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Short-Term Wind Power Prediction Using A Wavelet Support Vector Machine, Jianwu Zeng, Wei Qiao
Short-Term Wind Power Prediction Using A Wavelet Support Vector Machine, Jianwu Zeng, Wei Qiao
Department of Electrical and Computer Engineering: Faculty Publications
This paper proposes a wavelet support vector machine (WSVM)-based model for short-term wind power prediction (WPP). A new wavelet kernel is proposed to improve the generalization ability of the support vector machine (SVM). The proposed kernel has such a general characteristic that some commonly used kernels are its special cases. Simulation studies are carried to validate the proposed model with different prediction schemes by using the data obtained from the National Renewable Energy Laboratory (NREL). Results show that the proposed model with a fixed-step prediction scheme is preferable for short-term WPP in terms of prediction accuracy and computational cost. Moreover, …
Support Vector Machine-Based Short-Term Wind Power Forecasting, Jianwu Zeng, Wei Qiao
Support Vector Machine-Based Short-Term Wind Power Forecasting, Jianwu Zeng, Wei Qiao
Department of Electrical and Computer Engineering: Faculty Publications
This paper proposes a support vector machine (SVM)-based statistical model for wind power forecasting (WPF). Instead of predicting wind power directly, the proposed model first predicts the wind speed, which is then used to predict the wind power by using the power-wind speed characteristics of the wind turbine generators. Simulation studies are carried out to validate the proposed model for very short-term and short-term WPF by using the data obtained from the National Renewable Energy Laboratory (NREL). Results show that the proposed model is accurate for very short-term and short-term WPF and outperforms the persistence model as well as the …
Support Vector Machine-Based Short-Term Wind Power Forecasting, Jianwu Zeng, Wei Qiao
Support Vector Machine-Based Short-Term Wind Power Forecasting, Jianwu Zeng, Wei Qiao
Department of Electrical and Computer Engineering: Faculty Publications
This paper proposes a support vector machine (SVM)-based statistical model for wind power forecasting (WPF). Instead of predicting wind power directly, the proposed model first predicts the wind speed, which is then used to predict the wind power by using the power-wind speed characteristics of the wind turbine generators. Simulation studies are carried out to validate the proposed model for very short-term and short term WPF by using the data obtained from the National Renewable Energy Laboratory (NREL). Results show that the proposed model is accurate for very short-term and short-term WPF and outperforms the persistence model as well as …
Short-Term Solar Power Prediction Using An Rbf Neural Network, Jianwu Zeng, Wei Qiao
Short-Term Solar Power Prediction Using An Rbf Neural Network, Jianwu Zeng, Wei Qiao
Department of Electrical and Computer Engineering: Faculty Publications
This paper proposes a radial basis function (RBF) neural network-based model for short-term solar power prediction (SPP). Instead of predicting solar power directly, the model predicts transmissivity, which is then used to obtain solar power according to the extraterrestrial radiation. The proposed model uses a novel two-dimensional (2D) representation for hourly solar radiation and uses historical transmissivity, sky cover, relative humidity and wind speed as the input. Simulation studies are carried out to validate the proposed model for shortterm SPP by using the data obtained from the National Solar Radiation Database (NSRDB). The performance of the RBF neural network is …