CN112055065A - Relay protection SaaS layer application data processing method based on regulation and control cloud - Google Patents
Relay protection SaaS layer application data processing method based on regulation and control cloud Download PDFInfo
- Publication number
- CN112055065A CN112055065A CN202010877795.XA CN202010877795A CN112055065A CN 112055065 A CN112055065 A CN 112055065A CN 202010877795 A CN202010877795 A CN 202010877795A CN 112055065 A CN112055065 A CN 112055065A
- Authority
- CN
- China
- Prior art keywords
- data
- protection
- service
- model
- processing method
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/51—Discovery or management thereof, e.g. service location protocol [SLP] or web services
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/12—Applying verification of the received information
- H04L63/123—Applying verification of the received information received data contents, e.g. message integrity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/10—Numerical modelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/04—Power grid distribution networks
Abstract
The invention discloses a relay protection SaaS layer application data processing method based on a regulation cloud, which comprises the following steps: establishing a general protection data model, and acquiring power grid operation data from each service system according to the general protection model; processing logic data of each service based on a universal protection data model; the method and the device can provide better service support for relay protection.
Description
Technical Field
The invention belongs to the technical field of power system operation control, and particularly relates to a relay protection SaaS layer application data processing method based on a regulation cloud.
Background
A large amount of online operation information and offline operation information generated by the relay protection equipment in the operation process provide conditions for management, operation maintenance, setting of a fixed value, action analysis and state evaluation of the relay protection equipment, but with increasing data, relatively dispersed information and relatively independent application, the problems of large data maintenance workload, difficulty in deep data mining, difficulty in improving comprehensive application and the like are brought, and the requirements for unique data sources, accurate data contents and wide data sharing are more and more urgent.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a relay protection SaaS layer application data processing method based on a regulation cloud, which can provide better service support for relay protection.
The technical scheme for realizing the invention is as follows:
a relay protection SaaS layer application data processing method based on a regulation cloud comprises the following steps:
establishing a general protection data model, and acquiring power grid operation data from each service system according to the general protection model;
processing logic data of each service according to the universal protection data model;
and providing a service interface for the universal protection data model and the processed business logic data.
Further, the establishing of the general protection data model, and the obtaining of the power grid operation data from each service system according to the general protection model, are as follows: planning the power grid operation data of each service system according to a uniform rule to obtain a universal protection data model of the power dispatching system, and acquiring the power grid operation data from each service system at the source end according to the model.
Further, a data integrity principle, a data relevance principle and a data normalization principle need to be followed when the protected data model is established.
Further, the data integrity principle includes: data acquisition integrity and data definition integrity.
Further, the data association principle is as follows: and establishing a data association relation between different data according to the service requirements and the data types.
Further, the data normalization principle is as follows: and naming each table field in the protection data model according to a uniform specification.
Further, the processing of the business logic data according to the general protection data model specifically includes: and associating the data objects in the universal protection data model according to the service logic to obtain associated service logic data for service application.
Further, the providing a service interface for the generic protection data model and the processed business logic data includes:
and providing a message bus service interface, a data management service interface, a model management service interface, a permission management service interface and a man-machine visualization service interface for the universal protection data model and the processed business logic data.
Further, the data management service interface specifically includes: and aiming at different characteristic data, unified storage management is adopted.
Further, the message bus service interface is: and transmitting data in the interval area by adopting a message bus.
Has the advantages that: the method uses the technologies of computing, storing, networking, virtualization resource pool and the like of a regulation cloud platform to extract, collect and store real-time data and operating data, and forms a uniform relay protection model which has unique data source and accurate content and supports wide sharing. The problem that the existing system data modeling and application can only meet the requirement of a single service, the whole planning for protecting professional data flow is lacked, each application is independently complete, and the protection operation data and the analysis result of each independent system cannot be shared is solved. The unified protection full-service data modeling and service-based application support system is provided, so that source end maintenance and global sharing of protection data, technical analysis and professional management such as relay protection state evaluation, intelligent fixed value setting and checking, online monitoring and diagnosis and the like play important support roles.
