Robust support vector machine‐based zero‐crossing detector for different power system applications. Issue 1 (1st January 2019)

• Record Type: Journal Article
• Authors: Ghosh, Minati; Koley, Chiranjib; Roy, Nirmal Kumar
• Is Part Of: IET science, measurement & technology. Volume 13:Issue 1(2019)
• Page Start: 83
• Page End: 89
• Publication Date: 2019-01-01
• Subjects: support vector machines -- power engineering computing; robust support vector machine‐based zero‐crossing detector -- power conversion -- grid synchronisation -- power conditioning -- power system automation -- supply frequency -- harmonic distortions -- robust SVM‐based ZC detection technique -- power system applications -- transients -- noise levels; Measurement -- Periodicals; Electrical engineering -- Periodicals; Electronics -- Periodicals; Nanotechnology -- Periodicals; Electromagnetism -- Periodicals; Medical instruments and apparatus -- Periodicals; 621.3
• DOI: 10.1049/iet-smt.2018.5025
• Languages: English
• ISSNs: 1751-8822

Abstract

Abstract : The detection of zero‐crossing (ZC) points in several power system applications, such as power conversion, grid synchronisation, power conditioning, and power system automation and control, is important toward ensuring a consistent performance even when there is variation in the supply frequency. However, the state‐of‐the‐art techniques of ZC detection are not very accurate in the presence of noise and harmonic distortions. This study introduces the concept of a support vector machine (SVM) in this context and subsequently proposes a robust SVM‐based ZC detection technique that addresses the aforementioned limitations. The simulation results show that the proposed technique obtains accurate values in the presence of transients, noise levels of up to 20%, and harmonic distortions of up to 50%. The experimental results provide similar observations.