Reactive Point Processes: A New Approach to Predicting Power Failures in Underground Electrical Systems
Name
Rudin_SWP_5033-13.pdf
Description
Rudin_SWP_5033-13.pdf
Size
3.69 MB
Format
Adobe PDF
Checksum (MD5)
b6a367ac1818fa26a9a98532fe401b13
Author(s)
Ertekin, Seyda
Rudin, Cynthia
McCormick, Tyler H.
Date Issued
September 26, 2013
Series/Report no.
Sloan Working Paper Series;5033-13
Abstract
Reactive point processes (RPP’s) are a new statistical model designed for predicting discrete events, incorporating self-exciting, self-regulating, and saturating components. The self-excitement occurs as a result of a past event, which causes a temporary rise in vulnerability to future events. The self-regulation occurs as a result of an external “inspection” which temporarily lowers vulnerability to future events. RPP’s can saturate when too many events or inspections occur close together, which ensures that the probability of an event stays within a realistic range. RPP’s were developed to handle an important problem within the domain of electrical grid reliability: short term prediction of electrical grid failures (“manhole events”), including outages, fires, explosions, and smoking manholes, which can cause threats to public safety and reliability of electrical service in cities. For the self-exciting, self-regulating, and saturating elements of the model, we develop both a nonparametric estimation strategy and introduce a class of flexible parametric functions reflecting how the influence of past events and inspections on vulnerability levels gradually fades over time. We use the model to predict power grid failures in Manhattan over a short term horizon.
Subjects
Bayesian analysis, Energy grid reliability, Point processes, Hawkes processes, Time series
Terms of Use
Attribution-NonCommercial-NoDerivs 3.0 United States
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