Work

Day-ahead wind power prediction using an ensemble model considering multiple indicators combined with error correction

Year: 2023

Type: article

Source: Applied Soft Computing

DOI: 10.1016/j.asoc.2023.110873

Authors: Siyi Zhang, Mingbo Liu, Mingde Liu, Zhenxing Lei, Guihua Zeng, Zirui Chen

Institution: South China University of 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

Open Access status: green

Funders: Guangdong Science and Technology Department, Special Project for Research and Development in Key areas of Guangdong Province

Award: G4660366032

OpenAlex ID: W4386954302

FWCI: 1.802

Cites: 40

Cited by: 25

Related to: 10