CN110932405A - Intelligent monitoring and analyzing system for power transformation equipment based on big data - Google Patents

Abstract

The invention belongs to the technical field of intelligent operation and maintenance management of the Internet of things, and particularly relates to a transformation equipment intelligent monitoring and analyzing system based on big data, which comprises a central monitoring system and a terminal system; the central monitoring system mainly completes multi-source data access and storage, provides a function of quickly constructing an analysis process, and calls the packaged analysis algorithm service to perform multi-dimensional and multi-scale correlation analysis on data; meanwhile, the service subsystem provides functions of overall monitoring, remote maintenance, power supply management and control, safety control, fault analysis and prediction of the equipment; the terminal system is mainly responsible for encrypting local data of the transformer substation, controlling data retransmission and adapting a data source interface, and sends data to the data acquisition server through two access modes, namely VPN wired access and GPRS wireless access. The invention has high operation and maintenance efficiency, can effectively improve the operation and maintenance management level of national power grid companies, reduces the operation and maintenance cost, and can realize the global monitoring and fault prediction and diagnosis of various electrical equipment.

Description

Intelligent monitoring and analyzing system for power transformation equipment based on big data

Technical Field

The invention belongs to the technical field of intelligent operation and maintenance management of the Internet of things, and particularly relates to a transformer equipment intelligent monitoring and analyzing system based on big data.

Background

With the increase of safe and efficient power supply and clean energy demand, the problems of energy shortage and sustainable development are highlighted, and the smart grid becomes a core power for the development of the global power industry. In China, national grid companies propose the aim of constructing a strong intelligent grid with informatization, automation and interaction characteristics, and realize the highly integrated fusion of power flow, information flow and service flow.

The power generation groups and the power supply companies are used as important bases and node supports in the intelligent power grid and are one of the core contents for building the strong intelligent power grid to realize energy conversion and control. At present, auxiliary production control systems configured by power generation groups and power supply companies, such as fire alarm, lightning detection, environment monitoring, overhaul management and the like, accumulate a large amount of historical data of substation equipment state monitoring with useful value in the large-scale development process. The existing state monitoring and diagnosing device has more types of equipment and different interfaces. The state monitoring data are often stored in different databases, data sharing cannot be achieved, and the state of each transformer device is difficult to be comprehensively analyzed effectively. Meanwhile, with the increase of data scale and the acceleration of updating speed, the traditional data analysis is more and more difficult to effectively meet the requirement of intelligent operation of the transformer substation. Therefore, the development of an intelligent monitoring analysis platform capable of supporting the storage and analysis of the massive high-speed equipment state monitoring data is urgently needed.

In recent years, with rapid development of technologies in related fields such as cloud computing and big data processing, more and more advanced technologies are applied to intelligent monitoring analysis. Hadoop is a mainstream mass data processing platform, parallel data processing and analysis can be realized through decomposition and aggregation operation of tasks, analysis efficiency is guaranteed, and a technical basis is provided for storage and analysis of equipment monitoring data in a power grid. However, the monitoring data of the power grid equipment has both structured data and unstructured data, and the monitoring data has various sources and different acquisition frequencies and communication modes. Meanwhile, events (such as equipment faults) which happen suddenly need to be analyzed in time, and therefore a set of appropriate equipment monitoring big data storage and analysis solution is required to be designed and developed according to the characteristics of the power grid equipment monitoring service.

Disclosure of Invention

The invention aims to overcome the defects of the prior art and provides the intelligent monitoring and analyzing system for the power transformation equipment based on the big data, which has high operation and maintenance efficiency, can effectively improve the operation and maintenance management level of a national power grid company, reduce the operation and maintenance cost and realize the global monitoring and fault prediction and diagnosis of various electrical equipment.

In order to solve the technical problem, the invention is realized as follows:

the intelligent monitoring and analyzing system for the power transformation equipment based on the big data is characterized by comprising a central monitoring system and a terminal system;

the central monitoring system mainly completes multi-source data access and storage, provides a function of quickly constructing an analysis process, and calls the packaged analysis algorithm service to perform multi-dimensional and multi-scale correlation analysis on data; meanwhile, the service subsystem provides functions of overall monitoring, remote maintenance, power supply management and control, safety control, fault analysis and prediction of the equipment;

the terminal system is mainly responsible for encrypting local data of the transformer substation, controlling data retransmission and adapting a data source interface, and sends data to the data acquisition server through two access modes, namely VPN wired access and GPRS wireless access.

