This paper proposes artificial neural networks in combination with wavelet transform for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility....

Affected by various environment factors, wind speed presents characters of high fluctuations, autocorrelation and stochastic volatility; thereby it is hard to forecast with a single model. A hybrid model combining with input selected by deep quantitative analysis, Wavelet Transform (WT), Genetic...

Full scale blade fatigue testing is required to verify that the horizontal axis wind turbine (HAWT) blades posses the strength and service life specified in the design. Unfortunately, fatigue tests must be run for a long time period, which has led blade testing laboratories to seek ways of...

Spectra of many meteorological data such as wind speed and temperature are time variable. Thus a Fourier analysis is not sufficient. In the present work, the wavelet transform is applied as a time-frequency analysis to the meteorological data for the region of Adrar (27.9°N, 0.3°W, 263m),...

The non-stationary and stochastic nature of wind power reveals itself a difficult task to forecast and manage. In this context, with the continuous increment of wind farms and their capacity production in Portugal, there is an increasing need to develop new forecasting tools with enhanced...

Wind power forecasting system is useful to increase the wind energy penetration level. Latest statistics show that China has been the biggest wind energy market throughout the world. However, few studies have been published to introduce the wind energy forecasting technologies in China. This...

In this paper, artificial neural networks (ANNs) are used for the performance prediction of large solar systems. The ANN method is used to predict the expected daily energy output for typical operating conditions, as well as the temperature level the storage tank can reach by the end of the...

Cetane number (CN) is one of the most significant properties to specify the ignition quality of any fuel for internal combustion engines. The CN of biodiesel varies widely in the range of 48–67 depending upon various parameters including the oil processing technology and climatic conditions...

Wind speed forecasting is one of the most important technologies to guarantee the wind energy integrated into the whole power system smoothly. In this paper a hybrid model named EMD–ANN for wind speed prediction is proposed based on the Empirical Mode Decomposition (EMD) and the Artificial...

This paper introduces a neural network technique for the estimation of global solar radiation. There are 41 radiation data collection stations spread all over the kingdom of Saudi Arabia where the radiation data and sunshine duration information are being collected since 1971. The available data...