redundancy verification, consistency verification, statistical value verification, standardization verification, integrity verification, graphical verification, topology verification, and system configuration. To further enhance model data quality, model assessment and evaluation are conducted. Based on the model validation results and evaluation rules, automatic scoring is performed, and manual scoring is also possible. The final assessment score for each grid province is calculated based on weights. Assessment and validation are conducted every two hours. To expedite data retrieval, Elecsearch is used for storage and retrieval.

[0137] refer to Figure 10 The operational data platform includes functional modules such as data extraction and transmission, data interaction, data reception and storage, data supplementation, and data aggregation and monitoring. It enables the collection, processing, storage, and query services of seven major categories of power grid operation-related data, including measurement, alarms, faults and events, power consumption, planning and forecasting, environment, and data, thereby achieving integrated management and control of operational data.

[0138] The design of the data platform follows the principles of "configurability, controllability, and monitorability." Through the source data extraction configuration function, the range of data to be sent to the cloud can be flexibly configured; through the sending control function, the data sending time, cycle, and data recall can be controlled; and through the status monitoring function, the results of each extraction and sending of each type of data can be monitored.

[0139] The data platform mainly consists of two parts: a sending client and a receiving server.

[0140] The sending client is primarily responsible for extracting relevant data from various business systems, converting the object codes into object codes recognizable by the control cloud, and then sending it to the cloud via the control cloud message bus. For operational data that the sending client cannot directly extract from the business system database (e.g., planning and forecasting data), it needs to be stored on the control cloud source data end (written into the database); however, for operational data that the sending client can directly extract from the business system database (measurements, alarms, etc.), there is no need to store it on the sending client.

[0141] The data receiving and storage module of the receiving server is responsible for receiving various types of runtime data messages from the message bus, parsing them, and storing them in the database. The storage of runtime data is designed in accordance with the general data object structure specification.

[0142] The formats of operational data messages sent by the client and received by the server, as well as the formats of uplink and downlink control messages, are standardized to facilitate the expansion of operational data aggregation functions and unified monitoring of the operational data platform.

[0143] refer to Figure 11 The data exchange platform uses Kafka message messages for data interaction between the source data end, the platform itself, and the target data end, employing protobuf technology for message serialization. Three data access / sending methods are provided: message push, service call, and file exchange. Among them:

[0144] Push notifications are an asynchronous data interaction method that sends data proactively, making them suitable for scenarios with large data volumes and high real-time requirements.

[0145] Service invocation is a synchronous data interaction method in which the data requester calls the service to obtain data on demand. It is suitable for scenarios with small data volume and high real-time requirements.

[0146] File exchange complements the first two data interaction methods, sending data via proactive push, and is suitable for scenarios with large data volumes and low real-time requirements.

[0147] refer to Figure 12 The power grid geographic information navigation platform leverages the human-computer interaction of internet maps to integrate geographic, meteorological, and spatiotemporal information from the control cloud, constructing a geographic information platform of "one interconnected power grid, one unified model, and one cloud graphics platform." This enables automatic hierarchical and integrated display of the power grid and environment on the geographic information map. By implementing rapid comprehensive information query and retrieval and automatic labeling display technologies, it improves the human-computer interaction experience and information acquisition efficiency.

[0148] The business service module is built in the business middle platform, which is divided into four parts: service provider, service consumer, service registration center, and service monitoring.

[0149] The service container is responsible for starting, loading, and running the service provider;

[0150] When a service provider starts up, it registers the services it provides with the service registry.

[0151] When a service consumer starts up, it subscribes to the services it needs from the service registry. The registry then returns a list of service provider addresses to the consumer.

[0152] It also includes building a scenario-based personal cloud desktop, using SPA (Single Page Application) front-end technology, and dynamically rewriting the current page.

[0153] Building within a cluster of micro-applications:

[0154] refer to Figure 13 The model topic retrieval micro-application group is used to analyze and extract the most important and frequently used information of model objects to form topic profiles, and to design typical scenarios that conform to business characteristics, and to display topics in a graphical and visual way.

[0155] The automated operation and intelligent command micro-application group includes:

[0156] The perception layer is used to acquire perception information and convert it into transmission signals after edge computing.

