CN106325252A - Multi-level large-span large data oriented power equipment state monitoring and evaluating system - Google Patents

Abstract

The invention discloses a multi-layer and large-span big data-oriented power equipment state monitoring and evaluation system belonging to the field of power equipment state research. The system is divided into four layers: collection and convergence layer, station control layer, provincial network layer and headquarters layer; the collection and convergence layer is further divided into a convergence subsystem and a collection subsystem; the station control layer includes a status monitoring server, a workstation, The mobile terminal access device and the mobile terminal; the state monitoring server stores the data transmitted by the gateway, and is connected to the workstation and the mobile terminal access device through Ethernet. The present invention organically combines advanced wireless sensor network technology with the power equipment status monitoring system, fully digitalizes the data transmission from the primary power equipment terminal to the provincial network headquarters level, and integrates information; introduces a cloud computing platform based on big data analysis, multi-time and space The risk assessment of the state system, etc., provides powerful data guarantee for intelligent decision support, so as to complete the life-cycle health prediction and cycle management of equipment assets.

Description

Multi-layer and large-span power equipment condition monitoring and evaluation system for big data

technical field

The invention belongs to the field of power equipment state research, and in particular relates to a multi-layer, large-span, big data-oriented power equipment state monitoring and evaluation system.

Background technique

Smart grid is the most cutting-edge economic growth point in the world today, and has become a research hot spot in many countries. As an important application system of the smart grid, the power equipment status monitoring and evaluation system completes the collection and analysis of the status parameters of the power equipment, realizes the status visualization, and evaluates and warns the equipment according to the status of the power equipment, and takes corresponding measures. By improving the reliability and controllability of power equipment operation, and then improving the overall power supply reliability, the intelligent function of the condition monitoring system can provide a solid foundation for the overall decision-making of the smart grid.

The traditional method of state monitoring of power equipment adopts methods such as regular preventive maintenance, test and manual inspection. In order to avoid accidents, during the operation of the equipment, the on-duty personnel need to patrol frequently, and make judgments based on appearance phenomena, indicating instruments, manual experience, etc., so as to detect abnormalities in time. In addition, the operation will be stopped regularly to conduct routine inspections of electrical equipment, do mechanical action tests or preventive insulation tests, and deal with structural defects in a timely manner. This method of regular maintenance and frequent inspections plays a vital role in the safe and normal operation of electrical equipment.

In recent years, domestic and foreign power equipment condition monitoring has made great progress in theoretical research, and has developed condition monitoring and fault diagnosis devices for transmission lines, transformers, circuit breakers and other equipment, but in many aspects of power equipment condition monitoring There are still many outstanding problems. The power equipment condition monitoring system is still in the decentralized monitoring stage and is independent of the computer monitoring system. Between the power control center and each substation, as well as between the condition monitoring system and other systems, the data information model and communication interface are highly heterogeneous, making it difficult to make full use of them. Different information is used for condition assessment, fault diagnosis and condition maintenance of equipment. In the smart grid, the status monitoring data of power equipment has the following characteristics:

(1) The amount of condition monitoring data is increasing geometrically, and the data scale is constantly expanding; the data types are complex and diverse, and there are many types; the monitoring data is distributed in a wide area; there are many calculation tasks and a large amount of calculation; the data reliability and real-time requirements are high.

(2) The data interaction of each platform is poor.

Faced with these massive, distributed, heterogeneous, complex, and computationally intensive state data, conventional data storage and management systems are difficult to adapt to the higher requirements of the smart grid for state monitoring data reliability and real-time performance.

Therefore, there is an urgent need to establish a set of big data-oriented, unified, open power equipment condition monitoring system that meets the development needs of smart grid equipment, to achieve large-span and rapid power equipment condition assessment, condition diagnosis and prediction, so as to realize intelligent Evaluate the health status and maintenance cycle of equipment, and complete the life-cycle health prediction and cycle management of equipment assets.

