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Bayesian predictive models for Rayleigh wind speed [PDF]
2017 IEEE 17th International Conference on Ubiquitous Wireless Broadband (ICUWB), 2017 One of the major challenges with the increase in wind power generation is the uncertain nature of wind speed. So far the uncertainty about wind speed has been presented through probability distributions. Also the existing models that consider the uncertainty of the wind speed primarily view the distributions of the wind speed over a wind farm as being ...
Amir Shahirinia +2 more
openaire +1 more source
Frontiers in Energy Research, 2023 Introduction: In the field of wind power generation, short-term wind speed prediction plays an increasingly important role as the foundation for effective utilization of wind energy.
Lu Wang, Lu Wang, Yilan Liao
doaj +1 more source
Energy Reports, 2022 Wind speed prediction plays an essential role in wind energy utilization. However, most existing studies of wind speed forecasting used data from one location to build models and forecasts, which limited the accuracy of wind speed forecasting. Therefore,
Lili Wang +3 more
doaj +1 more source
Using conditional kernel density estimation for wind power density forecasting [PDF]
, 2012 Of the various renewable energy resources, wind power is widely recognized as one of the most promising. The management of wind farms and electricity systems can benefit greatly from the availability of estimates of the probability distribution of wind ...
Jeon, Jooyoung, Taylor, James
core +4 more sources
Journal of Marine Science and Engineering, 2023 Wind energy is an effective way to reduce emissions in ports. However, port wind power generation exhibits strong intermittency and randomness. Predicting port wind speed enables timely scheduling of port operations and improves wind energy utilization ...
Yong Gu +6 more
doaj +1 more source
A novel two-stage data-driven model for ultra-short-term wind speed prediction
Energy Reports, 2022 Accurate prediction of wind speed and its output power is playing an essential role in the planning and scheduling of wind power grid. This study presents a novel two-stage data-driven model for ultra-short-term wind speed prediction based on the ...
Weicheng Hu +8 more
doaj +1 more source
A combined model for short-term wind speed forecasting based on empirical mode decomposition, feature selection, support vector regression and cross-validated lasso [PDF]
PeerJ Computer Science, 2021 Background The planning and control of wind power production rely heavily on short-term wind speed forecasting. Due to the non-linearity and non-stationarity of wind, it is difficult to carry out accurate modeling and prediction through traditional wind ...
Tao Wang
doaj +2 more sources
dscheepens/Deep-RNN-for-extreme-wind-speed-prediction: v1.0.0-alpha
, 2022 Paper code for "An adapted convolutional RNN model for spatio-temporal prediction of wind speed extremes in the short-to-medium range for wind energy ...
Daan Scheepens
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Energy Reports, 2022 The wind speed signal measured by the mechanical anemometer lags behind the wind speed at the wind wheel surface of the wind turbine in time. The wind speed reconstruction algorithm adopted by the ordinary lidar anemometer is insufficient.
Liang Zhang +4 more
doaj +1 more source
A hierarchical classification/regression algorithm for improving extreme wind speed events prediction [PDF]
, 2022 A novel method for prediction of the extreme wind speed events based on a Hierarchical Classification/Regression (HCR) approach is proposed. The idea is to improve the prediction skills of different Machine Learning approaches on extreme wind speed ...
Deo, Ravinesh C. +11 more
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