Univariate and multivariable forecasting models for ultra-short-term wind power prediction based on the similar day and LSTM network-Reference-Cited by-同舟云学术

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Univariate and multivariable forecasting models for ultra-short-term wind power prediction based on the similar day and LSTM network

Published:2021-11 Issue:6 Volume:13 Page:063307
ISSN:1941-7012
Container-title:Journal of Renewable and Sustainable Energy
language:en
Short-container-title:Journal of Renewable and Sustainable Energy

Author:

Xu Hai-Yan¹,Chang Yu-Qing¹^ORCID,Wang Fu-Li¹²,Wang Shu¹,Yao Yuan³

Affiliation:

1. College of Information Science and Engineering, Northeastern University, Shenyang 110819, China

2. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China

3. State Grid Liaoning Electric Power Co. Ltd, Shenyang 110000, China

Funder

National Nature Science Foundation of China

National Key Research and Development Program of China

Publisher

AIP Publishing

Subject

Renewable Energy, Sustainability and the Environment

Link

https://aip.scitation.org/doi/pdf/10.1063/5.0027130

Reference49 articles.

1. Smart wind speed forecasting using EWT decomposition, GWO evolutionary optimization, RELM learning and IEWT reconstruction

2. Markov chain‐based wind power time series modelling method considering the influence of the state duration on the state transition probability

3. A review of combined approaches for prediction of short-term wind speed and power

4. Wind Power Forecasts Using Gaussian Processes and Numerical Weather Prediction

5. Wind speed forecasting for wind farms: A method based on support vector regression

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Ultra-short-term wind power forecasting techniques: comparative analysis and future trends;Frontiers in Energy Research;2024-01-12

2. A novel integrated method for short-term wind power forecasting based on fluctuation clustering and history matching;Applied Energy;2022-12

3. Predicting wind power generation using machine learning and CNN-LSTM approaches;Wind Engineering;2022-07-21

4. A novel hybrid wind speed interval prediction model based on mode decomposition and gated recursive neural network;Environmental Science and Pollution Research;2022-07-08

5. Regional Ultra-Short-Term Wind Power Combination Prediction Method Based on Fluctuant/Smooth Components Division;Frontiers in Energy Research;2022-03-02

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