New Technqiues and Algorithms for UHF Partial Discharge Detection and Localization in Power Transformers
Transformers belong to the most important and expensive components of power transmission and distribution systems. Therefore it is of special interest to prolong their life duration while reducing the service and maintenance expenditure for these apparatus. In order to reach these aims and to give recommendations about their future life expectation it is necessary to keep the transformers under surveillance during operation, which is done by using various kinds of so-called monitoring systems. Up to now these monitoring systems usually do not include on-line Partial Discharge (PD) measurements although this method is one of the most favorable and effective in diagnosing and therefore in reliability and life assessment of power transformers. The reason for this is mainly related to the fact that no simple and precise automatic evaluation algorithms for the PD detection and localization are available on-site. However, using PD techniques in the ultra-high frequency (UHF) range could be helpful for solving this problem, because of the advantages of this method, like the immunity against noises in the on-site and on-line tests, thus the data evaluation becomes less complex and therefore it becomes possible to determine the location of defects in the dielectric structure and estimate their criticality if automatic evaluation algorithms could be developed.
In this contribution a new algorithm is shown in order to estimate the arrival time of the PD Electromagnetic Waves (EM) to the antennas taking into account the effects of the active part of the transformer on the EM wave propagation. Therefore the automatic calculation of the arrival times from the measured UHF signal is very important, thus a new automatic algorithm is introduced too. In addition a new method based on the particle swarm optimization (PSO) algorithm was developed for the PD localization and the accuracy of this method is validated by both simulation and measurement results, which are extensively described and discussed within the contribution.
Furthermore it will be shown that more accurate PD localization is possible if the antennas are installed in positions, in which all probable PD sources inside the transformer are sufficiently distinguishable from each other. The optimum types of antennas as well as the best position for installing these kinds of sensors in power transformers are important issues for applying UHF method. An effective algorithm based on Characteristic Time Difference is suggested for optimizing the installation points of suggested UHF sensors. The efficiency of the proposed antenna positioning method as well as a new proposed UHF antenna design is approved by experimental UHF PD detection and localization in a power transformer.