A Case Study: Layout Optimization of Three Gorges Wind Farm Pakistan, Using Genetic Algorithm

Muhammad Bin Ali; Zeshan Ahmad; Saad Alshahrani; Muhammad Rizwan Younis; Irsa Talib; Muhammad Imran

doi:10.3390/su142416960

A Case Study: Layout Optimization of Three Gorges Wind Farm Pakistan, Using Genetic Algorithm

Muhammad Bin Ali
, Zeshan Ahmad
, Saad Alshahrani^*
, Muhammad Rizwan Younis
, Irsa Talib
, Muhammad Imran

^*Corresponding author for this work

University of Management and Technology (UMT) Lahore
King Khalid University

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

27 Downloads (Pure)

Abstract

Wind is an important renewable energy source. The majority of wind farms in Pakistan are installed in Jhimpir, Sindh Wind Corridor. At this location, downstream turbines encounter upstream turbines’, wake, decreasing power output. To maximize the power output, there is a need to minimize these wakes. In this research, a method is proposed to maximize the power output using a Genetic Algorithm (GA). Hub heights and inter-turbine spacing are considered variables in this method. Two wind farms located at Jhimpir, Sindh, namely, Second and Third Three Gorges Wind Farms (TGWFs), have been analyzed. Three different cases are considered to maximize the power output. In Case 1, thesame hub heights and inter-turbine spacing without wake effects are considered. In Case 2, the same hub heights and inter-turbine spacing with wake effects are considered. In Case 3, variable hub heights and inter-turbine spacing with wake effects are considered. The results revealed that TGWFs, with variable hub heights and inter-turbine spacing, produce more power output. It is also revealed that the increase in power output, in the case of two different hub heights, is greater in comparison to three different hub heights. Eventually, the proposed method may help in the layout optimization of a wind farm.

Original language	English
Article number	16960
Number of pages	18
Journal	Sustainability (Switzerland)
Volume	14
Issue number	24
DOIs	https://doi.org/10.3390/su142416960
Publication status	Published - 17 Dec 2022

Bibliographical note

Funding Information:
Deanship of Scientific Research at King Khalid University, Saudi Arabia, Grant No: R.G.P.2/32/43.

Funding Information:
Deanship of Scientific Research at King Khalid University, Saudi Arabia, Grant No: R.G.P.2/32/43.

Publisher copyright © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Funding

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University, Saudi Arabia, for funding this work through the Research Group Program under Grant No: R.G.P.2 /32/43. Deanship of Scientific Research at King Khalid University, Saudi Arabia, Grant No: R.G.P.2/32/43.

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

genetic algorithm
hub height
inter-turbine spacing
layout optimization
turbine
wind energy

Access to Document

10.3390/su142416960Licence: CC BY 4.0

Layout Optimization of Three Gorges Wind Farm Pakistan
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Final published version, 4.34 MBLicence: CC BY 4.0

Cite this

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title = "A Case Study: Layout Optimization of Three Gorges Wind Farm Pakistan, Using Genetic Algorithm",

abstract = "Wind is an important renewable energy source. The majority of wind farms in Pakistan are installed in Jhimpir, Sindh Wind Corridor. At this location, downstream turbines encounter upstream turbines{\textquoteright}, wake, decreasing power output. To maximize the power output, there is a need to minimize these wakes. In this research, a method is proposed to maximize the power output using a Genetic Algorithm (GA). Hub heights and inter-turbine spacing are considered variables in this method. Two wind farms located at Jhimpir, Sindh, namely, Second and Third Three Gorges Wind Farms (TGWFs), have been analyzed. Three different cases are considered to maximize the power output. In Case 1, thesame hub heights and inter-turbine spacing without wake effects are considered. In Case 2, the same hub heights and inter-turbine spacing with wake effects are considered. In Case 3, variable hub heights and inter-turbine spacing with wake effects are considered. The results revealed that TGWFs, with variable hub heights and inter-turbine spacing, produce more power output. It is also revealed that the increase in power output, in the case of two different hub heights, is greater in comparison to three different hub heights. Eventually, the proposed method may help in the layout optimization of a wind farm.",

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note = "Funding Information: Deanship of Scientific Research at King Khalid University, Saudi Arabia, Grant No: R.G.P.2/32/43. Funding Information: Deanship of Scientific Research at King Khalid University, Saudi Arabia, Grant No: R.G.P.2/32/43. Publisher copyright {\textcopyright} 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).",

year = "2022",

month = dec,

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AU - Younis, Muhammad Rizwan

AU - Talib, Irsa

AU - Imran, Muhammad

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N2 - Wind is an important renewable energy source. The majority of wind farms in Pakistan are installed in Jhimpir, Sindh Wind Corridor. At this location, downstream turbines encounter upstream turbines’, wake, decreasing power output. To maximize the power output, there is a need to minimize these wakes. In this research, a method is proposed to maximize the power output using a Genetic Algorithm (GA). Hub heights and inter-turbine spacing are considered variables in this method. Two wind farms located at Jhimpir, Sindh, namely, Second and Third Three Gorges Wind Farms (TGWFs), have been analyzed. Three different cases are considered to maximize the power output. In Case 1, thesame hub heights and inter-turbine spacing without wake effects are considered. In Case 2, the same hub heights and inter-turbine spacing with wake effects are considered. In Case 3, variable hub heights and inter-turbine spacing with wake effects are considered. The results revealed that TGWFs, with variable hub heights and inter-turbine spacing, produce more power output. It is also revealed that the increase in power output, in the case of two different hub heights, is greater in comparison to three different hub heights. Eventually, the proposed method may help in the layout optimization of a wind farm.

AB - Wind is an important renewable energy source. The majority of wind farms in Pakistan are installed in Jhimpir, Sindh Wind Corridor. At this location, downstream turbines encounter upstream turbines’, wake, decreasing power output. To maximize the power output, there is a need to minimize these wakes. In this research, a method is proposed to maximize the power output using a Genetic Algorithm (GA). Hub heights and inter-turbine spacing are considered variables in this method. Two wind farms located at Jhimpir, Sindh, namely, Second and Third Three Gorges Wind Farms (TGWFs), have been analyzed. Three different cases are considered to maximize the power output. In Case 1, thesame hub heights and inter-turbine spacing without wake effects are considered. In Case 2, the same hub heights and inter-turbine spacing with wake effects are considered. In Case 3, variable hub heights and inter-turbine spacing with wake effects are considered. The results revealed that TGWFs, with variable hub heights and inter-turbine spacing, produce more power output. It is also revealed that the increase in power output, in the case of two different hub heights, is greater in comparison to three different hub heights. Eventually, the proposed method may help in the layout optimization of a wind farm.

KW - genetic algorithm

KW - hub height

KW - inter-turbine spacing

KW - layout optimization

KW - turbine

KW - wind energy

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JO - Sustainability (Switzerland)

JF - Sustainability (Switzerland)

IS - 24

M1 - 16960

ER -

A Case Study: Layout Optimization of Three Gorges Wind Farm Pakistan, Using Genetic Algorithm

Abstract

Bibliographical note

Funding

UN SDGs

Keywords

Access to Document

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