Contents of the invention

The purpose of the present invention is to provide a multi-layer, large-span and big-data-oriented power equipment status monitoring and evaluation system, which is characterized in that the equipment status monitoring and evaluation system is divided into four layers: collection and convergence layer, station control layer, provincial Network layer and headquarters layer; the collection and convergence layer is divided into a convergence subsystem and a collection subsystem; the station control layer includes a status monitoring server, a workstation, a mobile terminal access device and a mobile terminal; the status monitoring server stores a gateway The transmitted data is connected to the workstation and mobile terminal access device through Ethernet;

The provincial network layer is built based on a cloud platform, including a big data management platform and a status evaluation system based on data mining algorithms. Considering the security of the cloud platform, use a firewall to isolate the cloud platform from the external network, and install an intrusion detection system to prevent malicious attacks;

The headquarters layer includes a decision management workstation, a large screen server, and a decision support server; the headquarters layer obtains and summarizes evaluation data, and the decision management workstation obtains early warning data according to the evaluation data, submits fault locations and early warning levels, and outputs results on the large screen server to realize The evaluation results are visualized; the workstation administrator gives the final decision to provide further decision support for the evaluation results.

As the bottom layer of the whole system, the acquisition subsystem includes multiple primary equipment status monitoring IED groups, and the status monitoring IEDs are directly attached to the primary equipment; various sensors in the status monitoring IEDs respectively collect primary equipment related information, and the data processing module summarizes And perform simple calculations, the ZigBee module sends information to the converging IED in the form of broadcasting, here setting the broadcasting radius to 1 hop can meet the needs of the system; ZigBee is a short-distance, low-complexity, low-power consumption, low-speed , Low-cost two-way wireless communication technology. It is mainly used for data transmission between various electronic devices with short distance, low power consumption and low transmission rate; IED is the abbreviation of intelligent electronic device.

The convergence subsystem includes a convergence IED group and a coordination concentrator; various primary equipment convergence IEDs form a convergence IED group; the coordination concentrator includes a coordinator and a gateway; the convergence IED group expands the ZigBee transmission range, and the convergence IED receives and collects sub-systems The broadcast message sent by the status monitoring IED of the system is identified first, and only the message sent by the corresponding status monitoring IED is processed; the ZigBee module sends the information processed by the aggregated IED to the coordinator through unicast; the coordinator is responsible for the establishment of the entire network, Maintain and summarize the information sent by each converged IED, use the optical fiber to transmit the data to the gateway through the RS-485 serial port, the gateway performs protocol conversion, and transmits the data to the server through the Ethernet.

The workstation mainly includes a monitoring workstation, an engineer workstation, and a data operation workstation; the monitoring workstation provides services such as graphical browsing, alarm, monitoring, and control of equipment status monitoring data; the engineer workstation provides engineers with maintenance and improvement of the status monitoring system. The data operation workstation provides data browsing, exporting, querying, printing and other services. The mobile terminal accesses the status monitoring server through the mobile terminal security access device, and the mobile terminal mainly realizes functions of failure notification and personnel notification. The condition monitoring server is also responsible for transmitting data to the provincial network layer. The whole station control layer system adopts C/S structure.

The provincial network layer receives the data transmitted by the station control layer, and through transformation, cleaning, integration, classification, and unstructured data feature extraction technology processing on the big data management platform, the data with higher utilization rate is obtained, and the ETL tool is used Extract and transform the data and load it into the data warehouse; conduct preliminary query and fault analysis on the data in the data warehouse, and if a fault is found, send an alarm to the station control layer, and the station control layer receives the alarm and repairs the fault in time.

In the state assessment system based on data mining algorithms, the data is further analyzed and the state assessment is carried out; methods of time series analysis, cluster analysis, classification analysis, unstructured data feature analysis, association analysis and/or regression analysis are used Perform data analysis and use the log generator to generate log files; use the state assessment algorithm to evaluate the data analysis results, diagnose faults, and complete risk assessment. The provincial network layer transmits the data to the headquarters layer through Ethernet.

The identity identification and only processing the messages sent by the corresponding state monitoring IEDs means that the GIS aggregation IED only processes the messages sent by the GIS state monitoring IED group.

