Extreme Learning Machine for Economic Dispatch with High Penetration of Wind Power

Yuanzheng Li; Yong Zhao; Lei Wu; Zhigang Zeng

doi:10.1007/978-981-99-0799-1_8

Extreme Learning Machine for Economic Dispatch with High Penetration of Wind Power

Yuanzheng Li
, Yong Zhao
, Lei Wu
, Zhigang Zeng

Department of Electrical and Computer Engineering

Huazhong University of Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

In recent years, renewable energy has been paid more attention and utilized more extensively throughout the world [1].

Original language	English
Title of host publication	Engineering Applications of Computational Methods
Pages	157-182
Number of pages	26
DOIs	https://doi.org/10.1007/978-981-99-0799-1_8
State	Published - 2023

Publication series

Name	Engineering Applications of Computational Methods
Volume	14
ISSN (Print)	2662-3366
ISSN (Electronic)	2662-3374

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Access to Document

10.1007/978-981-99-0799-1_8

Cite this

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title = "Extreme Learning Machine for Economic Dispatch with High Penetration of Wind Power",

abstract = "In recent years, renewable energy has been paid more attention and utilized more extensively throughout the world [1].",

author = "Yuanzheng Li and Yong Zhao and Lei Wu and Zhigang Zeng",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.",

year = "2023",

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BT - Engineering Applications of Computational Methods

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