Application of Differential Evolution for Wind Turbine Micrositing

• Main Authors: SHAFIQ -UR-REHMAN MASSAN, ASIM IMDAD WAGAN, MUHAMMAD MUJTABA SHAIKH, MUHAMMAD SALEH SHAH
• Format: Article
• Language: English
• Published: Mehran University of Engineering and Technology 2017-04-01
• Series: Mehran University Research Journal of Engineering and Technology
• Subjects: Wind Turbine Micro-Siting; N.O. Jensen Model; Heuristics,Wind Turbine Optimization,Differential Evolution Algorithm; GeneticAlgorithm.
• Online Access: http://publications.muet.edu.pk/research_papers/pdf/pdf1495.pdf

WTM (Wind Turbine Micrositing) has been an important topic of discussion in recent times. A number of Evolutionary Algorithms have been applied to the WTM problem. The DEA (Differential Evolution Algorithm) is used for a bi-constrained optimization for getting maximum power production at the least cost from a 2x2 km space. It is shown that the DEA performs comparably to the GA (Genetic Algorithms) for wind farm optimization. The optimal configuration obtained enlists the number of turbines, the cost of power generated as well as the power produced. Moreover, this study is augmented by comparison with past approaches by using the GA for the same purpose.