Shafi and Farouq Sultan for their help in conducting the lab experiments. ... [13] R.L. Vasquez-Arnez, M. G. M. Jardini, M. Masuda, L.A. Carita, J.A.. Jardini ...
Flashover Monitoring System Using Wireless Sensor Network Munir Al-Absi, Uthman Baroudi*, Khaled Al-Soufi** and Salam Zummo Dept. Electrical Engineering, Dept. Computer Engineering* Center for Engineering Research** King Fahd University of Petroleum and Minerals Dhahran, Saudi Arabia e-mail: {mkulaib, ubaroudi, kysoufi, zummo}@kfupm.edu.sa Abstract—Flashover of insulators in transmission and distribution electric power systems causes a reduction of the system reliability and costly outages for the power company and their customers. In this paper, we present a system in which a wireless sensor network is used for continuous wirelessly monitoring contamination in high voltage insulators. The new system consists of different sensor nodes (e.g. humidity, temperature and dust) mounted on a dummy insulator that has to be placed close to high voltage substation or transmission line tower. The proposed approach is based on the Equivalent Salt Deposit Density (ESDD) severity method in order to check the pollution level on the insulator and to correlate with flashover voltage levels of the insulator string. In this approach, the photons measurement level (i.e. light intensity) is adopted as an indicator to the accumulated pollution level on the insulators. Extensive lab tests were carried out using different pollutants. ESDD measurements have been collected for all the pollution tests performed in the lab and a relationship between these values and the light intensity values has been established to correctly model the contamination level. Using, the established relationship between EESD and light intensity shall enable the power system control unit to accurately predict the flashover and accordingly schedule its crew to visit the site and clean these insulators. Index Terms-- Flashover, High Voltage Insulator, Transmission Line Monitoring, Wireless sensor networks (WSN).
I.
INTRODUCTION
The economic activities within a society depend on existence of reliable electric network so that power is supplied to industry, offices and homes. One of the most important factors is the condition of high voltage transmission lines’ insulators. The high voltage insulators experience harsh environment in the form of extreme temperatures, dust, humidity and more importantly mineral laden air that deposits salt and other chemicals on the insulators. Deposited pollution over the insulator surface in addition to wetting parameters and high voltage stresses are the culprit for changing negatively the insulator performance and may cause total insulation failure. Such failures are very This work is supported by King Abdulaziz City for Science and Technology (KACST) under a project # ARP-30-134.
costly for the utilities, industry and end users especially when such failures occur during the peak hours. IEEE has defined flashover as “disruptive discharge through air around or over the surface of an insulator, between parts of different potential or polarity, produced by the application of a voltage such that the breakdown path becomes sufficiently large to create and maintain an electric arc” [1]. Industrial and coastal contamination of external insulators is the major cause for such events in normal power system operation. The probability of flashover on an insulator with pollution depends mainly on two factors: the degree of pollution and the wetting conditions. The pollution flashover process, as generally accepted, is that it consists of the following phases: deposition of the pollution on the surface of the insulators, moistening resulting in a conductive electrolyte film, leakage currents developing, heating and dry band formation, partial arcing, and arc elongation leading, finally, to complete flashover between the electrodes of the insulator [2]-[5]. Determining when to take corrective action on contaminated high voltage insulators has been a challenging problem for electric utilities for many years. In particular, the setting of realistic threshold levels to trigger corrective action has been very difficult. This problem has become even more important because of the need for better utilization of field personnel as a result of the continuing downsizing and reengineering of electric operating companies. There has been a renewed interest in predictive monitoring devices that can initiate just-in-time maintenance. Utilities usually adapt extensive and costly maintenance program to keep these insulators in good working conditions. Early warning of insulator conditions will help the utilities to re-schedule their maintenance programs and use their assets more efficiently. Monitoring the insulator conditions will provide a powerful tool to early diagnose the insulator health.
