Wind Power Forecasting in the presence of data scarcity: A very short-term conditional probabilistic modeling framework
The uncertainty of wind power (WP) poses a significant challenge to power systems with a
high percentage of WP. Accurate WP forecasting is an important approach to mitigate this …
high percentage of WP. Accurate WP forecasting is an important approach to mitigate this …
Proactive failure warning for wind power forecast models based on volatility indicators analysis
Y Chen, C Lin, Y Zhang, J Liu, D Yu - Energy, 2024 - Elsevier
With the promotion of low-carbon models, the proportion of wind power energy has
significantly increased. Accurate wind power forecasting is of great significance for the …
significantly increased. Accurate wind power forecasting is of great significance for the …
An adaptive distribution-matched recurrent network for wind power prediction using time-series distribution period division
A Meng, H Zhang, Z Dai, Z Xian, L Xiao, J Rong, C Li… - Energy, 2024 - Elsevier
Precise wind power prediction (WPP) can address the issue caused by large-scale wind
power grid integration to the power system operation. Most WPP research focus on the …
power grid integration to the power system operation. Most WPP research focus on the …
A wind speed forecasting framework for multiple turbines based on adaptive gate mechanism enhanced multi-graph attention networks
Accurately forecasting wind speed is crucial for efficiently utilizing wind energy and
scheduling power grids. Recently, Graph Neural Network (GNN) models have been widely …
scheduling power grids. Recently, Graph Neural Network (GNN) models have been widely …
A reconstruction-based secondary decomposition-ensemble framework for wind power forecasting
R Cheng, D Yang, D Liu, G Zhang - Energy, 2024 - Elsevier
Accurate wind power forecasting remains challenging due to the instability and volatility of
wind power generation. Decomposition methods are widely used to improve forecasting …
wind power generation. Decomposition methods are widely used to improve forecasting …
Short-term wind power prediction based on ICEEMDAN-Correlation reconstruction and BWO-BiLSTM
J Liu, Y Wu, X Cheng, B Li, P Yang - Electrical Engineering, 2024 - Springer
To solve the problems of high volatility and low prediction accuracy of wind farm output
power, this paper proposes a short-term wind power prediction model with improved …
power, this paper proposes a short-term wind power prediction model with improved …
Forecasting hybrid renewable power generation in Luxembourg: a comparative study of convolutional neural network's application
V Arabzadeh, R Frank - 2024 IEEE 15th International …, 2024 - ieeexplore.ieee.org
Access to reliable renewable power generation forecasting tools is crucial for optimizing grid
operations and advancing the integration of renewable energy, which in turn leads to the …
operations and advancing the integration of renewable energy, which in turn leads to the …
An Adaptive Photovoltaic Power Interval Prediction Based on Multi-Objective Optimization
Y Jiang, X Wang, D Yang, R Cheng, Y Zhao… - Available at SSRN … - papers.ssrn.com
Photovoltaic (PV) power interval prediction can provide a variation range of prediction
results, which is of great significance to promoting the optimization of power grid dispatching …
results, which is of great significance to promoting the optimization of power grid dispatching …