Advanced Metering and Demand Response
Communication Performance in Zigbee based HANs
Velin Kounev
David Tipper
School of Information Science
University of Pittsburgh
Pittsburgh, PA 15260
Email: vkounev@pitt.edu
School of Information Science
University of Pittsburgh
Pittsburgh, PA 15260
Email: dtipper@pitt.edu
Abstract—Using IEEE 802.15.4 and Zigbee for home area
networks (HANs) in the Smart Grid is becoming an increasingly
prominent topic in the research area. As the standard designed
for low data rate and low cost wireless personal area networks,
IEEE 802.15.4 is widely employed in the construction of home
sensor networks to assist with real-time environment information. For the purposes of Smart Grid the Zigbee Alliance has
defined new Smart Energy Profile Protocol that leverages the
existing TCP and HTTP protocols. In this paper, we provide an
overview of the Smart Grid’s Advanced Metering Infrastructure
(AMI) and Demand Response (DR) functionalities, and the
communication requirement they pose for the new SEP protocol.
The discussion is followed by an evaluation of the theoretical
performance bounds of the new architecture based on a analytical
model. We conclude, by extending the model to account for WiFi
interference which is expected to be present in home and office
environments.
I. I NTRODUCTION
Number of independently own and operated power plants
and transmission lines is what today constitutes the U.S.
electric grid. This complexity of the network coupled with
aging infrastructure and ever increasing power consumption,
has forced the experts to examine the status and health of the
system. The grid includes the wires, transformers, switches and
substation that carry the electricity from the power plants to the
customers. One of the main drawback is the time and money
spend on repairs. Utility companies have to send out workers
to gather most of the information needed to provide electricity,
such as read meters, look for broken equipment and measure
voltage. Currently many options and products are being made
available to the electrical industry to modernize it [1]-[3]. The
vision is that fully automated information and process control
system would provide improved performance, by automated
information gathering and assistance prior to any repairs.
By using computer based remote control and automation
systems, the current electrical grid is envisioned to be evolved
into “Smart Grid”. This is made possible by two-way communication technology and computer processing. Great improvements in energy efficiency, isolation of electrical failures
and short recovery times are few advantages to customers and
utilities.
A. Smart Grid Application Requirments
The U.S. Department of Energy (DOE), in collaboration
with the Federal Energy Regulatory Commission (FERC) and
the National Institute of Standards and Technology (NIST),
sets forth six key functionalities to be achieved by Smart
Grid Infrastructure: (1) Advanced Metering Infrastructure;
(2) Demand Response; (3) Electric Vehicles; (4) Wide-area
Situation Awareness; (5) Distributed Energy Resources and
Storage; and, (6) Distribution Automation [4].
Each set of functions has its own requirements in terms
of bandwidth, latency and availability for the communication
systems. The communication infrastructure is divided into 3
parts: Home Area Network, Neighborhood Area Network and
Wide Area Network. Summaries and network allocation for
each Smart Grid functionality is presented below.
1) Advanced Metering Infrastructure (AMI): An advanced
two-way communication system to collect and measure energy
consumption for billing and statistical purposes. Future AMI
evolutions envision near-real-time operations. Requirements
such as bandwidth, availability and latency are expected to
grow to significantly higher level.
2) Demand Response (DR): One of the most significant
advantages of Smart Grid conceived to reduce peak loads. The
final most advance version of DR is automated DR, allowing
on-premise smart appliances to respond to dynamic condition
on the grid, and shift load consumption in a near-real-time
manner.
3) Wide Area Situational Awareness (WASA): A set of
technologies designed to improve the monitoring of the power
system across large geographical areas, and in the event of
emergency to isolate failures from spreading to the rest of
the network. A disturbance in the power supply in one area
can quickly spread and become a widespread problem, with
cascading and deleterious consequences [4]
4) Distributed Energy Resources and Storage (DER): In
Smart Grid the energy flow will be multi-directional, from
utility to home, home to utility, or from home to home. The
real-time net metering is required as to measure the electricity
drawn from the grid minus the energy provided by energy
sources on the premises.
