This study proposes a hybrid forecasting approach that consists of the EWT (Empirical Wavelet Transform), CSA (Coupled Simulated Annealing) and LSSVM (Least Square Support Vector Machine) for enhancing the accuracy of short-term wind speed forecasting. The EWT is employed to extract true...

Wind energy is regarded as a worldwide renewable and alternative energy that can relieve the energy shortage, reduce environmental pollution, and provide a significant potential economic benefit. In this paper, a hybrid method is developed to properly and efficiently forecast the daily wind...

Electrical load forecasting has always played a key role in power system administration, planning for energy transfer scheduling and load dispatch. For electrical load forecasting, due to the fact that combined model has the capacity to effectively calculate the seasonality and nonlinearity...

Due to energy crisis and environmental problems, it is very urgent to find alternative energy sources nowadays. Solar energy, as one of the great potential clean energies, has widely attracted the attention of researchers. In this paper, an optimized hybrid method by CS (Cuckoo Search) on the...

Electric load forecasting is an important task in the daily operations of a power utility associated with energy transfer scheduling, unit commitment and load dispatch. Inspired by the various non-linearity of electric load data and the strong learning capacity of support vector regression (SVR)...

For accurate electricity demand forecasting, this paper proposes a novel approach, MFES, that combines a multi-output FFNN (feedforward neural network) with EMD (empirical mode decomposition)-based signal filtering and seasonal adjustment. In electricity demand forecasting, noise signals, caused...

Electric load forecasting is crucial for managing electric power systems economically and safely. This paper presents a new combined model for electric load forecasting based on the seasonal ARIMA forecasting model, the seasonal exponential smoothing model and the weighted support vector...

Wind energy has been well recognized as a renewable resource in electricity generation, which is environmentally friendly, socially beneficial and economically competitive. For proper and efficient evaluation of wind energy, a hybrid Seasonal Auto-Regression Integrated Moving Average and Least...