Case study: Real Time Decision Making with Smart Data Analytics. Thomas Doggett Co-founder & Chief Marketing Officer Calico Energy

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1 Case study: Real Time Decision Making with Smart Data Analytics Thomas Doggett Co-founder & Chief Marketing Officer Calico Energy

2 Real-Time Decision Making with Smart Data & Analytics

3 About Calico

4 Data: Lifeblood of Utilities Demand Side Mgt. Planning Financial & Back Office Executive Customer Service Operations Marketing

5 The Importance of Real-Time Decisionmaking What could the impact be if you had near realtime analytics? Cost reduction Real-time, targeted load control Pay for performance Avoidance of outages Customer service

6 Siloed Systems Barrier Direct Load Control Direct Load Control #2 Where is the demand? How much demand can you shift? Thermostat C&I EV Pilot Legacy Billing CIMS MDMS CRS EE CDW DR

7 Case Study: System-Wide Integration Challenges: Enabling a complex AMI residential program with Demand Response, Price Response, and Advanced Rate Structures Reducing peak demand and increasing customer awareness Establishing a single point of view to energy data and system control across different vendor solutions Meter Data Pricing Data PTR Data (via SFTP/HTTPS) Device Management Device Provisioning Pricing Data PR/DR Signals Cost Data/Rate Mgt. Usage Data Messaging (via HTTPS/Zigbee) Solution: EIS OpCenter Energy Data Management Platform Solution Components: Utility Legacy Billing Systems Utility Legacy IT Systems Utility EIS OpCenter Command and Control Software Calico EIS Central Energy Data Warehouse Calico EIS Web Services OPower Web Portal Open Peak IHD MV&A System Silver Spring Head-End Tendril IHD Utility Legacy Billing & IT Systems Pricing Data PR/DR Signals PTR Data Messaging (via HTTPS/Zigbee) Pricing Data PR/DR Signals PTR Data Messaging (via HTTPS) Pricing Data PR/DR Signal Data Peak Time Rebate Data Device Provision (+) Device Provision ( ) (via SFTP) AMI Head End Pricing Data PR/DR Signals Cost Data Usage Data Messaging Benefits Integrated, single-point access to energy data from each solution component (above) Ability to push energy data, pricing signals, usage, DR signals, messaging, etc. to all systems Collection of energy usage data for more than 130,000 residents Demand Reduction Improved customer communications IHD Web Portal M&V Analytics IHD

8 and the Difficulties are Expanding! Distributed & Renewable Energy Data Explosion of New Technologies & Devices Proprietary, Third-Party & Legacy Systems Data Market Data & Dynamic Pricing? Emerging Standards Operational Data AMI Data Regulatory & Compliance Requirements

9 Case Study: Lots of Data, no Analytics Executive Enable powerful dashboard reporting for Executive team Enable Company-wide visibility into operational/financial health in real-time Improve Management s ability to make informed decisions Improve the consistency of data and ensure reliable reporting Financial Support revenue requirements; more effectively identify and capture unbilled revenue Demonstrate compliance with regulations and requirements Optimize the balance between Operational and Capital expenditures Improve the accuracy of financial data and other critical company information Monitor and minimize financial losses Define the cost/benefit of new hardware Operational Manage distribution infrastructure loads, reducing repair and replacement costs Manage the flow of renewable sources throughout our distribution network Analyze the cause of outages & make recommendations for repair/replacement Optimize and reduce field crew deployment Identify where to deploy Smart Grid technologies to maximize value Monitor and minimize line losses Better manage assets in the field Determine voltage, power quality, transformer loads Improve data management while reducing the overhead required to manage it

10 Case Study: Centralized DR OpCenter Head-End DRMS >75 Utilities in province OpCenter Distributor DRMS BusinessSMART C&I Energy Management Portal 4.5 Million customers HomeSMART Residential Energy Management Portal

11 Unified Operations Center

12 Dashboard Visibility

13 Forecasting

14 Benefits of Smart Data & Analytics Discover. Model programs, management strategies, and reports in minutes. Identify & justify new ways to capture load, reduce costs, and increase revenues. Detect theft. Assess. Determine what contribution DSM and EE programs can have to the situation based on a variety of variables. Establish quantifiable metrics for business & rate cases. Strategize. Better plan, target, define & validate energy management programs. Simplify. Reduce complexity. Correlate dispersed information to expose risk, loss, capacity, and inefficiency. Automate and support time-consuming decisions & analysis. Optimize. Create optimized asset, pricing, demand, power purchase, and usage reduction strategies based on insight gained from analytics. Target specific customer segments for programs based on multiple attributes. Achieve. Realize operational efficiencies, optimized field staffing, reduced costs, and improved business value.

15 Criteria for Technology Selection Interoperability the solution must be able to integrate easily with existing energy data systems, devices, and applications. It should be open architecture and support current industry standards. Flexibility the solution should utilize a SOA and work with all required data, devices, engines, and applications to reduce risk and provide long-term options. Intelligence just having access to more data isn t helpful. The right system must be able to mine, analyze, and distill information in a way that enables you to manage energy and reduce costs. Track record if it hasn t been deployed beyond pilot stage, it isn t proven. Adaptability the solution should provide value for all stakeholders (as well as customers!); DSM programs should be expandable and adaptable for future needs and requirements. Adoptability the solution must be simple to use, effective, and provide a clear value for utilities and their customers. Automation the solution must be able to automate energy management for customers. Changing behavior is too expensive, unreliable, and time consuming.

16 Tom Doggett QUESTIONS?

17 Weather Grid Legacy Home & Business Portals Utility Control SCADA Unified Analytics & Control Third-Party Portals Pricing Gateways Customer Data EVCS Meter Distribution LLCs PCTs

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