Optimizing the layout of 1000 wind turbines

Markus Wagner; Kalyan Veeramachaneni; Frank Neumann; Una May O'Reilly

Optimizing the layout of 1000 wind turbines

Markus Wagner, Kalyan Veeramachaneni, Frank Neumann, Una May O'Reilly

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

Abstract

In this paper we demonstrate an accurate, efficient, and parallelizable optimization algorithm for the layout of hundreds, then 1000, turbines. It is modular and therefore allows different wake effect models to be incorporated. Its computational cost is a relation which depends upon how many candidate layouts it investigates and the complexity of its wake loss calculation. We demonstrate how well it maximizes energy capture and show how it allows one to examine how wake loss scales with energy capture and number of turbines. Keywords: Wind farm design, output maximization, wake consideration, Covariance Matrix Adaptation, Evolutionary strategy.

Original language	English
Title of host publication	European Wind Energy Conference and Exhibition 2011, EWEC 2011
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	205-209
Number of pages	5
ISBN (Print)	9781618399915
Publication status	Published - 2011
Externally published	Yes
Event	European Wind Energy Conference and Exhibition 2011 - Brussels, Belgium Duration: 14 Mar 2011 → 17 Mar 2011 http://toc.proceedings.com/14893webtoc.pdf (Proceedings)

Conference

Conference	European Wind Energy Conference and Exhibition 2011
Abbreviated title	EWEC 2011
Country/Territory	Belgium
City	Brussels
Period	14/03/11 → 17/03/11
Internet address	http://toc.proceedings.com/14893webtoc.pdf (Proceedings)

UN SDGs

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

Cite this

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title = "Optimizing the layout of 1000 wind turbines",

abstract = "In this paper we demonstrate an accurate, efficient, and parallelizable optimization algorithm for the layout of hundreds, then 1000, turbines. It is modular and therefore allows different wake effect models to be incorporated. Its computational cost is a relation which depends upon how many candidate layouts it investigates and the complexity of its wake loss calculation. We demonstrate how well it maximizes energy capture and show how it allows one to examine how wake loss scales with energy capture and number of turbines. Keywords: Wind farm design, output maximization, wake consideration, Covariance Matrix Adaptation, Evolutionary strategy.",

author = "Markus Wagner and Kalyan Veeramachaneni and Frank Neumann and O'Reilly, \{Una May\}",

year = "2011",

language = "English",

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pages = "205--209",

booktitle = "European Wind Energy Conference and Exhibition 2011, EWEC 2011",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "European Wind Energy Conference and Exhibition 2011, EWEC 2011 ; Conference date: 14-03-2011 Through 17-03-2011",

url = "http://toc.proceedings.com/14893webtoc.pdf",

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TY - GEN

T1 - Optimizing the layout of 1000 wind turbines

AU - Wagner, Markus

AU - Veeramachaneni, Kalyan

AU - Neumann, Frank

AU - O'Reilly, Una May

PY - 2011

Y1 - 2011

N2 - In this paper we demonstrate an accurate, efficient, and parallelizable optimization algorithm for the layout of hundreds, then 1000, turbines. It is modular and therefore allows different wake effect models to be incorporated. Its computational cost is a relation which depends upon how many candidate layouts it investigates and the complexity of its wake loss calculation. We demonstrate how well it maximizes energy capture and show how it allows one to examine how wake loss scales with energy capture and number of turbines. Keywords: Wind farm design, output maximization, wake consideration, Covariance Matrix Adaptation, Evolutionary strategy.

AB - In this paper we demonstrate an accurate, efficient, and parallelizable optimization algorithm for the layout of hundreds, then 1000, turbines. It is modular and therefore allows different wake effect models to be incorporated. Its computational cost is a relation which depends upon how many candidate layouts it investigates and the complexity of its wake loss calculation. We demonstrate how well it maximizes energy capture and show how it allows one to examine how wake loss scales with energy capture and number of turbines. Keywords: Wind farm design, output maximization, wake consideration, Covariance Matrix Adaptation, Evolutionary strategy.

UR - https://www.scopus.com/pages/publications/84870186212

M3 - Conference Paper

AN - SCOPUS:84870186212

SN - 9781618399915

SP - 205

EP - 209

BT - European Wind Energy Conference and Exhibition 2011, EWEC 2011

PB - IEEE, Institute of Electrical and Electronics Engineers

T2 - European Wind Energy Conference and Exhibition 2011

Y2 - 14 March 2011 through 17 March 2011

ER -

Optimizing the layout of 1000 wind turbines

Abstract

Conference

UN SDGs

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