A physics-inspired neural network model for short-term wind power prediction considering wake effects-Reference-Cited by-同舟云学术

A physics-inspired neural network model for short-term wind power prediction considering wake effects

Published:2022-12 Issue: Volume:261 Page:125208
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Guo Nai-Zhi,Shi Ke-Zhong,Li Bo,Qi Liang-Wen,Wu Hong-Hui,Zhang Zi-Liang,Xu Jian-Zhong

Funder

China Three Gorges Corporation

National Natural Science Foundation of China

Chinese Academy of Sciences

China Postdoctoral Science Foundation

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

General Energy,Pollution,Mechanical Engineering,Building and Construction,Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Civil and Structural Engineering

Reference41 articles.

1. A review of multiphase energy conversion in wind power generation;Peng;Renew Sustain Energy Rev,2021

2. GWEC| global wind report 2021,2021

3. A critical review of wind power forecasting methods—past, present and future;Hanifi;Energies,2020

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