Join the Grid Analytics Community on Wednesday, October 13, 2021 at 1:45 - 2:45 PM CT for a presentation with Q&A and open discussion on "Improve Fault Location Accuracy for Historical Electrical Outage" with Amin Tayyebi, Data Science Manager at Exelon Utilities.

Utilities are spending millions of dollars on storm hardening and other engineering solution deployments and leveraging outage and damage data for advanced analytics use cases such as storm prediction and vegetation spot-trimming. Accurate outage location is fundamental to supporting and enabling this work. Historical outage data records the geographical location where an outage was reported (i.e. the coordinates of the residence of a customer who called to report the outage) but does not reflect the actual location where crews worked to repair faulty/damaged equipment. Exelon integrated various GIS data sources called 1) mobile dispatch system (MDS) that enables crew to automate routing and scheduling processes efficiently, 2) outage management system (OMS) that stores the location of outage and assist in restoration of power, 3) GIS system provides the location of utility assets (i.e. poles, breakers, fuses and feeders), 4) Verizon Telematics allow complete connectivity to any vehicle with safety and security as the beginning. With integrating various data source, Data Science, Operation Dashboard, and ArcGIS API for Python, Exelon built an algorithm that improves the accuracy of outage location.