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Itron and Teradata: Active Smart Grid Analytics
 

Itron and Teradata: Active Smart Grid Analytics

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Centralized data warehousing can optimize how the smart grid world addresses business needs and captures business opportunities.

Centralized data warehousing can optimize how the smart grid world addresses business needs and captures business opportunities.

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Itron and Teradata: Active Smart Grid Analytics Itron and Teradata: Active Smart Grid Analytics Presentation Transcript

  • Itron and Teradata: Active Smart Grid Analytics TM Stephen Butler Managing Partner Industry Consulting Sharelynn Moore Director Product Marketing
  • Topics for Discussion
    • Smart Grid business drivers
    • AMI and MDM as enabling technology
    • Active Smart Grid Analytics (ASA) Platform
      • A new approach for Smart Grid architecture
      • Business Opportunities
      • Use Cases
      • Case Studies
    • Teradata and Itron – A World Class Solution
  • Utilities are looking to meet these corporate goals
    • Move to a Smarter Grid
      • Support distribution automation devices
      • Support distributed generation
      • Manage new load conditions – plug-in hybrid electric vehicles
    • Enable Customers and offer new products/services
      • Give customers ability to control and manage costs
      • Provide more detailed energy information
      • Facilitate time-sensitive pricing
      • Improve reliability
    • Improve Operational Efficiency
      • Automate manual processes
      • Provide information to optimally manage resources
      • Extend useful life of assets
      • Reduce field trips and safety incidents
  • AMI and MDM as enabling technology
    • AMI and MDM are the first step toward broader Smart Grid initiatives
    • A robust AMI system facilitates the physical infrastructure to automate communications with every meter, and a mechanism to communicate within the home
    • A robust MDM enables the mission critical “Meter to Bill” process
      • Typically Phase 1 of every AMI deployment is to get meters billing in production
      • Operational system to manage and distribute raw and validated usage information
      • MDM can serve as a broker between numerous utility systems with multiple AMI technologies
      • Key enabler for Demand Response rate programs
    But what are the technologies that will take the utility beyond AMI and MDM integration, into ADO, ATO, and AAM?
  • Why a new solution architecture for Smart Grid?
    • Ever tighter “business-time” decisions will need to act on both “near real-time” and historical information, across domains.
    • Adoption will be incremental and have multiple entry-points.
    • Varying measurement & control systems (MCS) for AMI, ADO, ATO.
    • But tremendous value will come from harvesting knowledge aggregated from multiple MCS and business systems.
    • A “smart grid” uses that knowledge to help make decisions quicker.
  • Introducing a new concept: Active Smart Grid Analytics
    • Active – near-real time loading, analysis and action of data
    • Smart Grid – data from all functions and aspects of the utility’s infrastructure
    • Analytics – reporting, analysis and application of results for accurate decision-making
    Active Smart Grid Analytics will deliver the data intelligence value of the Smart Grid Active Smart Grid Analytics is the confluence of business needs and business improvement opportunities in one platform for the Smart Grid world
  • Proposed Solution Architecture
  • How do we get there?
    • Partner with Teradata
    • Look to other industries such as Retail, Telecommunications and Financial Services
    • Don’t start by building applications; build analytics and plug into workflows.
    • Develop a partner eco-system of analytic “application” ISVs or System Integrators.
    • Develop expertise in plugging into new business processes outside of meter-to-cash.
  • Best Practices Example: Large Retailer
    • Active Retail Analytics Environment is loaded every 6 minutes with data from Point-of-Sale systems, Vendors and Distribution Centers across the world
    • Has models running in real-time on the data to forecast and manage stock-outs, and sends alerts to the buyers with vendor recommendations for sourcing when a stock-out event is predicted
    • Runs complex analyses of purchase patterns to determine timing of product mix and distribution for everything from weather disasters to flu outbreaks.
    Utility parallel with Active Smart Grid Analytics
    • Active Smart Grid Analytics Environment is loaded every 5 minutes with AMI data and integrated with SCADA, CIS and Asset data
    • Has models running in real-time to identify demand response events in the usage forecast and sends alerts to participating customers in programs to alter usage (shut off pool pumps, water heaters, etc.) when outage is predicted
