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

2. Overview Background Outage Prediction Implementation Future

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

4. Avista’s GIS  ESRI ArcGIS/SDE 9.2  Oracle 10g  400+ Users  Avista Facilities Management (AFM) – Edit - Electric and Gas – OMS (OMT) - Electric – Design - Electric and Gas – Gas Compliance – Engineering Analysis - SynerGEE – Servers (OMT, Batch Posting, Compliance, Work, Statistics) – Mobile – TC Technology Mapbook

5. 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.

6. 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.

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

8. Outage Prediction

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

12. Implementation

14. The Future… Analysis vs Scanning Storm Curve Verification of restoration