Journal of Northeastern University Natural Science ›› 2017, Vol. 38 ›› Issue (1): 6-10.DOI: 10.12068/j.issn.1005-3026.2017.01.002

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Phase Estimation Method for Power System Based on Complex Adaptive Neural Network

LI Yun-lu, WANG Da-zhi, NING Yi, HUI Nan-mu   

  1. School of Information Science & Engineering, Northeastern University, Shenyang 110819, China.
  • Received:2015-07-09 Revised:2015-07-09 Online:2017-01-15 Published:2017-01-13
  • Contact: LI Yun-lu
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Abstract: Aiming at the difficulty of grid phase detection under non-ideal voltage caused by unbalanced voltage and frequency fluctuation, a phase estimation method was proposed for power system based on complex adaptive neural network. On the basis of neural network model of non-ideal grid voltage, the weight update method of complex least mean squares to the process of weight update procedure of neural network was introduced. Then the weights of neural network were used to calculate the phase. To trace the frequency of grid, a frequency tracing unit was designed and it was proved to be convergent. The simulation and experiment results demonstrate that the proposed method is able to estimate the phase rapidly and precisely under non-ideal voltage conditions.

Key words: phase estimation, neural network, unbalanced voltage, frequency tracing, grid phase

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