Elman neural network considering dynamic time delay estimation for short-term forecasting of offshore wind power-Reference-Cited by-同舟云学术

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Elman neural network considering dynamic time delay estimation for short-term forecasting of offshore wind power

Published:2024-03 Issue: Volume:358 Page:122671
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Huang Jing,Qin Rui

Publisher

Elsevier BV

Reference67 articles.

1. Role of policy in innovation and international trade of renewable energy technology: empirical study of solar PV and wind power technology;Kim;Renew Sustain Energy Rev,2015

2. Changes in wind turbine power characteristics and annual energy production due to atmospheric stability, turbulence intensity, and wind shear;Kim;Energy.,2021

3. Power system planning based on CSP-CHP system to integrate variable renewable energy;Li;Energy.,2021

4. Importance subsampling: improving power system planning under climate-based uncertainty;Hilbers;Appl Energy,2019

5. Operations management of wind farms integrating multiple impacts of wind conditions and resource constraints;Yang;Energ Conver Manage,2020

Cited by 4 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. 3DTCN-CBAM-LSTM short-term power multi-step prediction model for offshore wind power based on data space and multi-field cluster spatio-temporal correlation;Applied Energy;2024-12

2. Research on the Short-Term Prediction of Offshore Wind Power Based on Unit Classification;Electronics;2024-06-12

3. Innovative Strategies for Wind Turbine Reliability: Leveraging Vibration Data for Early Prognosis;2024 International Conference on Communication, Computing and Internet of Things (IC3IoT);2024-04-17

4. An Adaptive Wind Speed Synergy Power Prediction Framework Considering Offshore Wind Power Boundary Effect;2024

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