Wired detectors and monitoring devices are commercially available. Most of these devices are based on wired technology which has not been adopted commercially in large scale. Wireless sensor network (WSN) is set of miniaturized components (called sensor nodes) that are capable of sensing, processing and communicating with each other and each sensor node is typically powered by a battery. The collected information will be conveyed to a data collecting node (called base station (BS)). WSNs are finding applications in supervising and monitoring industrial plants and complexes. The convenience of connecting devices or components in an industrial plant without the use of wires is of tremendous advantage over the wired network particularly in remote and dangerous areas through which high voltage (HV) transmission lines pass. In this case, the use of wireless sensor technology is a highly needed option to monitor the condition of insulators, provide early warning and avoid expensive consequences of flashovers. In this work, we shall introduce a new system based on WSN that is able to monitor the nearby environment of the power transmission lines and collect the environmental variables which causes flashovers, in particular humidity and dust. The collected information will be transmitted wirelessly on a multi-hop network to the main node in the control room. The data collected will be compared with a predetermined threshold. An alarm signal will be activated if the contamination profile exceeds the threshold value, and hence action has to be taken to clean the insulators. The proposed system is practical and can be used for monitoring insulators in both high voltage yards or/and power transmission networks. The new system has many advantages such as the continuous monitoring nature of it, low cost deployment, plugand-play installation, and many others. The next section introduces briefly the different methods existing in the literature that are suggested to monitor/prevent flashover. The proposed monitoring system is detailed in section III. Section IV describes the experimental setup adopted in this work. Then, we present the ESDD models in section V. Finally, we end this paper with conclusions and future work. II.
FLASHOVER MONITORING: RELATED WORK
Flashover is the second serious hazard after the lighting that power transmission line may suffer from [7]. Recently, a lot of attention has been directed towards finding methods and measures to overcome flashover. The existing measures have taken different directions. One of the oldest techniques to avoid the pollutant buildup has been to coat the insulators with materials having low surface energy [8]. Historically, oil reservoirs [9] were used to wet the insulator surface with oil to prevent the contaminants from sticking to the insulator surface. More, recently, specialized grease coatings including petroleum jellies and silicone based grease compounds have
been used to increase the resistive nature of the insulating structure. Petroleum based coatings melt under heavy discharge environments; contributing to the pollution contents. The silicone based coatings, on the contrary, start to discharge at excessive temperatures and hence act as pollutants. Considering the pollution and the temperature situation in hot climate such as Saudi Arabia, silicone based coatings are not suitable. Another method to prevent flashover is to increase the width of the dry band (also referred to as the leakage distance). This can be done by increasing the number of insulating structures installed on a given transmission line. Due to the additional costs of the insulating structures, this method is seldom used nowadays. Therefore, most of the companies adopt periodic cleaning procedure [8] of the insulators to prevent accumulation of foreign particles on them. However, these methods are not cost effective. In fact, there are several issues that need to be determined for better understanding/treatment of Flashover. Hence, the existing literature took different directions to answer these issues/concerns. Firstly, can we predict when the flashover is going to occur and where? Secondly, if we cannot predict, can we localize the position where flashover occurred. For the first question, the existing techniques are much diversified. One technique as in [12], proposed a monitoring system that uses a piloted drone equipped with electric field sensing, thermal infra-red imaging, video imaging, acoustic and corona discharge sensing equipments. Moreover, some researchers have proposed smart material to indicate the status of flashover. And others suggest selfrepellent methods [11]. On the other hand, researchers have done modeling experiments to characterize the arching process so that preventive methods can be developed to overcome this issue. The leakage current received a lot of attention as an indicator for the pollution level. The interesting work of Li et al. [10] have proposed a pre-warning mechanism for the prediction of flashover. The technique relies heavily on the characterization of the leakage current to predict the contamination discharge. The authors have considered porcelain and glass insulating structures and through experiments they have classified the discharge process into three stages; security stage, forecast stage and danger stage. After conducting numerous laboratory experiments, the authors provide boundaries in terms of leakage current and the power spectrum. However, such approach needs to be embedded in the power system and hence, it lacks the portability feature. Another approach, in the same direction, used a UV camera to detect the presence of corona on 138 kV lines. The substitution of suspected flawed insulators represent to most of the distribution utilities one of the causes of major concern [13].
