Next Generation Networks for Telecommunications Operators

Providing Services to Transnational Smart Grid Operators

Gurkan Tuna

, George C. Kiokes

, Erietta I. Zountouridou

and V. Cagri Gungor

Department of Computer Programming, Trakya University, Edirne, Turkey

Hellenic Air-Force Academy, 1010 Dekeleia, Attica, Greece

National Technical University of Athens, Iroon Politechniou 9, Athens, Greece

Department of Computer Engineering, Abdullah Gul University, Kayseri, Turkey

Keywords: Smart Grid, Smart Grid Applications, Next Generation Networks, Performance Evaluations.

Abstract: Due to the networking expertise, services and technical support of telecommunications operators, Smart

Grid (SG) operators prefer telecommunications operators for their communications needs instead of creating

private networks. In this paper, the use of Next Generation Networks (NGNs) by telecommunications

operators to provide services to transnational SG operators for SG applications is evaluated. NGNs are all IP

networks which are packet based and use IP to transport the various types of traffic such as data, voice,

video, and signalling over converged fixed and mobile networks. The main idea of transnational SG

operators is simple. By creating a huge single infrastructure for energy, more than one countries and nations

can be powered at once. For this, it is not needed to install very huge power plants. Simply creating a

complex network of power grid connections to each participating country is enough. The results of a set of

simulation studies are given to show the efficiency of the NGN-based communication infrastructure for SG

applications in terms of important network performance metrics. The results show that NGN-based

communication infrastructures can carry packets based on their priority levels and bandwidth allocations in

order to meet the specific requirements of SG applications.

1 INTRODUCTION

Considering environmental concerns, limited

infrastructure is seen as one of the biggest

constraints in green energy since it is not easy to

shift to a totally different energy source and adapt of

new energy technologies. On the other hand, if

renewable energy systems are designed to provide

power to many countries and nations, it is possible

to connect each of their national energy systems

together. However, if transnational Smart Grids

(SGs) are designed, more economical issues and

complexities than national SGs if purely fuel-based

energy systems are involved. With renewable

energy, the problems may not be completely

resolved, but at least it will be possible to

concentrate more on the distribution of the SG’s

energy output to the entire grid. For national power

grids, load balancing may be a serious issue if

individual or single location-based renewable energy

systems are involved, but with a transnational power

grid, the problem of intermittency may be solved by

involving solar or wind farms connected to the grid

that would always supply energy. In this way, the

transnational power grid will basically just shift

energy loads to the connected countries.

To fully exploit the benefits of Smart Grid (SG),

many applications with varying levels of QoS,

reliability, robustness and security for different

purposes have been developed. The applications deal

with different issues including demand and response

management, asset management, and outage

management. Since, in the SG with an advanced

communication infrastructure, various types of data

are required to communicate efficiently with

different degrees of QoS, reliability, robustness, and

security (Gungor et al, 2010; Livgard, 2010; Moghe

et al, 2009; Sood et al, 2009). Therefore, the

communication infrastructure requires end-to-end

reliable two-way communications, and

interoperability between applications with sufficient

bandwidth and low-latencies (Erol-Kantarci and

Mouftah, 2011).

231

Tuna G., Kiokes G., Zountouridou E. and Gungor V..

Next Generation Networks for Telecommunications Operators Providing Services to Transnational Smart Grid Operators.

DOI: 10.5220/0005523902310238

In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics (ICINCO-2015), pages 231-238

ISBN: 978-989-758-123-6

 2015 SCITEPRESS (Science and Technology Publications, Lda.)

To the best of our knowledge, in the literature

there are no prior studies evaluating the

effectiveness of Next Generation Networks (NGNs)

by telecommunications operators for utility

applications in large scale SG deployments of

transnational SG operators. Therefore, in this paper,

we focus on the use of NGNs for smart grid and

evaluate its effectiveness. The contribution of this

paper is twofold. First, the use and advantages of

using an NGN-based communications infrastructure

are presented. Second, with the result of a set of

performance evaluations, the effectiveness of NGNs

for SG applications is shown. The rest of the paper is

organized as follows. A description of the SG

infrastructure is given in Section 2, focusing on the

data communication properties, followed by an

introduction to SG applications and their

communication requirements. Section 3 presents the

use of NGNs for SG applications and discusses

implementation aspects. Section 4 presents

performance evaluation. Finally, Section 5

concludes the paper.

