The objective of this paper is to develop a novel wind speed forecasting technique, which produces more accurate prediction. The Wavelet Transform (WT) along with the Auto Regressive Moving Average (ARMA) is chosen to form a hybrid whose combination is expected to give minimum Mean Absolute Prediction Error (MAPE). A simulation study has been conducted by comparing the forecasting results using the Wavelet-ARMA with the ARMA and Artificial Neural Network (ANN)-Ensemble Kalman Filter (EnKF) hybrid technique to verify the effectiveness of the proposed hybrid method. Results of the proposed hybrid show significant improvements in the forecasting error
Wind speed forecasting is of great importance for wind farm management and plays an important role i...
Wind has been a rapidly growing renewable power source for the last twenty years. Since wind behavio...
Accurate wind speed forecasting is a fundamental requirement for advanced and economically viable la...
It is important to improve the accuracy of wind speed forecasting for wind parks management and wind...
To mitigate the increase of anxiety resulting from the depletion of fossil fuels and destruction of ...
permits unrestricted use, distribution, and reproduction in any medium, provided the original work i...
Depending on their input, wind power forecasting models are classified as physical or statistical ap...
The need to deliver accurate predictions of renewable energy generation has long been recognized by ...
Wind energy is one of the most widely used renewable energy sources. Wind power generation is uncert...
© 2017, Springer International Publishing AG. Forecasting of wind speed plays an important role in w...
Environmental considerations and reducing carbon emission has accelerated the use of various renewab...
The nonlinearity and the chaotic fluctuations in the wind speed pattern are the reasons of inaccurat...
This article belongs to the Special Issue Deep Learning Applications with Practical Measured Results...
International audienceThe present paper focuses on developing and testing various reliable and robus...
In this research, monthly wind speed time series of the Kirsehir was investigated using the stand-al...
Wind speed forecasting is of great importance for wind farm management and plays an important role i...
Wind has been a rapidly growing renewable power source for the last twenty years. Since wind behavio...
Accurate wind speed forecasting is a fundamental requirement for advanced and economically viable la...
It is important to improve the accuracy of wind speed forecasting for wind parks management and wind...
To mitigate the increase of anxiety resulting from the depletion of fossil fuels and destruction of ...
permits unrestricted use, distribution, and reproduction in any medium, provided the original work i...
Depending on their input, wind power forecasting models are classified as physical or statistical ap...
The need to deliver accurate predictions of renewable energy generation has long been recognized by ...
Wind energy is one of the most widely used renewable energy sources. Wind power generation is uncert...
© 2017, Springer International Publishing AG. Forecasting of wind speed plays an important role in w...
Environmental considerations and reducing carbon emission has accelerated the use of various renewab...
The nonlinearity and the chaotic fluctuations in the wind speed pattern are the reasons of inaccurat...
This article belongs to the Special Issue Deep Learning Applications with Practical Measured Results...
International audienceThe present paper focuses on developing and testing various reliable and robus...
In this research, monthly wind speed time series of the Kirsehir was investigated using the stand-al...
Wind speed forecasting is of great importance for wind farm management and plays an important role i...
Wind has been a rapidly growing renewable power source for the last twenty years. Since wind behavio...
Accurate wind speed forecasting is a fundamental requirement for advanced and economically viable la...