Work

Wind power forecasting based on hybrid CEEMDAN-EWT deep learning method

Year: 2023

Type: article

Source: Renewable Energy

DOI: 10.1016/j.renene.2023.119357

Authors: Irene Karijadi, Shuo-Yan Chou, Anindhita Dewabharata

Institutions: Universitas Katolik Widya Mandala Surabaya, National Taiwan University of Science and Technology

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, Industry, innovation and infrastructure

Open Access status: closed

OpenAlex ID: W4386955786

FWCI: 11.97

Cites: 77

Cited by: 170

Related to: 10