2 SMART GRID

COMMUNICATION

INFRASTRUCTURE

As shown in Figure 1, the communication

infrastructure can also be considered to consist of

three different transmission categories: 1) Wide

Area Network (WAN), 2) Neighborhood Area

Network (NAN) and 3) Home Area Network (HAN)

(Gungor et al, 2013). Between these three networks

the core backbone, backhaul distribution and the

access points are located. These transmission

categories are briefly described below.

 WAN: Basically, it is a high bandwidth, two-

way communication network which can handle

long-distance data transmissions for

automation and monitoring of SG applications.

It provides all the communications between the

substations and the electric utility. In order to

be fully effective and scalable, it covers all the

substations, the distributed power and the

storage facilities along with any distribution

assets such as transformers, capacitor banks

and reclosers (Moghe et al, 2009).

 NAN: It is a broadband wireless resource and

uses low bandwidth channels which meet the

requirements for reliable and robust

communications. It is developed between

customer premises and substations with the

deployment of intelligent nodes to collect and

control the data from the surrounding data

points and includes the communication

between individual service connections, such

as devices destined for distribution automation

and control, and backhaul points to the electric

utilities (Sood et al, 2009).

 HAN: It is a dedicated network which allows

transfer of information between various

electronic devices in the home, including home

electrical appliances, smart meters, in-home

display devices, energy management devices,

distributed energy resources. It also contains

software applications to monitor and control

these networks. It enables consumers to get

information about the consumption behaviors

and the electricity usage costs via in-home

display devices or through a web interface.

Figure 1: Smart Grid communication infrastructure.

2.1 Common Smart Grid Applications

In this subsection, major applications that can be

found in a SG are briefly discussed along with their

communication requirements.

 Substation Automation: All devices in a

substation are controlled, monitored, and

managed by Substation Automation Systems

(SASs). They gather the data and perform

routing and other operations, to make the

system efficient, reliable, secure, and well

responsive, with reference to real-time

communication. The network technology is the

key element in SASs to provide for full control

over the devices, monitoring the operations,

conditions of devices, and also the operations

of substations. A successful deployment of a

SG system always requires the effective and

efficient communication infrastructure, which

can be selected based on various network

communication technologies. Wireless

communication technologies that can be

adopted in SASs are WiMAX or wireless mesh

networks. Moreover, cellular network can be

preferred for remote operations and

maintenance at remote sites. Similarly,

Wireless Local Area Network (WLAN) can be

preferred to protect, monitor, and control the

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distributed energy resources where data rate

requirements are less.

 Overhead Transmission Line Monitoring

(OTLM

): OTLM is one of the important

operations

of Transmission and Distribution

(T&D) side SG applications, because

overheating, icing, and lightning strikes always

create vulnerability to the SG transmission

lines. It monitors T&D systems to reduce the

risk of failure. Wireless sensor nodes are

deployed over the transmission lines and

communicate via relays, to notify about the

transmission lines and provide effective

monitoring.

 Home Energy Management (HEM): It is

generally considered at consumer side, where

home equipment can be monitored and

controlled. HEM can provide energy

efficiency, data measurement, transmission,

optimization, and balance to consumption and

power supply. Advance control systems, in-

home displays, smart appliances and smart

meters are the main components of HEM.

Mesh topology may be preferred in this type of

system, which can provide higher reliability to

various data paths.

 Advanced Metering Infrastructure (AMI): It

provides a handshake communication between

utility systems and smart meters and combines

a variety of computer hardware, software, data

management systems, monitoring systems,

smart meters, and advanced sensors. In this

way, it collects the distributed information

from utilities and meters. AMI is a complex

structure system, which requires efficient IT

and communication infrastructure, such as,

meter data management system which monitors

and manages a large amount of data in efficient

way to inform consumers and to maintain the

billing information in a more intelligent way

(Lu and Gungor, 2009).

