Infrastructure and applications of Internet of Things in smart grids: A survey

Abstract

The Internet of things (IoT) is a rapidly evolving technology capable of transforming numerous areas of our lives. Smart Grid (SG) is one of such areas, which has an immense potential of development, following the advances in IoT technology. The goal of the current survey is to summarize the infrastructure and applications of IoT in SGs. The infrastructure aspect is described from the viewpoints of physical and software implementation. A general configuration of IoT processing layers with a respect to SGs' infrastructure is introduced in this description. Applications of IoT in SGs are described for several structural and functional parts of SGs: Customer Interactions, Generation, Transmission, Distribution, Smart Metering, Grid Maintenance and Management. A summary of application advantages, such as real-time bidirectional data communication and advanced sensing, and implementation challenges, such as interoperability of various technological standards and rigorous privacy and security requirements, of IoT in SGs are presented in this survey.

Full text

Infrastructure and Applications of Internet of Things
in Smart Grids: A Survey
Ravil Bikmetov, M. Yasin Akhtar Raja, Tanmay U. Sane*
Physics and Optical Science, UNC Charlotte, USA
*Electrical and Computer Engineering, UNC Charlotte, USA
Email: rbikmeto@uncc.edu; raja@uncc.edu; sane.tanmay@gmail.com;
Abstract — The Internet of things (IoT) is a rapidly evolving
technology capable of transforming numerous areas of our lives.
Smart Grid (SG) is one of such areas, which has an immense
potential of development, following the advances in IoT
technology. The goal of the current survey is to summarize the
infrastructure and applications of IoT in SGs. The infrastructure
aspect is described from the viewpoints of physical and software
implementation. A general configuration of IoT processing layers
with a respect to SGs’ infrastructure is introduced in this
description. Applications of IoT in SGs are described for several
structural and functional parts of SGs: Customer Interactions,
Generation, Transmission, Distribution, Smart Metering, Grid
Maintenance and Management. A summary of application
advantages, such as real-time bidirectional data communication
and advanced sensing, and implementation challenges, such as
interoperability of various technological standards and rigorous
privacy and security requirements, of IoT in SGs are presented in
this survey.
Index Terms — Internet of things, smart grids, micro-grids,
Enernet, prosumers, net-metering.
I. INTRODUCTION
Demand of green, affordable, and manageable energy has
been ever-expanding since the onset of the 21st century. The
traditional grids are incapable to match such needs [1-3]. These
needs have led to quest and development of newer solutions
such as the smart grids (SGs), which were designed to fulfill the
growing demand of electrical energy by increasing the
efficiency of generation, transmission, and distribution [4-6].
As per the Title XIII of Energy Independence and Security Act
(EISA) of 2007, “Smart Grid is defined to include a variety of
operational and energy measures — containing smart meters,
smart appliances, renewable energy sources (RES), and energy
efficiency resources [3].”
In contrast to the traditional centralized grids, the two-way
communication aspect is a major change in decentralized SGs
(Fig. 1) [4, 5, 7-11]. Utilization of smart metering at the energy
users' site and data storage systems associated with them have
led to a significant increase in the amount of collected data.
However, the traditional grid infrastructure was not designed to
transport such a large amount of data in a bidirectional fashion
[4, 5, 8, 9, 12].
This issue was addressed by an Advanced Metering
Infrastructure enhanced with an Internet of Things (IoT)
technology [7, 13]. Although the definition of IoT is still
evolving, it was attributed a major role in providing
comprehensive access to services and data supplied by large
number of diverse devices in an interoperable way [14-17]. As
mentioned by the IoT European Research Cluster (IERC), IoT
is “a dynamic global network infrastructure with self-
configuring capabilities based on standard and interoperable
communication protocols, where physical and virtual “things”
have identities, physical attributes, and virtual personalities and
use intelligent interfaces, and are seamlessly integrated into the
information network [18, 19].” Seeking applications in different
areas of SGs’ infrastructure: smart metering, generation,
transmission, distribution etc., IoT play a key role in the current
development of SGs [20]. This development is accelerated by
recent improvements of main features of IoT devices: storage
capacity, processing power, miniaturization, and the self-
determining capability to “connect and sense” (Fig. 1) [2, 21-
24].