Drawings
FIG. 1 is a ledger data flow diagram of the present invention;
FIG. 2 is a data flow diagram of defect elimination, overhaul and the like in the present invention;
FIG. 3 is a data flow diagram of actions, alarms, etc. in the present invention;
FIG. 4 is a schematic diagram of a cross-region message bus according to the present invention;
FIG. 5 is a diagram of a wide area service communication framework in accordance with the present invention
FIG. 6 is a schematic diagram of a data management service in the present invention;
FIG. 7 is a schematic illustration of a human visual presentation;
FIG. 8 is a diagram of the overall framework of the relational library according to the present invention;
FIG. 9 is a schematic diagram of a distributed columnar database data management structure;
FIG. 10 is a diagram of the MPP database functional structure.
Detailed Description
The invention is further described with reference to the accompanying drawings.
As shown in fig. 1 to 10, a relay protection SaaS (Software as a Service) layer application data processing method based on a regulation cloud mainly includes the following aspects:
establishing a general protection data model, and acquiring power grid operation data from each service system according to the general protection model, specifically:
the method comprises the steps of taking data of certain equipment or certain index data of various business systems with source ends distributed in various places as data objects, modeling the data objects at a regulation cloud end, carrying out global unified planning on coding rules and formats of the data in the modeling process, mapping a model of the regulation cloud end and the data objects at the source ends (such as mapping relations between regulation cloud equipment codes and equipment IDs in the source end systems, regulation cloud alarms and operation events and source end system alarms), then obtaining required power grid operation data from the source end system according to the mapping relations of the model, converting the required power grid operation data into a unified data format which accords with the regulation cloud end in the data obtaining process, carrying out validity verification on the converted data, sending the data to the regulation cloud end through a regulation cloud message bus, and carrying out unified storage on the regulation cloud end.
The power grid operation data mainly comprises the following data:
the protection service data mainly includes protection device attributes, protection operation measurement data, operation events, external environment events, prediction data, feature data, and the like, and these data are stored in the original service system, and different types of data need to be integrated and synchronized to the regulation cloud, as shown in fig. 6.
The traditional method for protecting the data flow collected by the standing book information mainly uses a form or an equipment management system, the standing book is directly entered in the form or the system manually, and the standing book data is difficult to maintain, share and globally apply. By adopting the idea of data flow planning of hierarchical partitions, the protection ledger data flow of the service supporting platform is shown in fig. 1.
The data shown in fig. 1 includes:
firstly, detecting data: detecting the information of the organization and the professional detection result issued by the organization.
Delivery information of the equipment: and basic device information when the equipment leaves a factory.
Third, standard data: including device model information, software version, standardized data for ICD information, etc.
And fourthly, equipment identity identification codes.
Fifthly, equipment standing book: and (4) complete equipment basic ledger information.
The machine account APP is protection machine account management application software installed on a transformer substation field mobile operation terminal based on a mobile interconnection technology.
The equipment two-dimensional code is an equipment identity unique identification which is made by an electric power company for each equipment.
Detection data (data) issued by a professional detection mechanism, equipment delivery information (data) of a manufacturer and protection standard data (data) issued by scheduling are all-network general data, and are collected by a superior relay protection service support platform and issued to subordinate relay protection service support platforms in a unified mode so as to ensure the integrity, normalization and accuracy of the data. And the subordinate relay protection service supporting platform pushes the data to a protection account APP, field protection team personnel scan a two-dimensional code on the protection equipment and combine the data to complement and perfect protection account information in the account APP, complete account information is returned to the subordinate relay protection service supporting platform, and the account is reported to a superior relay protection service supporting platform by the subordinate relay protection service supporting platform, so that a complete and standard protection equipment account is formed.
The defect eliminating and overhauling data streams of the traditional protection equipment are distributed in respective independent application systems, such as operation plans of defect eliminating, overhauling, routing inspection and the like, field operation records and the like, the difficulty of data fusion and data sharing is high, and an operation information set in the whole life cycle process of the equipment cannot be formed. By adopting the idea of data flow planning of hierarchical partitions, the data flows of the service support platform such as protection deletion, overhaul and the like are shown in fig. 2.
