Wind power modeling using harmony search with a novel parameter setting approach

A significant portion of the world's renewable energy is being provided by wind farms. The produced power of a wind farm in not always a constant value because it is highly dependent on the environmental conditions. As the amount of wind power rapidly increases, wind power estimation will be an important issue in electricity markets. A number of wind power estimation methodologies have been developed that are competing to provide the best estimation to the electric power industry. In this paper, a harmony search (HS) algorithm is proposed for modeling the power of a wind farm by finding the optimal weighting factors of a mathematical model. HS with a novel parameter setting approach, named HS-NPSA, is also developed to eliminate the tedious parameter assigning efforts of HS algorithm. In order to evaluate the usefulness of the proposed methodologies, the performance of HS-based algorithms is compared with those of the other heuristic techniques in terms of mean absolute percentage error (MAPE). Simulation results confirm the superiority of HS-NPSA algorithm for wind power modeling.