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Keywords = all-phase discrete Fourier transform

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17 pages, 4527 KB  
Article
A Novel Synchrophasor Estimation Based on Enhanced All-Phase DFT with Iterative Compensation and Its Implementation
by Zengqin Li, Weifeng Zhang, Zhiyuan Zhuang and Tao Jin
Energies 2022, 15(19), 6964; https://doi.org/10.3390/en15196964 - 23 Sep 2022
Cited by 1 | Viewed by 1902
Abstract
Synchrophasor estimation was mostly used in transmission systems in the past, and it is difficult to directly apply an existing synchrophasor algorithm to a distribution system with a more complex structure and environment. A synchrophasor estimation algorithm with a high accuracy and fast [...] Read more.
Synchrophasor estimation was mostly used in transmission systems in the past, and it is difficult to directly apply an existing synchrophasor algorithm to a distribution system with a more complex structure and environment. A synchrophasor estimation algorithm with a high accuracy and fast response speed is required to complete the calculation of the phasor in the face of the complex and changeable power signal of a distribution network. Therefore, an enhanced all-phase discrete Fourier transform (e-apDFT) algorithm is proposed for a distribution system in this paper, and the algorithm is deployed in a phasor measurement unit (PMU) prototype based on digital signal processing (DSP). Aiming to solve the problem of the accuracy of the traditional apDFT being reduced when the response speed is fast due to the influence of a dense spectrum, the existing algorithm is improved through iteratively compensating the spectral interferences to the main bin produced by adjacent bins. The experimental results show that the e-apDFT algorithm still has a fast response speed and that its estimation accuracy is much better than that of the traditional apDFTs in the presence of adjacent harmonic components. The proposed algorithm also complies with the IEEE standards for P-class PMUs. Full article
(This article belongs to the Special Issue Machine Learning Algorithms for Operation and Control of Microgrids with Distributed Energy Sources)
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14 pages, 406 KB  
Article
Multi-Tone Frequency Estimation Based on the All-Phase Discrete Fourier Transform and Chinese Remainder Theorem
by Xiangdong Huang, Lu Cao and Wei Lu
Sensors 2020, 20(18), 5066; https://doi.org/10.3390/s20185066 - 7 Sep 2020
Cited by 2 | Viewed by 2775
Abstract
The closed-form robust Chinese Remainder Theorem (CRT) is a powerful approach to achieve single-frequency estimation from noisy undersampled waveforms. However, the difficulty of CRT-based methods’ extension into the multi-tone case lies in the fact it is complicated to explore the mapping relationship between [...] Read more.
The closed-form robust Chinese Remainder Theorem (CRT) is a powerful approach to achieve single-frequency estimation from noisy undersampled waveforms. However, the difficulty of CRT-based methods’ extension into the multi-tone case lies in the fact it is complicated to explore the mapping relationship between an individual tone and its corresponding remainders. This work deals with this intractable issue by means of decomposing the desired multi-tone estimator into several single-tone estimators. Firstly, high-accuracy harmonic remainders are calculated by applying all-phase Discrete Fourier Transform (apDFT) and spectrum correction operations on the undersampled waveforms. Secondly, the aforementioned mapping relationship is built up by a novel frequency classifier which fully captures the amplitude and phase features of remainders. Finally, the frequencies are estimated one by one through directly applying the closed-form robust CRT into these remainder groups. Due to all the components (including closed-form CRT, the apDFT, the spectrum corrector and the remainder classifier) only involving slight computation complexity, the proposed scheme is of high efficiency and consumes low hardware cost. Moreover, numeral results also show that the proposed method possesses high accuracy. Full article
(This article belongs to the Section Communications)
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