A Hybrid Communication Architecture for Internet of Things (IOT) Application in Smart Grid

A Hybrid Communication Architecture for Internet of Things (IOT) Application in Smart Grid Yijia Cao Hunan University, China 2014-10 10-21

OUTLINE 1 IOT Application in Smart Grid 2 3 Requirements for Communication Hybrid Communication Architecture 4 5 6 Evaluation & Optimization of Hybrid Communication Network Application Challenges and Opportunities

Smart Grid Vision High DER penetration Bidirectional electrical power flows Self-healing ability Flexible demand side management Diversified power quality Enabling energy market To realize the automated and intelligent management of power grid, a fast, reliable and secure communication network is required

Information and Communication (IC) Network Characteristics for Smart Grid Highly coupling of power grid and communication network Diversified communication environment Employment of various communication mode Dramatic growth of data amount Coexistence of different information Cyber security issues

IOT Vision The Internet of Things (IOT) is a global infrastructure for the information society that enabling the connection of Man to Man, Man to Thing, or Thing to Thing at anytime and anywhere. Hierarchical architecture of IOT

Key Technologies of IOT

IOT Applications in Smart Grid Power plant/substation monitoring & control WSN GSM/GPRS, 3G, 4G Ethernet GPS Transmission line monitoring PLC WSN GSM/GPRS, 3G, 4G WiMAX RFID GPS DER/Microgrid monitoring & control WSN WiFi Ethernet GPS Demand response, Automatic metering reading, load management WiFi Ethernet GSM/GPRS, 3G, 4G Zigbee PEV charging station monitoring & control RFID WiFi Ethernet GSM/GPRS, 3G, 4G

Requirements for Communication To protect the smart grid and ensure optimal operation, the communication infrastructure must meet several requirements, which are Network latency requirements Network reliability requirements Network security requirements

1 Network Latency Requirements Many types of information exchanges between electric devices is useful only within a predefined time frame Latency requirements for different applications in the smart grid Application class Typical maximum response Data burst size (range) Protection 1-10 ms Tens of bytes Control 100 ms Tens of bytes Monitoring 1 s Tens to hundreds of bytes Metering/billing Hours Hundreds of bytes Reporting/software update Days KB to MB Available solutions to reduce network latency Communication technology selection Network service mapping Network structure design Other delay guarantees

2 Network reliability Requirements It is extremely important for the network to be reliable for successful and timely message exchanges System faults occur with minimal probability The dysfunctional components are restored to normal working status in the shortest time The impact to the whole power system is minimized when some components go wrong Suitable solutions to improve network reliability Evaluation of system reliability Network redundancy Message prioritization and resource reservation mechanisms Periodic network maintenance checkup Automatic failure detection and path switching

3 Network Security Requirements It is imperative to protect the communication networks from cyber attacks for correct functioning of power system Availability Integrity Confidentiality Authenticity Non-repudiation Optional solutions to maintain network reliability Firewall Antivirus software Message encryption Identity authentication Intrusion detection Access control VPN

Hybrid Communication Architecture

Application of Hybrid Communication Architecture in Smart Grid The hybrid communication architecture for smart grid has been applied in two typical cases: Case A -- Power Transmission and Transformation Equipment (PTTE) Monitoring, Control and Management Case B -- Smart Substation Communication Network

Hybrid Communication Architecture -- Case A IOT-based Architecture for Power Transmission and Transformation Equipment (PTTE) Monitoring, Control and Management

Hybrid Communication Architecture -- Case A Smart Sensing Layer: Ubiquitous sensing of power equipment status RFID FLAG Smart transformer

Hybrid Communication Architecture -- Case A Data Communication Layer: Autonomous and cooperative communication networks to support data exchange in a heterogeneous network

Hybrid Communication Architecture -- Case A Information Processing Layer: To realize the integration, storage and analysis of massive data (Cloud computing, data fusion, data mining, etc.) Smart Application Layer: To extend the evaluative dimension of equipment status so as to improve the effectiveness of maintenance decisions and the ability of PTTE life cycle management Service type Support platform Key indicators Function module Model research Condition based maintenance State assessment Resource allocation Smart patrol Performance management Smart dispatching Panoramic information integration platform + Life cycle management system Reliability Economy Environment Forecasting and early warning Smart diagnosis Risk assessment Maintenance decision Environment assessment Performance evaluation Causal model of fault Time series model of fault Cost model of life cycle Deteriorating law caused by multi-factor Panoramic information fusion Basic research Experimental study Statistical analysis Typical fault Incidence relation Equipment account Operation condition Experimental data Monitoring data Environmental data Maintenance cost

Hybrid Communication Architecture -- Case B WSN-based Smart Substation Communication Network

Evaluation of Network QoS Quality of Service (QoS) is a key problem for WSN-based smart substation communication network (SCN), which has a great influence on network latency. QoS index User QoS: End-to-End delay Node QoS: Collision, packet loss ratio, bit error rate, signal/noise ratio, received power Network QoS: Media Access Control (MAC) delay, MAC throughput, MAC data dropped Influence factors of network QoS for WSN-based SCN Network topology Sensor node scale Node transmitted power Network node

Evaluation of Network QoS Typical network topologies Simulation prototype in OPNET Star topology Tree topology Mesh topology Cluster topology

Evaluation of Network QoS Conclusion: Cluster topology has the optimal MAC data drop rate, throughput, and delay characteristic. Conclusion: Adding of sensor nodes increases MAC throughput and causes longer MAC delay.

