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Many forecasting models have been developed for forecasting wind farm electricity output. In most situations, performance of models is problem-dependent. Thus, it is difficult for forecasters to choose the right technique for each unique situation. In order to overcome this problem, this paper integrates multiple models into an aggregated model to obtain further performance improvement. Firstly, three...
There are many multivariate forecasting models which incorporate weather indicators and other information for wind farm power output forecasting. In most situations, performance of these individual models is problem-dependent. Thus, it is difficult for forecasters to choose the right technique for unique situations. In this paper, firstly, indicators such as wind speed, and wind direction are analyzed...
In this paper, four new forecasting models ¨C univariate LS-SVM model and three hybrid models of ARIMA and LS-SVM models are introduced for wind power output forecasting. Historical data of 78 wind farms are used to compare and evaluate the performance of the best models. Empirical analysis indicates that the proposed univariate LS-SVM model and hybrid models can not significantly outperform linear...
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