Optimization of wind direction distribution parameters using particle swarm optimization

Abstract

Data describing various natural and industrial phenomena can be modeled by directional statistical distributions. In the field of energy, wind direction and wind speed are the most important variables for wind energy generation, integration, and management. This work proposes and evaluates a new method for accurate estimation of wind direction distribution parameters utilizing the well-known Particle Swarm Optimization algorithm. It is used to optimize the parameters of a site-specific wind direction distribution model realized as a finite mixture of circular normal von Mises statistical distributions. The evaluation of the proposed algorithm is carried out using a data set describing annual wind direction on two distinct locations. Experimental results show that the proposed method is able to find good model parameters corresponding to input data.