Intelligent optimization method for time period of power grid operation based on knowledge model
编号:62 访问权限:仅限参会人 更新:2023-11-20 13:45:38 浏览:482次 口头报告

报告开始:2023年12月10日 10:45(Asia/Shanghai)

报告时间:15min

所在会场:[S8] AI-driven technology [S8] AI-driven technology

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摘要
Modern power systems impose higher requirements on the time period selection of power grid operation. On one hand, factors influencing operating costs have become more intricate, and on the other hand, the disparities in costs across different time periods have become more pronounced. Therefore, based on a knowledge model, this paper proposes a method to determine the optimal time period for operations. Firstly, this paper analyzes various factors that affect the operation cost and provides a quantitative calculation model. Then, to accelerate the optimization process, a knowledge model for optimizing the operation time period is established based on historical operating data, especially operation ticket data. Finally, the proposed optimization method is applied to the power grid in northwest China. The results demonstrate that the proposed method can identify the optimal operational time period and has a higher computational efficiency compared to the traditional enumeration method.
关键词
power grid operation,risk assessment, time period optimization,knowledge model
报告人
Lu Gaohan
Student Southeast University

稿件作者
Lu Gaohan Southeast University
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重要日期
  • 会议日期

    12月08日

    2023

    12月10日

    2023

  • 11月01日 2023

    初稿截稿日期

  • 12月10日 2023

    注册截止日期

主办单位
IEEE IAS
承办单位
Southwest Jiaotong University (SWJTU)
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