Backbone Collection Aggregation
ESP
.
.
.
.
.
.
Smart Meter
Data Concentrator
.
.
.
Signal splitter / combiner
. . . . . .
.. .
. . . . . . . .
IoT sensor Optical Fiber connections
Telecom Network connections
Sensing
. . .
. . .
. . .
. . .
. . .
. . .
. . .
. . .
Fig. 1 - Schematic topology of telecommunication network in an Advanced
Metering Infrastructure (AMI) of SGs. An example of IoT implementation
presented by sensing devices is shown for an energy distribution level.
In order to better understand the current development of SGs
from distributed automation and intelligence perspectives and
identify the research topics emerging from such development,
this work describes the infrastructure and summarizes the
applications of IoT in various areas of SGs. The infrastructure
of IoT in SGs is presented from the viewpoints of physical and
software implementation. The applications are described for
several structural and functional parts of SGs: Customer
Interactions, Generation, Transmission, Distribution, etc.
The rest of the paper is organized as following. Section II
describes components of IoT including the aspects of their
physical implementation, utilized models, associated web
services, and cloud-computing. Section III describes the areas
of application of IoT in SGs. Sections IV and V describe the

implementation benefits & challenges of IoT, respectively.
Section VI finally provides concluding remarks.
II. COMPONENTS OF INTERNET OF THINGS IN SMART GRIDS
An Internet of things (IoT) implementation in Smart Grids
(SGs) mainly consists of physical components acquiring
information from metering/sensing devices, such as intelligent
sensors, actuators, etc. and sending it to a resultant data
concentrator (e.g., aggregator with corresponding gateways)
[21-23, 25]. This data concentrator in turn modifies information
to suit the required Internet protocols (e.g., TCP/IP) for web
services or cloud computing platforms, which further processes
it and takes the required actions [21-24]. Within a SG, such
computing platforms are located at the Energy Service
Providers' (ESP) sites. Those sites are connected with the
corresponding Aggregation layer through an underlying
Networks layer [21-24]. The process of data handling in general
IoT processing layers can be mapped to an infrastructure of SGs
as illustrated in Fig. 2. A specific realization of these IoT layers
in the infrastructure of a particular SG depends on the
underlying architecture of the corresponding power system
(scale, density of energy loads, etc.).
Network layer
Aggregation layer
Application layer
Sensing layer
Data Concentrators
Energy Service
Provider
Smart Meters
IoT processing layers Infrasrtucture of SGs
Access points
Fig. 2 - A structure of IoT processing layers implemented for SGs. Sensing,
aggregation, network, and application layers are mapped on corresponding
SG’s infrastructure.
Physical Implementation
Physical devices used for IoT based networks follow
multiple communication standards based on corresponding
limitations of information and telecommunication technologies
(required bandwidth and reach) and the architecture of a certain
power system. For instance, a lower radio frequency (RF) with
a Sub-1 GHz mesh network and the IEEE 802.15.4 2.4 GHz
ZigBee standards are the most popular in the US. In the UK and
Japan, implementations of Sub-1 GHz RF or power line carrier
(PLC) solutions with a longer reach are evaluated as better
options [26]. Smart metering devices, are capable of providing
data formatted in ZigBee, comma-separated values (CSV) and
java-script object notation (JSON) [27]. Several solutions with
6LoWPAN [28], ZigBee-IP [29], and Wireless Smart Utility
Network (WI-SUN) along with IEEE 802.11g are utilized for
monitoring of energy consumption [27, 30].
