DeepAI AI Chat
Log In Sign Up

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

by   Minghe Zhang, et al.

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.


page 3

page 11

page 15

page 16

page 27

page 28

page 34

page 35


Prediction of Solar Radiation Based on Spatial and Temporal Embeddings for Solar Generation Forecast

A novel method for real-time solar generation forecast using weather dat...

ECLIPSE : Envisioning Cloud Induced Perturbations in Solar Energy

Efficient integration of solar energy into the electricity mix depends o...

Extreme Value Analysis of Solar Flare Events

Space weather events such as solar flares can be harmful for life and in...

Towards data-driven modeling and real-time prediction of solar flares and coronal mass ejections

Modeling of transient events in the solar atmosphere requires the conflu...

Kronecker-structured Covariance Models for Multiway Data

Many applications produce multiway data of exceedingly high dimension. M...

Filament and Flare Detection in Hα image sequences

Solar storms can have a major impact on the infrastructure of the earth....

Crime Linkage Detection by Spatial-Temporal-Textual Point Processes

Crimes emerge out of complex interactions of behaviors and situations; t...