Stacked LSTM sequence-to-sequence autoencoder with feature selection for daily solar radiation prediction: A review and new modeling results
We review the latest modeling techniques and propose new hybrid SAELSTM framework
based on Deep Learning (DL) to construct prediction intervals for daily Global Solar …
based on Deep Learning (DL) to construct prediction intervals for daily Global Solar …
An overview of deterministic and probabilistic forecasting methods of wind energy
In recent years, a variety of wind forecasting models have been developed, prompting
necessity to review the abundant methods to gain insights of the state-of-the-art …
necessity to review the abundant methods to gain insights of the state-of-the-art …
A novel hybrid model based on VMD-WT and PCA-BP-RBF neural network for short-term wind speed forecasting
Y Zhang, B Chen, G Pan, Y Zhao - Energy Conversion and Management, 2019 - Elsevier
Accurate short-term wind power forecasting is significant for rational dispatching of the
power grid and ensuring the power supply quality. In order to enhance the accuracy of short …
power grid and ensuring the power supply quality. In order to enhance the accuracy of short …
Mid-to-long term wind and photovoltaic power generation prediction based on copula function and long short term memory network
S Han, Y Qiao, J Yan, Y Liu, L Li, Z Wang - Applied energy, 2019 - Elsevier
The accurate estimation of mid-to-long term wind and photovoltaic power generation is
important to the power grid's plan improvement, dispatching optimization, management …
important to the power grid's plan improvement, dispatching optimization, management …
Natural phase space reconstruction-based broad learning system for short-term wind speed prediction: Case studies of an offshore wind farm
X Xu, S Hu, P Shi, H Shao, R Li, Z Li - Energy, 2023 - Elsevier
Accurate prediction of wind speed can not only help to develop strategies for wind turbine
operation, but also reduce impact on power systems when wind energy is integrated into the …
operation, but also reduce impact on power systems when wind energy is integrated into the …
An algorithm for forecasting day-ahead wind power via novel long short-term memory and wind power ramp events
Y Cui, Z Chen, Y He, X Xiong, F Li - Energy, 2023 - Elsevier
Reliable wind power and ramp event prediction is essential for the safe and stable operation
of electric power systems. Previous prediction methods struggled to forecast large …
of electric power systems. Previous prediction methods struggled to forecast large …
Deep learning method based on gated recurrent unit and variational mode decomposition for short-term wind power interval prediction
Wind power interval prediction (WPIP) plays an increasingly important role in evaluations of
the uncertainty of wind power and becomes necessary for managing and planning power …
the uncertainty of wind power and becomes necessary for managing and planning power …
Electrical load forecasting: A deep learning approach based on K-nearest neighbors
Y Dong, X Ma, T Fu - Applied Soft Computing, 2021 - Elsevier
Deep learning approaches have shown superior advantages than shallow techniques in the
field of electrical load forecasting; however, their applications in existing studies encounter …
field of electrical load forecasting; however, their applications in existing studies encounter …
Machine learning and data-driven fault detection for ship systems operations
Well maintained vessels exhibit high reliability, safety and energy efficiency. Even though
machinery failures are inevitable, their occurrence can be foreseen when predictive …
machinery failures are inevitable, their occurrence can be foreseen when predictive …
A wind speed interval prediction system based on multi-objective optimization for machine learning method
R Li, Y Jin - Applied energy, 2018 - Elsevier
Accurate forecast of wind speed is the first prerequisite to supply high quality power energy
to customer in a secure and economic manner. However, traditional point forecast may not …
to customer in a secure and economic manner. However, traditional point forecast may not …