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Adaptive forecasting of photovoltaic power based on dual-type models’ ensemble and online error correction | Synapse
March 3, 2026
Adaptive forecasting of photovoltaic power based on dual-type models’ ensemble and online error correction
HL
Haipeng Liu
Kunming University of Science and Technology
HW
Hong Wu
Kunming University of Science and Technology
HJ
Huaiping Jin
Kunming University of Science and Technology
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Puntos clave
Forecasting accuracy improves with dual-type models' ensemble, enhancing system reliability.
The proposed adaptive approach shows a decrease in forecasting errors by over 20% compared to traditional methods.
Analysis using real-time data highlights the effectiveness of online error correction in power forecasting.
This method may enable better energy resource management in renewable energy systems, enhancing grid stability.
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Liu et al. (Sat,) studied this question.
synapsesocial.com/papers/69a75a2dc6e9836116a1fbf2
https://doi.org/https://doi.org/10.1016/j.apenergy.2026.127397