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OpenWorld 2016 Utility Analytics Roadmap Session CON7213
Creighton Oyler, VP Strategic Growth Markets Bill Devereaux, VP Industry Strategy Taj Ait-Laoussine, Sr Director Utility Data Analytics Julia Lundin, Sr Manager Product Marketing September 2016
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Safe Harbor Statement
The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.
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Enhancing the Customer Experience Julia Lundin
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Program Agenda
The need for Utility Analytics
Enhancing the Customer Experience
Improving Operational Efficiency
Analytics Roadmap and Getting Started
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The need for Utility Analytics Economic Necessity
Bill Devereaux
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Steeply rising costs and moderating electricity consumption are forcing Utilities to transform how they operate
Deloitte’s “The Math Does Not Lie”
• Generation, Transmission, Distribution additions
• Environmental regulation compliance
• Renewable portfolio standards and safety regulations
• Cost of capital / Interest rates
Apportioned Capital Costs
• Cost of fuel
• Incremental operating costs of environmental compliance retrofits
• New operating technologies
Operating Costs
• Moderate new sources of demand
• Changes in the economy
• Technological advances in energy efficiency
• Customer behavior and attitudes
kWhr Consumption
Increased Costs
Decreased kWh Consumed
Source: ‘The Math Does Not Lie: Factoring the Future of the US Electric Power Industry’ – Deloitte Energy & Resources Dbriefs, Jan 2013
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The utilities industry can pull key levers to affect the Math, each with varying levels of complexity and value. Utility Analytics can support these levers and potentially deliver additional upside
Analytics can directly support business performance
Value Levers
Cost per kWh sold ($/kWh)
Streamline operations, reduce and restructure controllable costs
Consider M&A or divestitures to achieve synergies or reconsider business structures
Change the regulatory paradigm (e.g. changing renewable portfolio standards, etc.)
Capture, Retain Customers
Evaluate opportunities for new products and services
Goal
Decrease Costs
Increase No. of kWh Consumed
Change the Business Model
Advanced
Analytics
Advanced
Analytics
Advanced
Analytics
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Analytics to Reduce Operation Costs Taj Ait-Laoussine
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The Impact of Electric Vehicle Charging on Infrastructure
The addition of one electric vehicle resulted in a 71% increase in Transformer Loading.
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This Electric Vehicle Started Charging in October 2014
Average Daily Usage 2013: 74 kWh
2014: 127 kWh
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Identifying and Distinguishing EV from Other End Uses
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Further Characterizing Electric Vehicle Charging Patterns
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All EV Meters
Peak Chargers
10pm – 4am
Off-Peak Chargers
4pm – 10pm
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kWh
Usa
ge D
uri
ng
Pe
ak (
4p
m-1
0p
m)
kWh Usage at Night (10pm-4am)
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The majority of usage from EV charging occurs disproportionately during peak hours, increasing strain
The Implications of EV Charging on Distribution Operations
Non-EV Meters (Random Sample)
EV Meters
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Opower Peak Day Alerts + DataRaker Analytics highly targeted DR big peak savings
Opower notifications for Demand Response
• Opower Peak Day Alerts uses timely, personalized notifications that leverage AMI data and behavioral science to motivate customers to reduce peak demand by 3%
• This is without a price signal or device and without DataRaker integration
• By combining this with DataRaker, we can do highly targeted DR for even greater peak demand reduction
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Enhancing the Customer Experience Julia Lundin
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Customer Activity Score is High
Motivation
Investment Likelihood
Propensity to Participate
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The Future of Integrated Analytics
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Technology integration
– On prem to cloud data unification (integration web services)
– Cross system translation mechanisms (standardized data exchange format)
– Multi service data preparation (generic ETL, data quality analytics)
Business process integration
– Closed loop meter to field and meter to customer meter and billing operations
– From meter to distribution comprehensive revenue protection
– Customer demand response impacted distribution operations
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Cross functional unification
– Enabled IoT ecosystems
– Sensor based data integration
– Comprehensive customer engagement
Analytics Investment Themes
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