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  • 标题:A high order derivation method for distribution network transient data
  • 本地全文:下载
  • 作者:Bo Xiao ; Li Lv ; Yuxuan Kang
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2021
  • 卷号:243
  • 页码:1004
  • DOI:10.1051/e3sconf/202124301004
  • 出版社:EDP Sciences
  • 摘要:Nowadays, high-order data needs to be processed quickly and accurately by various algorithms in distribution networks. It is difficult to ensure the accuracy of calculation both in low-order and high-order cases, due to the theoretical limitations of traditional high-order derivation methods. Aimed to improve the calculation accuracy, a new high-order derivative method based on the polynomial fitting is proposed in this paper. By analyzing the transient characteristics of voltage and current signals in the distribution network, the base fitting-function can be selected, and the coefficient of the base function can be obtained to fit the objective function by the least square method. The original discrete data will be replaced by new fitting-function for derivative operation, which not only ensures the anti-interference ability, but also overcomes the limitations of the traditional polynomial fitting method in high-order cases. The simulation results show that this method has high accuracy in high-order and low-order cases, and has good accuracy and anti-interference ability.
  • 其他摘要:Nowadays, high-order data needs to be processed quickly and accurately by various algorithms in distribution networks. It is difficult to ensure the accuracy of calculation both in low-order and high-order cases, due to the theoretical limitations of traditional high-order derivation methods. Aimed to improve the calculation accuracy, a new high-order derivative method based on the polynomial fitting is proposed in this paper. By analyzing the transient characteristics of voltage and current signals in the distribution network, the base fitting-function can be selected, and the coefficient of the base function can be obtained to fit the objective function by the least square method. The original discrete data will be replaced by new fitting-function for derivative operation, which not only ensures the anti-interference ability, but also overcomes the limitations of the traditional polynomial fitting method in high-order cases. The simulation results show that this method has high accuracy in high-order and low-order cases, and has good accuracy and anti-interference ability.
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