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RSS FeedsEnergies, Vol. 14, Pages 5893: Recognizing VSC DC Cable Fault Types Using Bayesian Functional Data Depth (Energies)

 
 

17 september 2021 12:39:14

 
Energies, Vol. 14, Pages 5893: Recognizing VSC DC Cable Fault Types Using Bayesian Functional Data Depth (Energies)
 


Diagnostics of power and energy systems is obviously an important matter. In this paper we present a contribution of using new methodology for the purpose of signal type recognition (for example, faulty/healthy or different types of faults). Our approach uses Bayesian functional data analysis with data depths distributions to detect differing signals. We present our approach for discrimination of pole-to-pole and pole-to-ground short circuits in VSC DC cables. We provide a detailed case study with Monte Carlo analysis. Our results show potential for applications in diagnostics under uncertainty.


 
55 viewsCategory: Biophysics, Biotechnology, Physics
 
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Energies, Vol. 14, Pages 5898: Carbon-Negative Scenarios in High CO2 Gas Condensate Reservoirs (Energies)
 
 
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