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Double Decomposition-Based Wind Speed Prediction Model for Urad Area

Published: 13 April 2022 Publication History

Abstract

Renewable energy becomes progressively more important as time goes on. Wind, as one of the main rapidly developing renewable energy, is free, widely distributed, clean, environmental protection and sustainable development. The uncertainty of wind power which causes the inaccuracy of traditional wind speed prediction has become great challenge for wind power utilization. This paper predicts the wind speed by analyzing the measured data of 70-100m wind tower in Urad area. Handling the high-frequency sub-sequences after the first-level decomposition which cause the inaccuracy, a double decomposition based on EWT-VMD is proposed, which uses SampEn to determine the parameters of them. And then applied LSTM neural network to predict the wind speed one step in advance. The MAE, RMSE and R2 of the proposed model improved by at least 10.5%, 11.4% and 1.5% when comparing with other models.

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ICMLSC '22: Proceedings of the 2022 6th International Conference on Machine Learning and Soft Computing
January 2022
185 pages
ISBN:9781450387477
DOI:10.1145/3523150
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 13 April 2022

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Author Tags

  1. decomposition algorithm
  2. optimization algorithm
  3. wind energy
  4. wind speed prediction

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