The ZigBee module should ensure the normal communication of the entire ZigBee network during the process of sending the information processed by the aggregation IED to the coordinator through unicast, that is, the status monitoring IED is set as a terminal node, the aggregation IED is set as a router node, and the coordinator Set as a coordinator node; among them, the terminal node is mainly responsible for data collection, can only send data, and cannot forward messages from other nodes; the router node is responsible for the routing of data packets, and the coordinator is responsible for the establishment and maintenance of the entire network, and can pass The serial port is connected to the gateway.

The beneficial effect of the present invention is that it solves the problems existing in the current power equipment status monitoring system, organically combines advanced wireless sensor network technology with the power equipment status monitoring system, and proposes a new multi-layer power equipment status monitoring system architecture with a large network span , from the primary power equipment terminal to the provincial network headquarters level to achieve full digital data transmission and information integration; introduce a cloud computing platform based on big data analysis to maximize data sharing and process massive monitoring data; the system is layered State assessment, equipment failure prediction, system risk assessment based on multi-temporal state assessment, etc., provide powerful data guarantee for intelligent decision support, so as to realize intelligent assessment of equipment health status and maintenance cycle, and complete life-cycle health prediction and cycle management of equipment assets .

Description of drawings

Figure 1 is an overall structure diagram of a multi-layer and long-span power equipment condition monitoring and evaluation system for big data.

Figure 2 is a software structure diagram of the headquarters layer and the provincial network layer of the big data-oriented power equipment condition monitoring and evaluation system.

Figure 3 is a structural diagram of the collection and convergence layer and the station control layer of the big data-oriented power equipment condition monitoring and evaluation system.

Figure 4 is a structural diagram of the primary equipment unit of the big data-oriented power equipment condition monitoring and evaluation system.

detailed description

The present invention provides a multi-layer, large-span and big-data-oriented power equipment status monitoring and evaluation system. The preferred embodiments will be described in detail below with reference to the accompanying drawings. It should be emphasized that the following description is only exemplary and not intended to limit the scope of the invention and its application.

Figure 1 shows the general structure diagram of a multi-layer and long-span power equipment condition monitoring and evaluation system oriented to big data. In Figure 1, the multi-layer, long-span, and big-data-oriented power equipment status monitoring and evaluation system is divided into four layers, namely the collection and convergence layer, station control layer, provincial network layer, and headquarters layer; the collection and convergence layer is further divided into aggregation Subsystem and acquisition subsystem; the station control layer includes a status monitoring server, a workstation, a mobile terminal access device and a mobile terminal; the status monitoring server stores the data transmitted by the gateway, and accesses the workstation and the mobile terminal through Ethernet The devices are connected; the provincial network layer is built based on the cloud platform, including a big data management platform and a status evaluation system based on data mining algorithms. The headquarters layer includes a decision management workstation, a large screen server, and a decision support server; the headquarters layer obtains and summarizes evaluation data, and the decision management workstation obtains early warning data according to the evaluation data, submits fault locations and early warning levels, and outputs results on the large screen server to realize The evaluation results are visualized; the workstation administrator gives the final decision to provide further decision support for the evaluation results.

The collection and convergence layer includes various state monitoring IED groups and convergence subsystems. Each status monitoring IED collects relevant information and sends the information to the aggregation subsystem, which aggregates the information and transmits it to the station control layer.

The state monitoring server of the station control layer stores the data transmitted by the collection and convergence layer, and is connected with the workstation and the mobile terminal. Users access the server through workstations and mobile terminals. The server transmits the data to the provincial network layer.

The provincial network layer receives the data transmitted by the station control layer, and processes it on the big data management platform through transformation, cleaning, integration, classification, and feature extraction of unstructured data to obtain data with a higher utilization rate. Then further analyze the data and use the status assessment algorithm to evaluate the data, analyze the results, diagnose the fault, and complete the risk assessment. The provincial network layer transmits data to the headquarters layer through Ethernet.

Figure 2 shows a software structure diagram of the headquarters layer and the provincial network layer of a big data-oriented power equipment condition monitoring and evaluation system.

The provincial network layer is built based on a cloud platform, including a big data management platform and a status evaluation system based on data mining algorithms. Considering the security of the cloud platform, a firewall is used to isolate the cloud platform from the external network, and an intrusion detection system is installed to prevent malicious attacks.

