ARTIFICIAL NEURAL NETWORK FOR OVERHEAD TRANSMISSION LINE MONITORING

The 6 th PSU-UNS International Conference on Engineering and Technology (ICET-2013), Novi Sad, Serbia, May 15-17, 2013 University of Novi Sad, Faculty of Technical Sciences ARTIFICIAL NEURAL NETWORK FOR OVERHEAD TRANSMISSION LINE MONITORING Yang Zhiwang 1, Chen Weiyun 2, Xu Ming, Prof. 3 1 Glorious Sun School of Business and Management, Donghua University, China Shanghai Electric Power Design Institute Co., Ltd., Shanghai. 2 Glorious Sun School of Business and Management, Donghua University, China 3 Glorious Sun School of Business and Management, Donghua University, China Abstract: This paper introduces a new idea of overhead transmission power line on-line monitoring, which includes the equipment components and the functions of the system. The system is designed for monitoring icing situation and detecting the insulator damage as well as other safety information of the power line. Artificial Neural Network(ANN)technology is used in this system, and the test examples of remote monitoring of the system in Shanghai China are also provided in the paper. Keywords: overhead transmission lines/ monitoring the power line/artificial neural network(ann)/ remote monitoring tests 1. INTRODUCTION On-line remote monitoring of overhead transmission power line is one of the key bases for Smart Grid [1]. China has suffered greatly of power system accidents in 2008, which were caused by heavy snow in the south China, usually this area never having such abnormal low temperature and big icing disaster, and more than 53.79 billion of RMB (equivalent of 8.54 billion of USD) direct economic loss and huge influence to social lives, including the death of 60 people, traffic paralysis and so on [2]. After that China pays great attention to power line safe operation and the power supply reliability. With the development of the technology of power transmission online monitoring and fault diagnosis, Advanced Transmission Operation (ATO) technology has been developed in China, in which the on-line remote monitoring system together with Artificial Neural Network (ANN) technology is used. 2. DEVELOPMENT OF TRANSMISSION LINE INTELLIGENTIZED For the reason of the grid security, reliability, economic, efficient and environment-friendly, power quality, adaption of development of electricity market, and so on, it is necessary to develop the smart grid and to speed up the development of state s intelligent maintenance of the transmission line. 2.1 Transmission line on-line monitoring system After many years of research, the engineers of Shanghai Power Bureau have developed a new type of system to conduct monitoring functions for power transmission line. The system consists of five sets of sensors,including insulator sensor (camera), line temperature sensor, current sensor, image sensor (micro cameras) and other devices such as icing monitoring, meteorologic station, and the connecting center device. The system takes 1

on-line monitoring of the transmission lines via high speed communication networks, collecting information of safety in real time. All kinds of sensors are installed on the transmission line tower directly to obtain the operation monitoring signals which are shown in Figure 1. Fig.1 Tower positioning of sensor devices These sensors operate in different ways for their different functions, for example, the temperature sensor applies infrared technology, the current sensor uses mutual inductance, and the force sensor is used in measuring the weight of ice which is covered on the power line in icing days. Once the information is collected by these sensors and devices, it will be transmitted to the connecting center device, and then it will be sent to the monitoring center wirelessly. 2.2 Functions of the monitoring system There are two main functions possessed by the system which are presented in the following. 2.2.1 Transmission lines icing situation monitoring The system has the function of monitoring the icing situation online. Serious icing situation is the cause of interphase flashover, equipment damage, line outage and other accidents which cause the safety problems of the line, so it is needed to monitor the line in the operation. There are many methods which can be used in the system, such as image method, weighing method and others. The image method is to install a remote video device in the tower pole, to collected pictures, among which the weighing method is most suitable used in this system. The weighing method uses wire inherent geometry, the icing area is calculated, then translated into an equivalent its thickness. The force sensor is installed in the transmission lines and the principle of which is to get the variance between normal and icing situation by the sensor signals. This method is direct, simple and relatively reliable. In the icing hit areas, it is consisted by monitoring and early warning, melting ice and so on. It can improve the safety operation of the grid. 2.2.2 Transmission line insulator flashover monitoring Usually, there are two kinds of damages of the insulators: one is caused by flashover, which changes the surface of the insulator with marks that will cause the leakage of the currents, and even seriously, the insulator will be broken physically. Early detecting such damage will benefit the operation safety of the line. The flashover occurs in the surface of insulators and makes burning marks on them being visible. Usually the burning marks of the insulator do not cause lose of insulating performance of them. The breakdown, which is another kind of damage, is caused by the flashover. The insulator flashover discharge between iron cap and iron pin ceramic, the trace can not be seen, but the insulation of the insulators has been lost, and it may be completely destroyed due to electric arcing. [3] Currently, the experts proposed online insulator flashover monitoring to diagnose the probability of flashover occurrence in advance in order to provide some effective measures to prevent such accidents. Because of the insulator flashover has been a hidden risk of transmission line. The CIGRE (Conseil International Des Grands Reseaux Electrocutes) recommended maximum leakage current method which is usually called I h law to reflect the comprehensive factors such as voltage, climate and pollution which can explain the formation of flashover. The measurement of leakage current is relative convenient, especially it is suitable for online monitoring. In the 2

