THE ENERGY INDUSTRY TIMES - MAY-JUNE 2020
13
Industry Perspective
T
he decarbonisation, decentrali-
sation and digitalisation of the
energy mix has already rede-
ned the way in which we produce,
consume and distribute power and
yet the energy transition is only just
beginning.
However, the transition is quickly
reaching a critical mass. The Interna-
tional Renewable Energy Associa-
tion recently announced that nearly
three quarters of global investment
in power generation was in renew-
able sources. And closer to home, for
the rst time ever in Q1 2020, re-
newable power was the UK’s prima-
ry source of energy thanks to the
wind revolution and deployment of
more solar power.
What’s more, with the mass de-
ployment of electric vehicles loom-
ing on the horizon and exponential-
ly increasing demand, usage
patterns are destined to change even
further. This intermittency and vari-
able demand bring a string of well-
documented challenges, including
the growing need for highly exi-
ble, data-driven grids.
Now more than ever utilities need
secure, exible and scalable solu-
tions with a high degree of automa-
tion and intelligence all the way
down to the grid edge. Smart meters
acting as grid edge sensors have al-
ready proven themselves capable of
both, sending real-time data back to
system operators and enabling great-
er customer engagement. As grid
edge intelligence is becoming a key
enabler of the low-carbon transition,
meters will be critical components of
the future electricity system.
Distribution system operators, or
DSOs, were some of the rst movers
in deploying grid edge technologies.
Scalable ‘Internet of Things’ connec-
tivity platforms enable monitoring
and control at the grid edge and are
designed to help utilities leverage in-
telligence at the community level
and across the distribution system, to
increase overall system efciency.
An example of how grid edge intelli-
gence helps DSOs optimise their
grid operations is the implementa-
tion of grid analytics that combine
information from smart metering
systems and other data sources.
These data sources can include the
geo-information system and utilities’
investment tools. Such applications
enable more accuracy in grid plan-
ning, better transparency in grid op-
eration and more focused invest-
ments in the low voltage distribution
network.
Having made the rst experiences
with grid edge technologies, DSOs
are now starting to implement even
more intelligence at the edge. New
intelligent end-points can process
measured data themselves and pro-
duce alarms when for example pow-
er quality standards are violated.
Such information is invaluable to
DSOs in a system where measures
of stability such as inertia, which
were once guaranteed, are now in-
creasingly unpredictable.
Another challenge for DSOs is the
impact of households installing
small scale renewable generators on
local voltage levels in the low volt-
age grid. For example, a newly in-
stalled PV system can increase the
voltage levels dramatically when
producing at 100 per cent during low
load periods, like on a Sunday morn-
ing. In such instances the smart me-
ter at that connection point needs to
be used to eliminate possible voltage
violations, sending a command to
the solar panel’s inverter when volt-
age measurements indicate a risky
situation, instructing it to compen-
sate with reactive power and, if nec-
essary, decrease active production.
By accessing data from neigh-
bouring meters, DSOs can now also
easily check whether a service qual-
ity problem agged by a local alarm
is on the grid side or on the custom-
er side. With this capability, they
can take the necessary action to
guarantee grid stability, mitigating
unnecessary conicts with industri-
al customers.
Households’ active participation in
the energy system is not conned to
behind-the-meter generation like
rooftop solar. Consumer access de-
vices are already in peoples’ homes
in the form of connected fridges,
washing machines and products like
smart thermostats. The consumption
of such products can be identied by
applications implemented in smart
meters like Sense Intelligence and
increase consumers’ awareness about
which appliances, equipment and
furniture in the home are driving the
demand and enable them to monitor
and optimise it.
This data can then be reviewed and
analysed by suppliers, enabling the
customer to take a deeper look into
whether they are using energy during
peak times and then make an in-
formed decision about the best time
to schedule high-consumption tasks,
like loads of laundry or running the
dishwasher.
Seeing and showing where energy
is being used in the home can create
opportunities to reduce consumption.
The forecast popularity of time-of-
use tariffs will capitalise on the data
provided by these grid edge technol-
ogies, shifting load in line with the
peaks and troughs of renewable gen-
eration and network demand.
The UK already sees load-shifting
at a formative level with Economy
7 contracts and now some suppliers
have introduced dynamic pricing
schemes. Tariffs such as these will
become increasingly important as
the power transformation under way
in the transport sector comes to
fruition.
