基于有限元和神经网络的电缆输送新能源极限能力评估
作者:
作者单位:

(上海电力大学电气工程学院,上海 200090)

作者简介:

通讯作者:

淡淑恒(1969—),女,博士,教授,主要从事电气设备与系统的相互影响研究;E?mail:danshuheng@shiep.edu.cn

中图分类号:

TM726.4

基金项目:

国家自然科学基金(50577040)


Evaluation of ultimate capacity of cable transmission new energy based on finite element and neural network
Author:
Affiliation:

(Electric Power Engineering of Shanghai University of Electric Power, Shanghai 200090, China)

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    新能源发电的不确定性对传输系统的输送能力提出了很大挑战。由于输电电缆具有一定过载能力,可在温度不超过限值的前提下短时过载运行,提出充分利用电缆的过载水平短时内提高电缆对新能源发电的输送能力的一种方法。该方法首先采用有限元法计算电缆温度场分布,确立线路允许过载运行时间并分析其影响因素,然后引入改进BP神经网络算法,结合实际发电出力曲线对过载时间进行预测。结果表明,该BP神经网络模型具有较高精度,可应用于评估电缆极限输送能力,为调度决策提供快速支持。

    Abstract:

    The uncertainty of new energy power generation poses a great challenge to the transmission system. Since the transmission cable has a certain overload capacity, it can be overloaded for a short time under the premise that the temperature does not exceed the limit value. A method of making full use of the overload level of the cable is proposed to improve the transmission capacity of the cable to new energy power generation in a short time. This method firstly uses the finite element method to calculate the cable temperature field distribution, establishes the allowable overload running time of the line and analyzes its influencing factors. Then the improved BP neural network algorithm is introduced to predict the overload time in combination with the actual power generation output curve. The results show that the BP neural network model has high accuracy and can be applied to evaluate the cable limit transmission capacity and provide rapid support for dispatching decisions.

    参考文献
    相似文献
    引证文献
引用本文

魏文青,淡淑恒.基于有限元和神经网络的电缆输送新能源极限能力评估[J].电力科学与技术学报,2023,38(1):191-200.
WEI Wenqing, DAN Shuheng. Evaluation of ultimate capacity of cable transmission new energy based on finite element and neural network[J]. Journal of Electric Power Science and Technology,2023,38(1):191-200.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2023-04-10
  • 出版日期: