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Data Analytics at American Electric Power Presentation to: SWEDE May 8, 2014 Tom Weaver, PE.

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Presentation on theme: "Data Analytics at American Electric Power Presentation to: SWEDE May 8, 2014 Tom Weaver, PE."— Presentation transcript:

1 Data Analytics at American Electric Power Presentation to: SWEDE May 8, 2014 Tom Weaver, PE

2 Business Analytics is the convergence of three key areas Business Opportunities  Working with OpCos, define business opportunities or problems we are trying to solve in 3 areas ‐ Distribution ‐ Meter ‐ Consumer Technical Solutions  Define the technical solutions that meet business needs for ‐ Data capture ‐ Data storage ‐ Complex processing ‐ Visualization Commercial Solutions  Define the commercial relationships that are required to make this journey successful ‐ Build vs. Buy ‐ Collaboration with others AEP Business Solution Collaboration is vital as considerations are inter-connected

3 Standard Reports Ad Hoc Reports Query Drilldown Alerts Statistical Analysis Forecasting Predictive Modeling Optimization Degree of Intelligence (Competitive Advantage) Analytic Capabilities Analytic CapabilityAnswers the Questions Standard Reports What happened? When did it happen? Ad Hoc Reports How many? How often? Where? Query Drilldown Or OLAP Where exactly is the problem? How to I find the answers? Alerts/Monitoring When should I react? What actions are needed now? Statistical Analysis Why is this happening? What opportunities am I missing? Forecasting What if the trends continue? How much is needed? When will it be needed? Predictive Modeling What will happen next? How will it affect my business? Optimization How do we do things better? What is the best decision for a complex problem? What does Business Analytics Mean?

4 S O U R C E D A T A – Conceptual View MACSS (MCS&OPS) AMI(UIQ&LGCC) MDM Operational Data Store TERS DA System(PI) OPERATIONAL PowerOn CES Data PEV Data PeopleSoft GIS Started simple pending maturity of vendor solutions Analytics framework today SWAMI AMIGO Metering Analytics Needs Analytic Capability Availability of Data for Load Research and Development of Detection Reports (Hot Sockets, Etc) Standard Service Order Processing Process/System Monitoring Standard GUI for the integration of meter events and orders Standard SAS

5 5 © 2013 Electric Power Research Institute, Inc. All rights reserved. Why is Data Analytics a Strategic Initiative for the Industry? SenseCommunicateComputeControl Power Plants TransmissionSubstations Distribution Consumers Sensor and Communication Technology Leapfrogging Ability to Mine Data for High Value Applications for Electric Utilities

6 6 © 2013 Electric Power Research Institute, Inc. All rights reserved. Distribution Modernization Demonstration on “Big Data” Data Management & Analytics to Support Operations, Planning and Asset Management Mission: Benchmark “State of the Industry” Demonstrate applications Collaborate with industry leaders Vision: Develop “best practices” Accelerate understanding Document cost benefit Take advantage of new opportunities afforded by a sensor enabled grid Potential Breakthroughs: –Better visualizations, insights –Emerging analytics capabilities –Application of data

7 7 © 2013 Electric Power Research Institute, Inc. All rights reserved. Day (0) Storm Event Day (+3) Storm Recovery Weather Forecasts Historical Damage Storm Protection Settings Management Systems Customers Interfaces Field Crew Interfaces Assets and Inventory AMI, SCADA, GIS Damage Assessments N+1 Data Sources Day –(3) Storm Forecast Predictive Analytics Situational Analytics Field Crew Support High Performance Computing Requirements Data Sets: Data Integration and Analytics Applied to a Storm Event and Recovery Leverage the New EPRI High Performance Computing System Define the right system for the application Evaluate fast pattern recognition for storm damage data

8 AMI Meter Temperature Monitoring Monitoring 502,310 meters. 85% accurate, 520 Issues out of 612 Field Orders. Next Steps for on-going Improvements: Automate monitoring. Change cutoff per season for more accuracy. Optimize parameters?

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10 Site Genie/Quality of Service Report Use SAS to decode then analyze the vectors. Broken CT and PT on transformer rated meters, poor connections under billing of commercial customers. New customer validation of service, saved Ohio 208 site visits this year. IssuesPopulation Ohio385, % PSO191, % I&M0473

11 Description of IssueNumber Corrected Service Type in Meter8 Bad Cable2 Service Incorrect in MACSS2 Bad PT2 Blown Transformer Fuse1 Theft1 No Issues1 Total Feedback17 Voltage Magnitude Analysis – Transformer Rated Meters Next Step: Create automated programs to analyze.

12 FUTURE: Energy Diversion Detection – Monitor Load Profile Analyze the Voltage and kWh of Load Profile Flag premises with high voltage drop but low kWh compared to neighbors. Program flagging premises documented on the wrong transformer.

13 FIRST: Clean Up AEP’s MACSS Data – Correlate Premises to Proper Transformer 2179 South

14 Texas Voltage Magnitude Monitoring Hi Volt/Failing Transformers – 111 found Oct. ’13 to Feb. ‘14 2S on 12S Service: 75% registration

15 Utilities looking for Optimize Utilization & Costs Improve grid efficiency Speed up Restoration Limit the Impact Avoid the Outage Grid Resiliency Grid Restoration Grid Hardening Grid Health Improving grid reliability Grid Utilization Used with permission from General Electric

16 Typical grid reliability objectives Total Grid Risk Management – Proactive service & maintenance – Reduction of capital expenses – Lower repair costs – Enhance system reliability, availability & performance – Support optimized asset replacement – Optimize workforce productivity & safety Used with permission from General Electric Focused maintenance Reduced CapEx, OpEx Enhanced Performance Manage asset risks Efficient & Optimized Operations Proactive asset risk management across entire life cycle 16 Used with permission from General Electric

17 AEP Distribution Analytics Currently planning Load analytics Vegetation management Convert sensor data to actionable steps Future Plans Automating reliability metrics Tying asset age and health to outage trends Storm damage prediction

18 18 Questions? Tom Weaver –


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