The described IoT standards were implemented in several
hardware platforms: SmartEnergy, which manages assets
dynamically and reduces energy costs and outages [31]; and
Techno-Pole, which predicts energy behavior based on data-
incentive solution [27], etc. Besides, the communication
standards for IoT implementation in SGs are defined by a scale
of an underlying power system. For instance, GPRS, 3G, and
Power 4G standards were utilized at Henan Hebi, the first large-
scale demonstration project of IoT’s implementation in SGs
[32]. Additionally, expansion of IoT in SGs is related to
integration of its communication link in an electrical network,
which in turn is subject to supported transmission and reception
data rates, network topology, layered architecture, routing
delays and onboard processing speeds [33].
Thus, it is evident that a single wireless solution might not
be the best choice, but its selection can depend on the country's
existing infrastructure, type of grid, cost of transition or
deployment, requirements of application in terms of wireless
connectivity options, power constraints, and bandwidth
requirements [26]. Besides, aspects over the air (OTA) updates
can affect scalability, maintainability, security, and
interoperability, which will define the choice of a wireless
solution.
As per Architectural Considerations in Smart Object
Networking [34], four models of IOT communication are
currently considered [34, 35]: Device to Device, Device to
Cloud, Device to Gateway, and Back-End Data Sharing Pattern.
TABLE I. IOT MODELS IN SMART GRIDS
Model
Implementation example
Device to Device
An IoT sensor with another one
Device to Cloud
An IoT sensor with the ESP
Device to Gateway
An IoT sensor with the access point
Back-End Data
Sharing Pattern
The ESP with another one
Computing Platforms and Web Services
Several software packages were developed to
accommodate the transition from traditional to smart energy
grids. These packages represented by distribution management
system (DMS), geographic information systems (GIS), outage
management systems (OMS), customer information systems
(CIS), and supervisory control and data acquisition system
(SCADA) [36-38].
Ubiquitous sensing, data analytics, and an information
presentation platform are required for communicating between
numerous applications designed during further development of
SGs [39]. For SGs to be reliable and efficient, the computational
requirements are very important. It was shown that cloud-
computing platforms can be successfully used for energy
management, security of grid utilities and consumers, as well as
communication and information management within a SG [20,
40]. These platforms can be classified based on their models,
architecture and services offered/provided [40]. Utilization of
computing platforms, such as Aneka [39], Fog Computing [20],
XENDEE [41], are beneficial with the dynamically changing
nature of IoT environment. Additionally, XENDEE provides a
cloud-computing platform for smart micro-grid project
management and power system analysis [41]. Development of
diverse yet user-friendly platforms can help reduce the time,
effort, and costs associated with SG deployment and
management.
Different computing platforms enable various web services
for monitoring, management, and control of the SG

infrastructure: Energy Management Systems (EMS), GreenBus
Microgrid Solutions, Advanced Microgrid Solutions, etc. [28,
42, 43]. These services vary in terms of the cost, ability to
integrate with third-party solutions, digital infrastructure (e.g.,
databases), and the scope of utilization/ customization (of
existing versus new infrastructure). Besides, such web services
differ in predictive generation methods, pricing adaptability,
weather prediction, load control, extent of savings, and
optimized utilization of energy resources.
The operation of computing platforms and web services in
IoT is based on corresponding protocols, which are considered
to be the other component of IoT in this survey.
Protocols
Integration of IoT with web-services and protocols are key
challenges for smooth IoT’s transitioning to a SG model [2, 8,
9, 23, 44, 45]. Considering application specific requirements
and constrained resources, protocols for IoT in general can be
classified into the following broad categories: application
protocols, service discovery protocols, infrastructure protocols,
and other influential protocols [46]. Application protocols are
only discussed in this section. Constrained Application Protocol
(CoAP), Message Queue Telemetry Transport (MQTT),
Advanced Message Queuing Protocol (AMQP), Extensible
Messaging and Presence Protocol (XMPP) with Data
Distribution Service (DDS) are few such examples [46]. These
application protocols can be compared using following aspects:
Representational State Transfer (REST) compliant services,
header size, Quality of Service (QoS), Transport Layer
dependency (TCP/UDP), and offered security, which can be
divided in Transport Layer Security (TLS) / Datagram TLS,
messaging pattern, and request/response functionality [46].