As a preferred solution, the central monitoring system of the present invention includes:

(1) data source layer: the system comprises various electrical equipment auxiliary management systems distributed in various power generation groups and power supply companies;

(2) collecting an access layer: the problem of semantic conversion and matching of data distributed among various auxiliary management systems of electrical equipment of various power generation groups and power supply companies is solved; providing a universal data interface API, and realizing a service data conversion function through definition and maintenance of industrial terms and matching conversion rules among the terms; meanwhile, a message communication mechanism based on a longitudinal encryption technology is provided;

(3) a data management layer: the storage requirements of structured and unstructured data in the power grid system are met. While providing fast storage of time series data;

(4) the data analysis processing engine layer: a monitoring data query engine of the built-in power grid equipment supports rich query semantics; meanwhile, the big data analysis threshold is reduced;

(5) basic data service layer: providing an analysis business process close to an analysis target, and further realizing the rapid construction of the analysis process by separating the analysis business from an analysis algorithm;

(6) a data application layer: the method provides the functions of overall equipment monitoring, fault prediction diagnosis, remote maintenance, power supply management and control, safety control, video diagnosis, risk source management, emergency plan management, potential safety hazard management and post-evaluation management for an end user.

Taking an 'intelligent substation equipment monitoring and analyzing platform' of a certain power supply company in a certain city as an example, a city-level power supply company configures 1 set of central monitoring systems. The functions realized by the system are global monitoring, remote maintenance, safety control, failure analysis and prediction, fusion storage, data storage and the like. The city power supply company belongs to a plurality of transformer substations, each transformer substation is provided with 1 set of terminal system, functions such as encryption service and QoS guarantee service are mainly achieved, the transformer substation terminal systems are accessed to a city power supply company central monitoring system in a VPN or GPRS mode, and the functions of overall monitoring, remote maintenance, power supply management and control, safety control, fault analysis and prediction of all devices are achieved.

The budget of a central monitoring system of an intelligent monitoring analysis platform for substation equipment of a city power supply company is 150 ten thousand yuan, the budget of a terminal system of each substation is 12 ten thousand yuan, each city power supply company has an average of about 100 subordinate substations, and the total budget of the substations is 1200 ten thousand yuan. The total project budget of each urban power supply company energy intelligent monitoring analysis platform is 1350 ten thousand yuan. At present, 661 cities exist in China, wherein 4 cities are directly administered, 283 cities are local cities, and 374 cities are county cities. If the energy intelligent monitoring and analyzing platform is comprehensively applied to national smart power grids, huge economic benefits and social benefits can be generated. The research and development of the system can realize the global monitoring and fault prediction diagnosis of various electrical equipment, improve the working efficiency of operation and maintenance personnel, further effectively improve the operation and maintenance management level of a national power grid company, improve the operation and maintenance efficiency and reduce the operation and maintenance cost. Better and more stable operation of the national power grid is ensured.

Drawings

The invention is further described with reference to the following figures and detailed description. The scope of the invention is not limited to the following expressions.

FIG. 1 is a schematic diagram of the overall structure of the system of the present invention.

Fig. 2 is a structural block diagram of the intelligent monitoring and analyzing platform for the substation equipment based on big data according to the present invention.

Detailed Description

As shown in the figure, the intelligent monitoring and analyzing system for the power transformation equipment based on the big data comprises a central monitoring system and a terminal system;

the central monitoring system mainly completes multi-source data access and storage, provides a function of quickly constructing an analysis process, and calls the packaged analysis algorithm service to perform multi-dimensional and multi-scale correlation analysis on data; meanwhile, the service subsystem provides functions of overall monitoring, remote maintenance, power supply management and control, safety control, fault analysis and prediction of the equipment;

the terminal system is mainly responsible for encrypting local data of the transformer substation, controlling data retransmission and adapting a data source interface, and sends data to the data acquisition server through two access modes, namely VPN wired access and GPRS wireless access.