 Wide-Area Situational Awareness (WASA):

WASA is basically a set of technologies which

provide an overall, dynamic picture of the

operation of the grid. One of the key functions

of SGs is monitoring and situational awareness

to get reliability, protection, and

interoperability among so many interconnected

devices and systems. Any abnormalities can

result in a widespread problem that endangers

the system’s dependability and protection.

 Demand Response Management (DRM): To

reach a balance between demand and supply of

electrical energy, DRM is responsible for

controlling the energy demand and loads

during critical peak situations (Quak et al,

2002).

 Asset Management (AM): The management of

SG assets and the data they create requires the

ability to capture, store and visualize data

pertaining to asset status, performance and

real-time risk. For this objective, asset

management systems play a key role.

 Future T&D Systems: By the integration of a

SG, the distribution and transmission

infrastructures of existing power grids can be

renewed for better reliability and flexibility to

AC transmission systems. In urban areas,

renewable energy sources, such as High-

voltage DC (HVDC) technologies, may be

used.

 Renewable Resources: In last few decades,

there is a tremendous growth in the use of wind

power generators and distributed solar plants.

 Advanced Forecasting Algorithms: In recent

years, power demand has rapidly increased

(Wagenaars et al, 2009) in the USA. Proper

estimation of demand can provide better

planning for the electricity generation. It can be

promising to introduce SG technologies to

existing systems to enhance the generation

resources by robust two-way communications,

active customer participation, dynamic pricing

schemes, and other flexible technologies.

In addition to the abovementioned applications,

Meter Data Management (MDM), Distribution

Automation (DA), Distribution Management (DM)

and Outage Management (OM) are also important

applications

3 NEXT GENERATION

NETWORKS FOR SMART

GRID APPLICATIONS

Since SG concept relies on the seamless integration

of the traditional power grid infrastructure with a

sophisticated advanced communication

infrastructure (Gungor et al, 2013), the

communication infrastructure plays a key role for

the overall system and moves different types of data

with different communication requirements and

varying degrees of reliability, Quality of Service

(QoS), and security. Therefore, it must be flexible,

interoperable, scalable, and secure to meet the

communication requirements of each SG component

(Tuna et al, 2013; Amin and Wollenberg, 2005;

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Yigit et al, 2014; Yang et al, 2007). A list of the

common requirements of SG applications is given as

follows.

 Data rate: Different SG applications require

different data rates. For instance, the data rates

for some SG applications such as SASs,

OLTM, DA, AMI, DRM, HEM, OM, AM,

MDM, DM, Distributed Energy Resources and

Storage (DERS), Vehicle to Grid (V2G), and

Electrical Vehicles Charging (EVC) are low,

typically <100Kbps (ALCATEL, 2014). On the

other hand, a few applications which transmit

audio and video data require higher data dates,

such as WASA, require data rates of 1-

1.5Mbit/s (Gungor et al, 2013).

 Throughput: Throughput requirements are

different for each specific SG application.

 Latency: Some SG applications such as AMI,

HEM, OM, AM, MDM, V2G, and EVC can

tolerate latencies up to 2 sec (Gungor et al,

2013). On the other hand, mission-critical SG

applications such as WASA may not tolerate

such high latencies.

 Reliability: Although most SG applications

need highly reliable data communication, some

specific SG applications can tolerate short

outages during data transfers (Moslehi and

Kumar, 2010).

 Frequency Range: To achieve reliable and

high-quality data communication, and

overcome environment-specific problems and

line of sight issues such as penetration through

walls, rain fade and foliage lower frequency

ranges (<2 GHz) are preferred in the service

area of electric utilities (Kilbourne and Bender,

2010; Sahin et al, 2014).

 Security: The critical data gathered from

various SG components must be protected

against both physical and cyber attacks (Leon

et al, 2007).

Considering the application specific

requirements of different SG applications along with

the integration with different access networks and

complexity introduced by heterogeneous network

infrastructures, meeting the QoS requirements of SG

applications becomes a significant performance

issue. Moreover, fixed and wireless access networks

converge towards IP based transport in SG

networks. Therefore, addressing the requirement for

scalable and effective control and management

becomes critical. To address this challenge, policy-

based management tools can be employed. To meet

QoS requirements of SG applications, network

designers should take into consideration several

parameters including bandwidth, delay, jitter, and

packet loss rate, and employ various mechanisms

such as rerouting in the core of the network control

access at the corners of the network, and filters.