The provincial network layer receives the data transmitted by the station control layer, and processes it on the big data management platform through transformation, cleaning, integration, classification, and feature extraction of unstructured data to obtain data with a higher utilization rate. Use ETL (Extract Transform Load) tools to extract data, transform it and load it into the data warehouse. Carry out preliminary query and fault analysis on the data in the data warehouse. If a fault is found, an alarm is sent to the station control layer. The station control layer receives the alarm and repairs the fault in time.

In the state assessment system based on the data mining algorithm, the data is further analyzed and the state assessment is performed. Use time series analysis, cluster analysis, classification analysis, unstructured data feature analysis, correlation analysis, regression analysis and other methods to analyze data, and use the log generator to generate log files. Use state assessment algorithms to evaluate data analysis results, diagnose faults, and complete risk assessments. The provincial network layer transmits data to the headquarters layer through Ethernet.

The headquarters layer is to use the evaluation results for further decision support. The headquarters layer obtains and summarizes the evaluation data, obtains the early warning data based on the evaluation data, submits the fault location and early warning level, and draws the output results to realize the visualization of the evaluation results. The workstation administrator makes the final decision.

Fig. 3 is a structural diagram of the collection and convergence layer and the station control layer of a big data-oriented power equipment status monitoring and evaluation system provided by the present invention. In Fig. 3, the collection and convergence layer is further divided into a convergence subsystem and a collection subsystem.

The acquisition subsystem, as the bottom layer of the entire system, includes a variety of primary equipment status monitoring IED groups, such as: GIS (gas insulated switchgear) status monitoring IED group, high voltage circuit breaker status monitoring IED group, arrester status monitoring IED group groups etc. Each primary device requires multiple condition monitoring IEDs to form a condition monitoring IED group. Condition monitoring IEDs are directly attached to primary equipment such as GIS, high-voltage circuit breakers, and lightning arresters. Various sensors in the status monitoring IED collect device-related information once, and the data processing module summarizes and performs simple calculations. The ZigBee module sends a broadcast to send the information to the converging IED. Here, setting the broadcast radius to 1 hop can meet the needs of the system.

The convergence subsystem includes a convergence IED group and a coordinating concentrator. All kinds of primary equipment converge IEDs to form a converged IED group. The coordination concentrator includes a coordinator and a gateway. Converging IED groups expands the ZigBee transmission range. The converging IED receives the broadcast message sent by the state monitoring IED of the collection subsystem, first performs identification, and only processes the message sent by the corresponding state monitoring IED. For example, the GIS aggregation IED only processes the messages sent by the GIS status monitoring IED group. The ZigBee module sends the information processed by the aggregated IEDs to the coordinator through unicast. The coordinator is responsible for the establishment and maintenance of the entire network, and summarizes the information sent by each converging IED, and transmits the data to the gateway through the RS‐485 serial port using optical fiber. The gateway performs protocol conversion and transmits the data to the server via Ethernet.

In order to ensure the normal communication of the entire ZigBee network, the state monitoring IED is set as a terminal node, the aggregation IED is set as a router node, and the coordinator is set as a coordinator node. The terminal node is mainly responsible for data collection, it can only send data, and cannot forward messages from other nodes. Router nodes are responsible for the routing of data packets. The coordinator is responsible for the establishment and maintenance of the entire network, and can be connected to the gateway through the serial port.

The station control layer includes a status monitoring server, a workstation, a mobile terminal access device and a mobile terminal. The state monitoring server stores the data transmitted by the gateway, and is connected with the workstation and the mobile terminal access device through Ethernet. The workstations mainly include monitoring workstations, engineer workstations and data operation workstations. The monitoring workstation provides services such as graphical browsing, alarming, monitoring, and control of equipment status monitoring data. The engineer workstation provides services for engineers to maintain and improve the condition monitoring system. The data operation workstation provides data browsing, exporting, querying, printing and other services. The mobile terminal accesses the status monitoring server through the mobile terminal security access device, and the mobile terminal mainly realizes functions of failure notification and personnel notification. The whole station control layer system adopts C/S structure.

