Researchers in Argentina Explore New Diagnostic Methods to Support Live Line Replacement of Composite Insulators
TESTING
Researchers in Argentina Explore New Diagnostic Methods to Support Live Line Replacement of Composite Insulators The growing requirement for high network availability means that maintenance work on overhead lines must increasingly be performed employing live working techniques. This is a process generally made easier by the light weight of composite insulators. Indeed, one of the most desirable features of these insulators is that they facilitate handling, not only
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during initial installation but also whenever damaged or defective units need to be replaced However, the application of live line techniques that also ensure maximum worker safety depends greatly on workers having a proper knowledge of what exactly constitutes a deteriorated state of such insulators.
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This goal has led a team of researchers in Argentina to look for practical new methods to reliably determine the condition of polymeric insulators in service. This would then provide live working teams in that country better information so that they can decide, with a high level of assurance, whether or not to replace these types of insulators
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with the line still energized. The researchers involved in this project included professors and specialists from three regional faculties of that country’s Universidad Tecnológica Nacional (i.e. Facultad Regional Concordia, Facultad Regional Santa Fe and Facultad Regional La Plata). Support for their work was provided by some of the country’s leading power supply companies, including Empresa de Energía de Santa Fé, Comisión Técnica Mixta de Salto Grande and Empresa Hangar Servicios. This article, summarizing the findings, was prepared by INMR Contributor, Martín Portillo – a former Head of Maintenance and Projects at Spain’s Red Eléctrica (REE) and now an independent consultant in the field.
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Argentina’s Electrical System Over the past 20 years, annual growth in electricity demand in Argentina has been strong and averaged 5.5%. The peak was reached in 2009 with demand and generation of 19,566 MW and almost 120,000 GWh. This burgeoning demand, coupled with the large size of the country, has meant that Argentina relies heavily on a backbone of 500 kV transmission lines that together run some 11,300 circuit km with 42 substations having a total transformer capacity of 15,200 MVA. An additional 5000 km of new 500 kV lines are already scheduled to be built in the coming years. Polymeric insulators first began to be installed in Argentina in the early 1990s, motivated largely by historic problems with large birds depositing conductive biological wastes on porcelain or glass cap & pin strings. Traditional Techniques for Predictive Maintenance of Polymeric Insulators To date, routine inspection of polymeric insulators has relied on a number of predictive techniques, summarized below: A. Visual Inspection This is perhaps the method still most commonly used
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by power companies worldwide to identify faulty insulators. It can be done from the ground, from the tower or even from a helicopter and is best performed with high-power binoculars. Unfortunately, this form of inspection makes it possible only to detect damage at the surface of an insulator. Still, even a small surface imperfection may be a reliable indicator of internal damage that warrants a subsequent more detailed examination.
B. Image Intensification Instruments These types of devices are useful to detect the presence of potentially dangerous surface discharges. For example, there have been cases documented where small but stable discharges detected with image intensification equipment have eventually caused considerable erosion of the bulk material of an insulator. It is worth noting that most of the energy radiated by partial discharges is in the UVA band, generally between 300 and 400 nm. Therefore, to ensure optimal results in early detection of potentially harmful discharge activity, it is ideal to employ ultraviolet imaging equipment with quartz optics that function in this range. C. Infrared Thermography This method of inspection has been used successfully for years now, both in the laboratory and the field. Using an infrared camera equipped with a telephoto lens, it’s even possible to conduct ground-based examinations of insulators on towers at heights of 30 or 40 meters. For best results, it has been found best to conduct such measurements on cloudy days with little or no wind and temperatures between 5º and 15ºC.
Typical finding from an infrared examination of polymeric insulator.
D. Measurements of Electric Field Distribution To carry out measurements of electric field, maintenance workers must climb
Typical electric field of polymeric insulator in good condition.
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the tower carrying a device equipped with a sensor mounted onto a carrier support and adapted to each type of insulator profile. However, one problem with this instrument is that it’s difficult to detect defects located near the end fittings, where many typically occur. Moreover, only those defects whose conductivity is high enough to modify the distribution of the potential can be identified. E. Partial Discharge Measurements This is usually performed only in a laboratory setting and is difficult to carry out on high voltage composite insulators due to the elevated voltage levels required for testing. Nevertheless, results obtained have demonstrated that this method is able to detect insulators that are in imminent danger of failure. As such, developing a method that facilitates the application of this technique in the field is clearly a worthwhile goal.
Background to Research Project According to the three Professors heading up this Argentine research project, the main goal behind their work has been to contribute to the field of predictive maintenance of insulators. In this regard, one of their main tasks has been to search for more
Example of electric field distribution of polymeric insulator in deteriorated condition.
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Polymeric insulators subjected to strong electric fields will over time often begin to lose dielectric strength and experience decreased performance. Professors Pérez, Neira, Cairol and Portillo.
practical procedures to measure partial discharges since this parameter has been determined to be especially valuable in correctly assessing the condition of polymeric insulators in service. It is expected that this portion of the project will conclude with development of a portable partial discharge meter for field use in order to provide line maintenance workers with in situ data that can quantify, in a simple way, the state of such insulators on the line. A second target will be to develop an expert system for assessing polymeric insulators in service, which can serve to effectively support decision-making by an operator whether or not it is necessary to intervene with an energized
line. Such an expert system would have to rely on data from a series of measurements taken on the line. Ideally, the entire process should not be overly difficult so that it could be carried out even by maintenance staff not accustomed to this type of work (i.e. the expert system developed would have to be simple and practical enough to operate in the field).
