Optimization of the Offshore Wind Turbines Layout Using Cuckoo Search Algorithm

Ibrahim Abdulwahab; Solomon Andrew Onazi; Gideon Rimamfate; Akande Abdulwasiu; Abubakar Umar; N.A Iliyasu

doi:10.51173/jt.v6i2.2585

Authors

Ibrahim Abdulwahab Department of Electrical Engineering, Ahmadu Bello University, Zaria, Nigeria
Solomon Andrew Onazi Department of Electrical Engineering, Ahmadu Bello University, Zaria, Nigeria
Gideon Rimamfate Department of Electrical Engineering, Ahmadu Bello University, Zaria, Nigeria
Akande Abdulwasiu Ikeja Electricity Distribution Company, Lagos, Nigeria
Abubakar Umar Department of Computer Engineering, Ahmadu Bello University, Zaria, Nigeria
N.A Iliyasu Department of Computer Engineering, Ahmadu Bello University, Zaria, Nigeria

DOI:

https://doi.org/10.51173/jt.v6i2.2585

Keywords:

Cuckoo Search Algorithm, Renewable Energy, Wake Effect, Wind Farm, Wind Turbine

Abstract

Wind turbines have gained popularity as one of the efficient micro grid energy generation sources over the years. However, wind energy yield has been greatly impacted by the wind farm wake effect, especially when the size of the wind farm becomes very large. One way to address this challenge is through wind turbine arrangements and their scalability. Developing effective means of optimizing wind farm configurations is a major concern for energy communities. This has continuously led to increased power generation and a corresponding cost reduction. As such, this research article developed an optimal large-scale offshore wind turbine placement based on wind farm layout design. The system developed focuses on wind turbine placement in wind farm layouts that have a negative influence on the capital investment due to the increasing wake effect thereby reducing energy production. A multi-objective function consisting of wake effect and component costs within the wind farm is formulated. After-which a cuckoo search algorithm technique is employed in the wind farm model to optimize the optimization problem (minimizing the wake effect while improving power output and cost). Four test case scenarios were considered when implementing the wind model. The results obtained from the developed scheme were compared with those obtained when other optimization techniques were used, using power output and cost as performance metrics. The obtained power output and cost for the test case scenario in the ideal wind turbine position on the wind farm are 18288.3KW, 19680.1KW, 18879.9KW, 21105.8KW and 26.9, 28.7, 26.9, and 29.8KW, respectively. This shows that the result obtained from the developed scheme outperformed that obtained from PSO and that of WOA.

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Author Biographies

Ibrahim Abdulwahab, Department of Electrical Engineering, Ahmadu Bello University, Zaria, Nigeria

Solomon Andrew Onazi, Department of Electrical Engineering, Ahmadu Bello University, Zaria, Nigeria

Gideon Rimamfate, Department of Electrical Engineering, Ahmadu Bello University, Zaria, Nigeria

Akande Abdulwasiu, Ikeja Electricity Distribution Company, Lagos, Nigeria

Abubakar Umar, Department of Computer Engineering, Ahmadu Bello University, Zaria, Nigeria

N.A Iliyasu, Department of Computer Engineering, Ahmadu Bello University, Zaria, Nigeria

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