Comparative performance of twelve metaheuristics for wind farm layout optimisation
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Tarih
2022-01
Kurum Yazarları
Kunakote, Tawatchai
Sabangban, Numchoak
Tejani, Ghanshyam G.
Panagant, Natee
Pholdee, Nantiwat
Kumar, Sumit
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Yayınevi
Springer
Özet
This work bridges two research fields i.e. metaheuristics and wind farm layout design. Comparative performance of twelve metaheuristics (MHs) on wind farm layout optimisation (WFLO) was conducted. Four WFLO problems are proposed for benchmarking the various metaheuristics while the design problem is an attempt to simultaneously minimise wind farm cost and maximise wind farm totally produced power. Design variables are wind turbine placement with fixed and varied number of wind turbines. The Jansen's wake model is used while two types of energy estimation with and without considering partially overshadowed wake areas are studied. The results obtained from using various MHs are statistically compared in terms of convergence and consistency while the best performer is obtained. Comparison results indicated that moth-flame optimisation (MFO) algorithm is the most efficient algorithms. The results obtained in this work are said to be the baseline for future study on WFLO using metahueristics.
Açıklama
Anahtar kelimeler
Learning-based optimization, Differential evolution, Genetic algorithm, Turbines, Design, Selection, Model