Performance Evaluation of Cellular Communication ...

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Keywords: Smart Grid, Machine-to-Machine (M2M) Communication, Cellular .... on different wireless communication technologies, such as WLAN, WiMAX, ...
Performance Evaluation of Cellular Communication Systems for M2M Communication in Smart Grid Applications 1

Ganesh Man Shrestha , and Jürgen Jasperneite 1

1,2

inIT-Institut Industrial IT, Liebigstraße 87, D-32657 Lemgo 1 [email protected] 2 Fraunhofer IOSB-INA, Langenbruch 6, D-32657 Lemgo 2 [email protected]

Abstract. The increasing power demands and growing awareness for sustainable and green energy has led to distributed generation of power from different sources. This transition from centralized to a distributed power generation has increased the necessity to upgrade the traditional grid. The future grid, i.e. Smart Grid, should offer two way flow of power and information. Smart grid needs to intelligently manage the power generation, transmission, and distribution to generate optimal power resources and adapt consumers to those power resources. In addition, it should support smart metering and monitoring to reduce energy consumption and cost. This intelligent management demand near real time communication between the power generators, consumer utilities and the control center. Thus machine-to-machine (M2M) communication is the necessity of future smart grid applications. Smart grid is a huge infrastructure and its components are located at far-off locations. Hence, wired and short range wireless communication solutions would not be ideal for smart grid applications. This paper presents the performance evaluation of different cellular communication systems as a solution for M2M communication in smart grid applications. Keywords: Smart Grid, Machine-to-Machine (M2M) Communication, Cellular Communication

1 Introduction The traditional power grids are some of the biggest and most reliable systems built in th the 20 century and has served its purpose for almost a century. The hierarchical structure of the traditional grids, where power is centrally distributed from a few number of large scale generators to a large number of consumers, is not suitable for present power demand. The limited interconnection between the grids and one way flow of power without the balance between the generation and consumption has led to the underutilization of power. So, the power generation and distribution should be based on the real-time consumption. Moreover, the growing awareness for sustainable and green energy has resulted in distributed generation of power from different sources like sun, wind, household

waste, power-heat coupling etc. This transition from centralized to a distributed power generation has resulted in the need for intelligent transmission, distribution and management of the consumer demands. This requires an infrastructure where all the distributed generators, transmission line, distribution substations, and the consumer utilities can be interconnected as a single network or “smart grid”. The focal concept of a smart grid is to automate the power generation, distribution, and consumption with automated metering, monitoring, and management [1][2]. Smart grid is a vast infrastructure which consists of mechanical, electrical, electronic and communication systems. In this paper, we focus only on the communication perspective of the smart grid. A general architecture of a smart grid is shown in Figure 1. As seen in the figure the smart grid is the extension of the existing power grid with added communication infrastructure and the distributed power generator empowering the two-way flow of power and information. The electricity consumers like industrial factories, buildings, homes, and electric cars can also be an electricity producer. The produced electricity can also be put back into the grid. For example, a smart home may be able to generate electricity using solar panels and put it back into the grid, or electric vehicles may provide power to help balance loads by sending power back to the grid when demand is high. The smart metering and monitoring features are available in the smart grid. The smart metering enables the consumer utilities to optimize power consumption. The smart monitoring enables the distributor to monitor the real-time power demands for a reliable power transmission and also monitor grid status to detect mechanical failures. Thus, smart metering and monitoring demand secure, uninterrupted and near real-time communication between the electric utilities without any human assistance. Thus machine-to-machine (M2M) communication is the necessity of future smart grid applications. In M2M communication, the communicating utilities are able to exchange information and make decision based on the exchanged information without human assistance. The M2M communication using public networks becomes more important and some of potential areas are smart grids, vehicular telematics, health care, industrial plants etc. [3] - [5] . The dedicated connection between the consumer utilities, measuring points, distribution network, energy supplier and the transmission network would be very complex, expensive and difficult to maintain. Internet-based communication would be much easier to implement and maintain, especially to interconnect geographically distributed substations. Thus, the internet based communication would be the ideal communication solution in smart grid applications. Table I present an overview of smart grid communication technologies.

