Security for Smart Distribution Grid By Using Wireless Communication

Similar documents
Overcoming the Security Issues in Smart Distribution Grid Using Wireless Communication

SUMMERY, CONCLUSIONS AND FUTURE WORK

Chapter 8: Smart Grid Communication and Networking

International Journal of Scientific & Engineering Research, Volume 7, Issue 9, September-2016 ISSN

Smart Grid Communications Architecture: A Survey and Challenges

Analysis and Comparison of DSDV and NACRP Protocol in Wireless Sensor Network

Part I. Wireless Communication

Smart Grid Vision DRAFT FOR DISCUSSION PURPOSES ONLY

Power Transmission and Distribution Monitoring using Internet of Things (IoT) for Smart Grid

MOBILITY REACTIVE FRAMEWORK AND ADAPTING TRANSMISSION RATE FOR COMMUNICATION IN ZIGBEE WIRELESS NETWORKS

2. LITERATURE REVIEW. Performance Evaluation of Ad Hoc Networking Protocol with QoS (Quality of Service)

Performance Evaluation of Routing Protocols in Wireless Mesh Networks. Motlhame Edwin Sejake, Zenzo Polite Ncube and Naison Gasela

Performance Evaluation of MANET through NS2 Simulation

Computer Based Image Algorithm For Wireless Sensor Networks To Prevent Hotspot Locating Attack

Energy Conservation through Sleep Scheduling in Wireless Sensor Network 1. Sneha M. Patil, Archana B. Kanwade 2

Smart Distribution Grid: Status, Goals, Vision and Pathway for Success

DETECTING, DETERMINING AND LOCALIZING MULTIPLE ATTACKS IN WIRELESS SENSOR NETWORK - MALICIOUS NODE DETECTION AND FAULT NODE RECOVERY SYSTEM

Wireless Sensor Networks (WSN)

Questions & Answers From Thursday, September 16 Webinar Alternatives Case Examples Frequency and Spectrum Planning Security WiMAX Capabilities

Performance Evaluation of Quality of Service Parameters for Scheduling Algorithms in Wireless Mesh Networks Mayuri Panchal, Rajesh Bansode 2

EXPERIMENTAL EVALUATION TO MITIGATE BYZANTINE ATTACK IN WIRELESS MESH NETWORKS

Figure 1. Clustering in MANET.

PRIVACY AND TRUST-AWARE FRAMEWORK FOR SECURE ROUTING IN WIRELESS MESH NETWORKS

Blackhole Attack Detection in Wireless Sensor Networks Using Support Vector Machine

Cyber Security and Privacy Issues in Smart Grids

Chapter 5 Ad Hoc Wireless Network. Jang Ping Sheu

Progressing AMI in Asia Pacific Mike Wetselaar Director Sales South East ASia

Intra and Inter Cluster Synchronization Scheme for Cluster Based Sensor Network

Mesh Networking Principles

Introduction and Statement of the Problem

Mitigating Malicious Activities by Providing New Acknowledgment Approach

Optimizing Performance of Routing against Black Hole Attack in MANET using AODV Protocol Prerana A. Chaudhari 1 Vanaraj B.

The General Analysis of Proactive Protocols DSDV, FSR and WRP

Simulation and Comparison of AODV, DSR and TORA under Black Hole Attack for Videoconferencing Application

A Literature survey on Improving AODV protocol through cross layer design in MANET

Performance Comparison of DSDV, AODV, DSR, Routing protocols for MANETs

Detection and Removal of Black Hole Attack in Mobile Ad hoc Network

Ashish Srivastava Information Technology, Rajkiya Engineering College, Azamgarh, India

Index terms Wireless Mesh networks, Selective forwarding attacks, Route Reply Packet, Fuzzy Logic, Detection threshold.

