1. Allen Cousins – Senior GIS Analyst Frank Hardisty Ph.D. - Adviser
Integrating Automated Metering Infrastructure (AMI) with GIS to Predict Electrical Outages
Allen Cousins – Senior GIS Analyst
Frank Hardisty Ph.D. - Adviser

2. Overview
Background
Outage Prediction
Implementation
Future

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

9. Outage Prediction

10. Outage Prediction

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

12. Implementation
Existing Manual
Outage Analysis Process

13. Implementation
Three Phases to Automated
Outage Analysis

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

15. Thank you for your attendance. Questions?