Simulated Annealing With Parameter Tuning for Wind Turbine Placement Optimization

Because of wake effects and geographical constraints, the search for optimal positions of wind turbines has an important part to play for their efficiency. The determination of their positions can be treated as optimization problem and can be solved by various methods. In this paper, we propose optimization approaches based on Simulated Annealing (SA) to improve solutions for the wind turbines placement problem. We define neighborhoods of solutions and analyze the influence of specific parameters, e.g., neighborhood distance and SA temperature in experimental studies. The experiments are based on a real-world scenario with a wind model, wind data from a meteorological service, and geographical constraints. Inspired by adaptive step size control applied in Evolutionary Strategies (ES), we propose an approach using an adaptive neighborhood distance and compare the results to optimization runs with a constant neighborhood distance. Also the best and worst optimization run and the corresponding placement results are shown and compared.