relation: https://khub.utp.edu.my/scholars/6679/
title: Wind Farm Layout Design Using Cuckoo Search Algorithms
creator: Rehman, S.
creator: Ali, S.S.
creator: Khan, S.A.
description: Wind energy has emerged as a strong alternative to fossil fuels for power generation. To generate this energy, wind turbines are placed in a wind farm. The extraction of maximum energy from these wind farms requires optimal placement of wind turbines. Due to complex nature of micrositing of wind turbines, the wind farm layout design problem is considered a complex optimization problem. In the recent past, various techniques and algorithms have been developed for optimization of energy output from wind farms. The present study proposes an optimization approach based on the cuckoo search (CS) algorithm, which is relatively a recent technique. A variant of CS is also proposed that incorporates a heuristic-based seed solution for a better performance. The proposed CS algorithms are compared with genetic and particle swarm optimization (PSO) algorithms, which have been extensively applied to wind farm layout design. Empirical results indicate that the proposed CS algorithms outperformed the genetic and PSO algorithms for the given test scenarios in terms of yearly power output and efficiency. © 2016 Taylor & Francis.
publisher: Taylor and Francis Inc.
date: 2016
type: Article
type: PeerReviewed
identifier:   Rehman, S. and Ali, S.S. and Khan, S.A.  (2016) Wind Farm Layout Design Using Cuckoo Search Algorithms.  Applied Artificial Intelligence, 30 (10).  pp. 899-922.  ISSN 08839514     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85012889395&doi=10.1080%2f08839514.2017.1279043&partnerID=40&md5=5b8ba04b7e1045c161b22e8c650feffd
relation: 10.1080/08839514.2017.1279043
identifier: 10.1080/08839514.2017.1279043