Fast and effective multi-objective optimisation of wind turbine placement

Authors:
Raymond Tran;Junhua Wu;Christopher Denison;Thomas Ackling;Markus Wagner;Frank Neumann
Affiliations:
The University of Adelaide, Adelaide, Australia;The University of Adelaide, Adelaide, Australia;The University of Adelaide, Adelaide, Australia;The University of Adelaide, Adelaide, Australia;The University of Adelaide, Adelaide, Australia;The University of Adelaide, Adelaide, Australia
Venue:
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Year:
2013

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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.