Knowledge Network Node
Electrical Measurement ＆ Instrumentation. Core
(Accepted Version) Online First Publishing Date: 2024-06-18 15:14:45

Ultra-short-term wind speed prediction method based on CEEMDAN and BiLSTM-AMChinese Full TextEnglish Full Text (MT)

Yin Yuanya;Pan Wenhu;Zhao Wenguang;Su Zhipeng;Han Yi;Wu Hongbin;

Abstract: Accurate wind speed prediction results can promote the efficient consumption of wind power and enhance the safety and stability of novel power system. To further explore the nonlinear characteristics of wind speed sequences and improve the accuracy of wind speed prediction， an ultra-short-term wind speed prediction method based on CEEMDAN and BiLSTM-AM is proposed. In response to the random fluctuation of wind speed， the complete ensemble empirical mode decomposition with adaptive noise （CEEMDAN... More
Keywords：

ultra-short-term wind speed prediction; complete ensemble empirical mode decomposition with adaptive noise; bidirectional long short-term memory; attention mechanism; Bayesian optimization;

  • Series：

    (C) Architecture/ Energy/ Traffic/ Electromechanics, etc

  • Subject：

    Electric Power Industry

  • Classification Code：

    TM614

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