Conference Record of the 2004 IEEE International Symposium on Electrical Insulation, Indianapolis,IN USA, 19-22 September 2004
On-line Multi-sensor Monitoring System for Insulation Condition of Oilimmersed Power Transformer Wen-Bin Zhao', Guan-Jun Zhangl, Yan Sun', Zhang Yanl and Da-Ke Xu2 1 School of Electrical Engineering, Xi'an Jiaotong University, Xi'an 710049, P.R China 2 GuodianNanjing Automation Co.Ltd., Nanjing, 210003, P.R China
[email protected] Abshocr: An on-line monitoring and diagnostic system for a 22OkV oil-immersed power transformer with 3 *dings has
been established in a substation Of China. The operation monitoring and insulation condition evaluation were integrated into this system. Many sensors were applied to monitor multiple insulation items such as partial discharge, dissolved gas, moisture in oil, oil temperature, coil hot spot temperature, iron core current, bushing condition and so on. The structure of the system was introduced and a diagnostic flow, ria information fusion technology, was presented. Based on the system, it is easy to obtain the operating condition and insulation condition of the transformer.
substation of China. The system could be divided into 3 layers, i.e. the sensor layer, data acquisition layer and diagnostic layer, as shown in Figure 1,
INTRODUCTION A HV power transformer is one of the key components in a power system. Building an on-line monitoring system for its insulation condition is an effective method in reducing the failure rate of power transformers [I]. An on-line monitoring system for power transformers is a multi-sensor system utilizing many technologies such as sensor, computer and communication, etc [ Z ] . In this system, the communication method of applying local area network (LAN) technology in the field was applied. This enhanced the capacity of transporting data and made remote control easier. In the system, we applied the database software in the Windows 98/2000 Operation System (OS) and brought out a universal data interface, which allowed the system to be interconnected with another system easier. ~~
~i~~~~1 - me smcture of on-line monitoring & diagnostic system
Sensors Layer
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Ahout 20 sensors were installed, which could be roughly divided into 2 types. One type outputs the voltage, current or .on/off signals. These signals had to be digitized by an A/D converter and digital coder in the next layer. A second type had changed the monitoring parameters into digital data. Table 1 shows the specifics for all the sensors.
Based on the software and hardware structure of this system, a link between the monitoring system and management information system ( M S ) was presented. The insulation condition monitoring system would be one part of an enterprise network, which will make monitoring the transformer more convenient and even enable the transformer to he connected to the Intemet via professional software and remote control could be implemented easily in this system.
Table 1
For processing multiple different kinds of information from the sensors, the information fusion idea was applied to this system. A model of the diagnostic flow is presented, which attempts to provide a solution that is helpful to evaluate the insulation condition of the transformer based on a multisensor system The transformer had been in service for more than 10 years. We installed most of the sensors without changing the transformer. Figure 2 shows the approximate position of all sensors.
STRUCTURE OF MONITORING SYSTEM The on-line monitoring system for a 220kV oil-immersed power transformer with 3 windings has been established in a
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serial port was installed, which increased the number of serial ports and allowed the IPC to he connected with more than 2 serial output sensors at one time.
