DISCUSSION Topic: aMI DATA ANALYTICS 2017 Transmission & Distribution Benchmarking Community Insights Conference DISCUSSION Topic: aMI DATA ANALYTICS August 22-25, 2017 Burlington, VT

AMI DATA ANALYTICS Overview -- This year’s Discussions with our Community Goal and Scope of Our Discussions The goal of this 2017 discussion topic was to investigate how AMI data is currently being collected, stored, analyzed and leveraged to support business operations at T&D community companies that have established AMI data analytics groups. The companies that agreed to share information during the webinars were asked to comment on three aspects of their AMI data analytics activities: Organization and staffing of their AMI data analytics function Data processes, systems and tools that are being used Current and planned future applications of AMI data (“use cases”), with particular focus on applications that support T&D

Companies that shared information Company Spokespersons First Energy Robert Greene Oncor Electric Delivery Randall Schmidt PHI Bobby Besharati/ Belinda Kargbo Thanks for taking the time to share your information and answer our questions!

HOW TO LEVERAGE THE VALUE OF TODAY’S PRESENTATION AND OBTAIN ADDITIONAL INFORMATION Listen to recordings from the webinar sessions that were held on May 24 and May 30, 2017, and read and share copies of the presentation documents. These records are stored on the First Quartile website. Below is a link to the website. Please handle this material the same as you would any of our benchmarking data, following our confidentiality agreements. http://1stquartileconsulting.com/benchmarking/transmission_b/tddocs.html Today’s presentation is available for you to use as an overview document at any meetings you may have on this topic at your company Additional information might be obtained from the T&D community companies that shared information during the webinars and/or those that have made presentations on this topic in other forums. Contact the T&D benchmarking coordinators of those companies to arrange follow-up discussions.

Today’s Overview What are we talking about (definition and scope of the topic)? Why should we be interested in this topic? How have companies organized and staffed their AMI data analytics functions? What systems and tools are used to collect, store and analyze AMI data? How is AMI data being used to improve operations?

What are we talking about? Definition: The term “AMI data analytics” encompasses the people, business processes, hardware, software and communication network services that enable utilities to collect, analyze and apply customer metering data in order to improve operations and better serve customers

What are we talking about? Scope (process steps): Collect AMI Data Gather large volumes of smart meter data Filter out noise Identify and fix network problems (Out of Scope) Produce Information Produce Customer Bills Validate and clean up data Analyze and summarize meter data and correlate it to other available data Draw Insights Identify causal relationships Pinpoint locations of problems Identify improvement opportunities Make Decisions Managerial Operational Strategic Regulatory compliance Efficiency gains Reliability improvements Other benefits Achieve Outcomes Source: Adapted from a slide in First Energy’s webinar presentation, May 24, 2017, Robert Greene

What are we talking about? Scope (hardware and software): Direct Connect Meter Wide-Area-Network (WAN) CGR, Range Extender Head End (Itron OpenWay, “OWCE”) Connected Grid Network Management System (Cisco) Itron Meter Data Management (Itron Enterprise Edition) Mesh Network Standard Smart Meters Source: First Energy’s webinar presentation, May 24, 2017, Robert Greene Downstream Systems (SAP, Teradata, etc)

What are we talking about? Scope (potential operational impact areas): Our primary focus for T&D

WHY should we be interested? Companies that have installed smart meters throughout their system (47% of this year’s survey respondents) and those that are in the process of doing so (an additional 35%): To learn about the experiences of other companies that have deployed AMI technology and are in the process of developing their analytics capabilities -- identify what applications (“use cases) have proved to be beneficial -- so that you can refine your company’s developmental plans Companies that are piloting smart meters or about to start a pilot program (12% of this year’s survey respondents) and companies that have no current plans for smart meters (the remaining 6%) To identify potential AMI data analytics applications (“use cases”) and associated benefits that might be used to bolster a business case to proceed with widespread AMI deployment at your company 82% 18% Source: SG pg.19 – SG30, 17 responses

HOW HAVE COMPANIES ORGANIZED AND STAFFED THEIR AMI DATA ANALYTICS FUNCTIONS? Is the staff centralized or decentralized? How is it aligned with other functions? All three companies that shared information during the webinars have central AMI operations and data analysis groups within the Meter to Bill process organization which are focused on ensuring that the data collection system is working effectively, using data analytics tools to support problem root cause analysis and remediation All three companies have or expect to have decentralized data analytics groups embedded in multiple areas of the energy delivery business unit, including revenue management/collections, system planning, asset management, outage management, regulatory reporting, etc. – these people develop and maintain the AMI data applications (use cases) that support their operations What education and skills does the staff possess? All three companies reported that they staff their data analytics groups with a wide range of skill-sets and work experience, including people with IT backgrounds, people with deep field experience in meter reading, meter operations and/or dispatch, electrical engineering technicians, engineers and statisticians. Their educational degrees range from high school only all the way up to doctorate degrees in various branches of science, technology, engineering and mathematics What have been the most significant organizational challenges? Identifying and installing database and data analysis tools that are capable of efficiently handling “big data” volumes and that meet the needs of multiple user groups Establishing an effective data governance process as applications/use cases are identified and developed outside of the Meter to Bill process