[0157] The network layer is used to transmit the converted transmission signals;

[0158] Application layer: Used to receive edge computing results and distribute work specifications;

[0159] Platform layer: Provides and shares application layer information;

[0160] A cluster of micro-applications for new energy consumption analysis, used for monitoring, analyzing, and evaluating new energy consumption;

[0161] The equipment status monitoring micro-application group is used for real-time data analysis of substations, historical data analysis of equipment, early warning of equipment time-series status trends, multi-dimensional analysis of power generation equipment, power grid event analysis, and early warning of equipment operating status trends.

[0162] This also includes internal system interfaces. The control cloud platform-model data center is a physically distributed, unified national (branch) and provincial-level control cloud platform. The provincial control cloud platform needs to synchronize changes in model data in the local model data center to the national branch cloud platform-model data center in real time. In addition, it also needs to update the equipment information of cross-regional interconnection lines and related plants in a timely manner. In order to maintain the standardization and uniformity of data standards in the two-level model data centers, it is necessary to update the model metadata and data dictionary information from the cloud.

[0163] The interaction between the national cloud and the provincial cloud generally adopts two methods: service invocation and vertical data synchronization. After the metadata and data dictionary are updated, the national cloud sends an update message to the provincial cloud. After receiving the update message, the provincial cloud initiates a service invocation to update the metadata and data dictionary.

[0164] A unified power grid model is maintained on the national cloud platform. For changes to model data in provincial clouds, incremental data capture is used via a vertical data synchronization tool. The changed model data is then sent to the cloud via a message middleware deployed on the national cloud platform. The cloud receives the message and updates its model data. Simultaneously, provincial clouds can subscribe to model data on the national cloud platform. When the model changes on the cloud, the changes are automatically distributed to the provincial cloud platform's model data center.

[0165] For historical measurement data in the provincial cloud platform model data center, the data increments are periodically synchronized to the cloud using a timestamp scanning method through vertical data synchronization software.

[0166] In the above description, national (sub-) and provincial levels correspond to the leading node and the coordinating node, respectively.

[0167] It also includes external system interfaces:

[0168] The external interfaces of the model data platform are shown in the table below:

[0169]

[0170] The external interfaces for running data are shown in the table below:

[0171]

[0172]

[0173] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for constructing a scheduling and operation data foundation, characterized in that, Including the following steps: Building across scheduling agencies: It consists of one master node and N cooperating nodes, with two sites deployed in different locations on the same node, achieving high-speed data synchronization between the two sites and balanced configuration between the two sites; Information on dispatchable public resources can be obtained from the ubiquitous power Internet of Things via an interface; A data platform is constructed, which includes a model data platform, an operational data platform, a scheduling data exchange platform, and a power grid address navigation platform. The model data platform obtains model data parameters from surrounding business systems to form a model data center, and conducts model verification. It also provides reliable model data to the operation data platform and scheduling data exchange platform by sharing models on demand through model subscription. The operation data platform extracts power grid operation data through access services and transforms it into an object-oriented organization based on a general structured design to form power grid operation data. It then provides power grid operation data and model data to the application layer through a service bus. The scheduling data exchange platform facilitates interaction between the source data end, the data exchange platform, and the target data end. Data interaction is performed using Kafka message messages, and message serialization is implemented using protobuf technology, providing data access / sending capabilities. The power grid geographic information navigation platform uses the human-computer interaction method of Internet maps to build a geographic information platform, so as to realize the automatic hierarchical and graded integrated display of power grid and environment on geographic information map; Building a business middle platform: The system architecture developed using SOA is used to realize the service functions of common components of the PaaS platform and to enable high-performance and transparent RPC remote service calls between applications on different sites. It provides a service information interaction mechanism for applications in the form of interface functions, and realizes the interconnection and interoperability of wide-area services between control cloud sites; Building a cluster of micro-applications: The process of extracting, transforming, analyzing, and modeling large amounts of business data using data mining techniques to extract key data to support decision-making includes business understanding, indicator design, data extraction, data exploration, algorithm selection, model evaluation, model deployment, and model optimization. The schedulable public resources include the application manager, which consists of a server and a client. The server is built in the cloud on the leading node, and the client is built in the cloud on each collaborating node. Store application deployment packages uploaded by users through the cloud platform; Users upload application deployment packages and list them on the control cloud platform so that subsequent users can delete or download the deployment packages; Obtain the application deployment package and remotely deploy the application to the host; Management access methods for the host; When the model data in the collaborative node cloud changes, the incremental data capture method provided by the vertical data synchronization tool is used to send the changed model data to the cloud through the message middleware deployed on the master node cloud. The cloud receives the message and updates the model data in the cloud. The collaborative node cloud can subscribe to the model data of the master node cloud. When the model in the master node cloud changes, it is automatically sent to the model data center of the collaborative node cloud. Historical measurement data in the cloud model data center of the collaborative nodes are periodically synchronized to the cloud using a timestamp-based scanning method.