Fig. 4 is a structural diagram of a primary equipment unit of a multi-layer, large-span and big-data-oriented power equipment condition monitoring and evaluation system provided by the present invention. The multi-layer and large-span big data-oriented power equipment condition monitoring and evaluation system needs to monitor six types of primary equipment: GIS, high-voltage circuit breaker, transformer, capacitive equipment, generator and lightning arrester.

The primary equipment unit includes a primary equipment body and a primary equipment intelligent component cabinet. The primary equipment body contains several condition monitoring IEDs directly attached to the primary equipment, and the primary equipment intelligent component cabinet contains a primary equipment aggregation IED.

The structure of high-voltage circuit breakers, transformers and other primary equipment bodies and intelligent component cabinets is shown in Figure 4. The GIS body includes high-voltage part characteristics IEDs, circuit breaker characteristics IEDs, switch action judgment IEDs, and arrester characteristics IEDs directly attached to the GIS. The grounding point IED and various sensors in the status monitoring IED collect relevant information respectively, and the status monitoring IED summarizes and performs related calculations and then sends the information to the aggregation IED of the GIS intelligent component cabinet. The converging IED receives the information of the corresponding state monitoring IED of the acquisition subsystem, performs summary and related calculation, and sends the information to the coordinator concentrator.

The primary equipment GIS status monitoring IED specifically includes: high-voltage part characteristic IED, circuit breaker characteristic IED, switch action judgment IED, arrester characteristic IED, grounding point IED. The items that need to be monitored by the IED for the characteristics of high-voltage parts include: insulation characteristics; conductivity characteristics; SF ₆ gas characteristics. The corresponding monitoring parameters are: acceleration; temperature; pressure. The item to be monitored by the arrester characteristic IED is the circuit breaker characteristic, and the corresponding monitoring parameter is the action time. Switch Action Judgment The items to be monitored by the IED are the action judgment of the isolating switch and the grounding switch, and the corresponding monitoring parameter is the action. The item to be monitored by the arrester characteristic IED is the arrester characteristic, and the corresponding monitoring parameter is the current. The item to be monitored by the ground point IED is the ground point fault, and the corresponding monitoring parameter is the ground fault. Table 1 shows the functional structure of IEDs for primary equipment condition monitoring such as high-voltage circuit breakers and transformers. Table 1 Functional structure of primary equipment status monitoring IED.

The multi-layer and large-span big data-oriented power equipment condition monitoring and evaluation system has six types of monitoring equipment in the acquisition subsystem: GIS, high-voltage circuit breaker, transformer, capacitive equipment, generator and lightning arrester. Each type of equipment has several status monitoring IEDs, one status monitoring IED corresponds to one or more monitoring items, and one monitoring item corresponds to one or more monitoring parameters. The monitoring parameters can be directly monitored by the relevant sensors, and the indicators of the monitoring items are calculated by the parameters monitored by the sensors in the corresponding IED, and the results are shown in Table 2;

Table 2, the condition monitoring IED function table of the big data-oriented power equipment condition monitoring and evaluation system

Claims (8)

1. a multilayer large-span is towards the power equipment state monitoring of big data and assessment system, it is characterised in that described in set Standby status monitoring is divided into four layers with assessment system: gather convergence-level, station level, province's stratum reticulare and general headquarters' layer；Described collection convergence-level It is divided into again convergence subsystem and acquisition subsystem；Described station level includes that status monitoring services device, work station, mobile terminal access Device and mobile terminal；The data of described status monitoring services device storage gateway transmission, and by Ethernet and work station and shifting Dynamic terminal access device is connected；

Described province stratum reticulare is built based on cloud platform, comments including big data management platform and state based on data mining algorithm Estimate system, it is contemplated that the safety of cloud platform, utilize fire wall cloud platform to be isolated with external network, and be mounted with intrusion detection System, prevents malicious attack；

Described general headquarters layer includes decision-making management work station, big ping server and Decision Support Servers；General headquarters' layer obtains and collects Assessment data, decision-making management work station obtains warning data according to assessment data, submits abort situation and advanced warning grade to, at large-size screen monitors Server output result, it is achieved assessment result visualizes；SMT Station Management person provides final decision, and assessment result is entered one Step decision support.

