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PCA-Based Arc Detection Algorithm for DC Series Arc Detection in PV System
- Authors
- Ahn, J.-B.; Lee, J.-H.; Ryoo, H.-J.; Kim, Y.-J.; Lee, K.-D.; Lee, J.
- Issue Date
- Nov-2021
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- AFD (Arc Fault Detector); DWT (Discrete Wavelet Transform); PCA (Principal Component Analysis); Series Arc
- Citation
- ICEMS 2021 - 2021 24th International Conference on Electrical Machines and Systems, pp 258 - 261
- Pages
- 4
- Journal Title
- ICEMS 2021 - 2021 24th International Conference on Electrical Machines and Systems
- Start Page
- 258
- End Page
- 261
- ISSN
- 0000-0000
- Abstract
- In this paper, we present a PCA-based arc detection algorithm for photovoltaic (PV) DC series arc detection. PCA is a technique of extracting a new parameter that maximizes variance of a dataset while reducing the dimension of a dataset and arc noise can be effectively classified using the PCA parameter. As a dataset for PCA, DWT-based parameters acquired under various voltage and current conditions are used. The eigenvectors for PCA parameters extraction are obtained using MATLAB/simulation, and this is applied to the arc detection algorithm. The real-time arc detection test is performed through TMS320f28335 DSP. It is verified that not only the DC arc can be successfully detected with PCA-based algorithm, but also margin of the threshold value distinguishing the arc noise and inverter noise is increased. © 2021 KIEE & EMECS.
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Collections - College of Engineering > School of Energy System Engineering > 1. Journal Articles
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