What systems and tools are being used? AMI Meters Itron (FE); Landis & Gyr (Oncor); GE and Landis & Gyr (PHI) Head-end Processor and Network Management System Itron OpenWay and CISCO Connected Grid Network Management System (FE); Landis & Gyr Command Center (Oncor); Silver Spring Networks UIQ (PHI) Meter Data Management System Itron Enterprise Edition MDMS (FE); Gridstream MDMS (Oncor); Itron Enterprise Edition MDMS (PHI) “Big Data” Repository Teradata (FE); Oracle and Informix (Oncor); SAP, Oracle and Landis & Gyr Advanced Grid Analytics (PHI) Data Analysis and Presentation Tools QlikView and ServiceNow (FE); Numerous tools including Toad, Power BI, SQL Explorer/Developer and Cognos (Oncor); SAS, SQL, Toad, Tableau (PHI) Collect AMI Data Gather large volumes of smart meter data Filter out noise Identify and fix network problems Produce Information Validate and clean up data Analyze and summarize meter data and correlate it to other available data

HOW IS AMI DATA BEING USED TO IMPROVE OPERATONS? FIRST ENERGY AMI Deployment Status Deployment is in progress across four Pennsylvania operating companies (Penn Power, Penelec, West Penn and Met-Ed); now about 50% deployed in PA and using the collected data primarily for customer billing Current Data Analytics Applications Several current applications that support data collection continuous improvement Future Data Analytics Applications Remote Connect/Disconnect (RCD) Meter Tampering Detection Outage Management Ping (Restoration Verification) Anticipated future advanced analytics applications to support various areas of the organization including Asset Management, Customer Service, Field Operations, Resource Management, Supplier and Regulator Settlements, etc. Draw Insights Make Decisions Achieve Outcomes

HOW IS AMI DATA BEING USED TO IMPROVE OPERATONS? (CONTINUED) ONCOR ELECTRIC DELIVERY AMI Deployment Status Fully deployed as of late 2012 Current Data Analytics Applications Remote Connect/Disconnect Meter Tampering Detection Energy Theft Detection Predicting Meter Failures High/Low Voltage Detection Power Quality Improvement Re: Momentary Outages/Light Flickers Customer Outage Data “Scrubbing” For SAIDI Calculations Predicting Transformer Failures Predicting Asset Damage After Storms Outage Restoration Verification After Storms Customer Proactive Messaging (Outages,ERTs) Future Data Analytics Applications Asset Failure Prediction Cable, Capacitors, Other Line Devices Transformer Load Management System Planning Support Applications Network Connectivity Verification/Corrections Draw Insights Make Decisions Achieve Outcomes

HOW IS AMI DATA BEING USED TO IMPROVE OPERATONS? (CONTINUED) PHI AMI Deployment Status Fully deployed at two operating companies (PEPCO and DPL); no AMI currently at third operating company (ACE) Current Data Analytics Applications Asset Load Management Transformers Feeder Devices Conservation Voltage Reduction (CVR) Reliability Analysis Improve accuracy of KPI calculations Identify worst performing feeders for each region Optimize reliability improvement efforts Outage Restoration Verification After Storms Planning Support for DER Integration (major initiative at PHI due to high current DER penetration levels and high volume of interconnection applications (1,500 per month)) Future Data Analytics Applications Network Connectivity Verification/Correction (under development, should be rolled out in near future) Draw Insights Make Decisions Achieve Outcomes

conclusions Companies that have deployed AMI meters on a widespread basis have identified many opportunities to use the data that is collected through those meters to improve their business operations outside of the “meter to bill process” Additional information on this topic can easily found through internet searches, including some interesting developmental work performed at several T&D community companies that did not participate in our May 24 and May 30 webinars (e.g., PECO, BG&E, APS, Georgia Power)

Introduction of today’s speakers Steve Steffel – PHI Use of AMI Data Analytics to Support DG/DER Integration Jon Pettit – Oncor Electric Delivery Overall Impact of Smart Meters on Utility Operations

Thank you for your Input and Participation! Gene Dimitrov Gene.Dimitrov@1QConsulting.com 301-535-0590 Rob Earle Rob.Earle@1QConsulting.com 315-944-7610 Your Presenters: Ken Buckstaff Ken.Buckstaff@1QConsulting.com 310-922-0783 Debi Cook Debi.Cook@1QConsulting.com 760-272-7277 Dave Carter Dave Weiler Dave.Carter@1QConsulting.com Dave.Weiler@1QConsulting.com 414-881-8641 607-761-6778 About 1QC First Quartile Consulting is a utility-focused consultancy providing a full range of consulting services including continuous process improvement, change management, benchmarking and more. You can count on a proven process that assesses and optimizes your resources, processes, leadership management and technology to align your business needs with your customer’s needs. Visit us at www.1stquartileconsulting.com