Adaptive forecasting of photovoltaic power based on dual-type models’ ensemble and online error correction

Key Points

• 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.