Moreover, for some SG applications, meeting the

QoS requirements is not enough. In addition to this,

Quality of Experience (QoE), users’ perception of a

provided service, should be enhanced. Finally, some

SG networks should facilitate a single party to

establish QoS-enabled path between the two IP

providers mutually interconnected by one or more

transit providers (Stojanovic et al, 2013). Therefore,

negotiating and maintaining an end-to-end service

level agreement is needed.

For the seamless transformation from traditional

power grids to SGs, especially in large-scale SG

deployments, electric utilities can employ NGNs for

their communications infrastructures. The NGNs are

packet based networks and use IP to transport the

various types of traffic, e.g. data, signalling, voice

and video. They are fully managed services

platforms which combine multiple services over a

single access line (ETSI, 2014) and enable the

deployment of access independent services over

converged fixed and mobile networks to provide

flexibility, scalability and security at maximum cost

efficiency (Lovrek et al, 2011). IP Multimedia

Subsystem (IMS) can be viewed as the core

component of the NGNs and provides an access

independent platform for a variety of access

technologies (ITU, 2006). The NGNs offer many

advantages to SG operators which install and

manage their communication networks as well as the

ones who use the services provided

telecommunication operators.

For telecommunications operators, SG is an

opportunity to expand their businesses into the

energy market and become established players in the

electricity value chain. There is an urgent need for

this since in the SG each consumer location has a

piece of equipment, collocated with the smart meter,

that communicates information related to usage,

demand-response triggers, and failures to another

unit aggregating the information of multiple smart

meters and ultimately communicating the aggregated

data to the main SG operations center. Therefore,

telecommunications operators can offer competitive

services to SG operators in terms of investment cost,

operational complexity, reliability, and flexibility.

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4 PERFORMANCE

EVALUATION

Different from the traditional power grids, for the

SGs, the communication infrastructure plays a key

role for the overall system performance. Therefore,

there is a need to predict and analyze in time the

behaviour of NGNs for SG applications in terms of

major network parameters. The main objective of

the performance evaluation study presented in this

section is to analyze the effectiveness of NGNs for

SG applications with different priorities in large

scale SG deployments using the OPNET Modeler

(Riverbed, 2014). The performance evaluation study

is based on the Asynchronous Transfer Mode

(ATM) (Kouvatsos, 2002) protocols and architecture

modified to SG system requirements. Inside the

network, the packets are sent with random priority

from one to three, one being the highest weight

factor and three being the lowest as it is defined for

NGNs, in the control plane service layer with

uniform distribution, and are stored in several

buffers in the network with different priorities. The

nodes are outspread in large cities in the

geographical area of Turkey and Greece in order to

create a specified wide area network (WAN) which

occupies almost 500.000 Km

area and

interconnected through the Getaway node. As

shown in Figure 2, the topology study includes

twenty one nodes-cities which function as end users

(clients) and two gateways cities which

communicate between each other, Istanbul for the

Turkish region and Athens for the Greek region

through they pass all the data.

Figure 2: Next generation network nodes-cities location

for the two countries.

The explanation of the priority levels is given below.

 Priority level 1: It has the higher acceptance

indemnity in the network. This priority is

addressed in emergency telecommunications

over the NGN and data services are examined.

 Priority level 2: It has lower acceptance

indemnity from level 1, but higher acceptance

indemnity from the one that is granted in the

level 3. As examples of level 2 priority are the

real time services (VoIP, video), VPN and

voice services. In this study voice applications

are studied.

 Priority level 3: It has the smaller acceptance

priority in the network. As examples are

reported the “traditional” services of Internet

Services Provider (e.g. e-mail). In this study

email applications are studied.

The nodes are interconnected through the

Getaway node. Each node transmits packets that the

node itself generates and packets assumed are

guaranteed to be successfully delivered to the

Getaway node in NGN network. The application’s

operation mode is assigned as Simultaneous, and

start time is set to Constant (100). Links between

neighbouring nodes and Getaway are bi-directional

with transmission data rate of up to 155.52 Mbit/s

(payload: 148.608 Mbit/s; overhead: 6.912 Mbit/s,

including path overhead) using fiber optics. Thus, all

nodes can both send to and receive from the

Getaway. The simulation duration is set to End of

Simulation and lasts 6000 simulation sec. Finally all

nodes have an equal transmission power and

transmissions can reach up to the Getaway node

according the region. The assumptions that are

taken into account while developing the network are:

 20% bandwidth is occupied for data emergency

applications.