Expected Path Bandwidth Based Efficient Routing Mechanism in Wireless Mesh Network

Simulation and Analysis of AODV and DSDV Routing Protocols in Vehicular Adhoc Networks using Random Waypoint Mobility Model

TELECOM & ENERGY «Collaborating to Power the Smart Grids for Digital Growth«

A Survey on Path Weight Based routing Over Wireless Mesh Networks

Performance Of OLSR Routing Protocol Under Different Route Refresh Intervals In Ad Hoc Networks

FEMTOCELL WITH RELAYS TO ENHANCE THE MACROCELL BACKHAUL BANDWIDTH

International Journal of Scientific & Engineering Research, Volume 6, Issue 3, March ISSN

Research on Heterogeneous Communication Network for Power Distribution Automation

Geospatial Information Service Based on Ad Hoc Network

Simulation and Realization of Wireless Emergency Communication System of Digital Mine

A Review Paper on Secure Routing Technique for MANETs

Celtic-Plus Award winning projects present their results CIER

Smart utility connectivity

An Efficient Indoor Localization of Mobile Nodes on Novel Cooperative Algorithm

and coverage as the nodes can act both as clients and routers. In this paper, the clients are distributed using four different

LTE : The Future of Mobile Broadband Technology

WeVe: When Smart Wearables Meet Intelligent Vehicles

Link Lifetime Prediction in Mobile Ad-Hoc Network Using Curve Fitting Method

A Hybrid Routing Protocol for Ad-hoc Wireless Network Based on Proactive and Reactive Routing Schemes

IJREAT International Journal of Research in Engineering & Advanced Technology, Volume 1, Issue 2, April-May, 2013 ISSN:

Regression-based Link Failure Prediction with Fuzzy-based Hybrid Blackhole/Grayhole Attack Detection Technique

International Journal of Scientific & Engineering Research, Volume 4, Issue 9, September ISSN

Performance Analysis of Mobile Ad Hoc Network in the Presence of Wormhole Attack

ENERGY BASED AODV ROUTING PROTOCOL FOR WIRELESS MESH NETWORK

INTEGRATION OF AD HOC WIRELESS SENSOR NETWORKS IN A VIRTUAL INSTRUMENTATION CONFIGURATION

OPNET based Performance Evaluation of WIMAX Network with WIMAX Management using Different QoS

Performance Analysis of MANET Routing Protocols OLSR and AODV

Security and Privacy Issues In Smart Grid

CHAPTER 5 ANT-FUZZY META HEURISTIC GENETIC SENSOR NETWORK SYSTEM FOR MULTI - SINK AGGREGATED DATA TRANSMISSION

Principles of Wireless Sensor Networks

Energy Consumption for Cluster Based Wireless Routing Protocols in Sensor Networks

Performance Improvement of Wireless Network Using Modern Simulation Tools

Performance Evaluation of Routing Protocols (AODV, DSDV and DSR) with Black Hole Attack

A Reliable And Trusted Routing Scheme In Wireless Mesh Network

Performance Analysis of Ad Hoc Routing Protocols For Vehicular Ad Hoc - Networks

D2 01 _ 04 SMART, UTILITY-GRADE WI-FI MESH FOR DISTRIBUTION GRIDS

ANALYSIS OF METHODS FOR PREVENTING SELECTIVE JAMMING ATTACKS USING NS-2

References. The vision of ambient intelligence. The missing component...

Efficient Detection and Elimination of Vampire Attacks in Wireless Ad-Hoc Sensor Networks

IMPROVING THE DATA COLLECTION RATE IN WIRELESS SENSOR NETWORKS BY USING THE MOBILE RELAYS

Performance evaluation of Cooperative MAC and ZRP in Cooperative Communication Networking Environment

DISTANCE BASED CLUSTER FORMATION FOR ENHANCING THE NETWORK LIFE TIME IN MANETS

They avoid the cost, installation, and maintenance of network infrastructure.