5) Electric Vehicles (EV): A more robust grid is needed,
due to the fact that the current electrical grid is unlikely to
provide the peak capacity required to charge a significant
number of EV during peak hours.
6) Distribution Automation (DA): The primary function of
DA is to reduce voltage to an appropriate level in order to
isolate potential faults. Furthermore, the utilities would be
able to remotely monitor and control on-premise equipment
through automated decision-making.
2
Communication Network
Smart Grid Functionality
Bandwidth, Latency, Availability
(Most Stringent: 300 kbps/node, 0.02 seconds, 99.99%)
Home Area Network (HAN)
100 kbps/node, 2-15 sec, 99-99.99%
Advanced Metering Interface (AMI)
100 kbps/node, 0.5-2 sec, 99-99.99%
Demand Response (DR)
Distributed Energy Resources and Storage (DER) 100 kbps/node, 0.02-15 sec, 99-99.99%
100 kbps/vehicle, 2 sec-5 min, 99-99.99%
Electric Vehicles (EV)
(Most Stringent: 2 Mbps/home, 0.02 seconds, 99.999%)
Neighborhood Area Network (NAN)
Wide Area Network (WAN)
500 kbps/node, 2-15 sec, 99-99.99%
Advanced Metering Interface (AMI)
500 kbps/node, 2 sec, 99-99.99%
Demand Response (DR)
Distributed Energy Resources and Storage (DER) 500 kbps/node, 0.3-15 sec, 99-99.99%
100 kbps/vehicle, 2 sec-5 min, 99-99.99%
Electric Vehicles (EV)
100 kbps/vehicle, 0.1 sec-1 sec, 99-99.999%
Distribution Automation (DA)
(Most stringent: Gbps (variable), 0.02 seconds, 99.999%)
Advanced Metering Interface (AMI)
Demand Response (DR)
Distributed Energy Resources and Storage (DER)
Wide Area Situational Awareness (WASA)
Electric Vehicles (EV)
Distribution Automation (DA)
500 kbps/node, 2-15 sec, 99-99.99%
500 kbps/node, 2 sec, 99-99.99%
500 kbps/node, 0.3-15 sec, 99-99.99%
600-1500 kbps/node, 0.02-0.2 sec, 99.999%
100 kbps/vehicle, 2 sec-5 min, 99-99.99%
100 kbps/vehicle, 0.1 sec-1 sec, 99-99.999%
TABLE I
S UMMARY OF S MART G RID FUNCTIONS AND THEIR COMMUNICATION NETWORK ASSIGNMENTS . F OR EACH NETWORK TOTAL FOR BANDWIDTH ,
LATENCY AND AVAILABILITY REQUIREMENTS ARE PRESENTED , WITH MOST STRINGENT REQUIRMENTS LISTED ( AS INDICATED BY THE D EPARTMENT
OF E NERGY [4]).
B. Smart Grid Communication Networks
Four of the functions of Smart Grid span over all three
communication networks. Advanced Metering Infrastructure,
Demand Response, Distributed Energy Resources and Storage,
and Electric Vehicle would have communication needs in the
entire Smart Grid network. A summary of all Smart Grid
functions and their assignments are presented in Table I. For
each telecommunication network section, the total bandwidth,
latency and availability requirements are presented. Please
note, that for each communication network requirement, the
most stringent requirement is selected [4].
C. Home Area Network Communication Technologies
Home Area Network is the last hop of next-generation
Smart Grid networks [5]. The design envisions that the network shall be a one-hop network from each individual smart
appliance to a concentrator device. This device shall be in
charge of collecting the home information and sending it to
the utilities. The concentrator device is commonly referred as
a Smart Meter, and it is already available for purchasing. In
general, smart meters come equipped with at least two network
interfaces - one or more for inside communication and one
for outside communication. The outside interface connects the
Smart Meter to the Neighborhood Area Network (NAN), and
the inside one is used for connection to all smart appliances.
