Integrating Automated Metering Infrastructure (AMI) with GIS to Predict Electrical Outages
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Transcript of Integrating Automated Metering Infrastructure (AMI) with GIS to Predict Electrical Outages
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