Wind power, as a promising renewable energy source, has environmental benefits, as well as economic and social ones. To evaluate wind energy properly and efficiently, this study proposes a hybrid forecasting approach that combines the Extreme Learning Machine (ELM), which rarely presents in...

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...

It is of great importance and urgency for Taiwan to develop offshore wind power. However, relevant data on offshore wind energy resources are limited. This study imported wind speeds measured by a tidal station and a buoy into the software WAsP to estimate the high-altitude wind speeds in the...

We analyze correlations and cross-correlations in wind speed and solar radiation temporal series recorded at the Island Fernando de Noronha in northeastern Brazil, using Detrended fluctuation analysis (DFA) and Detrended cross-correlation analysis (DCCA). We find that both processes exhibit...

This paper presents a comparison of various forecasting approaches, using time series analysis, on mean hourly wind speed data. In addition to the traditional linear (ARMA) models and the commonly used feed forward and recurrent neural networks, other approaches are also examined including the...

Surface wind speed variability cannot be resolved by the current generation of Global Climate Models (GCMs) due to their relatively coarse spatial discretization. Downscaling techniques are thus needed to generate finer scale projections of variables like near surface wind speeds. However,...

The current model for energy production, based on the intense use of fossil fuels, is both unsustainable and environmentally harmful and consequently, a shift is needed in the direction of integrating the renewable energy sources into the energy balance. However, these energy sources are...

We studied the improved effects a diffuser had on the output power of small wind turbine systems, aiming to introduce these systems to radio relay stations as an independent power supply system. A frustum-shaped diffuser was chosen from an economical standpoint and wind speed distribution. The...

This paper examines a new time series method for very short-term wind speed forecasting. The time series forecasting model is based on Bayesian theory and structural break modeling, which could incorporate domain knowledge about wind speed as a prior. Besides this Bayesian structural break model...

Accurate forecasting of wind speed and wind power is important for the safety of renewable energy utilization. Compared with physical methods, statistical methods are usually simpler and more suitable for small farms. Based on the methods of wavelet and classical time series analysis, a new...