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Heterogeneous Networks for Smart Grid Communication Architecture and Optimal Traffic Allocation. Presented by : Ran Zhang Supervisor : Prof. Sherman( Xuemin ) Shen, Prof. Liang- liang Xie. Main Reference. [1] Levorato , M., Mitra , U., “ Optimal allocation of heterogeneous

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Heterogeneous networks for smart grid communication architecture and optimal traffic allocation

Heterogeneous Networks for Smart Grid Communication Architecture and Optimal Traffic Allocation

Presented by: Ran Zhang

Supervisor: Prof. Sherman(Xuemin) Shen,

Prof. Liang-liangXie


Main reference
Main Reference

[1] Levorato, M., Mitra, U., “Optimal allocation of heterogeneous

smart grid traffic to heterogeneous networks,” Smart Grid

Communications (SmartGridComm), IEEE International

Conference on, pp. 132–137, 2011

[2] Zaballos, A., Vallejo, A. and Selga, J.M., “Heterogeneous

Communication Architecture for the Smart Grid,” Network, IEEE,

vol. 25 , no. 5, pp. 30-37, 2011


Outline
OUTLINE

  • Background[1]

    • Traditional Energy Grid vs. Smart Grid

    • Heterogeneity of Smart Grid Communication

  • Heterogeneous Communication Architecture[2]

    • User Sensor Network (USN) Access Network Level

    • USN Next-generation Network (NGN) Level

    • USN Middleware Level

  • Optimal Traffic Allocation to Heterogeneous Networks[1]

    • System Model

    • Illustration of Optimal Allocation Strategy

  • Conclusions


Outline1
OUTLINE

  • Background

    • Traditional Energy Grid vs. Smart Grid

    • Heterogeneity of Smart Grid Communication

  • Heterogeneous Communication Architecture

    • User Sensor Network (USN) Access Network Level

    • USN Next-generation Network (NGN) Level

    • USN Middleware Level

  • Optimal Traffic Allocation to Heterogeneous Networks

    • System Model

    • Illustration of Optimal Allocation Strategy

  • Conclusions


Background traditional vs smart 1
Background – Traditional vs. Smart(1)

  • Traditional Energy Grid

    • Tree like hierarchically-controlled structure

    • Production -> Delivery -> Distribution to dispersed users

  • Smart Grid

    • Distributed Production Models

    • Deployment of Energy Market – trade energy

    • Implementation of Demand Response – individuals to receive periodic energy pricing information

      Fig 1. Smart Grid Overview


Background traditional vs smart 2
Background – Traditional vs. Smart(2)

  • Demand

    • The increasing complexity of the production and consumption model

       distributed control, control entities fully coordinate

    • Energy Trading + periodic energy pricing information obtain

       timely and reliable exchange of critical information among the control entities.

  • Solution

    • Information Communication Network for Smart Grid


Background heterogeneity
Background – Heterogeneity

  • Traffic heterogeneity in terms of QoS requirements

    • Control Packets – small size and stringent delay

    • Large Best Effort Packets – large size and relaxed delay

  • Information network heterogeneity

    • Internet

    • Wireless Access Networks

    • Power Line Communication (PLC) Network

      Distinct characteristics in terms of bit rate, delay, packet loss rate and cost.


Outline2
OUTLINE

  • Background

    • Traditional Energy Grid vs. Smart Grid

    • Heterogeneity of Smart Grid Communication

  • Heterogeneous Communication Architecture

    • Ubiquitous Sensor Network (USN) Access Network Level

    • USN Next-generation Network (NGN) Level

    • USN Middleware Level

  • Optimal Traffic Allocation to Heterogeneous Networks

    • System Model

    • Illustration of Optimal Allocation Strategy

  • Conclusions


Architecture
Architecture

  • End-to-end integration of

    heterogeneous technologies

    based on IP

  • Ubiquitous Sensor Network

    Architecture (USN)

