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
Overview Background Outage Prediction Implementation Future
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
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 Existing Manual Outage Analysis Process
Implementation Three Phases to Automated Outage Analysis
The Future… Analysis vs. Scanning Storm Curve Verification of restoration
Thank you for your attendance. Questions?