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Analysis of Real Overvoltage Disturbances by Using Nonstationary Signal Processing TechniquesVUJOSEVIC, S. , MUJOVIC, S. , DAKOVIC, M. |
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Author keywords
empirical mode decomposition method, harmonics, power quality, short time Fourier transform, switching surges
References keywords
power(22), quality(10), analysis(10), time(7), transmission(5), systems(5), line(5), vujosevic(4), upec(4), system(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2015-08-31
Volume 15, Issue 3, Year 2015, On page(s): 23 - 32
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2015.03004
Web of Science Accession Number: 000360171500004
SCOPUS ID: 84940747691
Abstract
Switching surges can cause voltage conditions degradation, and this paper presents a new approach in their analysis. Besides the amplitude properties, regarding to power quality, it is important to know the structure of their harmonic spectrum. For that purpose, characteristic surges (energization and deenergization of an unloaded 35 kV underground cable, energization of an unloaded 10 kV underground cable and deenergization of a 10 kV overhead line, with a multiple appearance of the arc between the circuit breaker contacts) were analyzed. The signals were obtained by an experiment, so the occurrence of noise makes them much more complex to analyze than the simulated ones. Their harmonic decomposition was performed by digital signal processing methods - Empirical Mode Decomposition and Short Time Fourier Transform. The obtained results were compared to the calculated ones, which allowed us to draw conclusions related to applied methods efficiency and characteristic harmonics values that occur during the switching surges. The performed analysis allows us to get a deeper insight into transient processes in the real transmission power lines. The obtained results can be especially useful to detect the locations of occurrence of various types of surges and for development of real-time power quality monitoring systems. |
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Digital Object Identifier: 10.1007/s12206-024-0424-2 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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