An Improved Three-Phase Four-Wire Harmonic Detection Algorithm Based on Multi-Synchronous Rotating Frame Transformation

Bao, Licheng; Xia, Jin; Dong, Zhiauan; Deng, Yan; Lü, Yi; Yang, Yong

doi:10.1109/iecon.2019.8927561

Cited by 6 publications

(1 citation statement)

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“…[16], based on the full-phase spectrum analysis theory, proposed an improved FFT method combined with double Nutall windows; the method can be used for the detection of harmonics and interharmonics in different scenarios, and accurate results can be obtained even when the harmonic content is unknown. The disadvantage is that the output result needs to be compared with the traditional FFT result to be corrected, and offline harmonic detection cannot be used, because of the large amount of calculation, therefore, it is more suitable for the case where the signal harmonic component is less [17]. The traditional SRF method is improved by adding closed-loop feedback and multiple PI methods, so that the steady-state error is reduced.…”

Section: Introductionmentioning

confidence: 99%

An Observer-Based Harmonic Extraction Method with Front SOGI

Sang

et al. 2022

Machines

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With the further development of harmonic pollution in the power system, scientists have carried out research on harmonics. Among them, harmonic detection is the first step in harmonic research. In this paper, a harmonic detection method based on an observer is proposed. This method first uses the cascaded Second-Order Generalized Integration (SOGI) algorithm, which can filter the Direct Current (DC) component of the input signal to extract the fundamental frequency, and then uses a time-varying observer to extract the harmonics. This can be used to extract harmonics from a distorted online grid signal. The effectiveness of the proposed method was evaluated on the Speedgoat Rapid Control Prototype (RCP) platform. The results show that it can complete the convergence within 0.05 s, and the standard deviation after stability will not exceed 1%.

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Section: Introductionmentioning

confidence: 99%