A large-scale multi-objective evolutionary neural network model considering robustness for short-term wind power prediction

Key Points

• Wind power prediction accuracy increased with a multi-objective evolutionary neural network model, achieving notable robustness.
• A key finding indicates significant improvements in prediction efficiency across diverse wind conditions within a 6-month data collection period.
• The analysis utilized a multi-objective evolutionary algorithm focusing on predictive robustness and adaptability to varying climatic factors.
• Enhancements in wind energy forecasting may lead to better integration of renewable sources into the energy grid.