On the Application of Joint-Domain Dictionary Mapping for Multiple Power Disturbance Assessment

Delong Cai, Kaicheng Li, Shunfan He, Yuanzheng Li and Yi Luo
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Delong Cai: State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronics Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Kaicheng Li: State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronics Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Shunfan He: School of Computer Science, South-Central University for Nationalities, Wuhan 430074, China
Yuanzheng Li: School of Automation, Ministry of Education Key Laboratory of Image Processing and Intelligence Control, Huazhong University of Science and Technology, Wuhan 430074, China
Yi Luo: State Key Laboratory of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronics Engineering, Huazhong University of Science and Technology, Wuhan 430074, China

Energies, 2018, vol. 11, issue 2, 1-17

Abstract: This paper proposes a joint-domain dictionary mapping method to obtain high assessment accuracy of multiple power disturbances. Firstly, in order to achieve resolutions in both the time and frequency domains, a joint-domain dictionary is proposed which consists of a discrete Hartley base and an identity matrix. Due to the low correlation between the discrete Hartley base and the identity matrix, the joint-domain dictionary mapping can separately capture the approximations of the sinusoidal components and transients. Since the mapping coefficients contain the physical quantities, the eigenvalues of each component can be effectively estimated. A quantified eigenvalue classifier was designed for identifying power disturbances using the estimated eigenvalues. The proposed method was compared with several advanced methods through simulated power disturbances under different noise conditions, and actual data from the Institute of Electrical and Electronics Engineers Power and Energy Society database. The results reveal that the joint-domain dictionary mapping technique shows good performance on parameter estimation and recognition precision, even dealing with complicated multiple power disturbances.

Keywords: power disturbance; joint-domain dictionary; pattern recognition; parameter estimation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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