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AMI to SmartGrid “DATA” October 20, 2011 John A Sotak – National Technical Sales Manager - Sensus Smart Grid Communication Data Network Sources EPRI CONFIDENTIAL Transformation of Data Producing Products Common Data Producers Meter Reads - Monthly OMS systems - reactive Work order management systems - reactive SmartGrid Data Producers (Real-time) Meter Reads – hourly / 15 minute OMS systems – real time Work order mgmt systems – real time Billing GIS SCADA – Real-time Distributed Energy storage devices Distributed Power Generators Billing GIS SCADA – Real-time Flexible demand response programs Distribution automation (pro-active) FCI Relays Sub-stations Transformer Price signals (Real-time) Customer info & notifications (Real-time) PHEV charging criteria CONFIDENTIAL 3 Impact of Data Producers Data volumes will increase 3,000x! What makes a smart grid SMART is precisely what causes so much difficulty: Information volume DATA, DATA, DATA !!! Installed base of smart technologies • Smart grid data volumes can be 3,000x what we are used to handling • It is far more than just meter data - many new smart devices and data types • Utilities need new tools, architectures, processes to manage smart grid data CONFIDENTIAL 4 SmartGrid Data Sources • Meter Usage Data: data representing condition or behavior of assets. Including: total usage, average demand, peak demand, TOU, peak demands. Additionally; voltages, power flows, power factor, & power quality data • Operational Data: electrical behavior of the grid data; voltage & current phasors, real & reactive power flow, demand response capacity, power flows, real time forecasting of the operational data CONFIDENTIAL 5 SmartGrid Data Sources • Event Message Data: asynchronous event messages from grid devices; outage & restoration messages, fault circuit messages, non-standard event notice messages. • Non-Operational Data: conditional behavior of grid assets; power quality & reliability data; asset stressor data; utilization data; additional work asset type of non-direct data. • Meta-Data: “KEY INTERPRETATION DATA”; grid connectivity, network addresses & groups, calibration constants, normalization factors, network parameters & protocols. CONFIDENTIAL 6 Critical Comms Criteria: Latency NOT Bandwidth High Business Repository data L A T E N C Y Days - Months Business Intelligence Dashboard & reports Enterprise Operations Historical data Minutes - days Op/Non-Op data Sec. – sub minute SmartGrid Data Producers Milli-sub seconds Transactional Analytics Reporting systems & processes Real-time Analytics Visualization systems & processes Business Intelligence Protection & Control Systems Low CONFIDENTIAL 7 SmartGrid Data Latency Examples CONFIDENTIAL Solving the Massive DATA Apps/Svcs Delivery System Application Based Risk DATA Everywhere! CONFIDENTIAL Reward 3 CSFs Usability Usability Usability Unified DATA Warehousing Solving the Massive Data Requirements • Matching data acquisition infrastructure to required outcomes – Number, kind, and placement of data measurement devices – Communication networks and data collection engines • Learning to apply new tools, standards, and architectures to manage grid data at scale – New open standards for interoperability – Distributed architectures – New analytics tools • Transforming business processes to take advantage of smart grid technology CONFIDENTIAL 10 Processing Tools for the Data: Complex Event Based & Event Stream Based • SmartGrid devices and systems increasingly generate asynchronous event messages – Such event messages tend to come in bursts and floods when something (usually bad) is happening on the grid – Normal operations also generate event message streams • Processing event streams requires a different approach – Standard approaches use dynamic queries against (more or less) static data – New approach continually runs static queries against dynamic data streams • Two forms of Platform Based Processing: ESP and CEP – ESP – Event Stream Processing – single stream – CEP – Complex Event Processing – multiple streams • Commercial platforms exist for implementation: CEP engines and development tools; CEP rule bases support other developed business processes (Look at the telecom, stock market, or Homeland Security) CONFIDENTIAL 11 Complex Event Processing Use Cases Telecommunications & Services Customer Centric Utilities • Manage your data before it reaches the databases • Protect your core business processes from the “data tsunami” Financial Services Homeland Security Security and Detection CONFIDENTIAL Low Latency Processing Best Practices: Pre-Deployment Planning Pre-deployment Analytics ensure accurate Scenario Planning, turning terabits of Meaningful Metadata into useful tools • • • • Distributed real-time analysis Actionable business intelligence Network optimized data-flows Organic analytic processes CONFIDENTIAL • • • • • Economic Modeling Business Modeling Measurable outputs Scalability Validation Rate Case Rationalization Smart Grid Data Management Tips • Look at the entire SmartGrid data, not just AMI. • Recognize smart grid data volume and classes. • Link business process transformation and SmartGrid designs. • Look to other tools like “CEP” to handle new classes of data. CONFIDENTIAL 14 Item to be Aware of: • Don’t underestimate the data associated with AMI and SmartGrid Producers • Data ownership. • Data usage is becoming more critical. • Data accuracy and quality increases as automation increases. • Asynchronous Data is increasing. • Data Volume – More is not always better (be aware of latency vs volume). – – – CONFIDENTIAL Protect your business logic • What filtering, correlation, aggregation can be done up front? • What events are critical, can be ignored, or can be processed later? Map your architecture to scale • Ensure high availability • Understand the impact of maximum throughput • Monitor and measure system performance Prototype and tune • Simulation, record-playback, what-if scenarios 15 DATA, DATA, DATA!!! “Any intelligent fool can make things bigger and more complex... It takes a touch of genius - and a lot of courage to move in the opposite direction”. Albert Einstein CONFIDENTIAL 16 Questions 17 CONFIDENTIAL