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A dual-path forecasting strategy for photovoltaic power with adaptive feature weighting and multi-scale attention
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DOI：10.1016/j.ijepes.2025.111474.png)
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Abstract
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• A dual-path PV forecasting model with adaptive feature weighting and multi-scale attention is proposed. • An error correction enhances signal decomposition for feature extraction (ECVMD) is introduced. • AFWformer and TFMformer are designed to model stable trends and fluctuating signals. • The model on real PV datasets is validated with superior accuracy over baselines.
Keywords:
Photovoltaic power forecasting
Dual-path forecasting model
Adaptive feature weighting
Time-frequency multi-scale Transformer
Bayesian optimization
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