Distributed Genetic Algorithm for Optimization of Wind Farm Annual Profits

In this paper, a distributed genetic algorithm is adopted to search the optimal number and locations of wind turbines in large wind farms. The objective of this optimal process is to find a solution that maximizes the annual profit obtained from a wind farm. It is well known that traditional genetic algorithms are time consuming and the quality of final solution is not very well. For improving the performance of finding the optimal solution in large search space, the distributed genetic algorithm provides a powerful strategy for searching the global optimal by dividing large population into multiple small subpopulations that occasionally exchange some individuals. Test results show that the distributed genetic algorithm well demonstrates its effectiveness on solution quality and execution time.