Eradication of Vulnerable host from N2N communication Networks using probabilistic models on historical data

CLUSTER BASED ROUTING PROTOCOL FOR WIRELESS SENSOR NETWORKS

ScienceDirect. Sensor Based Communication Network for WACS with DNP3

Selective Forwarding Attacks Detection in WSNs

Effects of Sensor Nodes Mobility on Routing Energy Consumption Level and Performance of Wireless Sensor Networks

PERFORMANCE EVALUATION OF DSDV, AODV ROUTING PROTOCOLS IN VANET

RECONFIGURABLE SMART SENSOR INTERFACE for INDUSTRIES USING ARMBASED ON IOT

IEEE 802 Standard Network s Comparison under Grid and Random Node Arrangement in 2.4 GHz ISM Band for Single and Multiple CBR Traffic

Translating lessons learned from TNBR-UNITEN s fully integrated smart grid test-bed to large scale deployments

Using Distributed Intelligence to Aid MicroGrid and Distribution Technology Deployment

Wireless Ad-Hoc Networks

Analysis of Black-Hole Attack in MANET using AODV Routing Protocol

Digital Transformation of Power Delivery

Exploring the Behavior of Mobile Ad Hoc Network Routing Protocols with Reference to Speed and Terrain Range

Effective Response of BT and SMS Hybrid Virus Propagation and Prevention in MANET Harsha Kubade, Deepali Khatwar, Dhananjay Sable

INTERNATIONAL JOURNAL OF RESEARCH SCIENCE & MANAGEMENT

A Study on Issues Associated with Mobile Network

OPNET BASED SIMULATION AND INVESTIGATION OF WIMAX NETWORK USING DIFFERENT QoS

Transcription:

Security for Smart Distribution Grid By Using Wireless Communication S.K.Saranya 1, Dr.R.Karthikeyan 2 P.G Scholar, Dept of EEE, M.Kumarasamy College of Engineering, Karur, Tamilnadu, India 1 Professor, Dept of EEE, M.Kumarasamy College of Engineering, Karur, Tamilnadu, India 2 Abstract: In Smart Grid, the communication network plays a significant role. Wired communication adopted to ensure robustness of the backbone for power transmission network but it does not provide any flexibility. Wireless communication for power distribution grid provide more benefits such as low cost, high speed links, easy setup of connections among different devices or appliances and so on. Connecting equipment, devices and appliances through wireless communication is essential for Smart Distribution Grid (SDG). Mounting suitable wireless communication design and its security measures is extremely important for SDG. The Wireless communication design is proposed for SDG on Wireless Mesh Networks (WMNs). Its bidirectional communication and electricity flow enable both utilities and customer to monitor, forecast and handle energy usages. Yet, Wireless communication is usually susceptible to security problem. Being compromised by a malicious node is adversary would causes significant damage includes extended power outages and destruction of electrical equipment. It is crucial to security measures for SDG against intrusion of a malicious node to provide the availability of effective communication in SG. Index Terms: Smart Grid (SG), Smart Distribution Grid (SDG), Wireless Communication, Wireless Mesh Network (WMNs). I. INTRODUCTION As compared to today s power grid, smart grid is notable by several features. Smart grid is vigorous to load fluctuations and the supply-demand balance can be properly maintained via intelligent real-time dispatching mechanisms, large-capacity high-performance battery, distributed energy, and close customer-grid exchanges. Smart grid is also flexible to equipment failure, which prevents a single failure from developing into power outage or shutdown. Smart grid makes a power system more sustainable and more environmentally friendly by integrate renewable energy sources into the same grid. In smart grid, energy can be utilized efficiently through well-maintained balance between supply and demand. Smart Grid can bring various profits to customers. For example, customers can reduce the amount of power bill by harmonizing the operation time of different electric appliances to the period with best price; they can even get profit by selling power to the grid. Moreover, smart grid appreciably improves power availability and quality. Many core technologies need to be developed to enable the above features of smart grid. Among them, one critical technology is real-time monitoring and control of a large scale power network, which demands a sophisticated communication network across the grid to fulfill two tasks: 1) exchange information acquired by distributed sensing; 2) disseminate management and control messages to electric equipment and appliances. Thus, developing novel communication technologies that meet the special requirements of a power network plays a critical role in smart grid. Recently, smart grid (SG) is the buzz word, which has attracted attentions from engineers and researchers in both electric power and communication sectors. The concept of smart grid has appeared in recent literature in different techniques used to control the power grid operation. Some referred it is intelligent grid whereas some called it the grid of the future. The main objective of the smart grid concept is to provide the consumers with power in a more stable and Copyright @ IJIRCCE www.ijircce.com 1

