Echo state network based ensemble approach for wind power forecasting-Reference-Cited by-同舟云学术

Echo state network based ensemble approach for wind power forecasting

Published:2019-12 Issue: Volume:201 Page:112188
ISSN:0196-8904
Container-title:Energy Conversion and Management
language:en
Short-container-title:Energy Conversion and Management

Author:

Wang Huaizhi,Lei Zhenxing,Liu Yang^ORCID,Peng Jianchun,Liu Jing

Funder

National Natural Science Foundation of China

Natural Science Foundations of Guangdong Province

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment

Reference61 articles.

1. An overview of the concept and technology of ubiquitous energy;Alanne;Appl Energy,2019

2. Marine renewable energy potential: a global perspective for offshore wind and wave exploitation;Carlos;Energy Convers Manage,2018

3. National and global wind resource assessment under six wind turbine installation scenarios;Jung;Energy Convers Manage,2018

4. Short-term wind power forecasting using a double-stage hierarchical ANFIS approach for energy management in microgrids. Protection and Control of;Zheng;Modern Power Syst,2017

5. Deep learning based ensemble approach for probabilistic wind power forecasting;Wang;Appl Energy,2017

Cited by 59 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. A hybrid model for deep learning short-term power load forecasting based on feature extraction statistics techniques;Expert Systems with Applications;2024-03

2. Wind power generation prediction during the COVID-19 epidemic based on novel hybrid deep learning techniques;Renewable Energy;2024-02

3. A novel sampled-data asynchronous CatBoost model with knowledge-based guidance for product quality estimation in the industrial processes;Measurement;2024-02

4. Wind speed and wind power forecasting models;Energy & Environment;2024-01-31

5. GATE: A guided approach for time series ensemble forecasting;Expert Systems with Applications;2024-01