The most according to claim 1, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special Levying and be, described acquisition subsystem is as the whole system bottom, including multiple primary equipment status monitoring IED group, state Monitoring IED is attached directly on primary equipment；In status monitoring IED, various kinds of sensors gathers primary equipment relevant information respectively, Data processing module collects and carries out simple computation, and ZigBee module uses the form sending broadcast to send information to converge IED, is set to 1 jumping broadcast radius here and just disclosure satisfy that system needs；Wherein, IED is the abbreviation of intelligent electronic device； ZigBee be a kind of closely, low complex degree, low-power consumption, low rate, the bidirectional wireless communication technology of low cost, be mainly used in away from Carry out data transmission between short, low in energy consumption and that transfer rate is the highest various electronic equipments.

The most according to claim 1, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special Levying and be, described convergence subsystem includes converging IED group and coordinating concentrator；All kinds of primary equipments converge IED composition and converge IED Group；Described coordination concentrator includes coordinator and gateway；Converge IED group and expand ZigBee transmission range, converge IED reception and adopt The broadcast that the status monitoring IED of subsystem sends, first carries out identification, only processes corresponding state monitoring IED and sends out The message sent；ZigBee module is sent to coordinator by converging the information after IED processes by clean culture；Coordinator is responsible for whole net The establishment of network, maintenance, and collect the information that each convergence IED sends, utilize optical fiber to be transferred data to by RS-485 serial ports Gateway, gateway carries out protocol conversion, and transfers data to server by Ethernet.

The most according to claim 1, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special Levying and be, described work station mainly includes monitor workstation, engineer work station and data operation element station；Described monitoring work The services such as offer primary equipment Condition Monitoring Data of standing graphically browses, alerts, monitors, control；Described engineer work station is Engineer provides and safeguards and improve the service of condition monitoring system, and described data manipulation work station provides browsing data, derives, looks into Inquiry, printing etc. service, and mobile terminal accesses status monitoring services device by mobile terminal safety access device, and mobile terminal is main Realizing malfunction notification, personnel's informing function, status monitoring services device is also responsible for transferring data to province's stratum reticulare, whole station level system System uses C/S structure.

The most according to claim 1, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special Levying and be, described province stratum reticulare receives the data of described station level transmission, big data management platform by conversion, cleaning, integrated, The technical finesse that classification, non-structural data characteristics are extracted, the higher data of the rate that is obtained by, utilize ETL instrument that data are carried out It is loaded into data warehouse after extraction, conversion；The data of data warehouse are carried out preliminary search and accident analysis, if it find that therefore Barrier, alerts to described station level, and station level receives alarm, and fault is carried out on-call maintenance.

The most according to claim 1, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special Levying and be, data, in described status assessing system based on data mining algorithm, are further analyzed by described general headquarters layer And carry out state estimation；Utilize time series analysis, cluster analysis, classification analysis, the analysis of non-structural data characteristics, association analysis And/or the method for regression analysis carries out data analysis, and log generator is utilized to generate journal file；Utilization state assessment algorithm Assessment data results, tracing trouble, and complete risk assessment, save stratum reticulare and transfer data to general headquarters' layer by Ethernet.

The most according to claim 1, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special Levy and be, described in carry out identification, only processing the message that corresponding state monitoring IED sends is that GIS converges IED and only processes GIS The message that status monitoring IED group sends.

The most according to claim 2, multilayer large-span is towards the power equipment state monitoring of big data and assessment system, and it is special Levy and be, during the information after IED processes that converges is sent to coordinator by clean culture by described ZigBee module, it should really Protect the proper communication of whole ZigBee-network, i.e. status monitoring IED is set to terminal node, converge IED and be set to router Node, coordinator is set to coordinator node；Wherein, terminal node is mainly responsible for the collection of data, can only send data, it is impossible to Forward the message of other nodes；Router node is responsible for the Route Selection of packet, and coordinator is responsible for the establishment of whole network, dimension Protect, and can be connected with gateway by serial ports.