The data shown in fig. 2 includes:
the method comprises the following steps of inspection, overhaul, defect elimination, spot inspection, technical improvement and overhaul work planning.
Checking, repairing, eliminating defect, sampling inspection, counter measure of technical improvement and overhaul work record.
And running condition, change condition and abnormal condition of the equipment in the running tour.
And fourthly, familial defect information including equipment model, version, defect phenomenon and the like.
The superior relay protection service support platform issues the identification result of the familial defect of the whole network protection equipment and the operation plans (data) of defect elimination, maintenance, inspection and the like which are approved by a competent department to the current relay protection service support platform, the association of the operation plans and the account information of the protection equipment in the region is completed in the current relay protection service support platform, then the plans, the familial defect data and the like are pushed to the mobile operation APP, and the mobile operation APP returns the work record (data) and the inspection record (data) of the region to the service support platform, so that complete and standard protection field operation data are formed.
The action and alarm data flow is recorded by a fault recorder in the transformer substation under the traditional condition, and the fault recorder is transmitted to a fault recording networking system of a main station; the protection information management system sub-station or the protection equipment on-line monitoring system sub-station finishes the collection of actions and alarm information of the protection equipment in the station and uploads the actions and the alarm information to the protection information management system main station, the protection equipment on-line monitoring system main station and the D5000 platform. By adopting the idea of data flow planning of hierarchical partitions, the data flow of the protection action and the alarm class information of the service support platform is shown in fig. 3.
The data shown in fig. 3 includes:
fault recording in fault recorder.
Secondly, the protection device alarm information and the protection bulletin comprise: protection hardware alarm information, software alarm information, internal self-checking information, external self-checking information, function locking information and the like.
Running state information, including: and recording files by the on-line monitoring device, the intermediate node information device and the protection device.
When the protected data model is established, a data integrity principle, a data relevance principle and a data normalization principle need to be followed.
The data integrity principle comprises: data acquisition integrity and data definition integrity; in order to support the relay protection full-life business process, the model information includes equipment detection, production and manufacturing, commissioning acceptance, operation and maintenance, decommissioning and the like. And completely defining the attribute and the structure of each type of data to ensure that various types of operation information can be completely described.
The data relevance principle is as follows: establishing a data association relation among different data according to business requirements and data types, establishing a complete and standard data index relation, taking a basic ledger as a main line and various types of running, overhauling and other information as branches, and establishing a strict and complete data search engine.
The data normalization principle is as follows: and naming each table field in the protection data model according to a uniform specification to avoid conflict with keywords, and establishing reference relations among different model tables. The model design and the service function are organically integrated, different application scenes can be supported, field redundancy is avoided, and conditions are created for future model expansion.
Secondly, processing logic data of each service according to the general protection data model;
and associating the data objects in the universal protection data model according to the service logic to obtain associated service logic data for service application.
The invention develops the service support to the logic business on the basis of the established standardized model. The bottom layer big data service completes data acquisition, realizes unified management and data fusion of relay protection professional data, realizes data management functions such as data collection, data storage, data processing, data calculation, data analysis and data service interface, and provides a standardized data service interface to realize data service support of a logic service layer. And the logic service layer realizes various application function modules required by relay protection professional management and operation analysis. Each functional module adopts a standardized data interface to realize the retrieval of data of the bottom layer big data service layer and provides storage support for analysis result data of the application functional module.
Corresponding information in a fault recorder, a protection information management system substation and a protection online monitoring system substation in the regional transformer substation is directly sent to the service support platform on the level through a scheduling data network. And realizing data management and data fusion on a big data service layer of the service support platform.
The logic service layer on the upper layer realizes various service function modules required by relay protection professional management and operation analysis, and covers application function modules such as a full life cycle information management module, an equipment evaluation module, a fault and action analysis module, an intelligent diagnosis module and the like. Each functional module adopts a standardized data interface to realize retrieval of data of the bottom layer big data service layer and storage of analysis result data of the module.
