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Article

A Hybrid Hilbert-Huang Method for Monitoring Distorted Time-Varying Waveforms †

1
Electrical Engineering Department, University Politehnica of Bucharest, 060042 Bucharest, Romania
2
Electrical Engineering and Computer Science Department, South Dakota State University, Brookings, SD 57007, USA
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in the 55th International Universities Power Engineering Conference, UPEC 2020, Torino, Italy, 1–4 September 2020.
Academic Editor: Gianfranco Chicco
Energies 2021, 14(7), 1864; https://doi.org/10.3390/en14071864
Received: 31 January 2021 / Revised: 21 March 2021 / Accepted: 23 March 2021 / Published: 27 March 2021
The electric power systems together with the entire energy sector are rapidly evolving towards a low-carbon, secure, and competitive economy facing revolutionary transformations from technical structure to economic value chain. Pathways to achieve sustainability led to the development of new technologies, accommodation of larger shares of unpredictable and stochastic electricity transfer from sources to end-users without loss of reliability, new business models and services, data management, and so on. The new technologies and incentives for local energy communities along with large development of microgrids are main forces driving the evolution of the low voltage energy sector changing the context and paradigm of rigid contractual binding between utilities and end-user customers (now progressing to flexible prosumers with generation and storage capabilities). The flexibility and operation of a prosumer can be enhanced by a non-intrusive time-frequency analysis of distorted power quality waveforms for both generation and demand at the point of common connection. Therefore, it becomes of importance to discriminate among successive quasi-steady-state operation of a given local system using only the aggregated waveforms information available in the PCC. This paper focuses on the Hilbert–Huang method with modifications such as empirical mode decomposition improved with masking signals based on the Fast Fourier Transform, Hilbert spectral analysis, and a post-processing method for separating components and their amplitudes and frequencies within distorted power signals for a low-voltage prosumer operation. The method is used for a time-frequency-magnitude representation with promising localization capabilities enabling efficient operation for prosumers. View Full-Text
Keywords: Hilbert–Huang spectrum; empirical mode decomposition; DFT; power quality; time-frequency analysis; prosumers; distorted current waveforms; quasi-steady-state Hilbert–Huang spectrum; empirical mode decomposition; DFT; power quality; time-frequency analysis; prosumers; distorted current waveforms; quasi-steady-state
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MDPI and ACS Style

Plamanescu, R.; Dumitrescu, A.-M.; Albu, M.; Suryanarayanan, S. A Hybrid Hilbert-Huang Method for Monitoring Distorted Time-Varying Waveforms. Energies 2021, 14, 1864. https://doi.org/10.3390/en14071864

AMA Style

Plamanescu R, Dumitrescu A-M, Albu M, Suryanarayanan S. A Hybrid Hilbert-Huang Method for Monitoring Distorted Time-Varying Waveforms. Energies. 2021; 14(7):1864. https://doi.org/10.3390/en14071864

Chicago/Turabian Style

Plamanescu, Radu, Ana-Maria Dumitrescu, Mihaela Albu, and Siddharth Suryanarayanan. 2021. "A Hybrid Hilbert-Huang Method for Monitoring Distorted Time-Varying Waveforms" Energies 14, no. 7: 1864. https://doi.org/10.3390/en14071864

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