Abstract
Accurate detection of ripple components of the direct-current (DC) signals is essential for evaluating DC power quality. In this study, the combination algorithm based on variational mode decomposition (VMD) and Hilbert transform (HT) is applied to detect and analyze the characteristics of the ripple components of the DC disturbance signals. Firstly, the optimal modal number of VMD algorithms is comprehensively determined by observing the center frequencies of the mode components and the Index of Orthogonality (IO) of mode components. Through utilizing the VMD algorithm, the DC disturbance signal is accurately decomposed into a series of amplitude modulation-frequency modulation (AM-FM) functions. Then, the HT algorithm is applied to each AM-FM function to obtain the corresponding instantaneous amplitude and frequency, and the characteristics of DC disturbance signal are determined. Some case studies are implemented to analyze the ripple components of the DC disturbance signal with the VMD-HT and empirical mode decomposition (EMD) algorithm. Finally, the experiment results of Gree Photovoltaic Cabin have verified the feasibility and effectiveness of the proposed combination VMD-HT algorithm by comparison with EMD and the window interpolation fast Fourier transform (WIFFT) algorithms.
Highlights
With the development of distributed energy such as PV systems, wind generation, or battery storage, and the increase of user-side direct-current (DC) loads, DC transmission, and distribution systems have been widely concerned due to their convenient access and low conversion losses [1,2,3,4].The DC distribution systems become more attractive in industrial plants [5], which usually include various DC loads and AC loads, and use power electronic converters to realize AC and DC power conversion
The sag/swell components may exist in the input DC signals, while this study mainly focusses on the detection and analysis of the ripple component
The experiment results with variational mode decomposition (VMD)-Hilbert transform (HT), empirical mode decomposition (EMD) and window interpolation fast Fourier transform (WIFFT) algorithms are presented
Summary
With the development of distributed energy such as PV systems, wind generation, or battery storage, and the increase of user-side direct-current (DC) loads, DC transmission, and distribution systems have been widely concerned due to their convenient access and low conversion losses [1,2,3,4]. The WIFFT is not effective to detect and analyze the non-stationary ripple components, where the accuracy is determined by the fixed size of analysis window [26]. The discrete Fourier transform (DFT) algorithm for ripple evaluation in DC Low Voltage networks are presented in [33], which exhibits similar performance with the analog bandpass filter It is limited for the random noise and the effective signal in the low-frequency band [34]. A combination algorithm based on VMD and Hilbert Transform (HT) is proposed to detect the ripple components of DC signals for the first time, which makes use of the advantages that the VMD algorithm is well processing densely distributed signals and the HT can accurately describe the characteristics of non-stationary signal transient parameters [35].
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