The central monitoring system of the invention comprises:

(1) data source layer: the system comprises various electrical equipment auxiliary management systems distributed in various power generation groups and power supply companies;

(2) collecting an access layer: the problem of semantic conversion and matching of data distributed among various auxiliary management systems of electrical equipment of various power generation groups and power supply companies is solved; providing a universal data interface API, and realizing a service data conversion function through definition and maintenance of industrial terms and matching conversion rules among the terms; meanwhile, a message communication mechanism based on a longitudinal encryption technology is provided;

(3) a data management layer: the storage requirements of structured and unstructured data in the power grid system are met. While providing fast storage of time series data;

(4) the data analysis processing engine layer: a monitoring data query engine of the built-in power grid equipment supports rich query semantics; meanwhile, the big data analysis threshold is reduced;

(5) basic data service layer: providing an analysis business process close to an analysis target, and further realizing the rapid construction of the analysis process by separating the analysis business from an analysis algorithm;

(6) a data application layer: the method provides the functions of overall equipment monitoring, fault prediction diagnosis, remote maintenance, power supply management and control, safety control, video diagnosis, risk source management, emergency plan management, potential safety hazard management and post-evaluation management for an end user.

The intelligent substation equipment monitoring and analyzing platform based on the big data is developed by researching an electric equipment monitoring data fusion method and an analysis technology, integrating a Hadoop big data technology and a service-oriented software development technology aiming at the main requirements of electric equipment monitoring data fusion and storage analysis of each power generation group and power supply company.

The invention integrates Hadoop frame technology to integrate data in each system to realize intelligent linkage among isolated systems, and applies big data technology to carry out correlation analysis on monitoring states and environmental states of various electric equipment on the basis of data integration, thereby realizing global monitoring and fault prediction diagnosis of various electric equipment, improving the working efficiency of operation and maintenance personnel, further effectively improving the operation and maintenance management level of national power grid companies, improving the operation and maintenance efficiency and reducing the operation and maintenance cost.

The invention can provide the management functions of overall equipment monitoring, fault prediction diagnosis, remote maintenance, power supply management and control, safety control, video diagnosis, risk source management, emergency plan management, potential safety hazard management, post evaluation and the like.

The platform is divided into 2 systems of a terminal system and a central monitoring system, which are respectively deployed in a transformer substation server and a central monitoring server. The terminal system is responsible for encrypting local data of the transformer substation, controlling data retransmission and adapting a data source interface, and sends data to the data acquisition server through two access modes, namely VPN wired access and GPRS wireless access. The central monitoring system completes multi-source data access and storage, provides a function for quickly constructing an analysis flow, and calls the packaged analysis algorithm service to perform multi-dimensional and multi-scale correlation analysis on the data; and the service subsystem provides functions of global monitoring, remote maintenance, power supply management and control, safety control, fault analysis and prediction of the equipment.

Data source layer: the data source layer mainly comprises various electrical equipment auxiliary management systems distributed in various power generation groups and power supply companies, and is a target for data acquisition.

Collecting an access layer: the data semantic conversion matching problem among various electrical equipment auxiliary management systems distributed in various power generation groups and power supply companies is solved by mainly adopting a data adapter conversion principle. The method provides a universal data interface API through packaging a database, and realizes a service data conversion function through definition and maintenance of industry terms and matching conversion rules among the terms. Meanwhile, in consideration of the characteristics of safety and quality requirements of data communication in a power grid system, a message communication mechanism based on a longitudinal encryption technology is provided for the problem of equipment information acquisition of unattended substations distributed in remote areas.

A data management layer: the Hadoop frame technology is mainly adopted, and various data storage engines are arranged in the Hadoop frame technology, so that the structured and unstructured data storage requirements in a power grid system are met. Meanwhile, aiming at a large amount of time sequence data existing in the power grid system, a data caching mode is adopted, and the time sequence data is rapidly stored based on a streaming computing framework.

The data analysis processing engine layer: a monitoring data query engine of the power grid equipment is mainly built in, and rich query semantics are supported. Meanwhile, a big data parallel analysis engine is combined, and the big data analysis threshold is reduced through seamless connection of big data and small data.