The usage of the above described protocols are already part
of the ongoing SG technologies: a ZigBee Mesh network with
MQTT is being used at Axelta, Axelta Systems Pvt. Ltd [47],
and CoAP at Silver Spring Networks [48] company to name a
few. Although a single implementation of IoT protocols may
not be available, a given solution may perform well in specific
scenarios and environments [46].
III. AREAS OF APPLICATION
Internet of things (IoT) devices seek applications in various
parts of Smart Grids (SGs). These parts can include the scope
of customer interactions, energy generation and distribution,
smart metering, grid management and maintenance.
Customer Interactions
In Home Area Networks (HANs), Building and Industrial
Automation Systems (BASs and IASs), IoT technologies are
used to attain an automated energy management, its efficient
usage, and comfort and dynamic functionality. These
applications include studying patterns of energy usage and
controlling the loads accordingly [7, 20]. A better control for
utilities, such as water, gas, and energy supply can be obtained
based on Machine-to-Machine (M2M) interactions supported
by optimized communication networks and advanced
communication technologies [18]. These networks are required
to maintain a broadband bidirectional connection between
utility users and their providers. The main implementation of
IoT in customer interaction can be observed in Demand
/Response schemes [8-10].
Generation, Transmission and Distribution
Deployment of IoT [8, 9] in energy harvesting farms (e.g.,
wind, solar, etc.) and energy storage systems, can help in better
energy forecasting by achieving a balance between energy
generation, storage, and consumption [18, 20, 39].
Additionally, IoT ’s implementation can be advantageous for
energy generation and distribution in autonomously powered
islands in case of failures and blackouts, for readjustment of
excitation controls and load shedding, system restoration and
aspects of self-healing [18, 20]. An IoT based online system
controlling power transmission lines presented in [45] describe
its major monitoring parameters: transmission tower leaning,
conductor galloping, wind deviation and vibrations, micro-
meteorology, conductor icing, and temperature control. Using
such online control systems, these parameters are monitored in
real-time and subjected to further analysis, which in turn would
be used to maintain a reliable operation of power transmission
[45]. Thus, IoT can play a functional role in various steps of
generation, transmission, and distribution.
Smart Metering
Along with IoT’s application in energy generation,
transmission, and distribution, IoT’s usage in smart energy
metering is the other major area of its implementation in SGs.
Using IoT and cloud-backed systems meters or data
concentrators can send data to Energy Service Providers (ESP)
or cloud services using suitable interfaces. More data can be
monitored with IoT utilization in SGs on frequent basis.
Therefore, it will in turn increase the probability of required
repairs that can be initiated in an event of damage or failures in
a timely manner [20, 49, 50]. Various leading providers of
industrial IoT smart meters, such as MOXA [42], Sierra
wireless [49], Itron [50], etc., are already leading the forefront
of smart metering. In addition to the increased amount of data,
IoT implementation in smart metering systems brings another
level of intelligence that enhances the functionality of
Advanced Metering Infrastructure (AMI), communication
network supporting smart metering [8, 9], and its scalability
[51].
Grid management and maintenance
IoTs can enable efficient asset management by better status
and operation monitoring of SG assets. Usage of information
about energy system parameters, such as the dynamic heat
capacity, line-icing, galloping of power lines, impact of wind
etc. can enable earlier fault detection and repairs [20, 45].
Maintenance of existing grid assets and planning of grid
expansion can be dealt with in a better manner using data
obtained from IoT [20].