Improved Procedures for Measuring Partial Discharges Polymeric insulators subjected to strong electric fields will over time begin to lose dielectric strength and experience decreased insulation performance. This generally occurs
Figure 1. Measurements on new polymeric insulator Measured leakage current: If= 33 μA Measured partial discharges: 1 mV
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because of tiny cavities or ‘microbubbles’ inside the bulk material that create pathways along which volumetric currents can flow. Such discharges that do not completely bypass the insulating element are referred to as partial discharges. Although their magnitude and energy dissipation are comparatively small, they can eventually lead to progressive deterioration of the insulator in an accelerating process that worsens until such time as failure occurs. In order to quantify the degree of deterioration that may be present in a polymeric insulator in service due to such volumetric leakage currents,
Figure 2. Measurements on failed polymeric insulator Measured leakage current: If= 2 mA Measured partial discharges: 175 mV
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a number of laboratory and field tests have been proposed. Essentially, these aim to obtain partial discharge measurements and then link them to the state of the insulator. In all cases, these tests rely on a fourchannel digital oscilloscope and an RF current transformer with a ferrite core. The data obtained in Argentina up to now confirm that this kind of transformer represents an effective tool to quantify the state of any abnormality in a polymeric insulator. For example, while no abnormal measurements have been observed on new insulator specimens being tested, high partial discharge pulses have been noted in the case of damaged units. These have also indicated, in a quantitative way, the relative level of deterioration, i.e. a significant increase in volumetric current was observed. As seen in Figures 1 and 2, this current can range from as little as 33 μA in an new insulator to as high as 2 mA in a damaged one, i.e. an increase by a multiple of around 60, given similar weather conditions. In these figures, the partial discharges vary from 1 mV for a new insulator up to 175 mV in the case of one whose condition has deteriorated. According to engineers at the power utility, Empresa de Energía de Santa
Any equipment to safely and reliably diagnose the true state of polymeric insulators will have to be simple to operate in the field but once available, will facilitate decision-making about replacing polymeric type insulators with the line still energized. rEsEarCHErs
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Fe, the results of field measurements using the new methodology and those conducted in the laboratory under controlled conditions could be considered virtually equivalent. For example, in the case of partial discharges, laboratory measurements on damaged insulators were on average 100 times higher than those for new insulators while field measurements taken with the new test protocol were some 80 times higher. As mentioned above, this part of the project will conclude once a portable partial discharge meter is developed that is simple enough to be operated reliably in the field by live line workers.
Development of Expert System to Assess Insulator Condition There are several parameters whose values can be closely linked with reliable information on the true condition of a polymeric insulator. These include: • Leakage current • Electric field • Partial discharge activity • UVA data • Environmental parameters In order to link field data obtained
from such measurements with the real state of polymeric insulators in service through an expert system, the Argentine research team studied different artificial intelligence algorithms. In particular, different neural network architectures were examined to see if they could recognize and classify patterns of behaviour directly applicable to the goals of the research. Artificial neural networks have been successfully applied in such diverse areas as speech recognition, image analysis and adaptive control. To select the best neural network for drawing conclusions about the behaviour of an insulator in any particular condition and considering the type of field data that would probably be available, researchers evaluated the suitability of different alternative architectures, including back propagation networks (BPN), counter propagation networks (CPN), self-organizing maps (SOM), bidirectional associative memory (BAM) and learning vector quantization (LVQ). The BPN neural architecture was ultimately selected as best being able to fulfil the necessary requirements. This type of network learns from predefined sets of pairs of inputs and outputs. For example, inputs could consist of sets of data from measurements made on the insulator being evaluated while outputs would
General architecture of the back propagation network (BPN)
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Considering the measurement data taken on polymeric insulators and after processing for optimal use, the steps required to train the neural network selected can be summarized as follows: 1. Apply an input vector data from laboratory and/or field measurements and calculate its output. 2. Calculate the error considering the actual state of the polymeric insulator linked to the data being introduced. 3. Determine in which direction (+ or -) and by what amount the weighted connections values between nodes in the network should change to reduce this error. 4. Correct the weights of the connections listed above. 6. Repeat the above for all data patterns that were selected for training in order to reduce the error to some acceptable value.
Conclusions
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then be the state of the insulator subjected to these measurements. Once an input set of data has been used as stimulus for the first layer of units in the network, it will spread upward through all the layers to generate the output. The output signal is compared with the desired output and any error signal calculated. This error signal is then transmitted backwards from the output layer to all nodes in the intermediate layer, which contributes directly to the output.
to the total. Based on this, the connection "weights" of each unit are updated and essentially converge the network to a state permitting all sets of data to be encoded.
As the network is ‘trained’ in this manner, the different nodes of the intermediate layers organize themselves so that they learn to recognize different features of the inputs. Then, after training, whenever any arbitrary input pattern containing measurements on a given insulator is received, the units of the hidden layers of the network will respond with However, the middle layer units receive only a fraction of the total error an output that represents the real state of that insulator. Basically, the signal, based roughly on the relative contribution of the unit to the original information contained in the new input pattern is thus interpreted, according output. This process is repeated, to its similarity to features that the layer-by-layer, until all nodes in the individual units have learned to network have received an error signal that describes its relative contribution recognize during their training process.
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Elaborating a general methodology to determine in situ and with a high degree of certainty the real state of a polymeric insulator in service is a very difficult task. This is due to the large number of variables involved as well as possible interference from other elements within the power system. Nevertheless, current research being carried out in Argentina suggests that equipment may soon be available which will enable such field measurements that can then supply inputs into predictive neural networks. Any equipment to safely and reliably diagnose the true state of polymeric insulators will have to be simple to operate in the field but once available, will facilitate decision-making about replacing polymeric type insulators with the line still energized. This will not only provide greater security for workers who perform such maintenance work but also save considerable time and expense for operators of lines.
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