Large Wind Farm Layout Optimization Using Nature Inspired Meta-heuristic Algorithms
S. K. Aggarwal, Lalit Mohan Saini, Vijay K. Sood
Abstract
Wind farm layout optimization (WFLOP) is a complex constrained optimization problem. In this paper, an application of biogeography based optimization (BBO) algorithm for large WFLOP is presented and its performance is compared against three other major meta-heuristic algorithms namely genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO). The performance is evaluated on the basis of a modified cost of energy fitness function across 25 different wind farm scenarios. Further statistical inference has been drawn on the basis of 99% Confidence Intervals and Student’s t-test which shows that the fitness function values obtained using BBO are better when compared to the other algorithms for the same number of iterations. The execution time in case of PSO is largest, while GA takes the lowest amount of time.