1. 1

Abstract— With the introduction of the smart grid, Advanced
Metering Infrastructure (AMI) has become an important element
in the modern power system. The successful implementation of
AMI is dependent on its communication scheme that provides
reliable two-way communications. The objective of this paper is
to provide a comprehensive review of possible AMI
communication network infrastructures based on real-world
smart grid projects, and analyze their advantages/disadvantages
in terms of deployment costs, communication range and
reliability. Based on this information, the most promising AMI
communication scheme is recommended, which is a hybrid
version of WiMAX and fiber optic. The recommended solution is
simulated in OPNET using the case study of a small-scale AMI
network. Network performance is then evaluated based on smart
metering system requirements specified in IEEE Std 2030-2011.
Keywords— Advanced Metering Infrastructure (AMI),
WiMAX; Fiber optic, OPNET.
I. INTRODUCTION
OWADAYS, the traditional electric power grid is
undergoing a significant transition into an intelligent grid
which is called a smart grid [1]. In a smart grid, many
intelligent features and functions can be achieved.
According to the U.S. Department of Energy’s Smart Grid
Investment Grant Program (SGIG), majority of the SGIG
projects (65 out of 98) are categorized as Advanced Metering
Infrastructure (AMI) [2]. These AMI projects aim at
installation of smart meters to allow use of real-time pricing,
demand response, load management and more. It appears that
out of many smart grid applications, AMI applications draw
the most attention. This is due to AMI promising potential.
For example, AMI can be used to achieve the supervisory
control and data acquisition (SCADA) based distribution
automation [3]. AMI can also be used for demand side
management [4], realizing transformer identification and
phase identification [5], smart energy management [6] and can
help implement distribution state estimation [7].
To fully realize benefits of AMI, it is necessary to
appropriately choose communication technologies and
This work was supported in part by the U.S. National Science Foundation
under Grant IIP-1114314.
The authors are with the Virginia Tech – Advanced Research Institute,
Arlington, VA 22203 USA (e-mails: desong85@vt.edu; mkuzlu@vt.edu;
mpipatta@vt.edu and srahman@vt.edu).
associated communication networks that provide two-way
communications. There are several previous studies that
discuss AMI communication technologies and network
structure [8-15]. Authors in [8] provide scalable distributed
communication architectures to support AMI. In [9], a bi-
directional communication protocol is introduced considering
the effect of AMI environment. The discussion of ZigBee and
Power Line Communication (PLC) technologies for AMI is
presented in [10-12]. Authors in [13] show a heterogeneous
WiMAX-WLAN network for AMI communications. A novel
path-sharing scheme for AMI network is shown in [14].
Authors in [15] develop a multipath routing method for AMI
networks in smart grid. As far as the literature is concerned, a
comprehensive review and analysis of different
communication schemes that support AMI applications based
on real-world smart grid projects is not available.
In this paper, major components of AMI and its
communication network architectures are reviewed.
Advantages and disadvantages of popular communication
technologies supporting AMI deployment are discussed. This
is followed by examples of possible communication schemes
used in real-world AMI projects. Lastly, a communication
scheme, which is a hybrid version of WiMAX and fiber optic,
is proposed as a recommended solution for AMI deployment.
This paper also presents simulation results of the WiMAX-
fiber optic technology for AMI applications using OPNET.
Simulation results are verified to meet AMI communication
requirements specified by IEEE Std 2030-2011.
II. OVERVIEW OF AMI
Advanced metering infrastructure (AMI) refers to a
measurement and collection system that includes smart
meters, communication networks, and data management
systems that make the information available to the service
provider. In general, AMI is deployed to enable a utility to
collect real-time consumption information, and enable end-use
customers to be informed about real-time pricing information.
A. Components of AMI and their Functions
An AMI system generally comprises three components:
1) A smart meter is a digital meter that can be used to
record consumption of electric power, water or gas, and
transfer consumption information to a utility. It is also used to
receive commands or price signals from a utility.
Analysis of Communication Schemes for
Advanced Metering Infrastructure (AMI)
D. Bian, Student, IEEE, M. Kuzlu, Member, IEEE, M. Pipattanasomporn, Senior Member, IEEE, and
S. Rahman, Fellow, IEEE
Virginia Tech – Advanced Research Institute, Arlington, VA 22203
N

2. 2
2) MDMS or metering data management system is another
critical component in realizing potential functions of AMI.
Major functions of MDMS include [16]: automating and
streamlining the complex process of collecting meter data
from multiple meter data collection technologies; evaluating
the quality of that data and generating estimates where errors
and gaps exist; and delivering that data in an appropriate
format to utility billing systems.