    • Runs complex analyses of utilization changes to determine program effectiveness for demand response, rate case analysis, and utilizations changes correlated with weather changes.
    How do we get there?
  • Role of ASA – Moving from this…
    • Disparate Analytical Systems
      • Proliferate ODS & data marts
      • More servers, licenses
      • More ETL jobs
      • More labor
      • Complexity
    • High Complexity and Cost
      • 2X-5X more databases, processing, files, labor?
      • Data Security?
      • Application development?
  • Active Smart Grid Analytics vs. Data Marts
    • Teradata
    • Centralized and leveraged
    • Mixed workload
    • Single database technology
    • Built for purpose appliance
    • Comprehensive model driven
    • Industry best practices
    • Incremental adoption by design
    • Infinite scalability
    • Open to several BI stacks
    • Re-usable solution blueprint
    • Data Mart Approach
    • Proliferation and distributed islands
    • Decision support
    • Multiple database technologies
    • General purpose computers
    • Local data models
    • Home grown
    • Incremental adoption by nature
    • Limited scalability
    • Bundled with BI stacks
    • Tactical architecture
  • Role of ASA – Provides integrated, cross-functional data
    • Complexity and proliferation will always exist but…
    • Active Smart Grid Analytics, an Enterprise Data Warehouse, allows:
      • Consolidated complexity
      • Lower TCO
      • Less strain on DBAs and CIO
      • Single set of facts, metrics, vocabulary
      • Deliver true Smart Grid business intelligence!
  • Itron and Teradata Combining World Class Companies for a World Class Solution
    • Can operational data systems such as MDM, SCADA and others can or should provide extensive cross-domain analytics and warehousing that Smart Grid business intelligence will require?
    • We believe the industry needs best in breed AMI, MDM and EDW working in concert to deliver the most robust Smart Grid platform.
    • Active Smart Grid Analytics will combine the AMI data domain with other Smart Grid, customer and financial data to solve business problems and comprehensively answer business questions.
    • Teradata has the expertise and architecture our industry needs, coupled with Itron’s industry expertise = ultimate combined solution.
  • Active Smart Grid Analytics
    • Smarter, Faster Decisions
    • Intelligence – Treat information as a strategic corporate asset – integrate data from across the enterprise for better decision making
    • Speed – Extending that intelligence to more decision-makers – front-line workers, partners, suppliers, and customers – to enable decision making at the right time and place
    Hundreds of Strategic Decisions Hundreds of Thousands of Operational Decisions Strategic Intelligence Operational Intelligence
  • Front Line “Operational” Users Back Office “Strategic” Users Enterprise Message/Service Bus Service Brokers Active Smart Grid Analytic EDW RDBMS Based Event Processing ASP / JSP Streaming Batch Internet / Intranet Decision Making Repositories Operational Repositories Data Acquisition Business Rules Event Notification Event Detection Field Force Operational Systems Active Smart Grid Analytics Business Process Automation Transactional Services Decision Making Services Call Center Finance Executive Supply Customers Marketing Market WMS CIS AAM MDM OMS ATO DA ADO AMI SCADA
  • Information Evolution: Disparate reporting systems and data marts
    • With each new data mart, the IT development efforts are repeated
    • This includes sourcing data that already exists in another environment
    Metering CIS 14 42 Business Value IT Development
    • Metering
    • What is the utilization for this customer during peak times?
    • How many reads had to be estimated?
    • CIS
    • How often does the customer pay their bill on time?
    • Does this customer make partial payments or pay their bill completely once a month?
    Each data mart can provide answers to questions that are subject-specific
  • Information Evolution: Data Warehouse Build on the Foundation!
    • Combining the environments requires only incremental work for each new subject area
    • Enables new cross-functional insights that can’t be achieved with separate data marts; differentiated new decisions
    Business Value IT Development
    • Combined Metering & CIS
    • How quickly do meter readings get billed and payment posted?
    • How do we easily track the lineage from meter set to reading to billing to collections?
    • Do we have the right kind of meter set up on the right kind of premise?
    • How does payment history correlate (lead or lag) utilization at a premise?
    Metering CIS 14 34 42
  • Information Evolution: Enterprise Data Warehouse and an Integrated View Of Your Business
    • Teradata customers find that as their warehouses grow, they add incrementally less data and less effort to enable new applications and new business value
      • Lowers the IT development line
    • The value-to-effort ratio increases significantly
