dc.contributor.author | Ertekin, Seyda | |
dc.contributor.author | Rudin, Cynthia | |
dc.contributor.author | McCormick, Tyler H. | |
dc.date.accessioned | 2015-10-05T16:32:47Z | |
dc.date.available | 2015-10-05T16:32:47Z | |
dc.date.issued | 2015-03 | |
dc.date.submitted | 2014-09 | |
dc.identifier.issn | 1932-6157 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/99145 | |
dc.description.abstract | Reactive point processes (RPPs) are a new statistical model designed for predicting discrete events in time based on past history. RPPs 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. RPPs incorporate self-exciting, self-regulating and saturating components. The self-excitement occurs as a result of a past event, which causes a temporary rise in vulner ability to future events. The self-regulation occurs as a result of an external inspection which temporarily lowers vulnerability to future events. RPPs can saturate when too many events or inspections occur close together, which ensures that the probability of an event stays within a realistic range. Two of the operational challenges for power companies are (i) making continuous-time failure predictions, and (ii) cost/benefit analysis for decision making and proactive maintenance. RPPs are naturally suited for handling both of these challenges. We use the model to predict power-grid failures in Manhattan over a short-term horizon, and to provide a cost/benefit analysis of different proactive maintenance programs. | en_US |
dc.description.sponsorship | Con Edison | en_US |
dc.description.sponsorship | MIT Energy Initiative (Seed Fund) | en_US |
dc.description.sponsorship | National Science Foundation (U.S.) (CAREER Grant IIS-1053407) | en_US |
dc.language.iso | en_US | |
dc.publisher | Institute of Mathematical Statistics | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1214/14-AOAS789 | en_US |
dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | en_US |
dc.source | arXiv | en_US |
dc.title | Reactive point processes: A new approach to predicting power failures in underground electrical systems | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Ertekin, Seyda, Cynthia Rudin, and Tyler H. McCormick. “Reactive Point Processes: A New Approach to Predicting Power Failures in Underground Electrical Systems.” The Annals of Applied Statistics 9, no. 1 (March 2015): 122–144. © 2015 Institute of Mathematical Statistics | en_US |
dc.contributor.department | Sloan School of Management | en_US |
dc.contributor.mitauthor | Ertekin, Seyda | en_US |
dc.contributor.mitauthor | Rudin, Cynthia | en_US |
dc.relation.journal | The Annals of Applied Statistics | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dspace.orderedauthors | Ertekin, Seyda; Rudin, Cynthia; McCormick, Tyler H. | en_US |
dc.identifier.orcid | https://orcid.org/0000-0001-6541-1650 | |
mit.license | PUBLISHER_POLICY | en_US |
mit.metadata.status | Complete | |