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A bottom-up approach to evaluate the harmonics and power of home appliances in residential areas

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  • Sun, Yuanyuan
  • Xie, Xiangmin
  • Wang, Qingyan
  • Zhang, Linghan
  • Li, Yahui
  • Jin, Zongshuai

Abstract

With expansion of the urban population, the power consumed by Chinese residential load is increasing rapidly. At the same time, power-electronic devices are widely adopted in home appliances, injecting a great amount of harmonics into the power system, which makes the harmonic problem in residential areas more serious than ever before. In this paper, a bottom-up approach is proposed to evaluate the harmonics of residential energy use. Firstly, a harmonic coupled model is proposed to calculate the harmonics generated by individual nonlinear home appliance. The model directly exhibits the couplings between different order harmonic voltages and currents. Secondly, based on the Markov chain Monte Carlo method, a random usage model is established to determine the usage pattern of home appliances. Various behavioral factors that affect the domestic use of energy in China are considered, and corresponding correction factors are proposed to improve the model accuracy. Thirdly, based on the proposed electrical and random usage models, a bottom-up approach is used to evaluate the harmonics and power of large-scale residential loads. Simulation results are compared with field measurements to verify the accuracy and validity of the proposed method. Furthermore, the proposed methodologies are applied to predict the harmonic generation and power consumption of some rapidly developing harmonic sources such as electric vehicles.

Suggested Citation

  • Sun, Yuanyuan & Xie, Xiangmin & Wang, Qingyan & Zhang, Linghan & Li, Yahui & Jin, Zongshuai, 2020. "A bottom-up approach to evaluate the harmonics and power of home appliances in residential areas," Applied Energy, Elsevier, vol. 259(C).
    • Handle: RePEc:eee:appene:v:259:y:2020:i:c:s030626191931894x
    DOI: 10.1016/j.apenergy.2019.114207
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    Cited by:

    1. Li, Yahui & Sun, Yuanyuan & Wang, Qingyan & Sun, Kaiqi & Li, Ke-Jun & Zhang, Yan, 2023. "Probabilistic harmonic forecasting of the distribution system considering time-varying uncertainties of the distributed energy resources and electrical loads," Applied Energy, Elsevier, vol. 329(C).
    2. da Silva, Roberto Perillo Barbosa & Quadros, Rodolfo & Shaker, Hamid Reza & da Silva, Luiz Carlos Pereira, 2020. "Effects of mixed electronic loads on the electrical energy systems considering different loading conditions with focus on power quality and billing issues," Applied Energy, Elsevier, vol. 277(C).
    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).
    4. Zhou, Wei & Wu, Yue & Huang, Xiang & Lu, Renzhi & Zhang, Hai-Tao, 2022. "A group sparse Bayesian learning algorithm for harmonic state estimation in power systems," Applied Energy, Elsevier, vol. 306(PB).
    5. Hongbo Cao & Faqiang Wang, 2023. "An Overview of Complex Instability Behaviors Induced by Nonlinearity of Power Electronic Systems with Memristive Load," Energies, MDPI, vol. 16(6), pages 1-25, March.

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