insulator leakage current online monitoring, the current sensor is installed on the insulator, it can real-time monitor the leakage current. Before insulator flashover, the common leakage current sensor technology provides that max leakage current is dynamic value (I h ). According to the on-set record, numerical and laboratory measure, I h value may be determined. The relative literature supposes alarm of leakage current is 40mA. Based on information of leakage current, the expert makes judge for the insulator pollution degree, and makes the warning notices of insulator flashover. 3. TRANSMISSION LINE OPERATION CONTROL SYSTEM At present, human patrol inspection of power transmission line is still the main method in China. How to develop a smart monitoring transmission line system to reduce huge human work load to deal with fast increase of transmission line expansion is the urgent task faced by China National Grid. Shanghai Power Bureau conducted a research of on-line monitoring system of transmission line and the design ideas are illustrated bellow. 3.1 Remote video monitoring Transmission line remote visual monitoring system is made up by cameras which are installed in multiple towers. Remote video surveillance is an open system which adopts B / S (Browser / Server) way, the structure of the remote video site includes the image monitoring unit, wireless communication unit and the tower device center unit. The key functions of the monitoring system include image and signal acquisition, digital image compression, and remote transmission, which are all connected by the connecting center device. The monitoring system supervises the status of power transmission line (line temperature and current intensity), environment situation (surrounding temperature, sunshine intensity, humidity and wind speed), and the line equipment s mechanical characteristics and so on. The different types of sensors are used to conduct the tasks, such as the scene image sensor linked by Computer Control Display (CCD), the analog video signal camera which is digitized by dedicated video processing chip (e.g., SAA71, FPGA series) and etc. The on-site situation signal and image are collected through the video image camera and the sensors and then compressing and coding, finally be sent to monitoring center through GPRS(General Packet Radio Service)/CDMA/3G. According to the visual image information, the operators in control center can monitor tower and line s real time situation, and make the analysis of the transmission lines working status and make right decision to treatment actions, therefore it greatly increase the safety of the line and its reliability and reduce greatly human power intensity of line patrol operators. 3.2 Remote wireless communication Nowadays, one of the designs to develop high voltage transmission line is to apply the sensors which are installed on transmission line towers, the transmissions of the signals are based on wireless network, which has the functions of remote data and image transmission. The system that Shanghai Power Bureau developed has the functions of real time monitoring the temperature of the power line, environment situation, leakage current of insulators, and surface image of icing situation, therefore it realizes remote equipment man-free patrol supervision. Based on such system, the decision making of maintenance of the line equipment is faster than before, which enhances the safety of the line. The GPRS wireless transmission technology has become the first choice in the remote communication system, which mainly uses General Packet Radio Service GPRS/CDMA/3G technology, and connects with Internet web thru GGSN (Gateway GPRS Support Node), forms of the network of central computer multiple 3

