Fast and effective multi-objective optimisation of wind turbine placement

Raymond Tran, Thomas Ackling, Junhua Wu, Markus Wagner, Christopher Denison, Frank Neumann

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

31 Citations (Scopus)

Abstract

The single-objective yield optimisation of wind turbine placements on a given area of land is already a challenging optimization problem. In this article, we tackle the multi-objective variant of this problem: we are taking into account the wake effects that are produced by the different turbines on the wind farm, while optimising the energy yield, the necessary area, and the cable length needed to connect all turbines. One key step contribution in order to make the optimisation computationally feasible is that we employ problem-specific variation operators. Furthermore, we use a recently presented caching-technique to speed-up the computation time needed to assess a given wind farm layout. The resulting approach allows the multi-objective optimisation of large real-world scenarios within a single night on a standard computer.

Original languageEnglish
Title of host publicationGECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference
PublisherAssociation for Computing Machinery (ACM)
Pages1381-1388
Number of pages8
ISBN (Print)9781450319638
DOIs
Publication statusPublished - 2013
Externally publishedYes
EventThe Genetic and Evolutionary Computation Conference 2013 - Amsterdam, Netherlands
Duration: 6 Jul 201310 Jul 2013
Conference number: 15th
https://dl.acm.org/doi/proceedings/10.1145/2463372 (Proceedings)

Conference

ConferenceThe Genetic and Evolutionary Computation Conference 2013
Abbreviated titleGECCO 2013
Country/TerritoryNetherlands
CityAmsterdam
Period6/07/1310/07/13
Internet address

Keywords

  • Multi-objective optimisation
  • Wind farm layout
  • Wind power

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