How Do We Manage the Data Generated by AMI? Wendy Lohkamp Director, Product Marketing, Itron

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1 How Do We Manage the Data Generated by AMI? Wendy Lohkamp Director, Product Marketing, Itron

2 Why Data Management with AMI? you are here With AMI: collecting shells in the surf while the tide is coming in Before AMI: collecting shells on the beach at low tide you are here

3 Three Layers of Data Management Collection Software Transitory data, current snapshot Manages network components Monitors data collection process for a single technology Collects data from backhaul Distributes raw data Meter Data Management Persistent data store, historical perspective Manages relationship of meter to rest of enterprise Collects data from all connected systems Validates, repairs data anomalies Distributes validated data to utility applications and market Knowledge Applications Composite applications with multiple sources Places meter data in context for specific functions Upstream Systems Collection Software Collection Technology Meters / End Nodes In-Home Devices & Displays Data Management Knowledge Applications Meter data stored for historical analysis Meter data queued to MDM, hours, days, months Meter data stored in memory, 4 hours to 1 year

4 Each Layer Adds Value Redundancy Time periods overlap; mitigates failure of any layer Security Link by serial number; keeps customer-specific information behind the corporate firewall Filtering and Normalization Multiple messages reduced to individual events; reduces data overload Normalize to a standard code value, a single time resolution or time zone; reduces complexity of later uses Context Blend with operational or customer attributes; makes data useful

5 AMI Data Management Challenges Data types Volume and Storage Timeliness Quality Aggregation Integration

6 AMI Data Management Challenges Data types Volume and Storage Timeliness Interval data New registers Quality Aggregation Integration Tamper events Legacy systems may not be able to process new data types Multiple systems may be concerned about the same events Power outage events Meter diagnostic events New devices present new messages AMI devices Communication networks

7 AMI Data Management Challenges Data types Volume and Storage Timeliness Volume of data significantly increases with AMI Quality Aggregation Integration Storage Monthly: 1 value per month Daily: 1 value per day Hourly: 24 values per day, 720 values per month Sub-hourly (5-min, 15-min, 30-min, etc.): up to 288 values per day Data is collected every day, in advance of when it is needed

8 AMI Data Management Challenges Data types Volume and Storage Timeliness AMI solutions process commands differently Quality Synchronous vs. asynchronous Aggregation Broadcasting vs. individually addressed Integration Upstream systems process data at different times Once per day vs. streaming File-based vs. web services

9 AMI Data Management Challenges Data types Volume and Storage Timeliness Quality Aggregation Stuff happens Optimizing network coverage is an art Integration Multiple layers of redundancy lead to new retry functions

10 AMI Data Management Challenges Data types Volume and Storage Timeliness Quality Aggregation Integration Required to support new, creative rates using interval data Reduces risk of meter program/rate synchronization issues

11 AMI Data Management Challenges Data types Volume and Storage Timeliness Quality Aggregation Integration Legacy systems often have limited integration options The effort to maintain point-to-point interfaces stifles IT, limits pilots and selection of best technologies for the job

12 Why Meter Data Management? Integrate and analyze frequently collected data Support new uses of detailed data across the enterprise Integrate non-billing features of meter reading systems Reduce risk in AMI implementation projects Enable change

13 Itron Enterprise Edition Solutions Knowledge Applications Residential CIS, C&I Billing Customer Service, Account Management Outage Management, Distribution Operations Load Research, Forecasting, Load Management Customer Care and Curtailment Revenue Protection Distribution Asset Analysis Handheld/Mobile Collection Systems AMR/AMI Collection Systems Interval Data Collection Systems Other Data (weather, prices, SCADA, etc.) Complex Billing

14 Meter Data Management and Applications Outage Management System Event Import Event Filtering Evaluation Asset Management System Readings Import Validation, Estimation, & Editing Meter Data Repository Aggregation Export Billing Two-way Control APIs Customer Care Revenue Protection Curtailment and Demand Response Distribution Asset Analysis

