Ensemble probabilistic wind power forecasting with multi-scale features-Reference-Cited by-同舟云学术

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Ensemble probabilistic wind power forecasting with multi-scale features

Published:2022-12 Issue: Volume:201 Page:734-751
ISSN:0960-1481
Container-title:Renewable Energy
language:en
Short-container-title:Renewable Energy

Author:

Wang Yun,Chen Tuo,Zou Runmin,Song Dongran,Zhang Fan,Zhang Lingjun

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hunan Province

Key Research and Development Program of Hunan Province of China

Key Project of Research and Development Plan of Hunan Province

Publisher

Elsevier BV

Subject

Renewable Energy, Sustainability and the Environment

Reference66 articles.

1. Coordinated optimization on energy capture and torque fluctuation of wind turbines via variable weight NMPC with fuzzy regulator;Song;Appl. Energy,2022

2. A review of wind speed and wind power forecasting with deep neural networks;Wang;Appl. Energy,2021

3. Uncertainties towards a fossil-free system with high integration of wind energy in long-term planning;Pizarro-Alonso;Appl. Energy,2019

4. A multi-objective wind speed and wind power prediction interval forecasting using variational modes decomposition based Multi-kernel robust ridge regression;Naik;Renew. Energy,2019

5. Prediction interval of wind power using parameter optimized beta distribution based LSTM model;Yuan;Appl. Soft Comput.,2019

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1. Dynamic non-constraint ensemble model for probabilistic wind power and wind speed forecasting;Renewable and Sustainable Energy Reviews;2024-10

2. Enhancement of Texas wind turbine power predictions using fractional order neural network by incorporating machine learning models to impute missing data;Knowledge-Based Systems;2024-09

3. Wind power generation forecasting based on multi‐model fusion via blending ensemble learning architecture;Electronics Letters;2024-08

4. Two-stage short-term wind power probabilistic prediction using natural gradient boosting combined with neural network;Applied Soft Computing;2024-07

5. Arbitrary polynomial chaos-based power system dynamic analysis with correlated uncertainties;International Journal of Electrical Power & Energy Systems;2024-06

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