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Data-driven dynamic harmonic model for modern household appliances

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  • Xie, Xiangmin
  • Chen, Daolian

Abstract

With the rapid development of power electronics technology and the enhancement of users' energy conservation awareness, the proportion of modern household appliances with power electronic devices is increasing year by year, which has become an important harmonic source. Together with the massive access of home photovoltaic and electric vehicles, the harmonics of the existing residential low-voltage distribution system (RLVDS) show higher distortions and stronger dynamics than ever before. Therefore, an accurate harmonic model of the modern household appliance is necessary for power quality analysis and improvement. This paper proposes a data-driven dynamic harmonic coupled admittance matrix model (HCAMM) based on measured voltage and current data. First, the parameters of the HCAMM are solved by the partial least squares method (PLSM), which can effectively overcome the matrix pathology problem in the solution process, and the HCAMM can reflect the coupling effect between each harmonic. Second, to address the voltage dynamics, the dynamic HCAMM is established by combining the recursive PLSM and the adaptive update strategy, which can accurately characterize the harmonics under different supply voltages. Finally, the accuracy, dynamics, and generality of the proposed harmonic model are verified by simulations and experiments, and the harmonic model is applied to the power quality harmonic evaluation, line power loss calculation with harmonics, and energy saving by reducing the harmonics.

Suggested Citation

  • Xie, Xiangmin & Chen, Daolian, 2022. "Data-driven dynamic harmonic model for modern household appliances," Applied Energy, Elsevier, vol. 312(C).
    • Handle: RePEc:eee:appene:v:312:y:2022:i:c:s0306261922002124
    DOI: 10.1016/j.apenergy.2022.118759
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    3. Xie, Xiangmin & Peng, Fei & Zhang, Yan, 2022. "A data-driven probabilistic harmonic power flow approach in power distribution systems with PV generations," Applied Energy, Elsevier, vol. 321(C).
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    5. Nadia Jahanafroozi & Saman Shokrpour & Fatemeh Nejati & Omrane Benjeddou & Mohammad Worya Khordehbinan & Afshin Marani & Moncef L. Nehdi, 2022. "New Heuristic Methods for Sustainable Energy Performance Analysis of HVAC Systems," Sustainability, MDPI, vol. 14(21), pages 1-14, November.

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