Intelligent optimization method for time period of power grid operation based on knowledge model
ID:62 View Protection:ATTENDEE Updated Time:2023-11-20 13:45:38 Hits:943 Oral Presentation

Start Time:2023-12-10 10:45(Asia/Shanghai)

Duration:15min

Session:S8 AI-driven technology » S8AI-driven technology

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Abstract
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.
Keywords
power grid operation,risk assessment, time period optimization,knowledge model
Speaker
Lu Gaohan
Student Southeast University

Submission Author
Lu Gaohan Southeast University
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Important Date
  • Conference Date

    Dec 08

    2023

    to

    Dec 10

    2023

  • Nov 01 2023

    Draft paper submission deadline

  • Dec 10 2023

    Registration deadline

Sponsored By
IEEE IAS
Organized By
Southwest Jiaotong University (SWJTU)