3) Communication network is another important
component of AMI, which provides a channel to exchange
information between end-use customers and a utility. With
two-way communications, utilities can monitor real-time
consumption from end-use customers; and at the same time,
end-use customers are able to participate in system operation
actively by receiving price or control signals from utilities.
To realize two-way communication infrastructures, a
concentrator is the key element. Generally, concentrators in
AMI are classified into two groups: local concentrator and
backbone concentrator. The former is to collect data from
smart meters and forward the data to the backbone network, as
well as to distribute commands or price signals received from
a backbone concentrator to meters. The latter are located in the
backbone network of AMI. Their major functions are to
collect information from local concentrators and to spread
commands or price signals received from the utility’s control
center. Local concentrators are not necessary in some AMI
deployments, especially those with a small number of
customers. In such cases, smart meters communicate with
backbone concentrators directly.
For an AMI system, smart meters are located at customer
premises usually outside residential buildings; the MDMS is
located at the utility side. Therefore, communications between
smart meters and MDMS happen within a neighborhood
through Neighborhood Area Network (NAN). Comprehensive
discussions about this topic can be found in [17, 18].
B. AMI Communication Framework
The schematic of a typical AMI communication network is
illustrated in Fig. 1.
Fig. 1. Typical AMI communication network.
The AMI communication network is generally classified
into two layers: the smart meter network connecting smart
meters, which may include local concentrator(s); and the
backhaul network connecting backbone concentrators and a
control center (or MDMS as shown in Fig. 1).
The smart meter network is a lower-layer network in an
AMI communication infrastructure. A mesh network is
typically used to collect consumption information from end-
use customers and upload them to the backhaul network
directly or through local concentrators. It also helps to
distribute commands/price signals among smart meters. Main
network requirements are its cost effectiveness and reliability.
The backhaul network consists of backbone concentrators
and a control center. The control center is the node which
manages the whole AMI system. Backbone concentrators are
used to collect consumption data from smart meters or local
concentrators. They are also used to transmit information and
receive commands from the control center. Main requirements
of the backhaul network are high reliability and low latency.
III. COMMUNICATION TECHNOLOGIES FOR AMI
Both wired and wireless technologies can be implemented
to support AMI deployment. Popular wired technologies for
AMI deployment include Power Line Communication (PLC)
and fiber optic. Popular wireless communication technologies
include cellular (4G, LTE, WiMAX), WLAN, ZigBee and RF
mesh (900MHz). In this section, advantages and disadvantages
of each communication technology are discussed.
A. Wired communication technologies
1) Power Line Communications (PLC)
PLC uses exiting power lines to realize the data
transmission. It is well known that PLC is promising for smart
grid applications due to availability of existing infrastructure.
PLC is a good choice for many control applications including
smart metering, home automation and others. It is especially
suited for rural areas that have access to power but other
communication infrastructures are not available. However,
PLC faces several technical challenges, e.g., noisy channel,
low-bandwidth and difficulty for signals to pass through
power distribution devices. Another drawback of PLC is its
security concerns.
2) Fiber optic communications
With advantages of high data rate and immunity to noise,
the fiber optic option has become a popular communication
technology to provide backbone communications to support
various smart grid applications. Fiber optic is best suited for a
long distance network with limited number of access points.
However, the high installation cost is its major drawback.
B. Wireless communication technologies
1) Cellular (4G, LTE and WiMAX)
An existing cellular network is a good option for setting up
an AMI system, especially to support data communications
between concentrators and the control center. If the cellular
network infrastructure exists, there is no extra time and cost
for a utility to set up the network for smart grid applications.
Furthermore, the security of cellular network is very strong.
However, a possible drawback includes sharing cellular
networks with other customers, which can result in network

3. 3
congestion in certain emergency situations. Additionally,
cellular networks may not provide a guaranteed service during
abnormal situations, such as a wind storm. Among all cellular
technologies, WiMAX is the most promising 4G wireless
technology based on the IEEE 802.16 series of standards. Its
data rate is up to 75 Mbps with the coverage distance of up to
50 km. WiMAX also provides low latency communications.
These good qualities make WiMAX a good candidate for
smart grid applications. However, WiMAX requires high
power consumption and it is relatively expensive to deploy.
2) ZigBee
ZigBee is a personal area network protocol based on the
IEEE 802.15.4 standard. In the U.S., its operation band is 915
MHz. The coverage distance of ZigBee is up to 100 meters;
and that of ZigBee pro is up to 1,600 meters. The range of
ZigBee pro is sufficient for AMI applications. Its data rate
varies from 20kbps to 250kbps. Generally, ZigBee is a low-
cost, low-power consumption technology and secure.