Figure 1: Smart Grid Architecture Table I: Smart Grid Communication Technologies [8][12] Communication Technology

Data Rate

Coverage Range

Remarks

Power Line Communication (PLC)

2-3 Mbps

1-3 km

Harsh and noisy channel environment

Ethernet

Up to 1 Gbps

100 m

High installation cost and less flexible

Optical Fiber

Up to 14 Tbps

160 km

Extremely costly to realize in a distributed system like smart grid.

WLAN1

Up to 54 Mbps

200-400 m

Easy installation but high interference, short range

Zigbee

250 kbps

30-50 m

Easy installation but low data rate and short range

2G2

Up to 170 kbps

1-10 km

Easy installation but low data rates, licensed band

3G3

384 kbps14.4 Mbps

1-10 km

Easy installation but licensed band

4G4

Up to 42 Mbps

1-10 km

Easy installation but licensed band

Digital Subscribers Line (DSL)

Wireless Cellular

1

Wireless Local Area Network (WLAN) Global Packet Radio System (GPRS) 3 High Speed Downlink Packet Access (HSDPA) 4 Long Term Evolution (LTE) 2

The power line communication (PLC) suffers from high attenuation due to unpredictable voltage transients and harmonics. The need for physical connections in DSL communication reduces flexibility and increases the installation cost in the field of substations. The wireless communication is the suitable solution for the smart grid applications because of its low cost, easy installation, and flexibility. There is no need for physical communication between the communicating utilities but the short communication range of wireless standards like WLAN and Zigbee make it unsuitable to use it as a general solution for smart grid communication. The WLAN and Zigbee can only be used for communication between the utilities within a home or building environment. Hence, cellular communication is the ideal solution for the smart grid communication because of its large coverage range, easy installation and flexibility. In this paper we want to share our results of evaluating cellular communication systems for this purpose. The rest of the paper is organized as follows: Section 2 presents an overview of recent works on the smart grid communications. Section 3 presents cellular communication setup for M2M communication in a smart grid. The results of the communication setup of section 3 are presented in section 4. Section 5 finally concludes the paper.

2 Recent Works The high cost of installing wired communication setup in smart grid applications has inclined more research towards the wireless solution. An overview of applicability of wireless M2M communication in a smart grid is presented in [3] and it further presents a network architecture of home energy management system (HEMS) in smart grid. Different areas of M2M communication such as smart grid, E-health, vehicular telematics are presented in [4] and the paper further presents the motivation for the transition from current cellular based M2M communication solution to the embedded internet based M2M communication. The paper presented in [6] presents the communication challenges, security and privacy issues for different smart grid communication networks. The paper also presents the smart metering standardization activities in Europe. The distribution feeder level communication requirements in smart grid applications are presented in [7] and the paper further proposes three-layer wireless communication architecture to increase the reliability and reduce the latency. A comparative study of different communication technologies applicable for smart grid and an overview of the smart grid standards are presented in [8]. The theoretical study on different wireless communication technologies, such as WLAN, WiMAX, Zigbee, Cellular etc., and the challenges for their deployment in smart grid application is presented in [9]. A general overview of wireless network architecture for smart grid applications is presented in [10] and the paper further present two network planning approaches for NAN communication using 3G cellular technology. In [11], the wireless technologies

– Wi-Fi, ROF (Radio-over-fiber), and 4G cellular network - are presented as a possible solution for smart grid communication. The above works illustrate the considerable advantages of wireless communication over wired communication in smart grid applications but most of the paper presents only the conceptual and theoretical research. Some of the paper presented the simulation results but the physical realization can be much more challenging. In this paper, we present the performance evaluation of M2M communication in smart grid application using cellular communication technology.

