Spatio-temporal graph deep neural network for short-term wind speed forecasting
M Khodayar, J Wang - IEEE Transactions on Sustainable …, 2018 - ieeexplore.ieee.org
Wind speed forecasting is still a challenge due to the stochastic and highly varying
characteristics of wind. In this paper, a graph deep learning model is proposed to learn the …
characteristics of wind. In this paper, a graph deep learning model is proposed to learn the …
Towards novel deep neuroevolution models: chaotic levy grasshopper optimization for short-term wind speed forecasting
SMJ Jalali, S Ahmadian, M Khodayar… - Engineering with …, 2021 - Springer
High accurate wind speed forecasting plays an important role in ensuring the sustainability
of wind power utilization. Although deep neural networks (DNNs) have been recently …
of wind power utilization. Although deep neural networks (DNNs) have been recently …
[HTML][HTML] Wind speed prediction using measurements from neighboring locations and combining the extreme learning machine and the AdaBoost algorithm
L Wang, Y Guo, M Fan, X Li - Energy Reports, 2022 - Elsevier
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 …
existing studies of wind speed forecasting used data from one location to build models and …
Wind speed prediction using artificial neural networks based on multiple local measurements in Eskisehir
In this study, artificial neural network (ANN) based models, which differently uses multiple
local meteorological measurements together such as wind speed, temperature and pressure …
local meteorological measurements together such as wind speed, temperature and pressure …
A deep attention convolutional recurrent network assisted by k-shape clustering and enhanced memory for short term wind speed predictions
Due to the increasing penetration of wind energy in nowadays power grids, the accurate
wind speed prediction (WSP) is critical to more efficient and reliable operations of power …
wind speed prediction (WSP) is critical to more efficient and reliable operations of power …
Leveraging data from nearby stations to improve short-term wind speed forecasts
In this paper, we address the issue of short-term wind speed prediction at a given site. We
show that, when one uses spatiotemporal information as provided by wind data of …
show that, when one uses spatiotemporal information as provided by wind data of …
Short-term wind speed forecasting by spectral analysis from long-term observations with missing values
In this paper, we propose a novel wind speed forecasting framework. The performance of
the proposed framework is assessed on the wind speed measurements collected from the …
the proposed framework is assessed on the wind speed measurements collected from the …
Long short-term memory (LSTM)-based wind speed prediction during a typhoon for bridge traffic control
A short-term wind speed prediction framework is proposed for bridge traffic control under
strong winds. The framework mainly focuses on improving the prediction accuracy for the …
strong winds. The framework mainly focuses on improving the prediction accuracy for the …
Identification of efficient sampling techniques for probabilistic voltage stability analysis of renewable-rich power systems
This paper presents a comparative analysis of six sampling techniques to identify an efficient
and accurate sampling technique to be applied to probabilistic voltage stability assessment …
and accurate sampling technique to be applied to probabilistic voltage stability assessment …
A hybrid wind speed forecasting system based on a 'decomposition and ensemble'strategy and fuzzy time series
H Yang, Z Jiang, H Lu - Energies, 2017 - mdpi.com
Accurate and stable wind speed forecasting is of critical importance in the wind power
industry and has measurable influence on power-system management and the stability of …
industry and has measurable influence on power-system management and the stability of …