Comparison of Offshore Wind Farm Layout Optimization Using a Genetic Algorithm and a Particle Swarm Optimizer

Ajit Pillai, John Chick, Lars Johanning, M Khorasanchi, Sami Barbouchi

Research output: Contribution to conferencePaper

Abstract / Description of output

This article explores the application of a binary genetic algorithm and a binary particle swarm optimizer to the optimization of an offshore wind farm layout. The framework developed as part of this work makes use of a modular design to include a detailed assessment of a wind farm’s layout including validated analytic wake modeling, cost assessment, and the design of the necessary electrical infrastructure considering constraints. This study has found that both algorithms are capable of optimizing wind farm layouts with respect to levelized cost of energy when using a detailed, complex evaluation function. Both are also capable of identifying layouts with lower levelized costs of energy than similar studies that have been published in the past and are therefore both applicable to this problem. The performance of both algorithms has highlighted that both should be further tuned and benchmarked in order to better characterize their performance.
Original languageEnglish
Number of pages11
Publication statusPublished - 19 Jun 2016
EventASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering - Busan, Korea, Republic of
Duration: 19 Jun 201624 Jun 2016

Conference

ConferenceASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering
Country/TerritoryKorea, Republic of
CityBusan
Period19/06/1624/06/16

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