reliable manner that the aging power grids of today may not be able to provide in the near future. Smart grid can be used a two-way communication between the suppliers and consumers of electric power. The bi-directional communication indicates the ability of smart grid to enable the end users to express their power requirement demands to the utility suppliers. In different segments of a power grid, different communication technologies are applied to meet their unique specific requirements. In a power transmission network that involves bulk power generation and power transmission, wired communications over power lines or optical cables are adopted to ensure robustness of the power backbone. However, in power distribution networks that provide power directly to customers, both wired and wireless communications should be considered. In a substation optical communication can be applied to monitor or control certain mission critical devices. Different types of wireless networks are available, but which one is the best fit for an SDG depends on the system architecture of the SDG and varieties of communication modules and wireless connection. Moreover communication modules in an SDG may pertain heterogeneous properties in terms of communication range, computing power, and power efficiency. In an SDG, communication modules associated with electric devices are usually stationary, but mobile connections need to be supported at the customer side or on some handheld devices. The aforementioned requirements of SDG communications lie in the advantages of wireless mesh network (WMNs), so WMNs are well suited for wireless networking in an SDG. In fact, some companies have started to consider mesh links for wireless communications in a power distribution network. II. WIRELESS COMMUNICATION In power distribution networks, wireless communications are preferred by many application scenarios, such as: 1) when many parameters in a substation need to be monitored, optical or power line communications can result in a costly and complicated system architecture; 2) power-line communications cannot easily bypass transformers in a power distribution network; 3) wired communications cannot provide peer-to-peer communications among electric devices in a flexible manner. In order to achieve cost effective and flexible monitoring and control of end devices, efficient dispatching of power to customers, and dynamic integration of distributed energy resources with power grid, wireless communication and networking functionalities must be embedded into electric equipments. There exist several choices of wireless communications for connecting monitoring, control, and consumer electric devices. However, most of them (e.g., wireless local area networks (WLANs) or wireless sensor networks (WSNs) are not directly applicable to an SDG due to several issues. The first one is the flexibility in topology formation. In an SDG, various electric devices need to have peer to peer communications, so mesh networking capability is a viable option. However, a WLAN can only support one-hop point-to-multipoint (PMP) communications. Usually a WSN like a Zigbee network is also a PMP network unless mesh networking capability is added into Zigbee nodes. The second issue is that rate-distance performance is not scalable for SDG wireless communications. For example, a WLAN can support a communication rate of tens of Mbps, but it can only reliably reach a distance of tens of meters. Moreover, to achieve reasonable throughput delay trade-off, the number of nodes that can be supported within the same WLAN needs to be small. Thus, one WLAN is obviously not enough for an SDG. In theory, multiple WLANs can be adopted to support a large scale SDG. However, communications and coordination among different WLANs become difficult to manage. The better solution is to build WMNs based on WLAN technologies. The third issue is that SDG wireless communications need to support different types of wireless applications. For example, some electric nodes only need to send control or measurement information in a low frequency, so the communication capability like WSN is sufficient. However, for some other nodes like the gateway node in a home or for an entire community definitely demand a much higher communication rate and a larger communication distance. In this case, communication technologies based on Copyright @ IJIRCCE www.ijircce.com 2

