MDM and Analytics: Solutions for Utilities in the Age of IoT

MDM and Analytics

Solutions for Utilities in the Age of IoT

Sylvia SmithVP, Customer Services

Phil DuncanSenior Consultant

Welcome and Introductions

• Sylvia Smith• VP, Customer Service

• 28 years in the electric industry

• Phil Duncan• Senior Consultant

• 30+ years professional experience in mission critical systems

Workshop Objectives

• Understand current MDM and Analytics offerings in the utility market

• Learn how those systems support utility company needs and requirements in the age of IoT

• Understand lessons learned and best practices for implementing

Numbers to Ponder

• Use of IoT for key utility areas (in production or underway)1

5

_______________1 SAS THE AUTONOMOUS GRID: Machine Learning and IoT for Utilities

OUTAGE CUSTOMERMDM CYBERSECURITY MWM MANAGEMENT ENGAGEMENT

55% 49% 46% 43% 43%

Numbers to Ponder

• Top 3 Concerns for IoT1

- Network Security

- Data Privacy

- Delivering Expected Business Value

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_______________1 SAS THE AUTONOMOUS GRID: Machine Learning and IoT for Utilities

Numbers to Ponder

• Top 5 IoT benefits:

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_______________1 SAS THE AUTONOMOUS GRID: Machine Learning and IoT for Utilities

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Bettercustomer service

Energyefficient

Improved data drivendecision making

IncreasedDER integration

Better customerchoice/engagement

37%

33%

28%

25%

24%

Numbers to Ponder

• From SAS/Zpryme report April 20161 –

• where they connected with 200 North American utilities – Per Gartner:

- Worldwide 6.4 billion connected

devices in 2016 – up 30% from 2015

- In 2016 alone, 5.5 million added each day

- Will reach 20.8 billion by 2020

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_______________1 SAS THE AUTONOMOUS GRID: Machine Learning and IoT for Utilities

The Need for MDM

• With smart meters, data volumesoverwhelm any non-MDM storage approach.

• MDM creates a system of recordfor meter data and alerts and alarms.

• MDM is a consistent approach to VEE and estimation, positively affecting the billing process.

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The Need for MDM

• MDM provides a central data point for integration to other systems like work management, GIS, outage, rate making, and marketing.

• MDM puts an infrastructure in place to add IoT data from other system devices on the network.

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Industry Trends

• Move from last generation of Business Intelligence (BI) approaches

• Utilities seek to be more proactive in decision making

• Adjusting business strategies using predictive views of the future

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Industry Trends

• Utilities seeking ROI for the smart metering investments

• Improve asset management

• Better grid operations management to reduce outage times and customer dissatisfaction

• Smooth integration of renewables and EVs

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Regulatory Trends

• Improving regulatory frameworks to align risks and rewards of deploying smart grid technologies

• Switching from a pure financial business case assessment toward measures reflecting society’s needs

• Applying economic incentives and penalties that foster application of the newer technologies

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Customer Trends

• Many want to be an active participant in their energy and water usage

• Want better and current information to understand their usage and ideas on how to reduce and manage

• Responsive to price signals for modifying usage behavior

• Need help to make better buying decisions on smart appliances and equipment

• Expect new technologies in order to engage with their utilities

• Next generation customer portals

• Device agnostic - Computer, tablet, phone access

• Real-time two way communications

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MDM and Analytics for NES

• How NES decided on the MDM and Analytics solutions that best fit their IT strategy and roadmap:

• TVA Pilot Smart Grid Project

• Best of Breed vs Holistic Approach

• Scalability and future-proof

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MDM and Analytics for NES

• Business Objectives:• Demand Response

• Streamline billing data (VEE)

• Consolidated Meter Data Analytics - (Theft of Service, Engineering Data, Outage

Management, etc.)

• Rate design

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MDM and Analytics for NES

• Selection Process• TVA Pilot Project (30,000 meters)

• Second RFP after data growth

• Technology Transformation Roadmap

• Decision Criteria and Selection• Best of Breed versus Holistic approach

• Partnership of software

• Seamless integration and process

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MDM and Analytics for NES

• Demonstration Scripts• NES created customized demonstration scripts

to highlight system functionality and integration. Vendors were asked to exercise their system against the demonstration scripts.

• Site Visits• The core team visited 4 sites (2 from each

vendor) to sit with and discuss the product with current end users and management.

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MDM and Analytics for NES

• Reference Checks• The core team created a customized mix of

questions and discussed with 4 references (2 per vendor). Each question was scored to arrive at a reference check score. Individual scores were averaged for a final scoring.

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Lessons Learned and Best Practices

• Use all data sources to realize value from the smart metering/grid infrastructure.

• Plan for the whole of the smart grid data in determining the best path for technology investment.

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Lessons Learned and Best Practices

• Use new tools like complex event processing to handle data volumes and classes.

• Use edge analytics to allow decision making closer to the event which helps with scale and latency.

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Utility Benefits

• Benefits to NES• Accurate system information

• Improved system reliability and power quality

• Dynamically manage system load

• Rate information

• Analytics

• Benefits to the Customer• Meter readings, turn-ons and disconnects done

remotely

• More accurate billing and usage information

• Better for the environment

• Improved responsiveness to an outage

• Future web presentment and prepay

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Q&A

Thank You!

For Additional Information:

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Sylvia SmithVP, Customer Services

Snsmith@NESPOWER.COM

Phil DuncanSenior Consultant

pduncan@teamAAC.com