 50% bandwidth is occupied for voice

applications.

 30% bandwidth is occupied for email

applications.

There are two main types of statistics in the

performance evaluation. The first type is the

collection of values from individual nodes in the

network (node statistics) and the second type is from

the entire network (global statistics). Global

statistics can be used when we are interested in an

overall picture of the network performance. Global

Statistics are collected for all nodes/links in the

network. Node statistics provide information about

individual node. The Global Statistics of the network

are evaluated based on the following factors.

 Delay (sec): It represents the end to end delay

of data received in the network. End to end

delay is measured from the time it is created to

the time it is reassembled at the destination.

 Delay Variation: It measures the variance

among samples of end-to-end delay

experienced by packets traversing the network

along all connections established network-

wide.

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 Cell Delay (sec): It represents the end to end

delay of cells received by all layers in the

network. It is measured from the time a cell is

sent from the source layer to the time it is

received by the layer in the destination node.

 Cell Delay Variation: It measures the variance

among end to end delays for cells received at

all layers in the network.

 Traffic Sent (bits/sec): It represents the

application traffic sent by the layer in bits/sec

through the network.

 Traffic Received (bits/sec): It represents the

application traffic received by the layer across

the network.

The Node Statistics of the network is evaluated

based on the following factor.

 Voice application traffic received (bytes/sec):

It represents average bytes per second

forwarded to the voice application by the

transport layer in this node.

 Traffic received signaling queue (bits/sec): It

represents traffic received (in bits/sec) by each

queue of a certain port.

 Queue delay deviation: It is standard deviation

of queuing delay experienced by packets in

each queue. This statistic is computed as:

(q_delay - E[q_delay])^2 and expressed in

seconds.

Figure 3 is the graph of delay variation and delay in

the simulation scenario. Delay variations and delay

across the network are crucial for providing

acceptable services. The analysis indicates that the

developed network offers minimum latency in order

to avoid distortion situations. Similar observations

can be also made for Cell delay and Cell variation as

shown in Figure 4. Figure 5 is the graph of data

traffic received for the sum of applications by the

network. If the first high spike for email traffic is

excluded, it can be seen that data emergency

application achieves the lowest values in traffic

which is in line with our priorities levels and a

steady stream of data traffic is sent without

disruption. The spikes at the beginning of the

simulation are the indications of control traffic due

to the presence of nodes. The results shown in

Figures 6 and 7 are related to node statistics. Blue

line represents Istanbul node statistics and red line

represents Athens node statistics. In Figure 7, the

results show that almost average equal performance

is obtained for delay deviation for the two nodes.

Figure 3: Delay and delay variation.

Figure 4: Cell delay and cell delay variation.

Figure 5: Traffic received comparison for applications.

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Figure 6: Traffic received – Signalling Queue two

getaways-nodes comparison.

Figure 7: Delay Deviation-CBR queue two getaways-

nodes comparison.

5 CONCLUSIONS

It is seen that all over Europe electric utilities and

telecommunications operators have started

collaborating to deliver information and

communications technology and telecommunication

services for smart grid. In addition, countries around

Europe and Asia have started to create huge single

power grid infrastructures for energy that can power

many countries and nations at once. To do this, they

have simply been creating a complex network of

power grid connections to each participating

country. But, several challenges have been

identified and called for further discussions and

investigations on how telecommunications operators

can meet the special requirements of the electric

utilities in building the proposed grid infrastructures.

It is widely recognized that meeting the

communications requirements is mission critical.

In this paper, the use of Next Generation

Networks for Smart Grid applications used by

transnational Smart Grid operators has been

discussed and a detailed analysis has been presented.

As depicted and shown with the results of the

simulation studies presented in this paper, Next

Generation Networks based backbones offer better

delay handling and bandwidth allocation features to

different Smart Grid applications, and in this way,

QoS requirements of these applications can be

handled efficiently.

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