Optimisation of offshore wind farms using a genetic algorithm

Ajit C. Pillai, John Chick, Lars Johanning, Mahdi Khorasanchi, Sebastien Pelissier

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

3 Citations (Scopus)

Abstract

A modular framework for the optimisation of an offshore wind farm using a discrete genetic algorithm is presented. This approach uses a bespoke grid generation algorithm to define the discrete positions that turbines may occupy thereby implicitly satisfying navigational and search and rescue constraints through the wind farm. The presented methodology takes a holistic approach optimising both the turbine placement and inter-array cable network, while minimising the levelised cost of energy and satisfying real world constraints. This tool therefore integrates models for the assessment of the energy production including wake losses; the optimisation of the inter-array cables; and the estimation of costs of the project over the lifetime. This framework will allow alternate approaches to wake and cost modelling as well as optimisation to be benchmarked in the future.

LanguageEnglish
Title of host publicationProceedings of the 25th International Offshore and Polar Engineering Conference
EditorsJin S. Chung, Fabian Vorpahl, Sa Young Hong, Ted Kokkinis, Alan M. Wang
Pages644-652
Number of pages9
Volume2015
Publication statusPublished - 2015
Event25th International Ocean and Polar Engineering Conference, ISOPE 2015 - Kona, Big Island, United States
Duration: 21 Jun 201526 Jun 2015

Conference

Conference25th International Ocean and Polar Engineering Conference, ISOPE 2015
CountryUnited States
CityKona, Big Island
Period21/06/1526/06/15

Fingerprint

Offshore wind farms
Genetic algorithms
Cables
Turbines
Costs

Keywords

  • genetic algorithm
  • offshore wind farm layout optimisation

Cite this

Pillai, A. C., Chick, J., Johanning, L., Khorasanchi, M., & Pelissier, S. (2015). Optimisation of offshore wind farms using a genetic algorithm. In J. S. Chung, F. Vorpahl, S. Y. Hong, T. Kokkinis, & A. M. Wang (Eds.), Proceedings of the 25th International Offshore and Polar Engineering Conference (Vol. 2015, pp. 644-652)
Pillai, Ajit C. ; Chick, John ; Johanning, Lars ; Khorasanchi, Mahdi ; Pelissier, Sebastien. / Optimisation of offshore wind farms using a genetic algorithm. Proceedings of the 25th International Offshore and Polar Engineering Conference. editor / Jin S. Chung ; Fabian Vorpahl ; Sa Young Hong ; Ted Kokkinis ; Alan M. Wang. Vol. 2015 2015. pp. 644-652
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abstract = "A modular framework for the optimisation of an offshore wind farm using a discrete genetic algorithm is presented. This approach uses a bespoke grid generation algorithm to define the discrete positions that turbines may occupy thereby implicitly satisfying navigational and search and rescue constraints through the wind farm. The presented methodology takes a holistic approach optimising both the turbine placement and inter-array cable network, while minimising the levelised cost of energy and satisfying real world constraints. This tool therefore integrates models for the assessment of the energy production including wake losses; the optimisation of the inter-array cables; and the estimation of costs of the project over the lifetime. This framework will allow alternate approaches to wake and cost modelling as well as optimisation to be benchmarked in the future.",
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Pillai, AC, Chick, J, Johanning, L, Khorasanchi, M & Pelissier, S 2015, Optimisation of offshore wind farms using a genetic algorithm. in JS Chung, F Vorpahl, SY Hong, T Kokkinis & AM Wang (eds), Proceedings of the 25th International Offshore and Polar Engineering Conference. vol. 2015, pp. 644-652, 25th International Ocean and Polar Engineering Conference, ISOPE 2015, Kona, Big Island, United States, 21/06/15.

Optimisation of offshore wind farms using a genetic algorithm. / Pillai, Ajit C.; Chick, John; Johanning, Lars; Khorasanchi, Mahdi; Pelissier, Sebastien.

Proceedings of the 25th International Offshore and Polar Engineering Conference. ed. / Jin S. Chung; Fabian Vorpahl; Sa Young Hong; Ted Kokkinis; Alan M. Wang. Vol. 2015 2015. p. 644-652.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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AB - A modular framework for the optimisation of an offshore wind farm using a discrete genetic algorithm is presented. This approach uses a bespoke grid generation algorithm to define the discrete positions that turbines may occupy thereby implicitly satisfying navigational and search and rescue constraints through the wind farm. The presented methodology takes a holistic approach optimising both the turbine placement and inter-array cable network, while minimising the levelised cost of energy and satisfying real world constraints. This tool therefore integrates models for the assessment of the energy production including wake losses; the optimisation of the inter-array cables; and the estimation of costs of the project over the lifetime. This framework will allow alternate approaches to wake and cost modelling as well as optimisation to be benchmarked in the future.

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Pillai AC, Chick J, Johanning L, Khorasanchi M, Pelissier S. Optimisation of offshore wind farms using a genetic algorithm. In Chung JS, Vorpahl F, Hong SY, Kokkinis T, Wang AM, editors, Proceedings of the 25th International Offshore and Polar Engineering Conference. Vol. 2015. 2015. p. 644-652