A1 Journal article (refereed), original research

Cuckoo search for wind farm optimization with auxiliary infrastructure


Publication Details
Authors: Afanasyeva Svetlana, Saari Jussi, Pyrhönen Olli, Partanen Jarmo
Publisher: Wiley: 12 months
Publication year: 2018
Language: English
Related Journal or Series Information: Wind Energy
Volume number: 21
Issue number: 10
Start page: 855
End page: 875
Number of pages: 21
ISSN: 1095-4244
JUFO-Level of this publication: 2
Open Access: Not an Open Access publication

Abstract

This paper focuses on the optimization problem of a wind farm layout. This area of Q3
research is currently receiving widespread attention, as optimal positioning of the turbines
promotes the financial viability of the wind farm and enhances the competitiveness
of wind projects in the energy market. In this work, cuckoo search (CS), a modern
population‐based metaheuristic optimization algorithm, is used. The objective is to
find the turbine layout and types that maximize the net present value of the wind
farm, while constraints on the turbine positions have to be met. The following constraints
are considered: Firstly, the minimum distance between turbines for safe operation;
secondly, a realistic wind farm shape including forbidden zones for installation
and the existing infrastructure. Furthermore, the optimization of the wind farm
includes an algorithm to find the least expensive layout of the wind farm roads and
the electrical collector system. The algorithm is based on Dijkstra's shortest path
and Prim's minimum spanning tree algorithms. The test results indicate that the
infrastructure cost has a significant effect on the optimum wind farm solution. A
genetic algorithm, commonly applied to wind farm micro‐siting problems, is used to
benchmark the performance of the CS. The results show that the CS is capable of
consistently finding better solutions than the genetic algorithm.


Last updated on 2019-13-03 at 12:00