However, ZigBee has severe interference problems with other
networks due to sharing the same channel spectrum. It also has
low processing capabilities. Therefore, implementation of
ZigBee needs a well-designed network structure and well-
organized communication traffic. The mesh topology is
commonly used to support large-scale applications.
3) WLAN
Wireless Local Area Network, also known as Wi-Fi, is a
kind of high-speed wireless network technology. It is based on
the IEEE 802.11 series of standards and operates on 2.4GHz,
3.6GHz and 5GHz bands. WLAN can provide reliable secure
and high-speed communications. However, its implementation
cost and power consumption are relatively higher than other
short-range (100 meters) technologies, such as ZigBee. Access
points are usually needed for setting up the network. Similar to
ZigBee, the mesh topology is commonly used.
4) 900 MHz
900 MHz band is unlicensed ISM (industrial, scientific and
medical) Radio Frequency (RF) bands. It does not need an
individual license from telecommunication regulatory
authorities. 900 MHz has a longer range (approximately two
times) than what is possible at 2.4 GHz. In addition, the mesh
protocol is most implemented for 900 MHz technology. As a
result, it inherits mesh network properties, which are self-
healing, high reliability and cost effectiveness with wide
coverage range. These properties are suitable for deployment
in both urban and suburban areas. The RF (900 MHz) mesh
network is a good choice for setting up AMI mesh network
connecting smart meters. On the other hand, similar to all
other networks using mesh protocol, 900 MHz has several
drawbacks, e.g., high bandwidth consumption, lack of
interoperability and privacy protection issues.
IV. COMMUNICATION SCHEMES DEPLOYED IN REAL-WORLD
AMI PROJECTS
With the deployment of smart grids, there are more than
100 AMI projects around the world. Table I summarizes
TABLE I. SELECTED REAL-WORLD AMI DEPLOYMENTS
Size Project name
Number of
meters
Backhaul network Smart meter network
Fiber
Cellular
Others
PLC
RF900
MHz
WiFi
ZigBee
900RF
PLC
Cellular
Smallscale
Customer driven design of smart grid capabilities 4,355 X X
Advanced metering infrastructure pilot 4,855 X X
Knoxville Smart Grid Community Project 3,393 X X
Model for small and midsize utility districts around the US 7,765 X X X X X
Advanced metering Infrastructure pilot 4,855 X X
Smart grid modernization initiative 5,033 X X
Mediumscale
advanced metering infrastructure/meter data management system 68,980 X X
Smart grid program 52,257 X X
Leesburg smart grid investment grant project 16,683 X X
Woodruff electric advanced metering infrastructure project 14,450 X X
Pacific Northwest Division Smart Grid Demonstration Project 30,722 X X X
Advanced metering Infrastructure/Meter Data Management system 44,920 X X
smart grid team 2020 program 38,551 X X
Advanced metering infrastructure/meter data management system 39,102 X X
AMI Smart Grid Initiative 85,582 X X X
Advanced Metering Infrastructure and Smart Grid Development Program 10,596 X X
Connected Grid Project 12,575 X X
Connecticut Municipal Electric Energy Cooperative Smart Grid Project 23,449 X X
Smart Currents 688,717 X X
Smart Grid Project 170,000 X X X X X X
IPC Smart Grid Program 380,928 X X
Smart Energy Project 10,275 X X
Lafayette Utilities System Smart Grid Project 63,967 X X X
Smart Grid Initiative 124,000 X X
Large
scale
Energy smart Florida 3 million X X X X
Smart grid initiative 1,272,911 X X X
Smart grid project 2,130,737 X X
Smart Grid Deployment 1.2 million X X X X X X X X

4. 4
information of selected AMI projects including number of
smart meters and the communication technologies deployed to
support AMI applications.
In this paper, these AMI projects are classified into three
groups based on the number of smart meters: small-scale,
medium-scale and large-scale. Small-scale projects deploy less
than 10,000 meters. The number of meters between 10,000
and one million are classified as medium-scale projects.
Lastly, large-scale projects have more than one million meters.
From Table I, it can be seen that fiber optic and cellular are
the two most popular communication technologies for AMI
backbone network. Between the two choices, the fiber optic
option has an advantage over the cellular option in that it can
provide higher bandwidth. This is because the bandwidth
needs to be shared with other customers in the same cellular
network. Furthermore, fiber optic technology can provide
higher reliability level than cellular during inclement weather
conditions.
To support communications between smart meters and local
concentrator, the 900 MHz mesh network appears to be the
most popular technology choice. This is because it has good
reliability and flexibility performance. In addition, the
implementation cost of 900 MHz mesh network is relatively
inexpensive as it can rely on an existing infrastructure.