  • Interoperability with the next

    generation network (NGN) as

    the smart grid backbone

  • Decentralized middleware to

    coordinate all the smart grid

    functions

    Figure 2 Layers of a USN architecture


Architecture1
Architecture

  • Sensor networks: transmit and

    collect information

  • Access Networks: collect info

    from sensors and facilitate

    communication with a control

    center or external entities (NGN)

  • USN Middleware: collect and

    process data (send requests)

  • Application platform

    Figure 2 Layers of a USN architecture


Architecture usn access network level 1
Architecture: USN Access Network Level(1)

Access Baseline Technology

  • Power Line Communication (PLC)

    • Dedicated, especially suitable for situations underground or in enclosed places

    • Drawbacks

      Technique: low rate, lack of control

      Economic: high cost

    • NB-PLC

      Used for electric company communications, meter reading and home automation

      Working frequency: 150KHz in Europe and 450KHz in United States

      Delivery rate: 2 to 128kb/s

    • BPL

      Used in in-home LANs and access Networks

      Bandwidth: 10 to 100Mb/s


Architecture usn access network level 2
Architecture: USN Access Network Level(2)

  • WIMAX

    • IEEE 802.16 is a standard technology for wireless wideband access.

    • Ease of installation

    • Support point-to-multipoint or mesh topologies

  • IEEE 802.11s

    • A draft from IEEE 802.11 for mesh networks

    • Define how wireless devices can be connected to create ad hoc networks

    • Implement over physical layer in IEEE 802.11a/b/g/n

  • IEEE 802.22

    • Use existing gaps in the TV frequency spectrum between 54 and 862 MHz

    • Based on the cognitive radio techniques


Architecture usn access network level 3
Architecture: USN Access Network Level(3)

Sensor Communication Technology

  • A mesh network is suitable for smart grid sensor network

    • Self-configuration and self-organization: easy to add new nodes

    • Robust and reliability

  • IEEE 802.15.4

    • Define MAC and PHY layers in low-rate personal area networks (LR-PANs).

  • IEEE 802.15.5

    • WPAN mesh standard

    • Define a mesh architecture in PAN networks based on IEEE 802.15.4

  • Upper layers protocols

    • Zigbee: Based on IEEE 802.15.4, specifying protocols used in low consumption digital radio

    • 6LoWPAN: allow to use IPv6 protocol over the base on IEEE 802.15.4


Architecture usn access network level 4
Architecture: USN Access Network Level(4)

Conclusions

  • Metropolitan/wide area networks

    • WIMAX will work from the core to the high/medium voltage substations

    • PLC from these substations up to the homes

  • Home area Networks

    • Mesh networks: 6LoWPAN, IEEE 802.15.5 and Zigbee (most currently used and mature)

  • The combination of PLC and Zigbee/IEEE 802.15.4g provides a new concept of home and substation automation with outside interaction.


Architecture usn access network level 5
Architecture: USN Access Network Level(5)

Figure 3. Communication Network Proposed


Outline3
OUTLINE

  • Background

    • Traditional Energy Grid vs. Smart Grid

    • Heterogeneity of Smart Grid Communication

  • Heterogeneous Communication Architecture

    • Ubiquitous Sensor Network (USN) Access Network Level

    • USN Next-generation Network (NGN) Level

    • USN Middleware Level

  • Optimal Traffic Allocation to Heterogeneous Networks

    • System Model

    • Illustration of Optimal Allocation Strategy

  • Conclusions


Architecture ngn level
Architecture: NGN Level

  • An NGN is a packet-based network in which service–related functions are independent of the underlying transport-related technologies

  • Support generalized mobility – consistent and ubiquitous service provision

  • Open Service Environment (OSE) capabilities of ITU’s NGN model

  • QoS parameters and security constraints should be well mapped among heterogeneous technologies to obtain suitable end-to-end technologies

    Figure 4 OSE functionalities


Architecture middleware level 1
Architecture: Middleware Level(1)

Figure 5. Middleware Interaction


Architecture middleware level 2
Architecture: Middleware Level(2)

