As one of the effective renewable energy sources, wind has received attention because it is sustainable energy. Accurate speed forecasting can pave way to goal development. However, current methods ignore temporal characteristics speed, which leads inaccurate results. In this paper, we propose a novel SSA-CCN-ATT model forecast speed. Specifically, singular spectrum analysis (SSA) first applied...

Affected by various environmental factors, wind speed presents high fluctuation, nonlinear and non-stationary characteristics. To evaluate wind energy properly and efficiently, this paper proposes a modified fast ensemble empirical model decomposition (FEEMD)-bat algorithm (BA)-least support vector machines (LSSVM) (FEEMD-BA-LSSVM) model combined with input selected by deep quantitative analysi...

This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and ...

The prediction of near surface wind speed is becoming increasingly vital for the operation of electrical energy grids as the capacity of installed wind power grows. The majority of predictive wind speed modeling has focused on point-based time-series forecasting. Effectively balancing demand and supply in the presence of distributed wind turbine electricity generation, however, requires the pre...

Using accurate inputs of wind speed is crucial in wind resource assessment, as predicted power is proportional to the wind speed cubed. This study outlines a methodology for combining multiple ocean satellite winds and winds from WRF simulations in order to acquire the accurate reconstructed offshore winds which can be used for offshore wind resource assessment. First, wind speeds retrieved fro...

To support large-scale integration of wind power into electric energy systems, state-of-the-art wind speed forecasting methods should be able to provide accurate and adequate information to enable efficient, reliable, and cost-effective scheduling of wind power. Here, we incorporate space-time wind forecasts into electric power system scheduling. First, we propose a modified regime-switching, s...

Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural net...

Since 2007 wind has become the major source of renewable energy in the UK. Moreover, increasing oil costs are driving researchers in the marine transport field to develop innovating wind ships. In order for wind power to be effectively and efficiently exploited, reliable forecasts on wind speed are needed. These will allow saving curtailments costs, improving safety, reducing damages due to ext...

wind speed is one of the major parameters required for an estimation of evapotranspiration and determination of crop water requirements. hence, several models and methods have been developed for a prediction of this needed climatic variable. in recent years, by development of soft computing tools, such intelligent systems as artificial neural network (ann) approach have been widely employed in ...