IV. IMPLEMENTATION CHALLENGES IN SMART GRIDS
Implementation of Internet of things (IoT) technologies in
Smart Grids (SGs) requires solutions of several important
design issues. For instance, to maintain the required quality of

service, Internet connection must be affordable, reliable, and
widespread. Besides, routing protocols and programming
applications should be efficient enough to ensure stable data
transmission, energy-efficiency, and scalability [20, 26].
Therefore, security, optimized infrastructure, and software
applications are important issues that need to be addressed for
an IoT implementation.
Infrastructure and Interoperability
The IoT system has typically evolved with distinguished
solutions, in which every component is designed for a particular
application context [52]. Hence, standardizations in technology
stack, communication protocols, and data sources along with
integration feasibility are required [36].
IPv4 is the most widely used version of a protocol at the
Network layer of IoT processing scheme (Fig. 2). The most
recent version, IPv6, has several advantages with respect to
IPv4. However, not all of currently utilized SG technologies
support IPv6 protocol. Due to this reason, a deep analysis of
communication network infrastructure is needed before
defining IPv6 protocol for network addressing of the loads and
other devices connected to a SG by IoT [20]. Additionally, a
secure communication interface would be required for
communication between TCP/IP stack supported devices with
non TCP/IP stack supported devices (e.g., protocols as ZigBee,
HART) [53]. This requirement is also applicable in the case of
devices supporting same protocol stacks but different feature
capabilities, such as one having Datagram Transport Layer
Security with/without certificate support [53].
With the demand to analyze a continuously growing
amount of data collected in SGs, new and optimized software
needs to be implemented [20, 54-56]. Thus, requiring the
software infrastructure to be modular and scalable.
Additionally, large volume of information exchanges in an IoT-
enabled smart grid would require systems capable of computing
and storing data in real-time. Due to this reason, the
corresponding data storage devices need to be selected for IoT
implementation in SGs. Such planning will bring an additional
cost to the manufacturing, deployment, maintenance of SG-
focused IoT devices [57].
Thus, the development of interoperable standards, modular
& scalable software infrastructure would be crucial making the
IoT based SG’s prevalent.
Privacy and Security
Providing numerous advantages, such as sustainability,
efficient energy distribution, grid control and manageability,
IoT based SGs also introduce new security and privacy
challenges [58, 59]. The challenges pertaining to IoT security
and privacy can be classified on the customer, communication,
and grid domains information [59].
Various aspects of users’ identification, authorization, and
access control are concerning in cyber security of IoT systems,
such as ‘Fog Computing’, and need to be addressed [20, 58, 59].
IoT based SGs are also subject to security issues based on
impersonation, data-tampering, malicious-software, DoS
(Denial of Service), and Cyber-attacks [53]. Various security
practices and approaches, such as anti-virus, firewalls, intrusion
prevention systems, network security design, defense-in-depth,
and system hardening, can be incorporated to protect SGs [60].
Usage of approaches based on security keys, cryptographic
algorithms, and hidden IDs can be used while integrating
embedded IoT devices to cloud services [61].
Along with security, privacy is the biggest concern for IoT
implementation in SGs, owing to which ESPs need to have
proper safeguards and means to have controlled access to users’
information [59]. Initiatives, such as IoTSec, Security in IoT for
Smart Grids, have provided Multi Metrics approach to calculate
system security, privacy, and dependability levels [62]. Pseudo-
nymizing (or differential privacy) and Cryptographic
computation approaches can be used for preserving privacy for
IoT enabled smart grids [56]. To resolve privacy issues and gain
efficient authentication and access control, an Elliptic Curve
Cryptography (ECC) based session key approach has been
introduced in [63]. A privacy preserving protocol was
suggested in [37] where in an ECC encryption scheme was
proposed to secure the exchange of data measurements between
an ESP and smart metering infrastructure.
