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Modeling and predicting solar events, particularly the solar ramping event,is critical for improving situational awareness for solar power generationsystems. It has been acknowledged that weather conditions such as temperature,humidity, and cloud density can significantly impact the emergence and positionof solar ramping events. As a result, modeling these events with complexspatio-temporal correlations is highly challenging. To tackle the question, weadopt a novel spatio-temporal categorical point process model, whichintuitively and effectively addresses correlation and interaction among rampingevents. We demonstrate the interpretability and predictive power of our modelon extensive real-data experiments.

Solar Radiation Ramping Events Modeling Using Spatio-temporal Point Processes