Solar Radiation Anomaly Events Modeling Using Spatial-Temporal Mutually Interactive Processes

01/27/2021 ∙ by Minghe Zhang, et al. ∙ 0

Modeling and predicting solar events, in particular, the solar ramping event is critical for improving situational awareness for solar power generation systems. Solar ramping events are significantly impacted by weather conditions such as temperature, humidity, and cloud density. Discovering the correlation between different locations and times is a highly challenging task since the system is complex and noisy. We propose a novel method to model and predict ramping events from spatial-temporal sequential solar radiation data based on a spatio-temporal interactive Bernoulli process. We demonstrate the good performance of our approach on real solar radiation datasets.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 3

page 11

page 15

page 16

page 27

page 28

page 34

page 35

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.