IntelliSense technology in the new power systems
The energy and climate crises have accelerated the decarbonization of electric power
systems. An important part of this decarbonization process, along with the incorporation of …
systems. An important part of this decarbonization process, along with the incorporation of …
Electricity price forecasting with high penetration of renewable energy using attention-based LSTM network trained by crisscross optimization
A Meng, P Wang, G Zhai, C Zeng, S Chen, X Yang… - Energy, 2022 - Elsevier
Accurate electricity price forecasts is the common concern of market participants. With the
integration of high penetration of wind and solar energy resources into the power system …
integration of high penetration of wind and solar energy resources into the power system …
Renewable Energy Forecasting Based on Stacking Ensemble Model and Al-Biruni Earth Radius Optimization Algorithm
Introduction: Wind speed and solar radiation are two of the most well-known and widely
used renewable energy sources worldwide. Coal, natural gas, and petroleum are examples …
used renewable energy sources worldwide. Coal, natural gas, and petroleum are examples …
Point and interval forecasting of ultra-short-term wind power based on a data-driven method and hybrid deep learning model
D Niu, L Sun, M Yu, K Wang - Energy, 2022 - Elsevier
Accurate and reliable wind power forecasting (WPF) is significant for ensuring power
systems' economic operation and safe dispatching and for reducing the technical and …
systems' economic operation and safe dispatching and for reducing the technical and …
[HTML][HTML] Decomposition-based wind power forecasting models and their boundary issue: An in-depth review and comprehensive discussion on potential solutions
Recently, numerous forecasting models have been reported in the wind power forecasting
field, aiming for reliable integration of renewable energy into the electric grid. Decomposition …
field, aiming for reliable integration of renewable energy into the electric grid. Decomposition …
A compound framework incorporating improved outlier detection and correction, VMD, weight-based stacked generalization with enhanced DESMA for multi-step short …
W Fu, Y Fu, B Li, H Zhang, X Zhang, J Liu - Applied Energy, 2023 - Elsevier
Precise wind speed forecasting contributes to wind power consumption and power grid
schedule as well as promotes the implementation of global carbon neutrality policy …
schedule as well as promotes the implementation of global carbon neutrality policy …
A wind power forecasting method based on optimized decomposition prediction and error correction
J Li, S Zhang, Z Yang - Electric Power Systems Research, 2022 - Elsevier
To reduce the effect of nonlinearity and volatility in the wind power time sequence, a two-
stage short-term wind power forecasting method based on optimized decomposition …
stage short-term wind power forecasting method based on optimized decomposition …
Wind power prediction based on outlier correction, ensemble reinforcement learning, and residual correction
Wind power prediction contributes to clean energy utilization and grid dispatching. In this
study, a wind power prediction model based on outlier correction, ensemble reinforcement …
study, a wind power prediction model based on outlier correction, ensemble reinforcement …
A short-term wind power forecasting method based on multivariate signal decomposition and variable selection
T Yang, Z Yang, F Li, H Wang - Applied Energy, 2024 - Elsevier
Accurate and effective short-term wind power forecasting is vital for the large-scale
integration of wind power generation into the power grid. However, due to the intermittence …
integration of wind power generation into the power grid. However, due to the intermittence …
A novel multi-layer stacking ensemble wind power prediction model under Tensorflow deep learning framework considering feature enhancement and data hierarchy …
H Wang, Z Tan, Y Liang, F Li, Z Zhang, L Ju - Energy, 2024 - Elsevier
Wind power prediction is crucial for energy production, but due to the complicated data
characteristics of wind farms, it's difficult to accurately predict wind power output and it is …
characteristics of wind farms, it's difficult to accurately predict wind power output and it is …