ELECTRIC ENERGY | Spring 2020 - 26

THE SHIFTING UTILITY PARADIGM
With the maturing of smart meters, the concentration of computing power and the explosion
of IoT, advanced processing and memory have
become much more cost-effective to deploy
in meters, enabling real time data access along
with the processing power to run local analytics
in the meter itself.
The smart meter of yesterday in traditional
advanced metering infrastructure (AMI) applications has evolved into a truly intelligent device
empowering real-time network monitoring and
control, along with a powerful and flexible user
engagement "engine" to drive higher value to
both the utility and its customers.
The emergence of distributed intelligence-
that is shifting intelligence from solely in the back
office to include the edge of the grid-is driving more intelligence in real-time to be able to
better predict and manage energy needs across
the entire network, while providing an unprecedented level of intelligence for consumers in
the use, monitoring and management of energy.
The shifting dynamics of the market-through
which solar technologies enable consumers to
generate their power, and regulatory initiatives
are beginning to allow distributed generators
to sell power directly to consumers across the
distribution grid-puts the traditional utility
business model in jeopardy. In its place, utilities
will have to build their offerings on their value.
That will take a massive change in mindsets, but
the upside is that utilities will find ways to offer
consumers more value.
Utilities face other risks. They are saddled with
regulatory edicts to maintain distribution infrastructure, but without the necessary funding
26  ELECTRIC ENERGY | SPRING 2020

to do so. What's more, the emerging transactive energy marketplace at the grid's edge will
involve many financial transactions that will fall
outside of the utilities' traditional business and
financial processes.
If utilities are to survive and thrive amid these
disruptive and competitive challenges, they
will need to turn these challenges into business opportunities and leverage their "energy
incumbency" and relationships with customers to
become (or remain) the key player in an increasingly distributed and transactive grid.
But today's edge intelligence-enabled meters,
sensors and other devices on the distribution
network can communicate and manage these
transactions and power flows in real-time, keeping utilities relevant and in control of their distribution systems and the financial transactions
that ensue.
And so, the pressure is on. As the incumbents,
utilities will be the logical choice to perform these
functions, but only if they can provide the services
when required. If they're not ready, other traditional technology vendors such as Google will
happily step up and fulfill that role. The bright spot
is that edge processing at the meter, combined
with the business agility it provides to manage
all these transactions, is the utilities' best defense
against that outcome.
Distributed intelligence is beyond smart-it
is active-pushing the analysis to the edge, on
the meter itself, allowing for a truly intelligent
platform to enable:
■	 Edge computing: Every device is a computing
and application platform
■	High-resolution data that delivers near real-time
decision-making and post-processing analytics

■	 Improved

safety and autonomous control at
every meter
■	 Coordinated, autonomous action between
meters
Each meter is an advanced computer and
application platform providing local access to
high-resolution data to:
■	 Drive peer-to-peer communications between
meters and devices
■	 Empower an open and vibrant ecosystem of
solution providers
■	 Drive real-time communications into the consumer premise for safety, and to deliver usage
insights at an extremely granular level

MAKING THE BUSINESS CASE FOR
DISTRIBUTED INTELLIGENCE
Making a strong business case for an innovative technology often requires providing a range
of real-life use cases, and that is nowhere truer
than on the distributed grid. Here are examples:
Location Awareness: A location awareness
Distributed Intelligence (DI) app provides the
electrical location of every meter on the distribution grid, including transformer, phase and
feeder. This information can be used to update
and validate GIS connectivity, improve outage
response, feeder phase balancing and multiple
other grid applications.
Transformer Load Management: A DI app for
transformer load management provides protection and extended life of distribution transformers
by continuously monitoring the total load on the
distribution transformer in both directions and
actively controlling consumer loads and distributed generation to maintain loads within safe
operating limits.



ELECTRIC ENERGY | Spring 2020

Table of Contents for the Digital Edition of ELECTRIC ENERGY | Spring 2020

Letter from the 2019-2020 RMEL President
Letter from the Executive Director
RMEL Board of Directors
The Future of Customer Experience in the Energy Industry
Customer Experience and Target Segmentation for Utility Solutions
Data as a Tool for Utility Customers
Intelligence at the Edge: Addressing the New Challenges and New Opportunities of the Modern Grid
Tucson Electric Power Increases Customer Convenience with Personalized Tools
RMEL’s 117th Fall Executive Leadership and Management Convention is Heading to Denver
2020 Calendar of Events
Member Listings
Foundation Board of Directors List
Advertisers’ Index
ELECTRIC ENERGY | Spring 2020 - Intro
ELECTRIC ENERGY | Spring 2020 - bellyband1
ELECTRIC ENERGY | Spring 2020 - bellyband2
ELECTRIC ENERGY | Spring 2020 - cover1
ELECTRIC ENERGY | Spring 2020 - cover2
ELECTRIC ENERGY | Spring 2020 - 3
ELECTRIC ENERGY | Spring 2020 - 4
ELECTRIC ENERGY | Spring 2020 - 5
ELECTRIC ENERGY | Spring 2020 - Letter from the 2019-2020 RMEL President
ELECTRIC ENERGY | Spring 2020 - 7
ELECTRIC ENERGY | Spring 2020 - Letter from the Executive Director
ELECTRIC ENERGY | Spring 2020 - 9
ELECTRIC ENERGY | Spring 2020 - RMEL Board of Directors
ELECTRIC ENERGY | Spring 2020 - 11
ELECTRIC ENERGY | Spring 2020 - The Future of Customer Experience in the Energy Industry
ELECTRIC ENERGY | Spring 2020 - 13
ELECTRIC ENERGY | Spring 2020 - 14
ELECTRIC ENERGY | Spring 2020 - 15
ELECTRIC ENERGY | Spring 2020 - Customer Experience and Target Segmentation for Utility Solutions
ELECTRIC ENERGY | Spring 2020 - 17
ELECTRIC ENERGY | Spring 2020 - 18
ELECTRIC ENERGY | Spring 2020 - 19
ELECTRIC ENERGY | Spring 2020 - Data as a Tool for Utility Customers
ELECTRIC ENERGY | Spring 2020 - 21
ELECTRIC ENERGY | Spring 2020 - 22
ELECTRIC ENERGY | Spring 2020 - 23
ELECTRIC ENERGY | Spring 2020 - Intelligence at the Edge: Addressing the New Challenges and New Opportunities of the Modern Grid
ELECTRIC ENERGY | Spring 2020 - 25
ELECTRIC ENERGY | Spring 2020 - 26
ELECTRIC ENERGY | Spring 2020 - 27
ELECTRIC ENERGY | Spring 2020 - Tucson Electric Power Increases Customer Convenience with Personalized Tools
ELECTRIC ENERGY | Spring 2020 - 29
ELECTRIC ENERGY | Spring 2020 - 30
ELECTRIC ENERGY | Spring 2020 - 31
ELECTRIC ENERGY | Spring 2020 - RMEL’s 117th Fall Executive Leadership and Management Convention is Heading to Denver
ELECTRIC ENERGY | Spring 2020 - 33
ELECTRIC ENERGY | Spring 2020 - 34
ELECTRIC ENERGY | Spring 2020 - 2020 Calendar of Events
ELECTRIC ENERGY | Spring 2020 - Member Listings
ELECTRIC ENERGY | Spring 2020 - 37
ELECTRIC ENERGY | Spring 2020 - Advertisers’ Index
ELECTRIC ENERGY | Spring 2020 - cover3
ELECTRIC ENERGY | Spring 2020 - cover4
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