Individual Particle Optimization Algorithm for Linear Forecasting of Wind Speed
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Concern to the growing of the wind energy, more accurate forecasting models seems essential. This prediction regarding to its time step varies in application such as design, sizing of wind systems and turbine control. In this study linear prediction optimized by Particle Swarm Optimization (PSO) and Individual Particle Optimization (IPO) was suggested and the results of this novel method were compared with ordinary linear prediction, Markov chain and ANN results. Then applying the real data, proposed methods and comparing their results, this idea came true that the proposed novel method (optimized linear prediction by PSO and IPO) resulted much better than other forecasting methods. Results are based on real data of an area in Denmark
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