V. BENEFITS OF INTERNET OF THINGS IN SMART GRIDS
Prosumers and M2M communication
Energy management systems designed on Internet of things
(IoT) for in-home and in-building automation help consumers
to monitor their own energy usage and adjust their habits and
behaviors [1, 2]. At the same time, IoTs’ application on
customers’ side of a Smart Grid (SG) allows them to actively
participate in providing energy to the grid. Thus, making energy
grid users ‘prosumers’, who not only manage their demand but
also produce and sell energy [7].
Besides, deep and extensive implementations of IoTs could
be established, through Machine-to-Machine (M2M)
communication in real-time and close interaction between
energy users and the Energy Service Providers (ESPs). This
interaction can in turn reduce the retail energy price and
improve the efficiency of distribution and generation by
renewable and traditional energy sources [3, 8, 10, 28, 29, 64-
68]. Besides, IoT friendly Advanced Metering Infrastructure
(AMI) supported by optimized telecom network architecture
are key to achieve such goals [28-30].
Data Analytics
Data analytics would aid to extract meaningful and
actionable insights from interconnected intelligent devices [69].
The captured data can be used to form an Information Value
Loop (IVL), a framework to guide users, and help to identify
where information bottlenecks exist and what technologies can
relieve them to create value [38]. Predictive analytics can make
smart grids proactive by aiding in the effective maintenance,
precise generation, load balancing, and efficiency improvement
of an energy grid. Using data analytics, ESPs can make quick
decisions and better adapt to supply and demand [69].
Specifically, data analytics is widely and extensively used for
future electricity price forecasting in SGs [70-73]. Various
statistical and mathematical tools are adapted for data analytics:
artificial neural networks, support vector machines, along with
engineering and statistical methods [65, 66, 74, 75]. Very often,

these tools are accompanied with the corresponding analysis
methods [76-82]. For instance, support vector machine
optimization algorithm based on differential evolution, Grey
Correlation Analysis, and Principle Component Analysis is
proposed to forecast price classification [55].
Self -healing Networks
The self-healing ability of a network to quickly repair itself
in the event of any external or internal disturbances would play
a crucial role in SGs [18, 20, 45]. In an event of destabilization,
intelligent devices based on real-time data distribution can
isolate faults and achieve global optimization and
reorganization to resume operation [43, 83]. In case of SGs,
such ability of the smart grids makes then able to resume
operation after attacks, blackouts and network failures.
Additionally, self-healing feature enabled by IoT technologies
implementation can increase network’s resiliency to external
attacks [38].
VI. CONCLUSION
An absence of a unique solution for IoT implementation in
Smart Grids (SGs) is evident. Based on existing infrastructures
and types of SGs, their scale and density of their energy users,
various physical designs and computational platforms are
currently utilized to accomplish the goal of IoT performance in
SGs. In this performance, the main IoT processing layers,
sensing, aggregation, network, and application can be mapped
on the existing infrastructure of SGs (Fig. 2).
One of the main areas of IoT’s application in SGs are
customer interactions through corresponding automation
systems supported by machine-to-machine communications. A
real-time information obtained from sensing is the key
advantage of IoT’s utilization in this area. Another area of
application is an advanced management and control of energy
generation, transmission, and distribution in SGs. Supporting
bidirectional information flow; smart metering enhanced with
IoT sensing plays an important role in this application. Other
key areas of IoT’s application in SGs are dynamic asset
management and maintenance. In this area, analysis of data
obtained from IoT sensors and other intelligent devices in
combination with predictive analytics can benefit SG with a
proactive decision-making.
Various technological standards, communication protocols,
and a wide range of information sources are required to be
feasibly integrated in IoT network for SGs. Besides, rigorous
privacy and security requirements need to be applied for data
transmitted within SGs. Hence, a development of optimized
interoperable standards, a design of scalable software
infrastructure in a cost-efficient manner and considering current
issues of privacy and security are the major goals of the future
research in the area of IoT implementation.
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