However, 900 MHz mesh has several drawbacks for AMI
implementation. First of all, the RF mesh network consumes
high network bandwidth. This makes RF mesh network facing
a hard time to deal with fast increasing number of smart
meters/sensors. Secondly, due to characteristics of mesh
protocol, the information of one house may go through several
other smart meters to finally get to the concentrators. This
factor brings lots of privacy and security concerns.
On the other hand, WiMAX, with its high-level reliability,
fast data rate and relative large coverage, has emerged as
another promising solution for the smart metering mesh
network. Unlike 900 MHz mesh technology, deployment of
one WiMAX base station can cover the entire district. Since all
smart meters are connected to the base station, the privacy
issues brought about by mesh protocol can be neglected.
V. ANALYSIS OF COMMUNICATION SCHEME FOR AMI USING
WIMAX AND FIBER OPTIC
In this section, analysis of communication scheme for AMI
using a hybrid version of WiMAX and fiber optic technologies
is presented.
The AMI network structure in this paper is assumed to have
two layers: backbone network and smart meter network. In this
case study, the backbone is set up containing a server and a
backbone concentrator. The smart meter network is set up
containing 60 smart meters. All 60 smart meters connect to the
backbone concentrator directly. With respect to communication
technologies, fiber optic is selected to serve as the backbone
network connecting the backbone concentrator and MDMS. On
the other hand, WiMAX is selected to support the smart meter
network. The case study is simulated in OPNET. Smart meters
are simulated by using subscriber stations (SSs); the
concentrator is simulated by using a base station (BS) and the
MDMS is simulated by using a server station. The small-scale
AMI network set up in OPNET is illustrated in Fig. 2.
Fig. 2. Small-scale AMI network simulation in OPNET.
The AMI communication traffic in this study is assumed to
be scheduled meter interval reads, where a utility obtains
interval usage information from smart meters in 15-minute
intervals.
As shown in Fig. 2, smart meters are separated into five
groups. Each group sends out their consumption packets to
MDMS through the base station in assigned time periods. The
size of consumption packet is chosen as 128 bytes. All 60
meters must report their consumption in 15-minute intervals.
Note that in practice, each meter sends out its packets at a
random time. For simplicity in interpreting the result, this study
assumes that all smart meters in each group sends all packets at
the same time, at two minute apart for each group.
Simulation results are shown in Fig. 3 and Fig. 4 for the
overall data rate and data dropping (reliability) and latency of
the hybrid WiMAX-fiber optic system, respectively.
Fig. 3. Overall data rate and data dropping.
From Fig. 3, as there are 12 smart meters in each group and
each smart meter sends out 128 bytes, the total data

5. 5
transmission is 128*12 = 1,536 bytes at every two-minute
interval. As shown, it can be concluded that communication
traffic of the WiMAX-fiber optic system is very reliable and
there is no data dropping. This meets AMI reliability
requirements specified by the IEEE Guide for Smart Grid
Interoperability (IEEE Std 2030-2011).
Fig. 4. Latency.
IEEE Std 2030-2011 specifies latency needs for AMI
applications between <4ms to 15 seconds. From simulation
results, the simulated latency is under one second, which meets
the specified requirement.
VI. CONCLUSION
In this paper, various communication technologies and
network structures for AMI applications are compared. In
addition, real-world AMI projects are summarized. Lastly, the
communication scheme for AMI based on WiMAX-fiber optic
scheme is simulated to analyze the AMI network reliability and
latency. Simulation results illustrate that the hybrid WiMAX-
fiber optic technology can fully meet AMI requirements
specified by IEEE Std 2030-2011. It is expected that the
content of this paper can benefit communication engineers
working in a utility to design an AMI network infrastructure
and select the most appropriate communication technology to
support their AMI deployment. Additionally, this paper also
shows how a performance of a selected communication
technology (i.e., a hybrid vision of WiMAX and fiber optic)
can be validated using OPNET to meet specific application’s
requirements. This can pave the way for validating the
performance of other communication technologies.
REFERENCES
[1] L. T. Berger and I. Krzysztof, “Smart grid, applications,
communications, and security”, published by John Wiley & Sons, Inc.,
Hoboken, New Jersey, 2011.
[2] U.S. Department of Energy, “Smart Grid Investment oGrant Program-
Progress Report July 2012” [online], available:
http://energy.gov/sites/prod/files/Smart%20Grid%20Investment%20Gra
nt%20Program%20-%20Progress%20Report%20July%202012.pdf
[3] Nunoo, S.; Ofei, A.K., "Distribution automation (DA) using supervisory
control and data acquisition (SCADA) with advanced metering
infrastructure (AMI)," Innovative Technologies for an Efficient and
Reliable Electricity Supply (CITRES), 2010 IEEE Conference on , vol.
