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

Author

Listed:
  • Radu Plamanescu

    (Electrical Engineering Department, University Politehnica of Bucharest, 060042 Bucharest, Romania)

  • Ana-Maria Dumitrescu

    (Electrical Engineering Department, University Politehnica of Bucharest, 060042 Bucharest, Romania)

  • Mihaela Albu

    (Electrical Engineering Department, University Politehnica of Bucharest, 060042 Bucharest, Romania)

  • Siddharth Suryanarayanan

    (Electrical Engineering and Computer Science Department, South Dakota State University, Brookings, SD 57007, USA)

Abstract

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.

Suggested Citation

  • Radu Plamanescu & Ana-Maria Dumitrescu & Mihaela Albu & Siddharth Suryanarayanan, 2021. "A Hybrid Hilbert-Huang Method for Monitoring Distorted Time-Varying Waveforms," Energies, MDPI, vol. 14(7), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:7:p:1864-:d:525271
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    References listed on IDEAS

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    1. Mihai Sanduleac & Lucian Toma & Mircea Eremia & Irina Ciornei & Constantin Bulac & Ion Triștiu & Andreea Iantoc & João F. Martins & Vitor F. Pires, 2019. "On the Electrostatic Inertia in Microgrids with Inverter-Based Generation Only—An Analysis on Dynamic Stability," Energies, MDPI, vol. 12(17), pages 1-23, August.
    2. Arman Ghaderi Baayeh & Navid Bayati, 2020. "Adaptive Overhead Transmission Lines Auto-Reclosing Based on Hilbert–Huang Transform," Energies, MDPI, vol. 13(20), pages 1-15, October.
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    Cited by:

    1. Gianfranco Chicco & Andrea Mazza & Salvatore Musumeci & Enrico Pons & Angela Russo, 2022. "Editorial for the Special Issue “Verifying the Targets—Selected Papers from the 55th International Universities Power Engineering Conference (UPEC 2020)”," Energies, MDPI, vol. 15(15), pages 1-8, August.
    2. Yu-Jen Liu & Cheng-I Chen & Wei-Chung Fu & Yih-Der Lee & Chin-Chan Cheng & Yen-Fu Chen, 2023. "A Hybrid Approach for Low-Voltage AC Series Arc Fault Detection," Energies, MDPI, vol. 16(3), pages 1-22, January.
    3. Anna Ostrowska & Tomasz Sikorski & Alessandro Burgio & Michał Jasiński, 2023. "Modern Use of Prosumer Energy Regulation Capabilities for the Provision of Microgrid Flexibility Services," Energies, MDPI, vol. 16(1), pages 1-13, January.

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