Considering the second question (i.e. positioning the flashover), the work in [14], exploits the fact that ultrasonic and ultraviolet energy is released when flashover occurs. Sensors are used to detect ultrasonic and ultraviolet waves near the insulators in real time. The detecting signals and accident position information will be uploaded to the monitoring center wirelessly using GSM/GPRS (Global System of Mobile communication / General Packet Radio Service). From the above presentation of the related work, we can observe that the existing techniques lack scalability, portability and plug-and-play features. The proposed approach in this work tries to accommodate these desirable features. III. THE PROPOSED MONITORING SYSTEM High voltage areas (HV transmission lines or HV switch yard) are very dangerous and restricted to be accessed unless it is scheduled for preventive maintenance. Consequently, it is difficult to place sensor nodes on any in-use insulator. To overcome this problem, we propose the use of a dummy unenergized insulator string/unit made of the same material and the same shape to monitor pollution on insulators at the same vicinity of the HV targeted area. The benefit of using the dummy insulator is the portability which provides a plug-andplay feature. Several types of sensors will be mounted on the top/bottom surfaces of the insulators to monitor pollution level as well as the weather conditions in the specific zone where the dummy insulator is positioned.
The following subsections discuss the test preparation and data collection. A. Test prepartion The phenomenon that was planned to observe is the accumulation of dust on a typical insulator. The photon intensity will be used to represent the amount of dust accumulation. Hence, a light sensor is suggested to be deployed and mounted on the insulator surface, due to its low cost and ease of integration with wireless sensor nodes. The TSL13s light-to-voltage sensors [17] have been used to sense the presence of dust on the insulator surface by sensing the light incident on it. As dust deposits on the insulator surface (and the light sensor attached on it), the incident light on the sensor decreases and hence the corresponding voltage reading. These readings will enable the system to estimate the deposition of pollutants on the insulator surface. In order to simulate the real condition of the insulator pollution, two insulator strings, each consist of two insulators units, were installed symmetrically around the center of the chamber in the High Voltage Laboratory (HVL) of KFUPM as shown in Figure 1.
The collected data shall be transmitted to the zone data collection node where it will be processed and transmitted wirelessly to the main control center. In the control center, the zone profile will be examined in order to find out any flashover alarming conditions and if so the maintenance crew will be ordered to take the standard corrective action. IV.
EXPERMINTAL SETUP
The proposed approach is based on the Equivalent Deposit Density (ESDD) standard method [19] in order to check the pollution level on the insulator and to correlate with flashover voltage levels of the insulator string. In this approach, the photons measurement level (i.e. light intensity) is adopted as an indicator to the accumulated dust level on the insulators. Extensive lab tests were carried out using different pollutants. ESDD measurements have been collected for all the pollution tests performed in the lab and a relationship between these values and the light intensity values has been established to correctly model the contamination level. Using, the established relationship between EESD and light intensity shall enable the power system control unit to accurately predict the flashover and accordingly schedule its crew to visit the site and clean these insulators.
Figure 2. Test setup (a) view of the test chamber with the two insulator strings (b) sensor placement definitions. STA-3T: station #3 on top surface, STA-3B: station #3 on bottom surface.
Lab tests with the TSL13s light sensor revealed that the sensor output is directly proportional to the supply voltage (Vcc) to the sensor. In order to ensure accurate light reading, all the sensor nodes must have exactly the same voltage supply; which is difficult to attain while using standard AAA size batteries. Hence a 110 VAC – 4.5 VDC regulated voltage distribution setup was devised and all the sensor nodes were powered by it. The sensor nodes were programmed to sense the light intensity and broadcast the data to the nearby basestation node (BN) periodically every 10 sec. The BN is connected to a laptop (placed at a safe distance to protect the PC from dust) to receive the data packets sent by the sensor
nodes. More, the light sensors contacts were water proofed using an epoxy resin and were attached to the insulator surface using industrial glue. Extensive experiments using two different types of dust; sand and white cement were carried out to study the distribution of dust deposits on the two insulator strings. The tests show homogenous level distribution of pollution on both strings on top surface as well as bottom surface. This important for the lab test when one sting is energized and other sting has the dummy insulators where we will place our monitoring system.
