IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 11, NO. 1,FEBRUARY 2015 187
Convergence of Smart Grid ICT Architectures
for the Last Mile
Michele Albano, Luis Lino Ferreira, and Luís Miguel Pinho, Member, IEEE
Abstract—The evolution of the electrical grid into a smart grid,
allowing user production, storage, and exchange of energy; remote
control of appliances; and, in general, optimizations over how
the energy is managed and consumed, is an evolution into a
complex information and communication technology (ICT) sys-
tem. With the goal of promoting an integrated and interoperable
smart grid, a number of organizations all over the world started
uncoordinated standardization activities, which caused the emer-
gence of a large number of incompatible architectures and stan-
dards. There are now new standardization activities that have
the goal of organizing existing standards and produce best prac-
tices to choose the right approach(es) to be employed in specific
smart grid designs. This paper follows the lead of the National
Institute of Standards and Technology (NIST) and the European
Telecommunications Standards Institute/European Committee
for Standardization/European Committee for Electrotechnical
Standardization (ETSI/CEN/CENELEC) approaches in trying to
provide taxonomy of existing solutions; our contribution reviews
and relates current ICT state of the art with the objective of
forecasting future trends based on the orientation of current
efforts and on relationships between them. The resulting taxon-
omy provides guidelines for further studies of the architectures,
and highlights how the standards in the last mile of the smart grid
are converging to common solutions to improve ICT infrastructure
interoperability.
Index Terms—Common information model (CIM), energy
saving, International Electrotechnical Commission (IEC),
protocols, survey.
I. I NTRODUCTION
T
HE ENERGY grid has evolved from a pipeline that brings
electricity from the production plant (production domain)
to the final user (consumption domain) through the transmis-
sion and distribution domains, to a much more complex system.
In this novel paradigm, multiple actors of these four domains
can interact, produce energy, as well as store it and exchange
it with other (peer) actors, in order to enhance the grid’s effi-
ciency. The concept of the “smart grid” has emerged, in which
Manuscript received January 28, 2014; revised May 15, 2014 and
September 17, 2014; accepted November 16, 2014. Date of publication
December 08, 2014; date of current version February 02, 2015. This work was
supported in part by the National Funds through FCT (Portuguese Foundation
for Science and Technology); in part by the European Union (EU) Advanced
Research & Technology for EMbedded Intelligence and Systems (ARTEMIS)
Joint Undertaking (JU) funding, within the Embedded iNtelligent COntrols
for bUildings with Renewable generAtion and storaGE (ENCOURAGE)
project, Ref. ARTEMIS/0002/2010; in part by JU under Grant 269354, within
Arrowhead project, Ref. ARTEMIS/001/2012; and in part by JU under Grant
332987. Paper no. TII-14-0112.
The authors are with the Research Centre in Real-Time and Embedded
Computing Systems (CISTER), Instituto Superior de Engenharia do
Porto/Instituto Politécnico do Porto (ISEP/IPP), Porto 4200-072, Portugal.
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TII.2014.2379436
the interaction between the involved actors is articulated into
an energy plane and a data plane. The new data plane relates to
the information that is used to drive the efficient allocation of
energy, to different actors as well as to different storage units
and energy-consuming appliances.
Smart grids are nowadays a very complex interplaying of
different systems at different levels. Existing smart grid sys-
tems and standards explore a large problem space to attain the
same goal of energy efficiency, and they end up featuring many
common points and many differences as well. There are numer-
ous challenges to address, such as the low-level communication
technologies to be employed [1], or the issues arising when
integrating distributed energy resources (DERs) [2] or electrical
vehicles [3] in the grid. In this paper, the focus is on the interac-
tion of final domestic and commercial users with the smart grid
information and communication technology (ICT) system, and
on involved systems and standards.
A common characteristic of smart grids is that the embed-
ded devices deployed into the final user’s home (the sensors
and actuators that manage energy and data planes) are too lim-
ited in computational power to be able to decode a complex
protocol; therefore the topology of the smart grid is usually
centered around a gateway installed in the users’ houses. The
gateway manages a subset of the sensors and actuators deployed
in the house using adequate protocols, and it is connected to the
internet to interact with services for energy management via a
data plane. The in-house topology usually carries the name of
home area network (HAN); in the rest of this work, the gate-
way installed in the user’s HAN will be called HAN gateway.
Another common characteristic of a typical smart grid sys-
tem is its size and complexity. In fact, an energy grid usually
serves a very large number of users. Together with the fact that
each actor is controlled by an independent entity, the emerg-
ing complexity is overwhelming for traditional centralized data
management paradigms.
Differences between smart grid approaches usually regard
the employed protocols and the management paradigm for the
data. To offer an estimate of the complexity of the ICT sys-
tem serving a heterogeneous smart grid, the number of involved
protocols can be considered. Potentially, a different protocol
can be used for each class of connections in the system, thus
between each pair of classes of actors; in this sense, the num-
ber of involved protocols in a system with n classes of actors
may grow as the number of lines between n points, i.e., (
n
2
),
which grows as fast as n
2
. While standardization processes
can decrease the complexity of the data plane, too many stan-
dards and architectures have been proposed in the past. In
the last few years, novel standardization efforts addressed the
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