An efficient binary Harris hawks optimization based on logical operators for wind turbine layout according to various wind scenarios
Nowadays, with the demand for renewable energy the interest in wind energy is increasing day by day and the use of wind turbines is becoming widespread. In order to efficiently generate electricity from wind turbines, it is important that the turbines are correctly positioned on wind farms. In this study, a standard wind farm area of 2 km × 2 km was used for wind turbine layout. In addition, different from the literature, a 4 km × 4 km wind farm area was also created. Both wind farming areas were divided into 10 × 10 and 20 × 20 grids as in the literature. In addition, 25 × 25, 40 × 40 and 50 × 50 grids were also created. Thus, the wind farming area is divided into more grids and more flexible positioning of the turbines is aimed. There are three different case scenarios for the layout of the wind turbines. Case A has a constant wind speed of 12 m/s and unidirectional wind, while Case B has a constant wind speed of 12 m/s with a 36-directional 10° angle. Case C has variable wind speeds of 8, 12 and 17 m/s with a 36-directional 10° angle. The HHO algorithm was used to perform all these processes. However, since the wind turbine layout problem is binary, the HHO algorithm is adapted to binary with logic operators. These binary methods are called HHO AND and HHO XOR . The proposed methods achieved competitive results compared to other algorithms in the literature and performed well for all grid structures. Thus, it can be said that the proposed methods are effective for the wind turbine layout problem.
Authors
- Ayşe Beşkirli (ORCID: https://orcid.org/0000-0002-8694-8438)
Institutions
- Karamanoğlu Mehmetbey University (TR)
Publication Details
- Journal
- Engineering Science and Technology an International Journal
- Published
- 2025-04-18
- DOI
- https://doi.org/10.1016/j.jestch.2025.102057
- Citations
- 1
- Primary Topic
- Wind Energy Research and Development
- Type
- article
- Field-Weighted Citation Impact
- 4.99