A Short-Term Calgorithm Based on Improved LSTM Neural Network

A Short-Term Calgorithm Based on Improved LSTM Neural Network

[Introduction] The volatility and intermittency of wind energy pose significant challenges for large-scale wind power integration. An effective approach to address this issue is to provide accurate wind power forecasting. [Method] In response to this challenge, this study proposed a wind power forec...

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Bibliographic Details
Main Authors: Sheng GAO, Peihua XU, Zhenghong CHEN, Chi CHENG
Format: Article
Language:English
Published: Energy Observer Magazine Co., Ltd. 2024-01-01
Series:南方能源建设
Subjects:
wind power day-ahead forecasting
lstm neural network
deep learning
anomaly detection and handling
wind speed fluctuation features
Online Access:https://www.energychina.press/en/article/doi/10.16516/j.ceec.2024.1.12

Internet

https://www.energychina.press/en/article/doi/10.16516/j.ceec.2024.1.12

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