2. The method for constructing a scheduling and operation data foundation according to claim 1, characterized in that: The data platform includes a message center, which is event-driven and uses subscription / publishing message middleware technology to realize message transmission between applications in the control cloud platform system, providing support for information transmission between internal and external applications of the control cloud system.

3. The method for constructing a scheduling and operation data base according to claim 1, characterized in that: It also includes building an instant messaging service module, which uses the network technology provided by the HTML5 standard for full-duplex communication between the client and the server. The client sends a WebSocket connection request and the server responds with the connection. Through "one-stop" chat, group chat, and file transfer, messages, notifications, and announcements from different applications and platforms are received, filtered, verified, assembled, encrypted, and stored before being pushed online or offline to third-party application clients.

4. The method for constructing a scheduling and operation data base according to claim 1, characterized in that: The model data platform utilizes metadata management and dictionary management to achieve modeling standardization and scheduling terminology normalization, respectively. Through the metadata management table structure, it realizes the standardized design and scalability of data objects, including standardized data objects, data object tables, data object table attributes, and dictionary objects.

5. The method for constructing a scheduling and operation data base according to claim 1, characterized in that: The model data platform uses a message bus to achieve vertical synchronization of model data among the source data terminal, collaborative nodes, and leading nodes in the cloud. The source-end model synchronization client uses database triggers to periodically detect data changes, encapsulates the data based on a specific message protocol, and sends it to the message bus. The cloud-based model synchronization server receives the data protocol packets, parses them, and then stores them in the database.

6. The method for constructing a scheduling and operation data base according to claim 5, characterized in that, include: Model data sending module: Capture database and image file data; Extract data from the captured database and image files; The extracted data is sent through the message bus; Model data receiving module: Receive data sent by the message bus; Load the received data.

7. The method for constructing a scheduling and operation data base according to claim 1, characterized in that, Model subscription: The cloud provides model subscription services, enabling monitoring, perception, analysis, processing, routing, and distribution based on content subscriptions. The source end implements full-process control over model subscription definition, monitoring, invocation, parsing, storage, and receipt.

8. The method for constructing a scheduling and operation data base according to claim 1, characterized in that, The operational data platform consists of two parts: a sending client and a receiving server. Sending client: Extract relevant data from various business systems, convert the object codes into object codes that can be recognized by the control cloud, and send them to the cloud through the control cloud message bus. For running data that cannot be directly extracted by accessing the business system database, write it into the database at the control cloud source data end. Receiving server: The data receiving and storage module is responsible for receiving various types of runtime data messages from the message bus, parsing them, and storing them in the database. The storage of runtime data is designed in accordance with the general data object structure specification.

9. The method for constructing a scheduling and operation data base according to claim 1, characterized in that, The business service module is built in the business middle platform, which is divided into four parts: service provider, service consumer, service registration center and service monitoring. The service container is responsible for starting, loading, and running the service provider; When a service provider starts up, it registers the services it provides with the service registry. When a service consumer starts up, it subscribes to the services it needs from the service registry. The registry then returns a list of service provider addresses to the consumer. It also includes building scenario-based personal cloud desktops, using SPA (Single Page Application) front-end technology, and dynamically rewriting the current page.

10. The method for constructing a scheduling and operation data base according to claim 1, characterized in that, Building within a cluster of micro-applications: The model topic retrieval micro-application group is used to analyze and extract the most important and frequently used information of model objects to form topic profiles, and to design typical scenarios that conform to business characteristics, and to display topics in a graphical and visual way. The automated operation and intelligent command micro-application group includes: The perception layer is used to acquire perception information and convert it into transmission signals after edge computing. The network layer is used to transmit the converted transmission signals; Application layer: Used to receive edge computing results and distribute work specifications; Platform layer: Provides and shares application layer information; A cluster of micro-applications for new energy consumption analysis, used for monitoring, analyzing, and evaluating new energy consumption; The equipment status monitoring micro-application group is used for real-time data analysis of substations, historical data analysis of equipment, early warning of equipment time-series status trends, multi-dimensional analysis of power generation equipment, power grid event analysis, and early warning of equipment operating status trends.

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