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

Solar power installations are becoming common in residential and commercial areas, largely due to their decreasing costs. However, the power system is vulnerable to some anomalies such as rainstorm or hurricane, which cost greatly to restoration. As a result, detecting and predicting abnormal events from the spatialtemporal series plays a vital role in the solar system, aiming to capture the variety of intrinsic reasons for the anomalies. For example, the rainstorm and drought would bring out different types and patterns of anomalies. In many cases, the abnormal event will also start at one location and then propagate to its neighbors with a time delay, leading to spatial-temporal correlation among anomalies. Thus it is crucial to make observations at multiple locations, which correspondingly form the spatial-temporal series. In this paper, we address non-stationarity and strong spatial-temporal correlation through the following contributions: - Strong spatial-temporal correlation: We present a spatial-temporal Bernoulli process (also extended to categorical observations), which is proposed by [19]. The model can flexibly capture the spatial-temporal correlations and interactions without assuming time-decaying influence. It can also efficiently make predictions for any location at any future time for timely ramp event detection.