Wi-Fi with high-gain antenna may be necessary. As a result, SDG wireless networks must be capable of integrating heterogeneous wireless networks. Furthermore, in an SDG there exist PLCs that shall be utilized as much as possible, particularly to enhance reliability and security. As pointed out in wired communications can be easily integrated into WMNs Fig. 1: Wireless communication architecture based on WMNs in smart distribution grid. Although a cellular network like 3G can provide satisfying rate-distance performance, its network capacity may not be enough to allow SDG wireless communications as an additional service, because emerging cell phone services are currently overloading 3G networks. Moreover, coupling power supply services with telecom services downgrades reliability and complicates management of an SDG. In contrast, a wireless mesh network (WMN) does not have the afore-mentioned issues. It can be deployed and managed proprietarily by a utility company. In addition, the mesh networking capability of WMNs provides more flexible interconnection among various electric devices than a cellular network can do. 1. Wireless Mesh Network Wireless Mesh Network (WMN), which is a communication network made up of radio nodes organized in a mesh topology, has emerged as a key technology for next-generation wireless networking. A WMN also provides basic networking infrastructure for the communication in SG. WMNs can easily integrate heterogeneous networks to fulfill different functions such as sensing, monitoring, data collection, control, pricing and so on. The system architecture that merges WMNs and power distribution networks depicted in Fig.1. An SDG below the level of substations consists of multiple Microgrids. Copyright @ IJIRCCE www.ijircce.com 3

Fig 2: Wireless Mesh Network Model Typically, a Microgrid managed by a micro control center, contains a few Picogrids. A Picogrid is usually formed by electric devices in a home or building, and it may also include some distributed energy sources like EVs or Solar Cells. Some of the benefits of using WMNs in SG are highlighted as follows: (i)increased communication reliability and automatic net- work connectivity. (ii) Large coverage and high data rate. III. PROPOSED SYSTEM Proposed system contains a healthy system made by 50 nodes based on AODV protocol with energy level and performance comparison of various protocol with different number of nodes are done by using NS2. NS2 Network simulator version2 Network simulator is a package of tools that simulates behavior of system/network. To predict the system behavior following step are followed: Create system/network Topologies. Log events that happen under ant load. Analyze events to understand the system/network behavior. AODV: Ad hoc On-Demand Distance Vector A routing protocol for ad hoc mobile networks with large numbers of mobile nodes. The protocol s algorithm creates routes between nodes only when the routes are requested by the sources nodes, giving the network the flexibility to allow nodes to enter and leave the network at will. Routes remain active only as long as data packets are travelling along the paths from the source to the destination. When the source stops sending packets. The path will time out and close. Protocols are of different types they are AODV, DSDV, DSR. The performance of a protocols are found by comparing throughput, packet deliver ratio(pdr) and time delay of a system designed based on the various protocol. Copyright @ IJIRCCE www.ijircce.com 4

Table 1: Comparison of Protocol 100 90 80 70 60 PACKET DELIVERY RATIO OF PROTOCOLS 20 50 80 COMPARISION OF PROTOCOL CHARACTERISTICS: 1000 900 AODV 800 DSDV 700 DSR 600 50 500 40 400 30 300 20 200 10 100 0 AODV DSDV DSR 0 THROUGHPUT DELAY Fig 3: Comparison of protocol among different number of nodes Fig 4: Comparison of protocol Characteristics From Table1, Fig 3 and Fig 4 it clearly explains that the AODV Protocol shows better performance among all protocols. It s having good throughput and high packet delivery ratio with low time delay. So, AODV protocol is chosen for creating system. Best system performance is also depends on the energy level of nodes. Normally, a node contains energy and it decreases while continuously sending the information from a node to another node. The energy dropping can be noticed by color change. Each and every color intimating the energy level of node. Before, communication starts all the nodes are in green color which indicates that nodes are having full energy (i.e.,) 100%. Once, the communication happened the nodes are send data to one another. During, the communication because of continuous sending of information leads to energy level gets fall then the green color changes into yellow, red and black for further. (i)green 100% Copyright @ IJIRCCE www.ijircce.com 5