The data management service implementation of the supporting business of the present invention is shown in fig. 6.
Providing unified storage management for different feature data, comprising: storing structured data based on a relational database; storing KV characteristic data based on a distributed column database; and importing the relational database and the distributed column database data into the MPP database through a loading tool. The unified data management provides efficient and unified model data service, operation data service and statistical analysis service for provincial and large-scale monitoring service systems.
The data management service mainly comprises three types of distributed relational database management, distributed column type database management and MPP database management.
The implementation of the distributed relational data management function is shown in fig. 8
The data storage and management based on the distributed relational database can provide reliable support for structured data storage of various businesses, and the main storage data types comprise: the data storage system comprises model structured data, management process data, alarm and operation event structured data and the like, and meets the storage requirement of relational data.
Relational data storage and management is based on a distributed relational database. The distributed relational database can use various relational databases as data storage child nodes, and a data access middle layer is used as a core technology to form an autonomous distributed relational database, so that the online smooth expansion and contraction capacity and the dynamic expansion of service capacity of a database cluster are supported; and the data storage spaces of different service applications can be safely isolated. The distributed database access middle layer automatically adapts the database types, provides a standard data uniform access interface for application services, and obtains execution results through steps of analyzing and reconstructing SQL requests submitted by clients, performing distributed execution, collecting distributed results and the like.
Distributed columnar database management function implementation as shown in FIG. 9
In order to meet the requirements of high concurrent reading and writing, high-efficiency storage, high expansibility and the like of service application on the sampled data, massive sampled data storage and management based on a distributed column-type database are provided.
The storage and management of the mass sampling data are based on a distributed column-type database. The distributed column-type database is a high-reliability, high-performance, column-oriented and scalable distributed storage system, and is mainly used for providing low-delay read-write access and bearing high-concurrency access requests. Unlike relational databases, distributed columnar databases are suitable for semi-structured and unstructured data storage, and have automatic indexing function and better compression and decompression algorithms for data storage. The storage structure of the distributed column-type database is loose data, a simple mapping relation of key and value is used, but the mapping relation is not a simple mapping relation, and the relation provides support for an ultra-large-scale high-concurrency mass data real-time response system. The stored data of the distributed columnar database is a large table logically, and the data can be dynamically increased according to needs. Distributed columnar databases may use either a local file system or a distributed file storage system. In order to improve the robustness and reliability of the system and fully utilize the large data processing capacity of the distributed columnar database, a distributed file system is used as a file storage system.
The distributed columnar database functions are described as follows:
1) column type storage, wherein a column-oriented storage model is used for storing data, and a group of related columns can be attributed through the columns, so that the aggregation characteristic of the data is fully exerted;
2) read-write operation, providing fast read-write operation of data;
3) linear expansion, namely realizing dynamic expansion of the storage nodes and uniformly distributing data to each node;
4) and monitoring management, which has node state management and monitoring capabilities and can monitor performance indexes such as requests per second, resource use conditions and the like.
MPP database management function implementation is shown in FIG. 10
In order to support the requirements of mass data storage and processing, high cost performance and the like, a high-end data warehouse solution is provided, and an MPP database suitable for large-scale parallel processing is provided. Through a data loading tool, data of a relational database, a distributed column-type database and other sources are synchronized, and efficient mass data analysis support is provided in the MPP database.
The MPP database is a database supporting large-scale parallel processing and is composed of two-stage cluster structures of a coordination node cluster of a plurality of coordination nodes and an operation node cluster of a plurality of operation nodes, and a load balancing mechanism is adopted among the coordination nodes to support distributed parallel execution of load tasks. The MPP database is suitable for processing large-scale complex analysis; the method has higher compression ratio, saves storage investment and electric energy loss for the storage of mass data; the method has the advantages of light weight, transparency and high efficiency intelligent indexing, and improves the complex query efficiency; the method has rich OLAP function libraries and meets the application requirements of business analysis.
