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

Gas Electric

Customers

Both

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

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

• ArcObjects 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