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Use of Artificial Neural Networks for Location of Defective Insulators in Power Lines
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作者 Renato Massoni Capelini Jose Feliciano Adami +2 位作者 Manuel Luis Barreira Martinez Marcel Femando da Costa Parentoni Ithamar Sene 《Journal of Energy and Power Engineering》 2012年第8期1308-1314,共7页
This is an extended version of the same titled paper presented at the 21st CIRED. It discusses a new technique for identification and location of defective insulator strings in power lines based on the analysis of hig... This is an extended version of the same titled paper presented at the 21st CIRED. It discusses a new technique for identification and location of defective insulator strings in power lines based on the analysis of high frequency signals generated by corona effect. Damaged insulator strings may lead to loss of insulation and hence to the corona effect, in other words, to partial discharges. These partial discharges can be detected by a system composed of a capacitive coupling device (region between the phase and the metal body of a current transformer), a data acquisition board and a computer. Analyzing the waveform of these partial discharges through a neural network based software, it is possible to identify and locate the defective insulator string. This paper discusses how this software analysis works and why its technique is suitable for this application. Hence the results of key tests performed along the development are discussed, pointing out the main factors that affect their performance. 展开更多
关键词 Corona effect current transformer insulator string neural network power line.
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The Influence of Surge Arrester Location on Over-Voltages Caused by Direct Lightning Strikes to MV Lines
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作者 Alexandre Piantini Thais O. de Carvalho +3 位作者 Paulo F. Obase Jorge M. Janiszewski Gilnei J. G. Santos Donorvan R. Fagundes 《Journal of Energy and Power Engineering》 2014年第3期508-514,共7页
In the period 2003-2011, lightning over-voltages accounted for about 47% of the total number of distribution transformer failures observed in the service area ofAES Sul, a power company that operates in the state of R... In the period 2003-2011, lightning over-voltages accounted for about 47% of the total number of distribution transformer failures observed in the service area ofAES Sul, a power company that operates in the state of Rio Grande doSul, in South Brazil. This paper presents the results of an investigation on the influence of the distance between transformer and MV arresters on the surges at the transformer windings caused by direct strikes to the MV network. The analysis, performed through simulations using the Alternative Transients Program, shows that in general higher voltages are produced by subsequent strokes. Although in relation to the primary side the surges transferred to the secondary are much less affected by the distance between transformers and primary arresters, such distance should always be kept as short as possible in order to reduce the probability of occurrence of transformer failures due to over-voltages at the MV bushings. 展开更多
关键词 Distribution transformer lightning surges overvoltages.
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