15 Meter Data Management Functions Multi-vendor data collection and management Persistent data storage with customer information in enterprise-class database Comprehensive interval data management Validation, Editing and Estimation Flexible billing determinant calculations Packaged tamper and diagnostic event interfaces Standard customer usage and exception reports Direct integration with Knowledge Applications

16 IEE MDM Business Processes

17 Import Multiple standard formats HHF, XML, CSV Non-standard formats transformed prior to import Normalizes data to single time zone (UTC) Manages data regardless of arrival time intra-day daily monthly (on cycle) Performs validation and estimation on import

18 Validation, Estimation & Editing Consistent validation, estimation, and editing capabilities, regardless of data source Built-in parameter-based validation and estimation rules User-defined validation and estimation rules for customerspecific evaluations, no coding required Exception-based work queue and manual editing and estimation user interface Data gaps Data overlap/multiple versions Usage tolerance registers versus interval data Demand tolerance registers versus interval data Usage low limit Usage high limit Demand low limit Demand high limit Power factor low limit Load factor low limit Load factor high limit Demand tolerance between consecutive intervals (%) Max number of zero intervals Spike tolerance Max number of status indicators Comparisons against previous periods

19 Meter Data Repository Fully versioned data store Validated Estimated, Edited Enterprise class database (Oracle or SQL Server) Minimal master data required Service Point (unique identifier) Meter/Module Premise Additional master data increases value Customer/Account Transformer Secured by user and role

20 Aggregation Consistent aggregation, allocation, netting, and other calculations, regardless of data source RTP, TOU, CPP Losses, netting, etc. Easy-to-use scripting language for new formulas, requires no code changes All changes to formulas tracked over time Rich function set delivered with product + - * / Square root, sine, cosine, etc. Unit conversion functions KWH, KVARH KVAH or power factor, V2H V, etc. Conditional and Logical Operators IF/AND/OR/NOT,<.>, etc 50 levels of nesting Conditional functions based on status Read statuses Write statuses Date and Time functions TOU functions

21 Price-based Demand Response Billing Determinant calculations based on interval data captured through AMI Time of Use Critical Peak Pricing Peak Time Rebate Real Time Pricing Calculation Engine to set up flexible TOU and CPP definitions

22 Interval Data for TOU Aggregated by billing period on cycle To CIS for billing Aggregated by day on demand Available to Customer Care Portals via web services From the meter

23 Export Multiple standard formats XML, CSV, handheld simulators Non-standard formats transformed after export Export over any interval length, time zone, date range Data aggregated on-the-fly during export Automated push or pull on demand

24 Event Management Receive events from capable meters and collection systems Standardize events codes, regardless of meter or collection system type Event filtering based on event age and type Export API to transfer of events to outage management and other systems Brokering of events to multiple destinations

25 Customer Care Web presentation to customer service reps, account managers and end-use customers Energy analysis Cost analysis Bill analysis What if analysis for rates and load shifting Alerts Push reports and data via Bill inquiry self service

26 MDM is a Key Part of the Demand Response Infrastructure load control through AMI network Public Backhaul AMI System(s) Meter Data Management Cell Relay Demand Response Analysis Demand Response Management load control through alternate network Load Control System(s) Public Backhaul Customer Portal DR Analysis DR Management Meter Data Management AMI System Load Control System Load Control Devices RF LAN ZigBee ZigBee

27 Targeted Demand Response Everywhere AMI provides reliable communication network to home, meter is in a good physical location to reach into home Collects interval data for TOU, CPP, RTP, PTR rates Captures data and device confirmations for timely and uncontested verification of DR events 2-way network supports remote upgrades as enhancements become available Portal provides customer education and verification Turns DR potential into a dispatch-able resource

28 Why Itron? Depth and breadth of meter data management application Commercial, industrial, residential Multiple packaged file interfaces Energy-specific and flexible calculation engine Experience with interval data Time-zone conversions, DST handling Industry-standard Validation and Estimation rules Energy-specific calculations, complex units of measure Pre-built aggregation across interval lengths Future adaptability Existing Knowledge Applications Analytic applications built by you or your partners

29 Cowabunga!