Diagnostic Layer Data from the data acquisition layer will he transferred to the diagnostic layer. The diagnostic layer was install on a personal computer (PC) in the control room and consisted of a database and diagnostic software. This handled the functions of managing monitoring data, displaying the operation condition, and evaluating the insulation condition etc. The shucture of the database system is described in Figure 4 with the diagnostic layer set up on the seiver. I ) Dissolved gas in oil
2) Pcial discharge
4)Current of bushing 3) Moisture in oil 5 ) Current of iron corel 6) Top oil temperature 7) Ambient temperame 8) Load current 9) Onioff state of cooler, step position of tap changer Figure 2 - T h e distribution of sensors
Data AcquisitiotvLayer All signals and data from the sensors were input into the data acquisition layer as shown in Figure 3. Ipc
Figure 4 - The shucture of database system
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Figure 3 - The configuration of data acquisition layer
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The core of this layer was an industrial control computer WC). For adapting the multiform outputs of the sensors, the IPC was-equipped with many standard interface cards. We selected two 16-channel AID cards to avoid the concem for a common interference and photocoupler circuits were applied to ensure that the AID card and the motherboard of the IPC would not he damaged by surge voltage. For the communication interference, a coaxial LAN card was used to build the LAN in the field. The coaxial cable linked the IPC to the control room of the substation. The wide band of the LAN improved the communication quality and made remote control possible. The YO card could convert the odoff condition into a digital signal. A card extending the
Windows 98 & Windows 2000 were loaded as the,OS of the P C and PC respectively, and the standard edition and the desktop edition of MS SQL Server database software was installed. Data acquired was preprocessed and initially stored in tables and then transfered automatically to the database of the PC in the control room at a fixed interval .using the linked server function of the database software [3]. Remote data source and inquiry was built up to implement the sharing of data. The real time data and historical data could be accessed by the diagnostic software.
LINK TO ENTERPRISE NETWORK
I.
Most companies have established management information system (MIS). Generally there are master databases and database management systems (DBMS)in the network [4]. Some companies have web sewer capabilities, which connect to the Intemet. The link between the company's network and the monitoring system could be established based on computer communication technology. ,
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Structure of Link All the files regarding the power transformer were recorded in a master database. Our system, with the many data interfaces, could be connected easily with the companies’ local area network. Based on MS SQL Server, our system allowed any authorized client to access the data by open database connectivity (ODBC) interface. At the same time, the monitoring system could access information on the power transformer fiom the master database. In other words, the monitoring system had become a part of company’s network and a new network structure formed. We divided the whole communication network into 2 layers, the management layer and measurement layer, as shown in Figure 5.
. Control Terminal
Control(LControl1ed Controlled Terminal Termlnal
Figure 6 - Model of remote control
Remote control software was applied in the system without any modification. General remote control software consists of a control and a controlled terminal. If a supervisor wants to control the IF’C in the field, there are 3 steps which need to be executed gaining access to the PC in the control rwm, initiating the remote control software in the PC and operating the IPC. In this manner, any portable or fixed control terminal could implement initiating a diagnosis, accessing data, adjusting parameters, etc. A test of the remote control using PSTN across 2 provinces, Guangdong and Hunan, has proven the validity of the system. It is possible, if a PC in the control m m was connected to the Internet, a broader and more convenient control means could be implemented [5].
DIAGNOSTIC FLOW BASED ON INFORMATION FUSION
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Information fusion technology has been used in the field of military affairs successfully for the past decades, especially in the command, control, communication and intelligence (C’r). Now this technology has gradually been introduced into civillian applications [ 6 ] . It is one of the methods that is capable of organizing the data 60m every sensor to reflect the actual condition, referenced hy many mathematical methods such as signal processing, optimization, artificial neural network etc. It is suitable to apply the information fusion technology to this multi-sensor system.
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Figure 5 - Link behvem enterprise network and monitoring system
The management layer includes the master database, MIS and web server, etc. The master database is the core of this network. Most managers have access to the master database via MIS or web server. The monitoring system was located in the measurement layer. The PC in the control room was the bridge, which linked the 2 layers to each other. The bridge could be a different physical link. Some substations, far *om towns, were not equipped with a commercial network cable so our system used a communication interface to a public switch telephone network (PSTN). In fact, after d any adding some devices the 2 layers could be c o ~ e c t e by one type of public communication media such as GSM, optical cable, microwave and so on.
The system’s sensors generated large amounts of information, hut only a single conclusion regarding the operating and insulation conditions of the transformer should be drawn. A diagnostic flow based on multi-sensor information fusion is presented. The fusion system was easily setup within the monitoring system for HV power transformer without changing the hardware. A parallel structure with feedback would be build up as shown in Figure I.