NAN communication network is outside the scope of this
paper.
There are two types of communication architectures envisioned to be used as last hop for Smart Grid: Power Line
Communication (PLC) and wireless transmission technologies.
PLC makes use of existing in-house power line infrastructure
to transmit data and control signals. The main advantage of
those technologies is that power lines have extended to every
residence with multiple outlets installed in each room. The
candidates protocols for HAN communication via PLC are
X-10, Insteon, PLC-BUS, LonWorks and HomePlug. While
the industry had not converged, the predominant technology
used in installation today is Zigbee, followed by HomePlug
[4]. In North America, wireless is the dominant technology
of choice for HAN while in Europe PLC is the leading
technology. According to study conducted by General Electric,
WiFi (802.11n) and Zigbee are the two technologies that best
meet HAN requirements [6]. One of the main reason for that
being cost effectiveness, and flexibility in contrast to any wired
based technology.
The remainder of this paper is organized as follows: Section
II gives an overview of Zigbee in regards to Smart Grid,
including Smart Energy Profile Protocol. Section III presents a
theoretical model for calculating the performance of Zigbee’s
SEP protocol in regards to AMI and DR functions. Finally,
theoretical results are shown in Section IV. Our conclusion is
drawn in section V.
II. Z IGBEE IN H OME A REA N ETWORK
A. IEEE802.15.4 and Zigbee Relatioship
IEEE 802.15.4 is part of the IEEE family of standards for
physical and link-layers for wireless personal area networks
(WPANs). The WPAN working group focuses on short range
wireless links, in contrast to local area and metropolitan area
coverage explored in WLAN and WMAN working groups,
respectively. The focus area of IEEE 802.15.4 is that of low
data rate WPANs, with low complexity and stringent power
consumption requirements. The standard is designed to be
a cost effective, low-power, and low-interference technology.
The technology operates on the same 2.4 GHz ISM band as
WiFi, Bluetooth and WiMax [7]. Depending on the environment and the power used for transmission, IEEE 802.15.4
compliant wireless devices are expected to transmit in a range
of 10 to 75 meters [8].
The Zigbee Alliance is a group of over 400 member companies that maintain and publish technical standards. Zigbee is a
3
registered trademark of Zigbee Alliance, and the relationship
between IEEE 802.15.4 and the group is similar to that of
IEEE 802.11 and WiFi Alliance. IEEE defines the physical
and medium access layers while the Zigbee Alliance defines
network and application layers. The group recognizes that
the co-existence of different wireless technologies on the
same frequencies can have a significant impact on network
operations.
B. Zigbee Modes of Operation
The channel access mode in IEEE 802.15.4 is carrier
sense, multiple access with collision avoidance (CSMA/CA)
[8]. The network can operate in beacon-enable and nonbeacon-enabled modes. Those modes allow the end devices to
choose their sleep patterns. In non-beacon-enable mode, devices simply transmit data frames using un-slotted CSMA/CA
to the coordinator [8]. Each device must perform two clear
channel assessments (CCA) prior to transmitting. The two
CCA operations ensure prevention of potential collisions.
Each time the channel is assessed as busy via CCA, the
device must back off for a random duration. If the number
of back-offs reaches the maximum, by default set to 5, the
high layer application is informed of communication failure.