The incremental load an electric
vehicle places on the distribution
system is roughly equal to that of a
new home, therefore much more
data and information will be required
to ensure that the distribution grid is
able to handle the demand, which is
destined to increase dramatically.
Central to this is the need for smart
charging to balance the intermittency
of what will increasingly be a renew-
ables-led generation system, a senti-
ment which was echoed in the EV
smart charging consultation that the
UK’s BEIS issued in July last year,
which commenced their programme
of work in earnest.
In the future EVs are likely to be
the largest load in domestic premis-
es, dominating households’ usage. In
the drive to increase domestic exi-
bility it will be logistically easier to
manage this single, large, output
than the multitude of smaller devices
– such as fridges, freezers, washing
machines and dishwashers – that
will otherwise have to be managed.
However, to deliver the scale of in-
frastructure necessary at a low cost
to the consumer whilst encouraging
individuals and businesses to switch
to electric vehicles, coordination be-
tween industry and government with
the right regulatory framework will
be essential.
Furthermore, the security of infra-
structure is critical. A growing con-
cern is the deployment of charge-
points, which lack a joined-up
communications and security frame-
work. Without this framework there
is a risk that sufcient ‘insecure’
smart chargers could be installed,
which will pose a signicant cyber
threat to the power grid.
The infrastructure deployed under
the smart meter roll-out, including
the communications networks and
industry frameworks, provides a
prime opportunity to efciently and
effectively support the widespread
deployment of electric vehicle
smart-charging infrastructure. Cru-
cially this network is secure, proven
and readily available – not just an
off-the-shelf solution, it’s a tailored
solution which now simply needs
scaling up.
This communications network un-
derpinning the roll out of smart me-
ters has been painstakingly devel-
oped in conjunction with the full
spectrum of stakeholders and as a re-
sult is as robust as it is practicable.
Having such a network readily avail-
able for smart charging of electric
vehicles represents the lowest cost
option for consumers, government
and industry alike by avoiding the
build-out of an equivalent nation-
wide solution.
Building on the smart meter net-
work for electric vehicle smart
charging would help governments to
deliver on their policy objectives to
accelerate the growth of the EV mar-
ket and, ultimately, deliver a net zero
economy.
With the right support and a robust
security framework from govern-
ment, industry can act with urgency
on deploying comprehensive, secure
infrastructure to support the growth
of electric vehicles.
Of the decarbonisation, decentrali-
sation and digitalisation mega-trends
at play in the UK power market, two
are already building momentum
thanks to the shovel-ready nature of
renewable power. But it is smart me-
tering’s foundational technology
which is only now being realised
through the grid edge technologies
that will have a materially benecial
impact on both consumers’ lives and
on the environment. Smart metering
has provided the data and the secure
infrastructure necessary for the full
digitalisation of the energy system,
enabling decarbonisation and decen-
tralisation of power.
The grid also needs to be able to
cope with the scaling up of power
loads, which will include the com-
munications, digital and governance
infrastructure needed to enable the
widespread deployment of electric
vehicles and smart chargers. Utilis-
ing the data from intelligent end-
points at the grid edge, such as smart
meters, sensors and connected IoT
devices, helps to develop new, data-
driven use cases. It also offers in-
creased transparency and control to
the distribution grid, new consumer
services, and opens up new business
models for operational efciency.
Getting the governance right to ef-
fectively manage this infrastructure
and the data it will yield is essential.
As with smart metering, the infra-
structure will be best delivered with
direction from government taking an
active role. Building on the smart
metering model for EVs and other
grid edge technologies will bring our
low-carbon future closer, faster.
As utilities and third parties learn
to capitalise upon these foundational
technologies and navigate emergent
frameworks, the full benets of
smart metering will be realised.
Nick Merricks is Head of UK Smart
Electricity Meter Products at
Landis+Gyr.
Having made the rst experiences with grid edge technologies, DSOs are now starting to implement even more
intelligence at the edge. Nick Merricks
Grid edge tech: the energy
transition’s latest frontier
Merricks: As grid edge
intelligence is becoming a
key enabler of the low-carbon
transition, smart meters will
be critical components of the
future electricity system