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The operation management of distributed new energy stations is closely related to meteorology, while traditional new energy power prediction is often based on a single meteorological factor and cannot fully consider the comprehensive impact of changeable meteorological conditions on energy output. By conducting research on complex meteorological characteristics in this paper, the complex influences of different meteorological conditions on the power output of new energy stations can be captured more accurately, improving the accuracy and reliability of prediction. Meanwhile, the adoption of deep feature mapping technology can provide more reliable prediction data for power grid dispatching and optimize the dispatching strategies and planning layout of the power system. During the in-depth study of complex meteorological characteristics and high-dimensional deep feature mapping technology, it can promote technological innovation and development in the field of new energy, contribute to improving the accuracy of new energy power prediction, reduce uncertainties and risks, and provide strong support for the stable operation of new energy and the dispatching management of the power grid.

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Research on High Dimensional Depth Feature Mapping Technology of Distributed New Energy Based on Composite Meteorological Characteristics

  • 会议论文

  • 发表日期：

    2025年

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  • Shengjun Luo,
  • Jiajia Huang,
  • Jian Peng,
  • Xiaoqiang Huang,
  • Zhe Lin,
  • Xiaodong Tian,
  • Zhiyong Liu,
  • Junwen Long,
  • Yong Huang,
  • Zichao Zhang

摘要

The operation management of distributed new energy stations is closely related to meteorology, while traditional new energy power prediction is often based on a single meteorological factor and cannot fully consider the comprehensive impact of changeable meteorological conditions on energy output. By conducting research on complex meteorological characteristics in this paper, the complex influences of different meteorological conditions on the power output of new energy stations can be captured more accurately, improving the accuracy and reliability of prediction. Meanwhile, the adoption of deep feature mapping technology can provide more reliable prediction data for power grid dispatching and optimize the dispatching strategies and planning layout of the power system. During the in-depth study of complex meteorological characteristics and high-dimensional deep feature mapping technology, it can promote technological innovation and development in the field of new energy, contribute to improving the accuracy of new energy power prediction, reduce uncertainties and risks, and provide strong support for the stable operation of new energy and the dispatching management of the power grid.