454, no. 458, pp.27-29 Sept. 2010.
[4] Huibin Sui; Ying Sun; Wei-Jen Lee, "A demand side management
model based on advanced metering infrastructure," Electric Utility
Deregulation and Restructuring and Power Technologies (DRPT), 2011
4th International Conference on , vol. 1586, no. 1589, pp.6-9 July 2011.
[5] Short, T.A., "Advanced Metering for Phase Identification, Transformer
Identification, and Secondary Modeling," Smart Grid, IEEE
Transactions on , vol.4, no.2, pp.651-658, June 2013.
[6] Nthontho, M.; Chowdhury, S. P.; Winberg, S., "Smart communication
networks standards for smart energy management," Telecommunications
Energy Conference (INTELEC), 2011 IEEE 33rd International , vol. 1,
no. 9, pp.9-13 Oct. 2011.
[7] Chen, Shi-Jaw; Lin, Chia-Hung, "Integrating SVM Classifier and
Distribution State Estimation for Detection and Identification of AMI
Customer's Meter Data," Computer Software and Applications
Conference (COMPSAC), 2013 IEEE 37th Annual , vol. 278, no. 279,
pp. 22-26, July 2013.
[8] Jiazhen Zhou; Hu, R.Q.; Yi Qian, "Scalable Distributed Communication
Architectures to Support Advanced Metering Infrastructure in Smart
Grid," Parallel and Distributed Systems, IEEE Transactions on , vol.23,
no.9, pp.1632-1642, Sept. 2012.
[9] Nam-Joon Jung; Il-Kwon Yang; Seung-Woon Park; Sei-Young Lee, "A
design of AMI protocols for two way communication in K-
AMI," Control, Automation and Systems (ICCAS), 2011 11th
International Conference on , vol. 1011, no. 1016, pp. 26-29 Oct. 2011
[10] Markowski, A.; Michta, E.; Szulim, R., "Communication structures and
data processing in AMI systems," Nonsinusoidal Currents and
Compensation (ISNCC), 2013 International School on , vol.1, no.6,
pp.20-21 June 2011.
[11] Shang-Wen Luan; Jen-Hao Teng; Shun-Yu Chan; Lain-Chyr Hwang,
"Development of a smart power meter for AMI based on ZigBee
communication," Power Electronics and Drive Systems, 2009. PEDS
2009. International Conference on , vol.661, no.665, pp. 2-5 Nov. 2009.
[12] Chen Xiang; Wu Runze; Cao Min, "Research of OFDM power line
carrier communication based on AMI," Wireless Mobile and Computing
(CCWMC 2011), IET International Communication Conference on ,
vol.278, no.281, pp. 14-16 Nov. 2011
[13] Khan, R.H.; Khan, J.Y., "A heterogeneous WiMAX-WLAN network for
AMI communications in the smart grid," Smart Grid Communications
(SmartGridComm), 2012 IEEE Third International Conference on , vol.
710, no.715, pp. 5-8 Nov. 2012
[14] Hirano, Y.; Sivakumaran, S.; Jain, S., "PS: Path Sharing Scheme for
AMI Networks," World Telecommunications Congress (WTC), 2012 ,
vol.1, no.6, pp. 5-6 March 2012
[15] Vaidya, B.; Makrakis, D.; Mouftah, H., "Secure multipath routing for
AMI network in Smart Grid," Performance Computing and
Communications Conference (IPCCC), 2012 IEEE 31st International ,
vol. 408, no.415, pp. 1-3 Dec. 2012.
[16] Sharelynn Moore, “Key features of meter data management systems”
[online]. Available:
https://www.itron.com/na/PublishedContent/Key%20MDM%20Features
%20Whitepaper_FINAL.pdf
[17] Kuzlu, M.; Pipattanasomporn, M., "Assessment of communication
technologies and network requirements for different smart grid
applications," In Proc. 2013 IEEE Innovative Smart Grid Technologies
(ISGT) Conference, vol. 1, no.6, pp., Washington, D.C., 24-27 Feb.
2013.
[18] Bian, D.; Kuzlu, M.; Pipattanasomporn, M., “Assessment of
Communication Technologies for a Home Energy Management
System”, accepted for presentation at IEEE Innovative Smart Grid
Technologies (ISGT) Conference, Washington, D.C., 19-22 Feb. 2013.
[19] SmartGrid. Gov, “SGIG smart grid project reports” [online]. Available:
smartgrid.gov.