Improved outage prediction using asset management data and intelligent multiple interruption event handling with fuzzy control during extreme climatic conditions

Abstract

Outage management system is key player in handling fault outages in distribution network where proportion of fault occurrences is more as compared to transmission network. Performance of such system is crucial during extreme weather conditions as multiple large scale outages results in thousands of customers without power. There are two factors that affect performance during such situations. One is quicker prediction of interrupted devices and another is systematic prioritization of work orders so as to effectively manage crews to reduce overall outage costs. For quicker for intelligent prioritization, fuzzy rule based approach has been implemented. Fuzzy rules based on utility operators experience considering both customer's satisfaction and utility lost revenue are defined. Lastly, effectiveness of this approach is checked by calculating aggregated outage cost considering all interruption events.