Parametric Study on Steady State Arc Detection Efficacy
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Date
2017-05
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The Ohio State University
Abstract
DC arcs are a growing problem as dc power systems increase in prevalence. These growing system interests include aviation, photovoltaic arrays, nationwide power distribution, and automotive vehicles. DC arcs are significantly different from ac arcs, and are more difficult to detect and protect against, as there is no zero crossing in the current signal. Being able to quickly detect and handle arcs is important to prevent insulation damage, fire, or other system hazards. Several arc current signal detection algorithms are examined through comparative analysis in order to characterize an optimal detection approach for a real-world implementation. This is a binary decision problem to optimize between sensor bandwidth, detection time, algorithm resolvability, and computational complexity. Algorithm resolvability is defined then the algorithms are tested under varying system parameters including test parameters and system noise. Presented are several ways these algorithms resolve and do not resolve given the test and detection parameters. The results of the study suggest new avenues for research including the influence of load power on detection error rate.
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Keywords
dc arc, arc detection, power systems, parametric study, comparative study, wavelet