Basic data service layer: the power grid system has business requirements for rapidly constructing and analyzing business processes to find equipment faults, diagnose the equipment faults, recommend fault solutions and the like. Therefore, a service packaging technology is adopted to package a bottom layer analysis algorithm, analysis experience in the field of analysis flow template curing is adopted, and various analysis flow templates, such as operation and maintenance cost analysis, physical asset models and the like, are built in. Therefore, an analysis business process close to an analysis target is provided by using an analysis process template recommendation technology, and the analysis process is quickly constructed by separating the analysis business from an analysis algorithm.

A data application layer: and by using the data acquisition and analysis results, the functions of equipment global monitoring, fault prediction diagnosis, remote maintenance, power supply management and control, safety control, video diagnosis, risk source management, emergency plan management, potential safety hazard management and post-evaluation management are provided for the end user. The overall monitoring mainly provides the function of remotely browsing display pictures of secondary equipment such as a substation telecontrol system, a protection management substation, fault recording and video monitoring. The fault prediction and diagnosis mainly provides the functions of equipment state fault prediction and fault diagnosis, and generates alarm information into standard alarm clauses which are directly transmitted to the operation and maintenance center in a text format through DL476 or IEC-104. The remote maintenance mainly uses one or more sets of keyboards, mice and displays to remotely manage and control a plurality of devices of the transformer substation based on the BIOS level of the IP through an intelligent operation and maintenance management system. The power supply management and control mainly realizes the operations of switching on, switching off, restarting and the like of all equipment power supplies of the transformer substation. The safety control mainly records an operation picture of an operation and maintenance person in remote operation on the controlled equipment so as to standardize the behavior of the operation person. The video diagnosis mainly comprises the steps of analyzing the incidence relation between an accident and a key area in a video through remote video data acquisition so as to find out the risk hidden danger and the accident source. The risk source management mainly completes the functions of risk source identification, evaluation and analysis. The emergency plan management is mainly responsible for emergency plan formulation, emergency plan simulation and evaluation. The potential safety hazard management mainly completes potential safety hazard identification, grading and tracking functions. The post-evaluation management mainly completes the functions of fault prognosis evaluation, event collection and the like.

It should be understood that the detailed description and specific examples, while indicating the embodiments of the invention, are given by way of illustration only, not limitation, and various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art from this detailed description. As long as the use requirements are met, the method is within the protection scope of the invention.

Claims (2)

1. The intelligent monitoring and analyzing system for the power transformation equipment based on the big data is characterized by comprising a central monitoring system and a terminal system;

the central monitoring system mainly completes multi-source data access and storage, provides a function of quickly constructing an analysis process, and calls the packaged analysis algorithm service to perform multi-dimensional and multi-scale correlation analysis on data; meanwhile, the service subsystem provides functions of overall monitoring, remote maintenance, power supply management and control, safety control, fault analysis and prediction of the equipment;

the terminal system is mainly responsible for encrypting local data of the transformer substation, controlling data retransmission and adapting a data source interface, and sends data to the data acquisition server through two access modes, namely VPN wired access and GPRS wireless access.

2. The big-data-based intelligent substation equipment monitoring and analyzing system according to claim 1, wherein: the central monitoring system comprises:

(1) data source layer: the system comprises various electrical equipment auxiliary management systems distributed in various power generation groups and power supply companies;

(2) collecting an access layer: the problem of semantic conversion and matching of data distributed among various auxiliary management systems of electrical equipment of various power generation groups and power supply companies is solved; providing a universal data interface API, and realizing a service data conversion function through definition and maintenance of industrial terms and matching conversion rules among the terms; meanwhile, a message communication mechanism based on a longitudinal encryption technology is provided;

(3) a data management layer: the storage requirements of structured and unstructured data in a power grid system are met, and meanwhile, the rapid storage of time sequence data is provided;

(4) the data analysis processing engine layer: a monitoring data query engine of the built-in power grid equipment supports rich query semantics; meanwhile, the big data analysis threshold is reduced;

(5) basic data service layer: providing an analysis business process close to an analysis target, and further realizing the rapid construction of the analysis process by separating the analysis business from an analysis algorithm;

(6) a data application layer: the method provides the functions of overall equipment monitoring, fault prediction diagnosis, remote maintenance, power supply management and control, safety control, video diagnosis, risk source management, emergency plan management, potential safety hazard management and post-evaluation management for an end user.

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