The MPP database is mainly suitable for application scenes of mass data analysis, and has the following main functions:
a) the parallel loading of data and the parallel execution of operation are supported, the data are stored in each node in a distributed manner, and TB/PB level data analysis can be supported;
b) the method supports most of the single-machine version functions of the DM, simultaneously supports row and column storage, and supports the storage process, triggers, indexes, partition tables, multimedia data types and the like;
c) the cost performance is high, special software and hardware do not need to be additionally configured, and the cost performance is ultrahigh;
d) each node in the MPP system is configured with one or more real-time standby nodes, and when the node fails, the corresponding standby node can be rapidly switched to a main library to continuously provide service, so that the high availability of the system is ensured.
The logic business service layer constructed by the invention mainly comprises 8 types of applications of information management, equipment evaluation, fault analysis, intelligent diagnosis, defect management, overhaul countermeasures, lean management and auxiliary decision making.
And thirdly, providing a service interface for the general protection data model and the processed business logic data.
And providing a message bus service interface, a data management service interface, a model management service interface, a permission management service interface and a man-machine visualization service interface for the universal protection data model and the processed business logic data.
In order to support service information interaction, the patent provides a service message bus which mainly comprises a cross-region message bus and a cross-renter station service bus.
The implementation method of the cross-region message bus is shown in FIG. 4
The existing message bus is mainly used for data interaction inside the partitions, and the message sharing and transmission among the partitions of the monitoring system are less considered. For a specific scenario, the existing communication bus also supports partial one-three-zone synchronization, but has no generality. In addition, for a large monitoring system, the message volume is improved, and the cross-region transmission requirement requires a message bus to realize the cross-region rapid message transmission according to the requirement, and the method has high speed, reliability and universality.
In order to improve the real-time requirement of the monitoring service, an asynchronous concurrency mechanism is adopted by a trans-regional message bus, so that the data synchronization efficiency is improved; a uniform technology is introduced to the messages between the partitions to realize the consistent forwarding and routing of the messages; in addition, a multi-priority mechanism is used for realizing the priority transmission of important messages.
FIG. 5 shows a method for implementing a wide area message bus crossing master stations
One area on the transformer substation side needs to support the uploading of an analysis result to a main station and support functions of calling station end detailed information and the like by the main station, so that a flexible and extensible main station communication means needs to be established. In order to solve the problems of flexibility and expandability of monitoring information interaction between a main station and a transformer substation, a high-performance wide area service communication framework based on a General Service Protocol (GSP) of a power system is designed, standardization of service calling between main stations is realized, and powerful support is provided for wide area cooperation of monitoring services of the main stations.
And the transformer station side deploys services such as analyzing data uploading and the like so as to meet the data requirement of the main station side. Since the substation end systems in different regions are of different models, these services communicate with the service agents via internal buses within the stations. The service consumer at the master station end communicates with the service agent at the master station end through the service bus, and the service agent at the master station end communicates with the service agent at the factory station end through a general service protocol.
In order to realize the unified management of the substation side services, a service management center needs to be deployed at the master station side. After the services of all the transformer substation ends are started, service registration needs to be carried out on the service management center of the main station end, and after the services are authorized by the service management center, the services can be provided online. The online service is monitored by the service monitor to carry out unified monitoring, the service running state is checked, and the service availability is ensured.
The human-machine visualization implementation of the support service of the present invention is shown in fig. 7.
The human-computer visual display is based on the grasp of the monitoring service requirements, combines the actual requirements of the monitoring system on the GIS-based monitoring service information display, carries out deep research on the GIS display and other technologies around the GIS-based monitoring service information display system architecture and standard specification, and develops the GIS-based monitoring service information display function on the basis.