All deposits were removed from insulator surface using wetted cotton and settled in glass beaker of 600 CC, then left for one night to dissolve, before making the conductivity measurement. The measured conductivity is converted into amount of sodium chloride content using chemical tables and the current temperature. The amount of calculated salt in (mg) is divided by the insulator surface area to find the ESDD. It is an applicable standard for insulator pollution level measurement to measure the ESDD separately for the top and bottom surfaces of the insulator. Accordingly, the two surfaces measurements were taken separately as recorded in the Table I.
TABLE I.
THE LIGHT SENSOR READINGS VERSUS ESDD
Top Surface Light ESDD Intensity mg/cm2
(a)
(b)
Figure 2. Snapshots of test setup for method 2 (a) Bucket with the pollutant solution (b) polluted insulators after the test.
B. Practical Test Procesdure In this set of tests, standard pollution solution was prepared as per IEC 60507 standard requirements. The polluting solution conductivity resembles the actual field levels. The following procedure was adopted: 1. Immerse the insulators in a solution consisting of Kaolin of 40 gm\liter of tap water, in addition to salt. 2. Hang the insulators to dry. 3. Record the light measurements of ambient light for 3 minutes without blowing any dust or steam. 4. Turn the fan on. 5. Stop the fan and let the dust settle for 10 minutes. 6. The light intensity values are constantly being recorded from steps 3 through 6. 7. Measure the ESDD level of pollution deposit on the insulator surface as explained in the following section. Fig. 2 shows a snapshot of the contaminant solution in a bucket and the polluted insulator at the end of the experiment.
C. Measuring ESDD The ESDD measurement of the contaminants deposited during the above performed experiments has been carried out using distilled water volume of 600 cubic centimeters, and having conductivity of 2.88 μS/cm at temperature of 21.5 ◦ C.
Bottom Surface Light ESDD Intensity mg/cm2
7.0136
0.112
7.108
0.173
7.1633
0.110
7.2271
0.066
7.2865
0.051
7.2988
0.023
7.3874
0.0225
V.
ESDD MODELLING & DISCUSSION
Having obtained the ESDD values and its corresponding light intensity readings, it is important to develop a mathematical model that can be used to predict the ESDD level for other light readings. As shown in Fig. 3 & Fig. 4, the ESDD values can fit a linear curve for both surfaces. We tried three other models namely; logarithmic, exponential and 2 nd order polynomial. The linear model showed the best correlation value in the least square sense. For the top surface, we obtained the following model: ESDD = -0.2562*L + 1.9213; R² = 0.8708 While for the bottom surface, we obtained the following model: ESDD = -0.7968*L + 5.8331; R² = 0.9893
corresponding light intensity values. Linear mathematical models were developed for the top and bottom surfaces. As a future work, in order to validate our lab results, outdoor experiment will be carried out. ACKNOWLEDGM ENT The authors gratefully acknowledge the support of KACST and KFUPM. A special thanks to Umar Johar, Ahmar Shafi and Farouq Sultan for their help in conducting the lab experiments. REFERENCES Figure 3: The top surface ESDD values vs. light intensity
[1] [2] [3] [4]
[5]
[6]
Figure 4: The bottom surface ESDD values vs. light intensity
This model will help the SCADA center experts to predict the pollution level and assess the likelihood of flashover. It is important to note that in practice the pollution distribution in non-uniform over the surface and the leakage current density is non-uniform over the insulator surface and in some areas sufficient heat is developed leading to the formation of dry bands [18]. Hence, multiple light sensors should be embedded on the top surface as well as the bottom surface. In addition, the humidity is the most critical factor for flashover to occur (if no humidity, then no flashover will occur). Finally, the light sensor works ideally during sunny days. Therefore, the monitoring system should differentiate between the day time and night time and also during the cloudy days. This is very accessible information via the weather forecasting agency. VI.