3 M2M Communication Setup The idea behind the M2M communication setup used in our experiment is to use the Internet and public cellular network as a communication system between the smart grid utilities. The stationary utilities in the home/building will be connected to the Internet while the utilities in the far-off location and mobile utilities (for e.g. electric car) will be connected to the cellular network. This idea is realized in M2M communication setup shown in Figure 2. The sender resembles the stationary utilities connected to internet while the responder resembles the utilities in the far-off location. Cisco 1800 series routers were used as sender and responder machines because of its built-in QoS measurement capabilities. The sender was installed in the test lab inside the university premises and connected to the internet via the university network. The responder was installed in a resident home in Lemgo, Germany and connected via a cellular modem to a German ISP (Internet Service Provider). The experiments were performed over a period of five days for different cellular technologies (2G, 3G and 4G). The GPRS, HSDPA and LTE services offered by a German telecommunication provider were used 2G, 3G and 4G technology respectively. The download and upload data rate of the different technologies are shown in Table II.

Figure 2: M2M Communication Setup (2G, 3G, and 4G)

4 Measurement Results The round trip time (RTT) and jitter were used as the performance metrics of our M2M communication setup. The cisco built-in IP SLA (service level agreement) support was used to measure the RTT and the jitter.

Table II: Data rate of different cellular technology Cellular Technology

Data Rate Download

Upload

2G (GPRS)

110 Kbps

26.8 Kbps

3G (HSDPA)

7.2 Mbps

5.76 Mbps

4G (LTE)

Not specified

Not specified

4.1 Round Trip Time (RTT) RTT is the time taken by a signal from the sender to reach the responder plus the time taken by the acknowledgment of that signal to be received back by the sender at the IP level (OSI layer 3). To measure the RTT, the sender periodically sends an ICMP echo request with a payload size of 60 byte at a transmission interval of 10 second and measures the time after successfully receiving the ICMP echo response from the responder. The measured values stored in text files on a daily basis. The RTT measured for duration of five days with 2G, 3G and 4G cellular technology is plotted in Figure 3. The highest RTT was measured for 2G (GPRS) and the lowest RTT was measured for LTE. The maximum fluctuation in RTT in case of GPRS is due to high number of active users. The mean RTT was measured as 300 ms, 126.7 ms, and 69.86 ms for GPRS, HSDPA, and LTE respectively. The low RTT shows that new generation cellular technology will offer good performance for near real-time M2M communication.

600

Day 1

Day 2

Day 3

Day 4

Day 5

GPRS HSDPA LTE

RTT in ms

500 400 300 200 100 0

0:00

0:00 0:00 time of day

0:00

0:00

Figure 3: RTT for GPRS (2G), HSDPA (3G), and LTE (4G) Cellular Communication Setup

4.2 Jitter Jitter is the time difference between the maximum and minimum packet transmission time from sender to responder. The sender periodically sends an UDP data burst of 20 packets at a transmission interval of 30 seconds to responder (OSI layer 4). The responder measures the time and stores the measured time and the time stamp received from the sender. The measured values are stored in text files on a daily basis. The jitter was calculated for GPRS and HSDPA for duration of five days. The low jitter was measured during early and late hours of the day while significant amount of jitter was measured in the other hours of the day. The mean jitter was measured 25.09 ms and 8.4 ms for GPRS and HSDPA respectively. For LTE no jitter was measured because the measurements were performed at a time when the LTEtechnology was just introduced in the region and very few users existed of this technology.

Jitter in ms

150

Day 1

Day 2y

Day 3 y Day 4

Day 5

GPRS HSDPA

100

50

0

0:00

0:00 0:00 time of day

0:00

0:00

Figure 4: Jitter for GPRS (2G), HSDPA (3G) Cellular Communication Setup

5 Conclusion The paper presented the idea of using the internet and the public cellular networks for M2M communication in smart grid applications. We used 2G (GPRS), 3G (HSDPA) and 4G (LTE) technology provided by a German telecommunication provider for a performance evaluation. The RTT and jitter was measured to demonstrate the performance of our M2M communication setup. The lowest RTT was measured for LTE and the highest RTT was measured for GPRS. The results demonstrate the possibility of realization of near real-time M2M communication using the internet and the public cellular network.

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