Furthermore, in CSMA/CA mode IEEE 802.15.4 supports
optional retransmission scheme based on acknowledgements
[9]. When retransmissions are enabled, the receiver node must
send a positive acknowledgement right after receiving a data
frame. If the acknowledgment is not (correctly) received by
the sender, a retransmission is started unless the maximum
number of retransmissions is reached. In this case, the data
frame is dropped. The maximum retransmission retries can
be set between 0 and 7 with a default value of 3. The
beacon interval/superframe equals to 960 symbols. Depending
on parameters, the range between beacons in 2.4 GHz Zigbee
varies between 15.35ms to 251.7s [10]. The active portion
of the superframe is divided into 16 slots. The default value
of each slot is 60 symbols, with 4 bits per symbol and 0.96
ms per time slot in the 2.4 GHz range. There are three
parts in the active portion: a beacon, a contention access
period (CAP), and a contention-free period (CFP). In the
CAP, all data transmissions shall follow a successful execution
of a slotted CSMA/CA algorithm [22]. The algorithm is the
same as un-slotted CSMA/CA, with the exception that each
operation - channel access, back-off count and clear channel
assessment, can only begin at the boundaries of a basic time
unit called Backoff Period (BP). This period is equal to 80 bits
or 0.32 ms [10].The BP must also align with the beginning
of each superframe. As in un-slotted CSMA/CA, nodes may
transmit after two consecutive successful CCA. For lowlatency applications, upon request from a node, the coordinator
may assign guaranteed time slots to an end device during the
guaranteed time slot (GTS) period. There are a maximum of
seven GTSs in a superframe, and time slots are allowed to
occupy more than one GTP. Prior to transmission the node
must ensure there is sufficient time left in the GAP for the
transmission and any consecutive acknowledgments packets, if
positive feedback option is selected. Multiple data frames may
be sent within a single time slot. The guaranteed portion of the
frame can dynamically shrink or grow; however, a minimum
of 440 symbols, or 7 ms, is reserved for the contention period,
for contention-based access of other networked devices or new
devices wishing to join the network. Due to the time-sensitive
nature of Smart Grid, GTS mode in beacon enabled mode is
assumed to be used.
C. Smart Energy Profile Protocol
In context of Smart Grid, appliances would only implement
4 network layers [11]. Contrary, to the classic OSI model,
transport, session and presentation layers are not present.
The HomePlug Alliance, Wi-Fi Alliance, HomeGrid Forum
and Zigbee Alliance have agreed to create a consortium for
interoperability. In July of 2012, the alliances published a new
draft for Smart Grid application communication as Smart Energy Profile 2.0 Application Protocol Specification [12] [13].
The purpose of the documents is to define the interface and
messages between smart appliances, smart meters and utilities,
to be used by layer 4 Smart Grid applications. The protocol is
defined as HTTPS over TCP based pull mechanism with the
assumption that the pull subscription/notification mechanism
may not be reliable. The TCP protocol is introduced as
part of the application layer. The basic operations in the
protocol are post, put and delete commands. Furthermore,
devices are expected to have intermediate connection to the
network due to sleep cycles. The draft states “to prevent
overwhelming network resources, notifications SHOULD be
sent to a given client for a given resource no more than once
every 30 seconds. Notifications for conditional subscriptions
SHOULD only be sent once within this time period for a given
client for a given resource and any additional notifications
SHOULD NOT be queued. All devices need to be considerate
of network resources.” [12]. Additionally, the end devices
are responsible for pulling network time from the network
controller; however, the granularity of the device time shall be
1 second. By default, smart appliances will have duty cycles
of 90%, meaning that for every 30 minutes, the devices shall
sleep for 3 minutes. These specifications directly contradict
with the requirements published by the Department of Energy
[4], in regards to Advanced Metering Interface (AMI) and
Demand Response (DR) and Distributed Energy Resources
and Storage (DER) applications in home area network (refer
to Table I). Table II presents minimum and maximum Smart
Energy Profile protocol data and control information lengths
(defined in [13]). The message size summary considers all 4
Zigbee layers, and it includes header size for mandatory and
optional HTTP headers (as defined in [12]), TCP and Zigbee
headers.
As it can be see from the summary above, the protocol
defined maximum and minimum lengths for each message
portion, as well as mandatory or optional status. Using the
information provided, we can compute the theoretical minimum and maximum for SEP protocol message. The minimum
considers the lower bound of fields lengths and excludes all
optional HTTP headers, resulting in total length of 508 bytes.
