Application of support vector machine models for forecasting solar and wind energy resources: A review
Conventional fossil fuels are depleting daily due to the growing human population. Previous
research has proved that renewable energy sources, especially solar and wind, can be …
research has proved that renewable energy sources, especially solar and wind, can be …
A review of applications of artificial intelligent algorithms in wind farms
Wind farms are enormous and complex control systems. It is challenging and valuable to
control and optimize wind farms. Their applications are widely used in various industries …
control and optimize wind farms. Their applications are widely used in various industries …
Wind power prediction using deep neural network based meta regression and transfer learning
An innovative short term wind power prediction system is proposed which exploits the
learning ability of deep neural network based ensemble technique and the concept of …
learning ability of deep neural network based ensemble technique and the concept of …
Transfer learning for short-term wind speed prediction with deep neural networks
Q Hu, R Zhang, Y Zhou - Renewable Energy, 2016 - Elsevier
As a type of clean and renewable energy source, wind power is widely used. However,
owing to the uncertainty of wind speed, it is essential to build an accurate forecasting model …
owing to the uncertainty of wind speed, it is essential to build an accurate forecasting model …
Short-term wind speed forecasting using wavelet transform and support vector machines optimized by genetic algorithm
D Liu, D Niu, H Wang, L Fan - Renewable energy, 2014 - Elsevier
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 …
autocorrelation and stochastic volatility; thereby it is hard to forecast with a single model. A …
Short-term wind speed prediction using an unscented Kalman filter based state-space support vector regression approach
Accurate wind speed forecasting is becoming increasingly important to improve and
optimize renewable wind power generation. Particularly, reliable short-term wind speed …
optimize renewable wind power generation. Particularly, reliable short-term wind speed …
Support vector machines in engineering: an overview
S Salcedo‐Sanz, JL Rojo‐Álvarez… - … : Data Mining and …, 2014 - Wiley Online Library
This paper provides an overview of the support vector machine (SVM) methodology and its
applicability to real‐world engineering problems. Specifically, the aim of this study is to …
applicability to real‐world engineering problems. Specifically, the aim of this study is to …
Prediction intervals for short-term wind farm power generation forecasts
A Khosravi, S Nahavandi… - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
Quantification of uncertainties associated with wind power generation forecasts is essential
for optimal management of wind farms and their successful integration into power systems …
for optimal management of wind farms and their successful integration into power systems …
A xgboost model with weather similarity analysis and feature engineering for short-term wind power forecasting
H Zheng, Y Wu - Applied Sciences, 2019 - mdpi.com
Large-scale wind power access may cause a series of safety and stability problems. Wind
power forecasting (WPF) is beneficial to dispatch in advance. In this paper, a new extreme …
power forecasting (WPF) is beneficial to dispatch in advance. In this paper, a new extreme …
Prediction, operations, and condition monitoring in wind energy
Recent developments in wind energy research including wind speed prediction, wind
turbine control, operations of hybrid power systems, as well as condition monitoring and fault …
turbine control, operations of hybrid power systems, as well as condition monitoring and fault …