(ii)yellow 50% (iii)red 20% (iv)black 0% The Output of proposed system is taken from the Nam. Nam is a Network Animator. A visual aid showing how the information travels in the system. 1. Healthy System: Fig 4: Healthy system with 50 nodes A System without any problem is termed as Healthy system. Here, a Healthy system made by 50 nodes based on AODV protocol is shown in Fig 4.Here node0 is base station, it is a stable node. Where all data are send and receive. Except node0 all other nodes are utilities (i.e.,) customer, these nodes are mobile node. At initial condition all nodes are in green color. Because, before the communication begins nodes are have full energy. As mentioned before green color indicates the full energy (i.e.,) energy level is 100%. 2. Commuinication among Nodes: Fig 5: Nodes Communication Copyright @ IJIRCCE www.ijircce.com 6

The communication begins among all 50 nodes which are connected based on WMN I shown in Fig 5. Times were set in the script. As per the script when the time reaches nodes will start the communication. 3. Exchanging of information: Fig 6: Information Exchanged Fig 6 explains the data transferring between the nodes. For motion of mobile nodes, time was set in script itself. When the time reached all mobile nodes starts to move and then the data exchange among the nodes will begin. It exchanges information of Voltage, current, power demand and utilization. From the above figure it s clearly shows the data are transferring from mobile nodes (customers) to stable node say node0 (base station) 4. Drains of Energy: Fig 7: Dropping of energy level green to yellow Copyright @ IJIRCCE www.ijircce.com 7

Fig 8: Dropping of energy level yellow to red Both Fig 7 and Fig 8 Explains the energy dropping on nodes. Due, to the movement of nodes and continuous exchange of data among nodes leads to dropping of energy. Continuous exchange of information nodes with Green color falls into Yellow color is intimates that the energy levels of nodes are drops from 100% to 50% and further continuation the nodes with yellow color changed into red color is intimates that the energy levels of nodes are drops beyond from 50% to 20%. The performance of system is showed in a graph below. Fig 9: System Performance Because of using AODV protocol the range information dropping get reduced and throughput of a system increased. Due to these reasons the performance of system is also increased. IV. CONCLUSION A Healthy system has been created with 50 nodes. To identify the faults occurring in the system, a communication has been created among each nodes by using WMN with energy level. The proposed system is analyzed with the best protocol to provide a appreciable solution with Throughput, Packet Delivery Ratio and Delay. Copyright @ IJIRCCE www.ijircce.com 8

Even though the Smart Grid system is stable always there are some chances for faults resulting in Blackhole. So, this work is further taken over to remove the malicious node. Finally a comparative study is provide for a secured system and un healthy system. REFERENCE [1] Security Framework for Wireless Communiation in Smart Distribution Grid ( Xudong Wang, Senior member, IEEE, and Ping Yi). [2] Wireless Sensors Network in Smart Grid: applications and Issues ( Yiying Zhang and Yan Zhen). [3] Securing Smart Grid: Cyber Attacks, Countermeasures, and Challenges (XU Li, Inria Lille-Nord Europe, Xiaohui Liang, Rongxing Lu, and Xuemin shen, University of Waterloo). [4] Communication Security for Smart Grid Distribution Networks ( Elias Bou-Hard. Claude Fachkha, Makan Pourzandi, Mourad Debbabi, and Chandi Assi, Concordia University). [5] NIST Smart Grid Cyber Security Working Group, Guidelines For Smart Grid Cyber Security: Vol.3, Supportive analyses and references NISTIR 7628, Aug.2010. [6] Y.Zhang and W.Lee, Intrusion detection techniques for Mobile Wireless Networks Mobile Netw. Appl.,Vol.9, no.5, pp. 545-556, 2003. Copyright @ IJIRCCE www.ijircce.com 9