A new Hybrid Metaheuristic Algorithm for Wind Farm Micrositing. | [Mehran University Research Journal of Engineering and Technology • 2017]

Author(s):

1. Shafiq-Ur-Rehman Massan: Shaheed Zulfiqar Ali Bhutto Institute of Science & Technology, Karachi, Pakistan

2. Asim Imdad Wagan: Mohammad Ali Jinnah University, Karachi, Pakistan

3. Muhammad Mujtaba Shaikh: Department of Basic Sciences & Related Studies, Mehran University of Engineering & Technology, Jamshoro, Pakistan

Abstract:

This work focuses on proposing a new algorithm, referred as HMA (Hybrid Metaheuristic Algorithm) for the solution of the WTO (Wind Turbine Optimization) problem. It is well documented that turbines located behind one another face a power loss due to the obstruction of the wind due to wake loss. It is required to reduce this wake loss by the effective placement of turbines using a new HMA. This HMA is derived from the two basic algorithms i.e. DEA (Differential Evolution Algorithm) and the FA (Firefly Algorithm). The function of optimization is undertaken on the N.O. Jensen model. The blending of DEA and FAinto HMAare discussed and the new algorithm HMAis implemented maximize power and minimize the cost in a WTO problem. The results by HMA have been compared with GA(GeneticAlgorithm) used in some previous studies. The successfully calculated total power produced and cost per unit turbine for a wind farm by using HMA and its comparison with past approaches using single algorithms have shown that there is a significant advantage of using the HMA as compared to the use of single algorithms. The first time implementation of a new algorithm by blending two single algorithms is a significant step towards learning the behavior of algorithms and their added advantages by using them together.

Page(s): 635-648

DOI: DOI not available

Published: Journal: Mehran University Research Journal of Engineering and Technology, Volume: 36, Issue: 3, Year: 2017

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