Large Wind Farm Layout Optimization Using Nature Inspired Meta-Heuristic Algorithms-Reference-Cited by-同舟云学术

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Large Wind Farm Layout Optimization Using Nature Inspired Meta-Heuristic Algorithms

Published:2021-04-05 Issue: Volume: Page:1-18
ISSN:0377-2063
Container-title:IETE Journal of Research
language:en
Short-container-title:IETE Journal of Research

Author:

Aggarwal Sanjeev K.¹^ORCID,Saini Lalit M.²,Sood Vijay³

Affiliation:

1. Electrical and Instrumentation Engineering Department, Thapar Institute of Engineering and Technology, Patiala, India

2. Electrical Engineering Department, National Institute of Technology, Kurukshetra, India

3. Electrical Engineering Department, Ontario Tech University (formerly University of Ontario Institute of Technology), Oshawa, Canada

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Computer Science Applications,Theoretical Computer Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/03772063.2021.1905082

Reference73 articles.

1. Global Wind Statistics 2019 - GWEC. https://gwec.net/global-wind-report-2019. accessed: June 20, 2020.

2. Wind wake influence estimation on energy production of wind farm by adaptive neuro-fuzzy methodology

3. An appraisal of wind turbine wake models by adaptive neuro-fuzzy methodology

4. Wind Farm Layout Optimization Competition. http://www.irit.fr/wind-competition/.

5. 2014 Optimal Power Flow Problem Competition. https://www.uni-due.de/ieee-wgmho/competition2014.

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