Application of Differential Evolution for Wind Turbine Micrositing

作     者：Massan, Shafiq-Ur-Rehman Wagan, Asim Imdad Shaikh, Muhammad Mujtaba Shah, Muhammad Saleh 

作者机构：Shaheed Zulfikar Ali Bhutto Inst Sci & Technol Karachi Pakistan Mohammad Ali Jinnah Univ Karachi Pakistan Mehran Univ Engn & Technol Dept Basic Sci & Related Studies Jamshoro Pakistan Govt Saifee Zahabi Edhi Coll Educ Karachi Pakistan 

出 版 物：《MEHRAN UNIVERSITY RESEARCH JOURNAL OF ENGINEERING AND TECHNOLOGY》 

年 卷 期：2017年第36卷第2期

页      面：353-366页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 

主　　题：Wind Turbine Micro-Siting N.O. Jensen Model Heuristics Wind Turbine Optimization Differential Evolution Algorithm GeneticAlgorithm 

摘      要：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.