PV-VLM fuses visual, textual, and temporal features via a vision-language model and cross-modal attention to improve intra-hour photovoltaic power forecasts by roughly 5 to 9 percent in RMSE and MAE.
The values of market -based demand response on improving power system reliability under extreme circumstances
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PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting
PV-VLM fuses visual, textual, and temporal features via a vision-language model and cross-modal attention to improve intra-hour photovoltaic power forecasts by roughly 5 to 9 percent in RMSE and MAE.