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- W2005551579 abstract "Accurate wind farm power prediction can relieve the disadvantageous impact of wind power plants on power systems and reduce the difficulty of the scheduling of power dispatching department. Improving accuracy of short-term wind speed prediction is the key of wind power prediction. The authors have studied the short-term wind power forecasting of power plants and proposed a model prediction method based on SVM with backstepping wind speed of power curve. In this method, the sequence of wind speed that is calculated according to the average power of the wind farm operating units and the scene of the power curve is the input of the SVM model. The results show that this method can meet the real-time needs of the prediction system, but also has better prediction accuracy, is a very valuable short-term wind power prediction method." @default.
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- W2005551579 date "2012-11-01" @default.
- W2005551579 modified "2023-10-05" @default.
- W2005551579 title "Short-Term Wind Power Forecasting Based on SVM with Backstepping Wind Speed of Power Curve" @default.
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- W2005551579 doi "https://doi.org/10.4028/www.scientific.net/amm.224.401" @default.
- W2005551579 hasPublicationYear "2012" @default.
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