Work

EALSTM-QR: Interval wind-power prediction model based on numerical weather prediction and deep learning

Year: 2020

Type: article

Source: Energy

DOI: 10.1016/j.energy.2020.119692

Authors: Xiaosheng Peng, Hongyu Wang, Jianxun Lang, Wenze Li, Qiyou Xu, Zuowei Zhang, Tao Cai, Shanxu Duan, Fangjie Liu, Chaoshun Li

Institutions: State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, China-EU Institute for Clean and Renewable Energy

Language: English

Topic: Energy Load and Power Forecasting

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Climate action

Open Access status: closed

Funder: National Key Research and Development Program of China

OpenAlex ID: W3117620741

FWCI: 5.313

Cites: 43

Cited by: 145

Related to: 10