Modeling temporal lag correlations for wind farm meteorology-power joint forecasting: A universal framework

Key Points

• The aim is to create a framework for joint forecasting of meteorology and power by modeling temporal lag correlations.
• Developed a unified framework for meteorology-power forecasting.
• Identified correlations using temporal lag modeling.
• Implemented an adaptive alignment mechanism to address dynamic temporal lags.
• Achieved improved forecasting accuracy through the proposed framework.
• Demonstrated effective identification of temporal lag correlations in varying conditions.
• Provided a systematic approach for adaptive alignment in meteorology and power data.