Integrating Automated Metering Infrastructure AMI with GIS to

Integrating Automated Metering Infrastructure (AMI) with GIS to Predict Electrical Outages Allen Cousins – Senior GIS Analyst

Overview • Background • Outage Prediction • Implementation • Future

Background Established 1889 355, 000 Electric Customers 314, 000 Gas Customers 26, 400 Sq. Miles 8 Hydro Facilities Customers Electric Gas Both

Avista’s GIS § ESRI Arc. GIS/SDE 9. 2 § Oracle 10 g § 400+ Users § Avista Facilities Management (AFM) – Edit - Electric and Gas – OMS (OMT) - Electric – Design - Electric and Gas – Gas Compliance – Engineering Analysis - Syner. GEE – Servers (OMT, Batch Posting, Compliance, Work, Statistics) – Mobile – TC Technology Mapbook

OMT - Overview • Logically connected network. • Customer driven. • Customer outages are georeferenced. • Outages are assessed and prioritized § Geographically related § Electrically related § Prioritized by number and type of customers effected.

OMT – Problems • Relies on customers to report outages. § May or may not report outage. § Customer observations may be unreliable. • Reactive versus proactive. • Labor and time intensive analysis. • Delay in analysis causes restoration delays. • Verification of outage restoration.

AMI – Overview • Automated Metering Infrastructure (AMI). § Two-way Automatic Communication System (TWACS). • Remote meter reading. • Allows for the “ping” of the meter.

Outage Prediction

Outage Prediction

Outage Prediction

Implementation - Technology • Visual Studio. NET and C# • Component-based Scalable Logical Architecture (CSLA. NET) by Rockford Lhotka www. lhotka. net • Arc. Objects used to create custom trace routines to trace the GIS logical network. • TWACS hijacking

Implementation

Implementation

The Future… • Analysis vs Scanning • Storm Curve • Verification of restoration