The man-machine visual display is based on GIS panoramic display, and different information layer display is realized by combining a GIS layer management means. The following figures have main body designs including a geographic layer, a monitoring device layer and a state information layer. The layer display of different types does not influence each other, can realize the correlation analysis under certain operation, offer the good picture display support means for decision maker. The rendering of the geographic layer adopts standard GIS vector grid deletion data, so that the drawing and displaying of various basic information can be realized; the monitoring equipment layer effectively supports energy monitoring display of the monitoring equipment layer by using a rendering mode of a primitive meeting CIM/G specification; the state information layer belongs to a dynamic change layer, and dynamically displays information such as maintenance conditions, fault conditions, defect abnormity and the like in a customized mode.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A relay protection SaaS layer application data processing method based on a regulation cloud is characterized by comprising the following steps:
establishing a general protection data model, and acquiring power grid operation data from each service system according to the general protection model;
processing logic data of each service based on a universal protection data model;
and providing a service interface for the universal protection data model and the processed business logic data.
2. The relay protection SaaS layer application data processing method based on the regulation cloud as claimed in claim 1, wherein the general protection data model is established, and power grid operation data are acquired from each service system according to the general protection model: planning the power grid operation data of each service system according to a uniform rule to obtain a universal protection data model of the power dispatching system, and acquiring the power grid operation data from each service system at the source end according to the model.
3. The relay protection SaaS layer application data processing method based on the regulation cloud as claimed in claim 2, wherein a data integrity principle, a data relevance principle and a data normalization principle need to be followed when a protection data model is established.
4. The relay protection SaaS layer application data processing method based on the regulation cloud as claimed in claim 3, wherein the data integrity principle comprises: data acquisition integrity and data definition integrity.
5. The relay protection SaaS layer application data processing method based on the regulation cloud as claimed in claim 3, wherein the data relevance principle is as follows: and establishing a data association relation between different data according to the service requirements and the data types.
6. The relay protection SaaS layer application data processing method based on the regulation cloud as claimed in claim 3, wherein the data normalization principle is as follows: and naming each table field in the protection data model according to a uniform specification.
7. The relay protection SaaS layer application data processing method based on the regulation cloud as claimed in claim 2, wherein the processing of each service logic data based on the general protection data model specifically comprises: and associating the universal protection data models according to the service logic to obtain associated service logic data so as to realize service application.
8. The relay protection SaaS layer application data processing method based on the regulation cloud as claimed in claim 1, wherein providing a service interface to the general protection data model and the processed business logic data comprises:
and providing a message bus service interface, a data management service interface, a model management service interface, a permission management service interface and a man-machine visualization service interface for the universal protection data model and the processed business logic data.
9. The relay protection SaaS layer application data processing method based on the regulation cloud as claimed in claim 8, wherein the data management service interface is specifically: and aiming at different characteristic data, unified storage management is adopted.
10. The relay protection SaaS layer application data processing method based on the regulation cloud as claimed in claim 8, wherein the message bus service interface is: and transmitting data in the interval area by adopting a message bus.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010877795.XA CN112055065A (en) | 2020-08-27 | 2020-08-27 | Relay protection SaaS layer application data processing method based on regulation and control cloud |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010877795.XA CN112055065A (en) | 2020-08-27 | 2020-08-27 | Relay protection SaaS layer application data processing method based on regulation and control cloud |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112055065A true CN112055065A (en) | 2020-12-08 |
