A new BP neural network based method for load harmonic current assessment

  • Authors:

  • Ke Zhang;Gang Xiong;Xiaojun Zhu

  • Affiliations:

  • Guangdong Power Grid Corp. Foshan Power Supply Bureau, Foshan, China;Guangdong Power Grid Corp. Foshan Power Supply Bureau, Foshan, China;Guangdong Power Grid Corp. Foshan Power Supply Bureau, Foshan, China

  • Venue:
  • ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
  • Year:
  • 2013

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Abstract

This paper proposed a new BP Neural Network (BPNN) based method for load harmonic current assessment where the nonlinearities of electricity loads have been modeled based on differential equations. With the trained BPNN, the load current due to fundamental voltage inputs can be well estimated and used to assess the harmonics components subsequently. The simulation results demonstrate that the proposed method can effectively estimate the total harmonic distortion of the load current when the supplied voltage is within the normal range of harmonic limits. The results also prove that the load harmonic current is nearly independent of load capacity and applied voltage, indicating its effectiveness to distinguish the responsibilities of harmonic pollution between the grid and load.