Figure 6. Message Exchange Process


Outline4
OUTLINE

  • Background

    • Traditional Energy Grid vs. Smart Grid

    • Heterogeneity of Smart Grid Communication

  • Heterogeneous Communication Architecture

    • User Sensor Network (USN) Access Network Level

    • USN Next-generation Network (NGN) Level

    • USN Middleware Level

  • Optimal Traffic Allocation to Heterogeneous Networks

    • System Model

    • Illustration of Optimal Allocation Strategy

  • Conclusions


Optimal traffic allocation 1
Optimal Traffic Allocation (1)

  • Problem : Try to dynamically allocate traffic with different QoS requirements in terms of throughput, delay and failure probability to information networks with different performance characteristics

  • System Model

    • The system is divided into input queues, comprised of buffers associated with a different QoS requirement and output networks, representing the various options for the delivery of the packets.

    • Input queues and output queues are connected by links associated with a potentially time varying channel in order to model variations in fading and capacity


Optimal traffic allocation 2
Optimal Traffic Allocation (2)

Figure 7. System model

  • Nq input queues, N0 output queues, slotted time operations.

  • The packet size is expressed in units

  • Packets entering the input queue i have fixed size equal to liq units

  • Uij(t)<=min{Cij(t), Qi(t)}

  • Fractions of packets cannot be transferred from a buffer to another, and thus Uij(t)=nliq


Optimal traffic allocation 3
Optimal Traffic Allocation (3)

Figure 7. System model

  • Packets in queue j are served at rate uj units/time slot.

  • Retransmission at most Fij times with failure probability ρij

  • Delivery Delay Dj


Optimal traffic allocation 4
Optimal Traffic Allocation (4)

System Dynamics

  • Assumptions: Ai(t) and Ej(t) are i.i.d random variables

  • Update rule for input queue i is

  • Update rule for output queue j is


Optimal traffic allocation 5
Optimal Traffic Allocation (5)

Performance Metrics

  • Long-time Average throughput

  • Average waiting time

    waiting time in input queue I

    waiting time spent by a packet transferred from the input queue i to output network j


Optimal traffic allocation 6
Optimal Traffic Allocation (6)

Performance Metrics

  • Delivery delay over the output networks

  • Average Financial Cost


Optimal traffic allocation 7
Optimal Traffic Allocation (7)

Optimization Problem

  • The performance metrics defined above are all functions of the allocation policy Uij(t)

  • Minimize/maximize one of the performance metrics given the constraints of the other average performance metrics, with guarantees on the mean rate stability of the system queues


Illustration
Illustration

  • Input queues

    queue1: Large packets with relaxed delay constraints

    queue2: Small packets with stringent delay constraints

  • Output queues

    queue 1: shared wired Internet network (large delivery rate, small delay,

    large amount of exogenous traffic, small financial cost)

    queue 2: shared wireless networks (relatively large output rate and small

    delay, large amount of exogenous traffic, high financial cost)

    queue 3: PLC (small output rate, large delivery delay, no exogenous traffic,

    on financial cost)

  • Packets Arrival

    λiin – input queues λjo - exogenous packets

  • Objective

    Minimize the overall financial cost while keeping the queues stable and meet

    constraints on the throughput and output buffer plus delivery delay


Illustration1
Illustration

  • Simulation Results

    Figure. 8 throughput, delay and financial cost as a function

    of the exogenous arrival rate λ1o in network 1


Outline5
OUTLINE

  • Background

    • Traditional Energy Grid vs. Smart Grid

    • Heterogeneity of Smart Grid Communication

  • Heterogeneous Communication Architecture

    • User Sensor Network (USN) Access Network Level

    • USN Next-generation Network (NGN) Level

    • USN Middleware Level

  • Optimal Traffic Allocation to Heterogeneous Networks

    • System Model

    • Illustration of Optimal Allocation Strategy

  • Conclusions


Conclusions
Conclusions

  • Distributed energy production, consumption and dispersed users in smart grid system pose a great necessity for ICT infrastructure

  • The heterogeneity of smart grid control and application messages and the available delivery networks requires an integrated system that can achieve interoperability among the heterogeneous technologies seamlessly

  • Traffic assignment (admission control) problem is far more complicated and need efforts for future exploration


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