Analysis of Power Quality Signals Using an Adaptive Time-Frequency Distribution

Nabeel A. Khan, Faisal Baig, Syed Junaid Nawaz, Naveed Ur Rehman and Shree K. Sharma
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Nabeel A. Khan: Department of Electrical Engineering, Foundation University, Islamabad 44000, Pakistan
Faisal Baig: Department of Electrical Engineering, Federal Urdu University of Arts Science and Technology, Islamabad 44000, Pakistan
Syed Junaid Nawaz: Department of Electrical Engineering, COMSATS Institute of Information Technology, Islamabad 44000, Pakistan
Naveed Ur Rehman: Department of Electrical Engineering, COMSATS Institute of Information Technology, Islamabad 44000, Pakistan
Shree K. Sharma: SnT - securityandtrust.lu, University of Luxembourg, Kirchberg, Luxembourg 1359, Luxembourg

Energies, 2016, vol. 9, issue 11, 1-13

Abstract: Spikes frequently occur in power quality (PQ) disturbance signals due to various causes such as switching of the inductive loads and the energization of the capacitor bank. Such signals are difficult to analyze using existing time-frequency (TF) methods as these signals have two orthogonal directions in a TF plane. To address this issue, this paper proposes an adaptive TF distribution (TFD) for the analysis of PQ signals. In the proposed adaptive method, the smoothing kernel’s direction is locally adapted based on the direction of energy in the joint TF domain, and hence an improved TF resolution can be obtained. Furthermore, the performance of the proposed adaptive technique in analyzing electrical PQ is thoroughly studied for both synthetic and real world electrical power signals with the help of extensive simulations. The simulation results (specially for empirical data) indicate that the adaptive TFD method achieves high energy concentration in the TF domain for signals composed of tones and spikes. Moreover, the local adaptation of the smoothing kernel in the adaptive TFD enables the extraction of TF signature of spikes from TF images, which further helps in measuring the energy of spikes in a given signal. This new measure can be used to both detect the spikes as well as to quantify the extent of distortion caused by the spikes in a given signal.

Keywords: time-frequency; power quality; power signals; smoothing; distribution (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: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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