Evaluation of Network QoS Conclusion: Increase of node transmitted power can improve MAC throughput and lower data drop rate, while has little effect on MAC delay. Conclusion: MAC throughput increases with network load, while there are no changes for MAC delay and data drop rate.

Optimization of Network Energy Consumption Network Energy Consumption has a great influence on the life time of WSN. A higher energy consumption of key cluster header nodes will cause the premature death on them, which seriously impact network reliability. The energy consumption of sensor nodes is required to be optimized and balanced to maintain the reliability of WSN. Control mechanism for energy consumption Shorten transmission distance Reduce intermediate hops Data integration to cut down data amount

Optimization of Network Energy Consumption Network model Sensor nodes are distributed uniformly in a circular area Cluster topology is configured with cluster header nodes CHi located in the center of sector area Cluster header nodes transmit data to sink node by single-hop or multi-hop mode Four typical paths are configured and studied especially for multi-hop mode Energy consumption model Energy consumption for data transmission (sensor nodes, cluster header nodes) E b, d be bd, d d Tx elec 0 2 GG t r, L 2 d0 2 0 0 ln 16 0 L d d d Energy consumption for data receiving and processing (cluster header nodes) rp elec fuse E b be be

Optimization of Network Energy Consumption The objective is to minimize and balance the energy consumption of node cluster as well as to maximize network lifetime by optimizing the location of cluster header nodes, perception radius, data compression ratio and transmission cycle. Objective function min F w E w / LifeTime w dis _ fac The objective function above is mainly related to three factors: 1 Tol 2 3 st.. g x 0, i1,2, L, n i Total energy consumption of node cluster E Tol Part 1: Energy consumption for data transmission between sensor nodes inside the cluster and cluster header node E Tol-ini Part 2: Energy consumption for cluster header node E Tol-CHi E E E Tol Tol-ini Tol-CHi 2 Tol-ini 4 i s i elec 2 i E b R d E d Tol-CHi i s i elec i fuse 2 2 3 4b g gsinigdi2 di Rs Rs ; i 1,2,3 3 E 4b R d E C E a gc g4 b R d E d ; i 1,2,3 i i i s i elec Data compression ratio of cluster header node 2

Optimization of Network Energy Consumption Objective function min F w E w / LifeTime w dis _ fac 1 Tol 2 3 st.. g x 0, i1,2, L, n i Lifetime of the sensor network LifeTime The network lifetime is to be maximized for normal data transmission LifeTime E E E E min min,, i 0 0 0 iv ei fij ETol-in1 ETol-CH1 ETol-in2 ETol-CH2 ETol-in3 ETol-CH3 jn Distance factor disc_fac i Distance factor is used to balance energy consumption of sensor network Minimal distance factor could help prevent unreasonable deployment of cluster header nodes disc _ fac 4p rd g 2 2 rc2d3 rc1d1c3d2 2C2d3 r rc2d5 C3d4 rc1d1c2d2 C3d4 g 2C d r 2 3 2 4 p rd 3 5 2 3 5 2 2

Optimization of Network Energy Consumption Optimization results based on Group Search Optimizer (GSO) algorithm Conclusions: Adding of network hops will increase the total energy consumption of node cluster It is suggested to use two-hop network to make the network lifetime longer Energy consumption for cluster header nodes could be balanced by properly configuring the data compression ratio and communication distance

Application in Yunan Power Grid Distribution of substations and transmission lines for IOT application in Yunnan province 863 Project, funded by MOST 1 ±800 kv convertor station 2 500 kv substations 7 220 kv substations 3 110 kv substations 3 transmission lines

Application in Yunan Power Grid IOT-based communication model for PTTE monitoring in Yunan porvince

Application Results False positive rate of PTTE condition monitoring has been lower than 5% Failure rate of PTTE is reduced by about 15% Cost of equipment maintenance has been reduced by about 30% Management efficiency of backup equipment has been increased by 50% Equipment lifetime has been extended by 20% Overall economic efficiency exceeds 30 million yuan

Challenges and opportunities Vulnerabilities and interactions of Interdependent network, Physical System and Cyber-System Interoperability of various devices and interface for different kinds communication mode Resource allocation and QoS in heterogeneous network Cyber security and privacy protection