By contrast, the maximum length considers all header field
and their maximum lengths, resulting in 1524 bytes per SEP
message. Those theoretical bounds would be used to calculate
the delay statistics presented in the sections that follow.
III. SEP T HEORETICAL P ERFORMANCE IN HAN
A. Performance in Ideal Conditions
In [14], Koubaa et al. proposed a mathematical model
to compute an upper bound on guaranteed data rate and
4
Type
Length
SEP Status
AMI & DR Application
256-1024 bytes
Mandatory
HTTP Accept Header
36-116 bytes
Mandatory
HTTP Connection Header
17-22 bytes
Mandatory
HTTP Content-Length Header
18-22 bytes
Optional
HTTP Content-Range Header
32-38 bytes
Optional
HTTP Content-Type Header
18-23 bytes
Mandatory
HTTP Host Header
30-100 bytes
Mandatory
HTTP Location Header
20-50 bytes
Mandatory
TCP Header
30 bytes
Mandatory
Zigbee Header
15 bytes
Mandatory
TABLE II
S UMMARY OF SEP PAYLOAD AND CONTROL INFORMATION MESSAGES
AND LENGTHS .
worst case latency in beacon-enabled GTS Zigbee networks.
The authors argued that Zigbee networks are low jitter, and
questioned the general assumption that network clients traffic
is Poisson generated. They recommended the use of a network
calculus (b,r) model since machine-to-machine traffic is cyclical in nature. There are two parameters to the model: an arrival
curve that upper bounds the actual traffic patterns, such that
the received service at any time slice never exceeds the offered
load; and minimum service curve guaranteed to approximate
the actual network service rate. In Figure 1, the arrival curve
(red line) is a function of maximum burst size b, and average
arrival rate r, as to α(t) = b + rt.
Fig. 1.
The GTS (b,r)-based performance model.
The service process is presented by stair function that
approximated IEEE 802.15.4 GTS service behavior, as
BC,T (t) = C ∗ TGT S + C ∗ (t − (2 ∗ BI − TReminder )) (1)
In the stair function, C (green lines) represents the service
rate, which in the case of Zigbee is 250 kbps. During the
Beacon Interval (BI), TGT S is the time during which the client
transmits data, and TReminder is the left over from the clients
GTS slot without any data transmission.
The total data rate of a client is summation of all Beacon
Intervals: all data transmissions in the previous time slots (k1), plus data transmission in the current time slot (k), or
X
Bstair =
BC,T (t)
(2)
The maximum horizontal distance (Dmax ) indicates the
delay bound, occurring immediately after the initial burst
period (the intersection of α(t) and the y-axis). Depending
on the transmission rate C, the horizontal delay line may or
may not intersect with the service curve during service cycle
1 (where k is the cycle index). As such, the initial burst may
not get serviced until a number of cycles later. To illustrate in
Figure 1, the initial burst gets serviced over the first 3 cycles.
The maximum delay bound is expressed as
b
+ (k + 1) ∗ BI − (TGT S + TReminder ) − k ∗ TGT S
C
(3)
We proceed to calculate guaranteed bandwidth and delay
bound for AMI and DR functions over SEP protocol in Smart
Grid’s HAN.
Dmax =
B. Performance in Real World Conditions
For the purposes of Smart Grid, 2.4 GHz ISM band must
be used. This is due to data rate requirements of around
300 kbps per node in home area networks (refer to Table
I), and the data rate limitations of the alternative two band.
This is the same frequency band as that used by the IEEE
802.11 standard. In North America, all but 2 Zigbee channels,
25 and 26, out of the 16 available are non-overlapping with
WiFi channels. Further, channel 26 is not legal in number of
locals and it is not supported by certain standards. In Europe,
WiFi channels have a different assignment, and only Zigbee
channels 15, 16, 21, 22 are non-overlapping with WiFi [15]. It
is a safe assumption that Home Area Network in Smart Grid
would experience interference from WiFi networks. Liang at
al. [16] conducted a thorough investigation of Wi-Fi to Zigbee
interference. The research was motivated by observations
made during a large conference (well above 7,000 attendees),
where the reachability of individual nodes in a Zigbee based
sensor network dropped down to 40% at worst. Given that
observation, an experiment was conducted with a pair of
Zigbee sender and receiver nodes and a pair of 802.11b/g
based interferers. The distance between the two networks was
varied between 15 to 170 feet, in order to characterize the
spacial effect. The authors found that in case of 802.11b the
ZigBee network packet loss/corruption varied between 99% at
15 feet to 30% at 170 feet. The authors noted that by using
CSMA/CA, Zigbee was able to detect WiFi transmission and
back-off as per protocol requirement. On the contrary, WiFi
was not able to detect Zigbee transmission via CSMA/CA
if the distance between the Zigbee transmitter and the WiFi
receiver was more than few meters. The authors concluded this
was due to the difference in transmission power between the
two: 16 dBm for Wi-Fi and 0 dBm for Zigbee. As such, a large
number of Zigbee packets were corrupted due to pre-emptive
(non-detected Zigbee channel occupancy) WiFi transmission.
5
Furthermore, in [17], Ghosh el al. conducted a large scale
WiFi traffic investigation in public hot-spots and showed the
probability of the number of WiFi clients present at any
given time. The investigation concluded that, the probability
of having at least one WiFi client was above 99.999%, and the
probability of having 10 or more clients was above 93%. We
can safely assume, that in during normal HAN operation in
home or business setting, Zigbee based networks would have
to overcome interference from WiFi networks.
To account for this fact, the theoretical performance model
is further extended to include the effect of WiFi interference,
taking into account the probability of Zigbee successfully
accessing the channel. We can assume that WiFi traffic pattern
are independent of Zigbee [18]. We can model the probability
of transmission of Smart Appliance during it’s assigned timeslot as product of the probability of sensing clear channel and
number of allowed re-tries, or
Cadj = p ∗ C 0 ∗
4
X
(1 − p)i
(4)
i=0
where p is the probability of Clear Channel Assessment and
C 0 the reminder of the GTS bandwidth. The equation captures
Zigbee’s protocol specification, as the node performs a backoff
after each unsuccessful transmission attempt. The backoff
interval is uniformly distributed and there is a maximum of
5 re-transmission attempts before channel access failure is
declared.
IV. M ODEL R ESULTS
Using the model presented in the prior section, we compute
theoretical SEP performance over Zigbee.
Parameter
Value
Duty Cycle
1
λ
1/16
Service Rate
250 Kbps
Protocol Overhead
12%
Beacon Duration
960 symbols (480 bytes)
Superframe interval
0.00192 sec
CAP size
440 symbols (4 bits/symbol)
Burst size
508-1524 bytes
Prob. of Clear Channel
0.1-99%
GTS allocation
1-7
TABLE III
S UMMARY OF PARAMERES USED IN MODEL COMPUTATION .
Table III presents the parameters used in the computation.
It is assumed that in the context of Smart Grid, appliances
would have sufficient power and therefore would not have a
sleep cycle, resulting in a duty cycle of 1. This means that the
entire portion of the Zigbee frame would be active and used
for communication. Since AMI and DR function are delay
sensitive, we assume that the minimum Superframe duration
is used, which results in Beacon Interval of 960 symbols, or
1.92 ms at 250 Kbps. Furthermore, minimum CAP interval per
protocol requirement is assumed, and each smart appliance is
assigned one or more GTS. The SEP protocol message size
has a minimum of 508 and maximum of 1524 bytes (Table II).
This is the length of one message, however due to the SEP
PULL mechanism design, each AMI or DR message would
require two transaction - one to query the smart meter, and
one response from the smart meter. One GTS slot is assumed
to take up to 1/16th of the Superframe duration and the Zigbee
protocol overhead is set at 12% (consistent with [14]). The
results presented in this section, do not include any processing
time, or further delay in the rest of the Smart Grid Network.
The only delay presented is the last hop delay experienced
during the final information handoff between the Smart Meter
and the smart appliances. In Figure 2, the theoretical delay
and guaranteed throughput of the SEP protocol over Zigbee
wireless links are presented as a function of the number of
GTS assignment per device. As indicated previously, Zigbee
can support up to 7 GTS clients, or 1 client with a maximum of
7 combined GTS. As expected, the guaranteed throughput has
linear relationship to the number of GTS time-slots assigned.
The minimum value is around 13.5 Kbps, and the maximum
is around 95 Kbps. The delay experienced, on the other hand,
is not linear and has a significant drop as the number of GTS
assigned slots increase. These results are somehow expected,
since with a single assigned time-slot the client has to wait for
most of the Superframe duration before transmitting. As the
number of assigned slots increases, the client spends less time
waiting and more time transmitting, thus achieving, higher
combined throughput and resulting in lower delay. After 3
or more GTS time-slots the delay is not reduced significantly,
since most of the SEP message data can be transmitted in one
or two cycles. From the results, we can conclude that with
1 assigned GTS time-slot, a SEP message would experience
delay between 1.10 and 3.35 sec; however, as for 3 time-slots
the delay drops to 0.1 and 0.034 sec. If all 7 time-slots are
assigned to a single smart appliance the Zigbee link delay drop
down to 0.015 and 0.043 sec. This is the theoretical minimum
delay.
The analysis is further extended to include effect of WiFi
interference, resulting in unavailable channel for Zigbee transmission. In Figure 3, the y-axis extends to 15 second, which
is the maximum delay for AMI function (Table I). The results
indicate that at 20% probability of clear channel assessment
and 1 assigned GTS, the delay is above the maximum allowed
(point A on the graph). In the case of 1 GTS, even at 99%
probability of clear channel assessment the delay bound is
3.6 seconds (point C), which is unsatisfactory for Demand
Response. Consistent with Figure 2, the delay drops sharply as
the number of assigned GTS slots are increased (slope between
points C and D). The minimum theoretical environment that
satisfies AMI requirements of 15 sec delay in the case of
7 GTS assignment is around 2.5% clear channel probability
(point F). The last two points shown on the graph, points B and
E, represent the boundary for probability of clear channel assessment parameter after which performance degrades rapidly.
Table IV presents summary of the the points of interest.
Futhermore, the theoretical operational areas for AMI and DR
functions are highlighted. For AMI most of the regions are
6
Fig. 2. Maximum, minimum delay and guranteed Kbps per client as
a function of number of assigned GTS per client.
included, with the exception of probability of clear channel
assessment under 0.1 for the case of 3 GTS slots or greater, and
0.2 for 2 GTS or fewer. The DR operational region is bounded
by the south corner of the graph and the points (presented
as {GTS, probability of CCA} coordinates): {4, 0.99}, {5,
0.7}, {6, 0.5} and {7, 0.3}. Any area outside of this region
theoretically does not satisfy the DR’s functional requirements.
Point
Prob. of CCA
GTS
Delay
A
0.2
1
15s (greater than)
B
0.5
1
7.1s
C
0.99
1
3.6s
D
0.99
3
0.4s
E
0.1
7
1.02s
F
0.1
7
15s (greater than)
TABLE IV
S UMMARY OF BOUNDRY POINTS OF INTEREST CALCULATED FROM THE
MODEL .
V. C ONCLUSION
In this paper, we presented a performance model of Smart
Energy Profile protocol in regards to Advanced Meter Infrastructure (AMI) and Demand Response (DR) function of Smart
Grid. A Network Calculus formulation was used to evaluate
the performance of Zigbee based Home Area Network in Guaranteed Time Slot mode of operation. The model accounted
for number of GTS assignments per client and interference
caused by co-located WiFi networks. The outputs of the model
are guaranteed throughput per time slot, and minimum and
maximum delay. Results show that each input parameter has
significant impact on the protocol’s performance.
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