Short-term wind power prediction method based on multivariate signal decomposition and RIME optimization algorithm-Reference-Cited by-同舟云学术

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Short-term wind power prediction method based on multivariate signal decomposition and RIME optimization algorithm

Published:2025-01 Issue: Volume:259 Page:125376
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Wang Yansong^ORCID,Pei Lili^ORCID,Li Wei^ORCID,Zhao Yuanlin,Shan Yihui

Publisher

Elsevier BV

Reference60 articles.

1. A boundary layer scaling technique for estimating near-surface wind energy using numerical weather prediction and wind map data;Allen;Applied Energy,2017

2. Short-term wind power forecasting using ridgelet neural network;Amjady;Electric Power Systems Research,2011

3. AWNN-assisted wind power forecasting using feed-forward neural network;Bhaskar;IEEE Transactions on Sustainable Energy,2012

4. A hybrid wind speed prediction model using improved CEEMDAN and autoformer model with auto-correlation mechanism;Bommidi;Sustainable Energy Technologies and Assessments,2024

5. Wind energy integration: Variability analysis and power system impact assessment;Ciupăgeanu;Energy,2019

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