Remote Control
In Figure 7,the lines with the arrows indicate the flow of the information. A variety of useful information from different sensors, PD, dissolved gas, core current, oil temperature, moisture in oil, and hushing current, etc is generated. The raw data from these sensors, yi ( i=l, 2, ..., 13), are sent to
Not only could data be transferred conveniently, but also remote control could be implemented based on this communication s t r u c t u ~The control model is as shown in Figure 6.
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discriminators, Si ( i=l, 2, ..., 7). respectively. Every discriminator is a partial fusion system. It is bener to select different sensors with a strong relationship as the input for a discriminator; this will make the fusion more reasonable and effective. A different fusion strategy could be applied in the seconday discriminators So and S8.
communication channel. Multiple types of interfaces and open data structures were connected with sensors and different types of systems. Remote control based on PSTN could be implemented conveniently in this type of network structure. Applying multi-sensor information fusion technology to distributed calculations for every discriminator, could decrease the number of diagnostic rules and make more appropriate diagnostic methods be selected respectively.
ACKNOWLEDGMENT
REFERENCES ._________. .--________. Partial Fusion Fusion Center
Sensor
I . Yan, 2. On-line Monitoring for Electrical Insulation, Press of China Power, 1995, p. 5 .
raw daufioom sensors ‘
partial discriminator output ofdiscriminator
2. Van Bolhuis, J.P., E. Gulski and J.J Smit “Monitoring . and Diagnostic of Transformer Solid Insulation” IEEE Trans Power Delivery, Vol. 17 No. 2, April 2002, pp. 528-536.
F’igure 7 - Diagnostic flow based on information k i o n
Partial fusion was a key process, which determined the effectiveness of whole system. Each discriminator had to evaluate several condition codes according to the r a y data. S, could output the type and grade of PD. S2 could tell the value and trend of gas concentration. Similarity S2, S3and Ss show the value and trend of core current and moisture in oil respectively. Sq. S6 and S7 were small fusion subsystems. S, . could calculate the hotspot temperature of the coil. Ss and S, could discriminate the failure model of the bushing 171. Ss was a special discriminator, which could covert the fault panems into specific codes according to experience. So drew a conclusion about the condition of transformer using the artificial intelligence (AI) method. If the conclusion was in conflict with a discriminator, the feedback mechanism would adjust the threshold of the discriminator.
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CONCLUSIONS
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We gratefully acknowledge the cooperation .of Tehian Electric Apparatus Stock Co. LTD P E A ) in the research and development of this monitoring and diagnostic system.
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y,[i=lJ, ...,13) S, ( i=lJ,...,7) U;[ i=O,l,...,8)
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3. Microsoft Corporation. Microsoft Introduction,.l998, p. 336, ..
SQL
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Server
4. Sbangl Y., M. Z. Yang, Z. Yan, H. M. Wang and R Li “Expert system for Insulation Diagnosis and Management”. Proceedings of the 2000 Conference on Propelties and Application of Dielectric and Materials. pp. 693-696.
5 . Zhao, W. B., G. I. Zbang andY. Zhang “Remote On-lime Condition Monitoring and Diagnosis System Based on Intemet Techniques for Power Equipment”, Electric Power, Vol. 36 No. 4, Apnl2003, pp.6043. 6. Steinberg, A.N. “Data Fusion System Enbneering”. IEEE A E S S System Magazine, Vol. 16No.6,2001, pp.7-14.
7. Zhao, W.B., M. Dong, Z. Yan, and M. ML&I “Application of Clustering Fusion for Multisensor On-line Monitoring System of HV Power Equipments”. Preceedings of the 2003 International Symposium on High Voltage Engineering. CD-ROM
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An on-line monitoring and diagnostic system for a 220kV
power transformer had been established, and some experience was acquired. On-site application of LAN in the field proved possible, which increased the capacity of the
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