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 and Muhammad Imran
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Muhammad Bin Ali: Department of Mechanical Engineering, School of Engineering (SEN), University of Management & Technology, C II Johar Town, Lahore 54770, Pakistan
Zeshan Ahmad: Department of Mechanical Engineering, School of Engineering (SEN), University of Management & Technology, C II Johar Town, Lahore 54770, Pakistan
Saad Alshahrani: Department of Mechanical Engineering, College of Engineering, King Khalid University, P.O. Box 394, Abha 61421, Saudi Arabia
Muhammad Rizwan Younis: Department of Mechanical Engineering, School of Engineering (SEN), University of Management & Technology, C II Johar Town, Lahore 54770, Pakistan
Irsa Talib: Department of Mechanical Engineering, School of Engineering (SEN), University of Management & Technology, C II Johar Town, Lahore 54770, Pakistan
Muhammad Imran: Department of Mechanical, Biomedical and Design Engineering, College of Engineering and Physical Sciences, Aston University, Birmingham B4 7ET, UK

Sustainability, 2022, vol. 14, issue 24, 1-18

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.

Keywords: wind energy; turbine; genetic algorithm; layout optimization; inter-turbine spacing; hub height (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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