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Abstract
The difficulties of predictive maintenance of power grids are related to the large spread of electrical infrastructures and the definition of early warning indicators. Such indicator is the partial discharge activities—which can be very informative about the rising insulation problems of electrical materials. However, the detection and the localization of the partial discharges are very complicate tasks and are currently subject to intensive studies in both theoretical and practical domains. The traditional way to approach the global surveillance of partial discharge sources is to first detect it and the second is to attempt to localize their positions. Despite the numerous proposed approaches, based on advanced transient signal processing tools, there is no any operational technique to efficiently asses the partial discharge sources in a real power network. In this context, our paper proposes a new approach based on the global evaluation of entropy of transient phenomena detected in a power network, without needing any localization of the sources of these phenomena. We will show that this approach provides an effective evaluation of partial discharges sources. Moreover, since the technique requires a reduced number of sensors, it is very advantageous to use in real contexts.
Highlights
In the last few years, more and more research has been conducted on the study of the systems we depend on in our daily lives from the perspective of analyzing their operation in order to obtain information on possible defects and degradations that can lead to system problems [1,2,3,4]
It has been shown that using spectral entropy can distinguish between two states of determine possible activities that may occur on an electrical cable
This paper is based on the analysis and statistical interpretation of an electrical system, according to which a characterization of its operating state can be made
Summary
In the last few years, more and more research has been conducted on the study of the systems we depend on in our daily lives from the perspective of analyzing their operation in order to obtain information on possible defects and degradations that can lead to system problems [1,2,3,4]. A typical case where this type of research is conducted is the surveillance of the power networks This is a crucial operation for maintaining the security of energy supply, and is vital for all economic (industry, transport, telecommunications, etc.) and social (supplying energy to individuals) activities. Network managers are faced with an aging network that must withstand two-way demands, in particular from intermittent energy production In this context, the continuous monitoring of electrical networks with distributed sensors is the solution that is being globally explored, with several new technologies currently in the study and development phase. The distributed sensors are generally aimed to detect the partial discharge activities, which represent early signs of faults that could become problematic in time [5]. The accurate detection of partial discharge activity is nowadays a general research topic of great interest, both theoretical and practical
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