    Metering CIS Operations Finance ??? ???? 34 ?? 14 42 Business Value IT Development ?? ?? ?? ???
  • Another Example – Major US Utility
    • More than $45 million in savings over 5 years
      • Integrated data made available to multiple organizations, reporting tools and automated analysis
      • 40-50% improvement in corporate collections
      • 25% improvement in residential collections
      • 46% reduction in direct marketing expense through targeted marketing
      • Annual productivity improvements of more than 16,000 person-hours from simplified reporting, automated analysis and information availability
      • More efficient turnaround on regulatory requests and audit findings
  • Information Evolution: Active Smart Grid Analytics Serves multiple data consumers who have questions
    • Customers wanting insight through self-service and analysis-driven customer communications
      • How can I go green?
      • How can I save money and lower my bill?
      • Where does my utility get the energy? Is it green?
    • Utilities wanting high-touch, high engagement with customers
      • How do we provide better communications and customer satisfaction to my customer base?
      • How do I interact with customers and which channel?
      • When and what should invest in new assets to affect the best customer experience?
    • Regulatory Agencies wanting insight into how their constituents are being served
      • How well are customers being served? Are the rates fair?
      • Are the utility operations meeting efficiency standards? Green?
      • How much energy is derived from alternative sources?
      • How many customers have deployed green programs?
  • New Smart Grid Business Intelligence Opportunities - Customer Participation
    • Who will be my most undependable customers for payment?
    • What conservation programs work best for what customers?
    • What customers are using which program, which are not, and would a new program suit these customers better?
    • As a customer, can I track how my usage profile compares to people in my region with a similar profile?
    • As a customer, can I track my usage on an ongoing basis, on the Web, on my iPhone/Blackberry, or on my gaming console?
    • As a customer, can I prepay for my energy?
    • As a customer, can you provide me options and tools to choose a usage and payment plan that suits me best?
  • New Smart Grid Business Intelligence Opportunities – Advanced Distribution Optimization
    • What correlations can I make from known momentary outages?
    • How long were my customers out of power?
    • When were my customers restored?
    • What are the impacts of these outages on my customers?
    • How can I more quickly communicate the status of outages and restorations to my customers?
    • What do the results of my voltage sensors tell me?
    • Do I have over loaded or under utilized transformers?
    • How well are my Distribution Automation devices running?
    • How much load is distributed generation providing?
  • New Smart Grid Business Intelligence Opportunities – Advanced Asset Management
    • What assets are under performing?
    • What is the cost over time of under performing assets?
    • Are my devices performing to the Service Level Agreements in my contract?
    • What is the financial impact of ill-performing smart assets?
    • Over time, what can I learn from trending the performance of my network health? Can I start learning how to prevent network reliability issues?
  • Some use cases that are integral to Active Smart Grid Analytics
    • “ Meter-to-Post” Management Solution
    • Bad Debt Management Analytics
    • Demand Response Analytics and Communications
    • Outage Management and Analytics
    • Downtime Reduction Analytics
    • PHEV load impacts
    • Customer Communications
    • Most Beneficial Rate Analysis
    • Fraud Detection and Analytics
    • Work Knowledge Management and Analytics
    • Safety Management and Analytics
    • Data Mart Consolidation
    • Rate Case Analytics
    • Real-time Energy Pricing Options
    • Wholesale Energy Purchase Price Optimization
    Pricing Operations CRM Smart Grid Finance
  • Backup slides Stephen Butler Managing Partner Industry Consulting Sharelynn Moore Director Product Marketing
  • The Alternative
  • Technical Blueprint
  • Typical Solution Architecture
  • ASA and MDM conceptual architecture
  • Best Practices Example #2: Large Wireless Carrier
    • Loads millions of call detail records from the network on an hourly basis with location and termination information
    • Integrates it with customer purchase, billing information and call center activity as part of the load process
    • All data is available to the customer service desktop within 10 minutes, enabling the call center representative to triage customer inquiries
      • Has the customer been experiencing dropped calls?
      • Did the customer just purchase a new phone?
      • How many times has the customer called customer service recently and why?