Multi-Objective Optimisation of the Benchmark Wind Farm Layout Problem

Wind farm layout optimisation has become a very challenging and widespread problem in recent years. In many publications, the main goal is to achieve the maximum power output and minimum wind farm cost. This may be accomplished by applying single or multi-objective optimisation techniques. In this paper, we apply a single objective hill-climbing algorithm (HCA) and three multi-objective evolutionary algorithms (NSGA-II, SPEA2 and PESA-II) to a well-known benchmark optimisation problem proposed by Mosetti et al., which includes three different wind scenarios. We achieved better results by applying single- and multi-objective algorithms. Furthermore, we showed that the best performing multi-objective algorithm was NSGA-II. Finally, an extensive comparison of the results of past publications is made.

Automated summary

Wind farm layout optimisation is a challenging and widespread problem that aims to achieve maximum power output and minimum cost. Single and multi-objective optimisation techniques, including NSGA-II, SPEA2, and PESA-II, have been used to achieve better results in different wind scenarios, with NSGA-II performing the best among the multi-objective algorithms. Extensive comparisons of past publications have also been made to evaluate the effectiveness of different algorithms.