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Numerical data concerning wind farm layout optimization using differential evolution algorithm at different wind speeds

In this work, the numerical data related to wind turbine micrositing problem is presented. The data is acquired using the differential evolution algorithm (DEA) at different wind speeds. The data obtained through DEA include total dissipated power, cost per installation of unit turbine, and the effi...

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Detalles Bibliográficos
Autores principales: Massan, Shafiq-ur-Rehman, Wagan, Asim Imdad, Shaikh, Muhammad Mujtaba, Shah, Muhammad Saleh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635204/
https://www.ncbi.nlm.nih.gov/pubmed/29034287
http://dx.doi.org/10.1016/j.dib.2017.09.040
Descripción
Sumario:In this work, the numerical data related to wind turbine micrositing problem is presented. The data is acquired using the differential evolution algorithm (DEA) at different wind speeds. The data obtained through DEA include total dissipated power, cost per installation of unit turbine, and the efficiency of algorithm after installation of any particular number turbines; and are depicted versus number of turbines. The data provided in this paper can be used directly without having to spend weeks of computational time to simulate the results; and can readily be used for comparison with other existing (Massan et al. [1] and Rajper et al. [2], etc.) and forthcoming algorithms in future.