A Hybrid Nonlinear Combination System for Monthly Wind Speed Forecasting

A Hybrid Method for Short-Term Wind Speed Forecasting

The accuracy of short-term wind speed prediction is very important for wind power generation. In this paper, a hybrid method combining ensemble empirical mode decomposition (EEMD), adaptive neural network based fuzzy inference system (ANFIS) and seasonal auto-regression integrated moving average (SARIMA) is presented for short-term wind speed forecasting. The original wind speed series is decom...

A Hybrid Approach for Short-Term Forecasting of Wind Speed

We propose a hybrid method for forecasting the wind speed. The wind speed data is first decomposed into intrinsic mode functions (IMFs) with empirical mode decomposition. Based on the partial autocorrelation factor of the individual IMFs, adaptive methods are then employed for the prediction of IMFs. Least squares-support vector machines are employed for IMFs with weak correlation factor, and a...

Hybrid Prediction Model for Short Term Wind Speed Forecasting

Due to notable depletion of fuel, non-conventional energy aids the present grid for Power management across the country. Wind energy indeed has major contribution next to solar. Prediction of wind power is essential to integrate wind farms into the grid. Due to intermittency and variability of wind power, forecasting of wind behavior becomes intricate. Wind speed forecasting tools can resolve t...

Evaluation of Optimal Fuzzy Membership Function for Wind Speed Forecasting

In this paper, a new approach is proposed in order to select an optimal membership function for inputs of wind speed prediction system. Then using a fuzzy method and the stochastic characteristics of wind speed in the previous year, the wind speed modeling is performed and the wind speed for the future year will be predicted. In this proposed method, the average and the standard deviation of in...

A Hybrid Intelligent System For Forecasting Gasoline Price