Medium-term wind power forecasting using reduced principal component analysis based random forest model
Jannet Jamii,
Mohamed Trabelsi,
Majdi Mansouri
et al.
Abstract:Due to its dependence on weather conditions, wind power (WP) forecasting has become a challenge for grid operators. Indeed, the dispatcher needs to predict the WP generation to apply the appropriate energy management strategies. To achieve an accurate WP forecasting, it is important to choose the appropriate input data (weather data). To this end, a medium-term wind power forecasting using reduced principal component analysis (RKPCA) based Random Forest Model is proposed in this paper. Two-stage WP forecasting… Show more
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