CONCLUSION
A new approach for monitoring contamination on high voltage insulator is proposed. The system is based on wireless sensor network. Dummy insulators are used as a plug and play apparatus to make insulator monitoring robust and provide flexibility in replacing or marinating the system without altering or disturbing the continuity of power supply. At least three light sensors are mounted on top and bottom surfaces of each insulator. In addition, humidity sensors are also mounted in the same proximity. The collected data are transmitted to the SCADA center. We have conducted many lab tests to where the standard method for depositing pollutant on insulators. Then, we measured the ESDD and
[7] [8]
[9] [10]
[11]
[12] [13]
[14]
[15]
[16]
[17] [18]
[19]
IEEE Standard 100, IEEE Dictionary of Standard Terms. IEEE, 2004. Looms J S T 1990 Insulators for High Voltage (IEE Power Engineering Series 7) (London: IEE) CIGRE WG 33-04 Taskforce 01 A Review of Current Knowledge: Polluted Insulators Sweden, 1998. Y.Suzuki, T. Fukuta, Y. Mizuno and K. Naito K, “Probabilistic assessment of flashover performance of transmission lines in contaminated areas,” IEEE Trans. Dielectr. Electr. Insul., vol. 6, pp. 337–41, 1999. Y. Mizuno, H. Nakamura and K. Naito, ” Dynamic simulation of risk of flashover of contaminated ceramic insulators ,” IEEE Trans. Power Deliv. vol. 12, pp. 1292–8, 1997. B. A. Akyol, H. Kirkham, S. L. Clements and M. D. Hadley, “A Survey of Wireless Communications for the Electric Power System,” Jan. 2010, Pacific Northwest National Laboratory, prepared for U.S. Department of Energy [Online]. Available: www.pnl.gov/nationalsecurity/technical/s ecure.../power_grid_wireless. pdf. Q-X. Zhao, et al., "A Summary of insulator pollution detection method," Electric Switchgear, vol. 4, pp. 96-98, 2012. R. S. Gorur, E. Cherney, “Protective coatings for improving contamination performance of outdoor high voltage ceramic insulators,” IEEE transactions on power delivery, vol. pp. 1995. P. J. Lambeth, “Effect of pollution on high-voltage outdoor insulators ,” in Proc. of the Institute of Electrical Engineers, 1971. Li, J.Y., C. X. Sun, W. X. Sima, and Q. Yang, “Stage pre-warning based on leakage current characteristics before contamination flashover of porcelain and glass insulators”, IET generation, transmission and distribution, pp. 2009. J. Zhuang, et al., “A novel application of nano anti-contamination technology for outdoor high-voltage ceramic insulators,” International journal of applied ceramic technology, vol. pp. 2009. R. A. Fernandes, "Monitoring system for power lines and right-of-way using remotely piloted drone." U.S. Patent No. 4,818,990, Apr. 4, 1989. R.L. Vasquez-Arnez, M. G. M. Jardini, M. Masuda, L.A. Carita, J.A. Jardini, "Preventive inspection of line insulators through corona emission: A case study," in Proc 2010 IEEE PES Transmission and Distribution Conference and Exposition, pp.1-6. K. Ding, Y. F. Lin, and H. Y. Jin, "Research on Positioning System of Insulator String Flashover in High Voltage Transmission Line," Advanced Materials Research, vol. 655, 753-756, 2013. I. Ramirez, R. Hernandez, G. Montoya, "Measurement of leakage current for monitoring the performance of outdoor insulators in polluted environments," IEEE Electrical Insulation Magazine, vol.28, no.4, pp. 29-34, 2012. G. Li, and L. Huang, "Research on wavelet‐based sparse representation of insulator leakage current signal," Wiley Int. Trans. Electr. Energ. Syst., 2013. http://www.ece.usu.edu/ece_store/spec/856-TSL14S-LF.pdf. C. Muniraj, K. Krishnamoorthi, and S. Chandrasekar, "Investigation on Flashover Development Mechanism of Polymeric Insulators by Time Frequency Analysis," Journal of Electrical Engineering & Technology vol. 8, no. 6, pp. 1503-1511, 2013. IEC 60507, 1991 – 04. “Artificial Pollution Tests on High Voltage Insulators to be used on A.C.Systems”.