Family
ID=73600365
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010877795.XA Pending CN112055065A (en) | 2020-08-27 | 2020-08-27 | Relay protection SaaS layer application data processing method based on regulation and control cloud |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112055065A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102508929A (en) * | 2011-12-01 | 2012-06-20 | 浪潮(北京)电子信息产业有限公司 | System, device and method for realizing data migration of heterogeneous database |
| US20130191418A1 (en) * | 2012-01-20 | 2013-07-25 | Cross Commerce Media | Systems and Methods for Providing a Multi-Tenant Knowledge Network |
| CN103825755A (en) * | 2013-11-27 | 2014-05-28 | 广东电网公司电力调度控制中心 | Power secondary system modeling method and system |
| CN104182818A (en) * | 2014-07-21 | 2014-12-03 | 国网山东省电力公司青岛供电公司 | Method and system for collecting substation information automatically and intelligently |
| CN104200402A (en) * | 2014-09-11 | 2014-12-10 | 国家电网公司 | Publishing method and system of source data of multiple data sources in power grid |
| CN106026405A (en) * | 2016-07-19 | 2016-10-12 | 国电南瑞科技股份有限公司 | Relay protection on-line monitoring and analyzing system based on EMS system |
-
2020
- 2020-08-27 CN CN202010877795.XA patent/CN112055065A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102508929A (en) * | 2011-12-01 | 2012-06-20 | 浪潮(北京)电子信息产业有限公司 | System, device and method for realizing data migration of heterogeneous database |
| US20130191418A1 (en) * | 2012-01-20 | 2013-07-25 | Cross Commerce Media | Systems and Methods for Providing a Multi-Tenant Knowledge Network |
| CN103825755A (en) * | 2013-11-27 | 2014-05-28 | 广东电网公司电力调度控制中心 | Power secondary system modeling method and system |
| CN104182818A (en) * | 2014-07-21 | 2014-12-03 | 国网山东省电力公司青岛供电公司 | Method and system for collecting substation information automatically and intelligently |
| CN104200402A (en) * | 2014-09-11 | 2014-12-10 | 国家电网公司 | Publishing method and system of source data of multiple data sources in power grid |
| CN106026405A (en) * | 2016-07-19 | 2016-10-12 | 国电南瑞科技股份有限公司 | Relay protection on-line monitoring and analyzing system based on EMS system |
Non-Patent Citations (2)
| Title |
|---|
| 张华宁: "继电保护在线监视与分析系统的功能提升与实践", 电气应用 * |
| 白雨竹: "蒙东电网继电保护故障信息采集及处理系统研究", 中国优秀硕士学位论文全文数据库-工程科技II辑 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10756809B1 (en) | Emergency communication satellite terminal management system | |
| CN109582717B (en) | Database unified platform for electric power big data and reading method thereof | |
| CN103500173B (en) | A kind of querying method of track traffic Monitoring Data | |
| CN108964996B (en) | Urban and rural integrated information grid system and information sharing method based on same | |
| CN105278373A (en) | Substation integrated information processing system realizing method | |
| CN103440367A (en) | Panoramic data modeling method for transformer substation | |
| CN103955510A (en) | Massive electricity marketing data integration method uploaded by ETL cloud platform | |
| CN114328688A (en) | Management and control platform for electric power energy big data | |
| CN104200331A (en) | Power grid model joining method and system of power system | |
| CN110932405A (en) | Intelligent monitoring and analyzing system for power transformation equipment based on big data | |
| CN103489139A (en) | Comprehensive analysis and management system for urban distribution network planning | |
| CN112559634A (en) | Big data management system based on computer cloud computing | |
| CN112651872A (en) | Community comprehensive treatment system and method based on data middlebox | |
| CN114152720A (en) | Monitoring platform for carbon emission | |
| Wu et al. | An auxiliary decision-making system for electric power intelligent customer service based on Hadoop | |
| CN102684307A (en) | Information intelligent layering and propelling method for comprehensively and automatically monitoring centralized control station and transformer substation | |
| CN105574204B (en) | Retrieval method and system for distributed power grid regulation and control operation data | |
| CN115439015B (en) | Local area power grid data management method, device and equipment based on data middleboxes | |
| Dong et al. | Research on Architecture of Power Big Data High-Speed Storage System for Energy Interconnection | |
| CN112055065A (en) | Relay protection SaaS layer application data processing method based on regulation and control cloud | |
| CN111414355A (en) | Offshore wind farm data monitoring and storing system, method and device | |
| CN116523328A (en) | Intelligent decision-making method for cooperation of aviation equipment and manufacturing industry chain | |
| CN112784129A (en) | Pump station equipment operation and maintenance data supervision platform | |
| CN113783304A (en) | Transformer substation monitoring cloud-side cooperative system | |
| Pan et al. | An open sharing pattern design of massive power big data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |