IDENTIFYING
TELECOMMUNICATIONS NETWORK NEEDS TO SUPPORT THE DEPLOYMENT OF SMART METERS IN A
WATER UTILITY
Samuel de Barros Moraes
Centro Estadual de Educação Tecnológica Paula Souza, Brazil
E-mail: samuel.moraes@ngdc.com.br
Celi Langhi
Centro Estadual de Educação Tecnológica Paula Souza,
Brazil
E-mail: celi@infolearning.com.br
Marcos Crivelaro
Brazil
E-mail: phdcrivelaro@gmail.com
Submission: 17/06/2014
Revision: 02/07/2015
Accept: 23/07/2015
ABSTRACT
This case study, based on
interviews and technical analysis of a Brazilian water utility with more than
10 million clients, aims to understand what kind of adjusts on a
telecommunications network, developed for operational and corporate use,
demands to support a smart metering system, identifying this synergies and
challenges.
Keywords: smart water, smart grid, telecommunications
1. INTRODUCTION
In the beginning, smart grid was a
term used only in reference of the computer-based systems for meter the
consumption, billing and manage the electricity usage, nowadays, this have been
expanded as functional concept to other utilities companies with similar
services, like water and gas. The smart grid changes completely the reality of
the utility operation, because it allows that actions and decisions be made as
soon as the information be available, what could mean huge savings to the
operation and still provide essential elements to decision making strategies.
Two are the technological bases that
support the concept of Smart Grid, on one hand automatic meters, installed on
consumption points, capable of collecting information in real time. On the
other side, the telecommunication distributed network capable of realizing the
transport of information collected remotely to the data processing centers,
where the billing are generated and the water distribution network management
is done.
The automatic meter system, also
called smart meters, describe the equipment that allow to collect billing and
usage information on the consumption premises and send this to different
business areas, enabling a more integrated management and actualized, or in
real time, information availability.
On the point of view of
telecommunication resources to support the water smart grid, we have as
principal question the demand for connection
between every meter installed in the system and a central point of information
processing.
The concern explored in this
article, consider that the treated water is available to large majority of the
urban population in Brazil, 95% of Brazilian homes, in the southeast region,
are attended by water distribution network (IBGE,
2014), what brings to a necessity of large amplitude communication
network in order to support water smart grids, with connection capacity in all
water distribution points.
2. SMART GRID
Smart Grid systems represent an
application of information technology in service consumption meters, such as
electricity, gas and water. The incorporation of new intelligent meters
integrated to communication system and network infrastructure allow to stablish
a trustful bidirectional communication system with several devices and the also
an active automation systems. With his origin in energy distribution industry,
allowing meter the consumption, billing and the management of electricity use,
this system have been expanded like a functional concept to other utilities
companies with similar services, like water and gas. (VIJAYAPRIYA; KOTHARI, 2011).
The demand for intelligent metering
systems in the water distribution industry comes, among other factors, from the
necessity of a sustainable management of urban systems of water distribution.
As motivators to the adoption of Smart Grids in the water distribution segment,
also called Smart Water Grid, there are external factors including climate
change impact, drought, population growth and the consolidation of urban
centers, leading the water utilities to adopt a more sustainable process in the
water distribution management, especially in urban areas, as opposed to the
processes existent in times of plenty of water
(BOYLE, et al., 2013).
Besides the advantages related to
improvement and simplification of the charging and billing process of the
companies, these systems provide a better control over the consumption allowing
a more effective loss prevention management and the waste of natural resources
associated (BOYLE, et al., 2013). For
example, in case of Brazil the estimate loss in the purified water distribution
process is superior a 37% (SECRETARIA NACIONAL
DE SANEAMENTO AMBIENTAL - SNSA, 2014), what is a clear problem that
demand an urgent action to warranty the environmental sustainability and the
consumption reduction.
Some of the benefits of use a Smart
Water Grid are:
·
Individual consumption reduction. When details of the
consumption are easily accessible, the consumer immediately generates a
reduction up to 15%;
·
Macro scale (city to block) reduction of water
consumption. The smart metering allows identifying non usual water consumption
patterns and consequently helping reduce leakages.
·
Identify seasonal needs of the water consumption. With
real time knowledge of water demand of the population and to anticipate the
volumes of needed resources. This information allows a more functional use of
resources and contributes globally to reduce the consumption.
·
Define a new approach about pricing. The knowledge of
real time water consumption opens the doors to a billing based on seasonal and
even hourly values (GOURBESVILLE, 2011).
3. SMART METERING
There are two kinds of smart meters
used by utilities, Automated Meter Reading (AMR) and Advanced Metering
Infrastructure (AMI), both with origin in the electricity utilities, figure 1
shows the services differences between both devices. The first one, AMR is a
simpler device that allows only Billing and Metering, did not allow the control
of the meter itself, it is an unidirectional device, the information flows from
customer premises to the processing central.
It was the first one in the market,
and a predecessor of the AMI. This second type in addition of the basic
functions, allows a more complex set of functions that leverage to the next
level the control of water distribution, when installed in a customer premises
enable demand-side management and is the start point for the smart grid (CRAEMER; DECONINCK, 2010).
Figure 1:
Differences between AMI and AMR
The concentration of this paper is
in Smart Grid using AMI technology, which is based in connections between
hardware components and pieces of software. Where smart meters in the customer
side, the premise area network (PAN), within the same neighborhood, equipped
with wireless communication interfaces, are connected to a central unit, called
neighborhood area network (NAN). Each NAN is connected to the wide area network
(WAN), also called backhaul, which provides consolidation for metering data.
All data sent by smart meters and other control devices are relayed to an
operation central where is running a management application for data
processing.
4. TELECOMMUNICATIONS
The three levels of communication
network, as showed in figure 2, are used to support smart grid application. The
telecommunication network in smart grid has to support all smart grid
functionalities and meet the performance requirements. As the infrastructure
connects a huge volume of devices and manages the complex communications
between them, the better approach is developed a hierarchical architecture with
interconnected sub networks and each one being responsible for a unique
geographical region. Normally, the communication networks are divided into
three levels: wide area networks – WAN, neighborhood area networks - NAN and
home area networks - HAN (WANG, et al., 2011).
Figure 2: Network levels
4.1.
Home area networks
Home area networks (HAN) are needed
in the customer domain, because besides water measurement they can support the implementation of
monitoring and control of smart devices in customer premises and to implement
new functionalities and advanced applications such as demand management,
response and control events remotely, acquire real-time information, automatic
fault detection and isolation. (CRAEMER:
DECONINCK, 2010).
Typically, they can be based in
wireline (e.g., Ethernet) or wireless (e.g., ZigBee) communication mediums. And
each smart device, alone, has a low demand for bandwidth, with small pieces of
information send periodically, and also it is not affected by transmission
delay. The issue is the aggregate demand for bandwidth, when the need of each
device is added to another in the same neighborhood area networks.
The table 1, based on the work of
Kuzlu, Pipattanasomporn, & Rahman (2014), shows the individual demand of a
smart meter; it shows the amount of data and frequency of this communications
for the most important information exchanged between the smart meters and the
central data processing facilities.
Table 1-Network usage
|
Application |
Typical
data size (bytes) |
Typical
data sampling requirement |
Latency |
|
Meter reading – scheduled interval |
1600–2400 |
4–6 times per residential meter per day (24 / 7),
12– 24 times per commercial/industrial meter per day |
<4 horas |
|
Neighborhood area network administration (from
utility to customer devices) |
25 |
As needed (24 / 7) |
<20 s |
|
Firmware updates (from utility to devices) |
400K–2000K |
1 per device per broadcast event (24 / 7) |
<2 min – 7 days |
|
Program/configuration update (from utility to
devices) |
25K–50K |
1 per device per broadcast event (24 / 7) |
<2 min – 3 days |
4.2.
Neighborhood
area networks
Neighborhood area networks (NAN)
form the communication facility for the water distribution systems, in ideal
world it will be the same infrastructure for all utilities, in a kind of shared
services. The application residents in the operation center utilize field area
networks to share and exchange information with the smart meter in the home
area network. These applications may be related to distribution facilities,
sensors, system regulators, etc. or customer based related to end customers,
like houses, buildings, industrial users, etc.
Each of these operational
applications has different critical requirements. For example, customer based
applications require the communication network between the utility and the
customer premises be highly scalable, allowing addition of more applications
and customers in future and are not time sensitivity (KUZLU, et al., 2014).
At this point, occur the traffic
aggregation from all the home area networks located in the same neighborhood,
it may sum the messages of thousands of devices, each one trying to send
information to the central data processing facilities at the same time.
4.3.
Wide
area networks
Wide area networks (WAN) are the
communication backhaul allowing the connection of the highly distributed field
area network, which aggregates the information produced in each customer
premise. These real-time measurements taken at the metering devices are
transported to the operation centers through the wide area networks and, in the
inverse direction, the wide area networks transport the instruction from
processing centers to the end consumers premises
(KUZLU, et al., 2014).
For use of smart grids the needs of
telecommunications corresponds to aggregated demand of the NANs, which are
constituted by the aggregated volume of all meters installed in the homes.
5.
METHOD
AND DISCUSSION
The survey about the existing
network were executed on the period of 05/16/2014 to 06/23/2014, in which the
researchers had access to electronic and print documentation of a big utility
in southeast region of Brazil, where it was possible to verify the amount of
the corporative communication circuits, its contracted velocities, amongst
other technical characteristics.
There are two kind of networks to
support the corporate demands of the utility studied, Frame Relay an old
technology more common in the network, and it is in replacement process MPLS,
both are nowadays in use for corporate applications. As shown in Figure 3, 62%
of the telecommunications services are based in Frame Relay technology, which
means small bandwidth.
Figure 3: Number of
circuits
As definition, multiprotocol label
switching - MPLS - is an evolving technology that assures permanent and steady
delivery of the communications services with lower network delay, efficient forwarding
technique, scalability, high transmission speed and guaranteed performance.
This features of MPLS technology makes it as an one of first choice to
effective implementations for backbone communications and computer networks (SLLAME, 2014).
In other side, frame relay is a
legacy protocol, a simplified form of packet-mode switching that provides
access to high bandwidth on demand, direct connectivity to all other points in
the network. To the customer, the frame relay technology offers a reduction in
the cost of transmission lines and equipment and improved performance and
response time. It was developed in nineties by vendors like StrataCom, Digital
Equipment Corporation, Cisco Systems and Northern Telecom (RODEN; TAYLER, 1993).
Figure 4 shows the difference of
bandwidth available in the complete utility corporate network, for all the
services, is possible to identify that the actual service is based in slow
capacity of transmission, indicating that 80% of the service speed is below
1Mbps.
Figure 4: Percentage of
circuits by bandwidth
This article uses as base for an
estimative demand of telecommunication network, the average number of houses
connected in general network of water distribution per city, based on IBGE 2010
census, this study are restricted to southeast region of Brazil, and consider
the average between all the states, the numbers are shown in table 2 (IBGE, 2014).
Table 2 - Houses
connected to general network of water distribution
|
State |
Houses
connected to general network of water distribution |
Quantity
of municipalities in the state |
Average
of houses connected per cities |
|
Espírito Santo |
857.048 |
92 |
9.316 |
|
Minas Gerais |
4.995.630 |
645 |
7.745 |
|
Rio de Janeiro |
4.089.699 |
78 |
52.432 |
|
São Paulo |
11.605.702 |
853 |
13.606 |
|
Totals |
21.548.079 |
1668 |
12.919 |
Below, in figure 5, are showed the
consumption of bandwidth in function of the size of the most common message, as
seen in table 1, sent by the smart meters to the operation control center. Is
possible to see that for a bandwidth smaller than 1Mbps the time needed to
complete transfer of the messages is about 8 minutes. How bigger is the amount of bandwidth
available less is the time needed to complete the transmission, trend to be
near 1 second to complete the data transfer. For this study, there is no
consideration about concurrent communications in the network, because the
better case is aim of the article.
Figure 5: comparative
bandwidth usage in function of smart meter message size
6.
CONCLUSIONS
The impact of smart meter data over
an existing network is very significant for slow telecommunication services.
The network evaluated in this article needed to be upgraded in order to be able
to support a smart grid network application.
There is another issue related to
the definition of data aggregation. The
utilities must understand where they will install the NAN to be capable of sum
the information generated by the spread distribution of the smart meters.
Considering that in this paper are
used an average city, and in Brazil southeast region there are some cities with
more than 2 million inhabitants, which means a huge problem to connect every
house to a collect network.
There is an imperative force to move
forward from legacy networks to the Internet Protocol (IP) based ones, this
transformation brings the promise of cost savings and agile, speedier networks.
But, the changes also carry implications for utilities, even for those that are
already moving aggressively, because the effort to evolve the network will
affect the way the company use telecommunications today, in some cases involve
changing data processing technology and equipment.
REFERENCES
BOYLE, T. et al. (2013) Intelligent Metering for Urban Water: A Review. Water,
v. 5, n. 3, p. 1052-1081.
CRAEMER, K. D.; DECONINCK, G. (2010) Analysis of state-of-the-art smart metering
communication standards. s.l., s.n.
GOURBESVILLE, P. (2011) ICT for Water Efficiency. Nice,
Dr Ema Ekundayo, p. 411-426.
IBGE (2014) Síntese de Indicadores Sociais. Available at: http://saladeimprensa.ibge.gov.br/noticias?view=noticia&id=1&busca=1&idnoticia=2722
[Acesso em 27 10 2014].
KUZLU, M.; PIPATTANASOMPORN, M.; RAHMAN, S. (2014). Communication network
requirements for major smart grid applications in HAN, NAN and WAN. Computer
Networks, p. 74-78.
RODEN, R. J.; TAYLER, D. (1993) Frame Relay Networks. Digital Technical Journal,
v. 5, n. 1, p. 1-8.
SECRETARIA NACIONAL DE SANEAMENTO AMBIENTAL - SNSA (2014) Diagnóstico
dos serviços de água e esgotos - 2013, Brasília: Ministério
das Cidades.
SLLAME, A. M. (2014) Modeling and simulating MPLS networks.
s.l., IEEE, p. 1-6.
VIJAYAPRIYA, T.; KOTHARI, D. P. (2011) Smart Grid: An Overview. Smart
Grid and Renewable Energy, p. 305-311.
WANG, W.; XU, Y.; KHANNA, M. (2011) A survey on the communication
architectures in smart grid. Computer Networks, 27-07, n. 55,
p. 3604-3629.