users. With GPRS technology, the safe operation level of transmission line and intelligent management capabilities are raised greatly. In short, the wide application of wireless communication technology is an important step towards smart grid. 4. THE APPLICATION OF ARTIFICIAL NEURAL NETWORK(ANN) Artificial neural network (ANN) is used to monitor the transmission line safe operation condition. The monitoring and control center of transmission line received the information that GPRS/CDMA/3G transmitted, Artificial neural network will analysis and judges for transmission lines safe operation and makes diagnosis, makes warning notices of transmission line hidden fault. Shanghai Power Bureau has set up a diagnosis system which is based on the technology of ANN. The structural explanation of ANN and its application tests in Shanghai are presented as following. 4.1 The structure of artificial neural network (ANN) The artificial neural network is becoming an ideal tool for on-line monitoring of the transmission line because of its easy self-learning function. Figure 2 shows its simplified topology structure [4]. Fig.2 structure of TRLANN system As showed in Figure 2, the TRLANN (Transmission Line Artificial Neural Network) system is a complex structure including many extensively-connected nodes which consists of three layers that are called input layer, middle layer and output layer respectively. The input layer node receives the input signal from the external source,and temperatures (T), current intensity (I), voltage strength (U) are three chosen input elements to the nodes for the TRLANN system. After the input of the pattern which is going to be identified, this information is transmitted forward to each hidden layer node through network, and then, it will be transmitted to the output node under the activation of the hidden layer through network, (there are 4 nodes selected for the output layer of the TRLANN system, which responding to four common situation of the operating transformer: Y1 normal, Y2 overheating, Y3 out of order, Y4 approaching to replacement stage). The error back-propagation learning algorithm is used for the TRLANN system sample training. In the online monitoring of transmission line, the possible fault and the alarm signals are regarded as input characteristics data to train ANN s system. And then, the operator of the monitoring system can determine the fault nature and make the diagnosis to the serious situation according to the alarm signal. The output information of the TRLANN system through the output layer nodes corresponds to different fault status: the value of Y ranges from 0 to 1, if the value of Y1, Y2, Y3, or Y4 is greater than 0.5, the fault is existed. The value is closer to 1, which indicates the transmission line fault is more serious. TRLANN can implement on-line monitoring and fault diagnosis for transmission line. Its trend is almost perfect. The advantages of the system using ANN can be listed as below: 1. Greatly reduce the frequency of the scheduled outages, improve the reliability of power system operation. 2. Earlier detection of the equipment faults which enables timely actions to prevent economic losses. 3. Prolong the working life of the power equipments of the lines. 4.2 Diagnosis examples of ANN monitoring system Shanghai Electric Power Design Institute has put the diagnosis system which is linked with TRLANN system into practice, test 4

examples are given as below. The table gives out the online-measured leakage current date of the tested transmission line of FXBX220/100 which is carried out by the Shanghai Power Bureau in June 2010, as shown in able 1. Table 1 Leakage current of the test examples Insulator 315 377 365 number 50 Leakage current Environmental temperature Environment humidity Voltage level <30 36 79% 220(kV) 290 According to the learned knowledge of ANN, the results and measurements of the tested examples can be mainly drawn as following: No.365 insulator should be replaced because it has been seriously damaged (Leakage current=290ma); No.315 insulators should be cleaned because it has been polluted (Leakage current=50ma); No.377 insulator is normal (Leakage current<40ma). system is a significant step forward to the smart grid development. 6. REFERENCES: [1] Yu Yixin, Luan Wenpeng, Smart Grid and Its Implementations, Proceedings of the CSEE, Dec. 5, 2009,Vol.29 No.34, pp.1-8. [2] Ma Lijun, Sun Gennian, Ma Yaofeng, Wang Jiejie and Shu Jingjing, A Study on the Influence of Extreme Weather and Climate on Tourism:A Case on Snowstorm in 2008, Resources Science, Jan.2010,Vol.32,No.1, pp.107-112. [3] Mao Yingke, Guan Zhicheng, Wang Liming and Yue Bo, Prediction of Leakage Current of Outdoor Insulators Based on BP Artificial Neural Network, Proceedings of the CSEE, Sep. 2007,Vol.27 No.27, pp.7-12. [4] Gu xueping, Zhang Wenqin, Gao Shu, Sheng Siqing and Yang Yihan, Studies of Integrating Artificial Neural Networks with Expert System for Fault Diagnosis in Power System, Journal of The Hebei Academy of Sciences, 1995, Vol.3 No.4, pp.33-39. 5. SUMMARY The transmission line online-monitoring system is based on the combination of remote wireless communication (GPRS/CDMA/3G) and the technology of ANN. It consists of a set of sensors (insulator sensor, temperature sensor, current sensor and image sensor), meteorologic station and the connecting center device, enabling the functions such as unmanned remote monitoring, icing situation monitoring, flashover caused insulator s damage monitoring and so on. The system has been put into practice in Shanghai, China for 2 years and shows its reliability of the operation. Further seen from research job prospect, it has great potential. Due to its great advantages of online-monitoring, it is reasonable to expect a great practical need in China as well as in other countries. Therefore the 5