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Energy Efficient Com m unication Netw orks Design for Dem and Response in Sm art Grid

• 1Dept. of Electrical & Computer Engineering,

2Institute for Integrated Energy Systems, Dept. of Mech. Eng.,

University of Victoria, Victoria, BC, Canada

Lei Zheng1, Simon Parkinson2, Dan Wang2, Lin Cai1, and Curran Crawford2

• I. Background & Motivations

Outline

• II. Main Contributions
• III. Future Topics
• IV. Conclusion

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• I. Background & Motivations

Outline

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 Demand Response (DR) in Smart Grid  DR Control Strategy  Impact of Communication on DR

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Dem and Response ( DR)

• Stable

power system

• peration

depends

• n

a constant balance between supply and demand；

• The increased supply-side uncertainty can result in

inefficiency in operating conventional power systems generation, such as intermittent renewable energy like Wind Power;

• Smart grid introduces a promising new direction for

accommodating the supply-side uncertainty by implementing demand-side control;

• I. Background & Motivations

DR Control Strategy in Sm art Grid

Fig.1 DR Control Strategy in Smart Grid

• Intelligence of Smart grid needs reliable communications.

Open topic: How m uch w ill com m unications perform ance im pact DR in Sm art Grid?

• I. Background & Motivations

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The m ain m otivations

• To investigate the impact of packet losses on

the DR control strategy introduced in [ 1] .

• To design an energy efficient communication

networks to satisfy requirement of DR control in the smart grid.

• I. Background & Motivations

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• II. Main Contributions
• I. Background & Motivations

 Impact of Communication on DR Control Strategy Packet loss in Communication Networks Energy Efficient Communication Network Design

Outline

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I ntroduction of DR strategy

• The Heater Pump control Problem in [1]
• The control logic: utilizing the device-level dynamics of the

local hysteresis control logic that governs the thermostat controlling the heat pump's operational state n.

• Discrete State-equation
• The Optimal DR Control
• II. Contribution-I

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I m pact of Packet Loss in Com m unications

• The error or missing of these data packets containing the

power-state from individual smart meters will lead to underestimation of the power demand by the LA;

• On the other side, packet loss results in more loads

currently participating in the aggregate load model than the LA expects, potentially leading to the dispatch of more demand than actually desired.

• II. Contribution-I

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Model-Driven Sim ulations

• A population of 1000

individual thermal heating loads are simulated;

• These loads represent electric

air-source heat pumps for residential applications (approximately 6 kWe/unit);

• Each unit is simulated through

coupling its thermostat response to a building heat transfer dynamics model that generates the air temperature input to the thermostats.

Table.1 Parameters in Model-driven Simulations

• II. Contribution-I

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Sim ulation Results - I

Fig.2 Model inputs and uncontrolled heat pump load subject to the outdoor temperature regime given in the bottom pane. Fig.3 The effects of packet loss on the performance of the aggregate load controller.

• II. Contribution-I

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Fig.4 The effects of packet loss on the total demand and response error. Each performance metric is plotted as a percent of the base case~ (i.e., PLR = 0, and controlled) The accuracy quickly deteriorates with increased PLR; The power gradient and regulation reserve capacity do not display the same level of sensitivity.

Sim ulation Results - I

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• II. Contribution-I

• Grid Network Topology

– Clustering-based hierarchical scalable network – service area with uniformly distributed nodes

• Grid Network Packet Forwarding

– Multi-hops forwarding with Manhattan Walk – Collision-free channel reservation – No retransmission or packet aggregation

• IEEE 802.15.4 Standards

– DSSS+ BPSK/ OQPSK:

• 868/ 915MHz, 2.4GHz

– PSSS+ ASK:

• 868/ 915MHz

About Com m unication Netw orks

L L×

Fig.5 Grid Network Topology.

• II. Contribution-II

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Packet Loss Perform ance

• End-to-End Packet-Loss-Ratio
• Bit-Error-Rate (BER) under different PHY options
• Two-way Path-Loss Model
• II. Contribution-II

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Fig.6 End-to-end PLR with different PHY options. Fig.7 Impact of DA location on end-to-end PLR.

• II. Contribution-II

Sim ulation Results - I I

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         + = − − ∏ ≤ < − − ∏ = − = = = ==

− − = − − = −

. 1 , ) 1 )( 1 ( ; 2 , ) 1 )( 1 ( ; 2 , ) 1 ( ; 1 , , 1 If

) ( 1 2 ) ( 1 2 ) 1 ( ) ( i a i r l k Η k l i a i r l k Η k l r k Η a i r i Η a i t i i

n k P P n k P P P k P P k P } kP P{E n

Com m unication Energy Consum ption

• Number of Hops
• Distribution of Energy Consumption

. aggregator data

• f
• n

coordinati

• )

, (x ; node

• f
• n

coordinati

• )

, (x

c c i i

y i y

; 1 , If = = == } P P{E n

t i i

; 2 , 1 1 , , 1 If    = − = = = == k P k P } kP P{E n

q i a i t i i

• II. Contribution-III

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Energy Efficient Netw ork Design

• With a small cluster size, the transmissions in each hop have a

shorter communication distance, which leads to a low packet loss for a single hop.

• The number of hops to relay a packet from a smart meter to the

data aggregator will be large, which means high energy consumption for communication

• II. Contribution-III

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Fig.8 Impact of DA location on mean energy consumption. Fig.9 The optimal designed communications networks.

• II. Contribution-III

Sim ulation Results - I I I

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• II. Main Contributions
• I. Background & Motivations
• III. Future Topics

Outline

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• Analysis Model；

Considering Geometric Distribution of nodes distance

• Fixed cluster-header -> Random cluster-header;
• Delay
• III. Future Topics

considering two “Range”: Transmission Range & Interference Range

Topics

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e.g.

• 1. Random Distance between two nodes in one/ two cluster;
• 2. Random Distance between a given node to a random node

in the same / neighbor cluster.

S

Outline

• IV. Conclusions
• II. Main Contributions
• I. Background & Motivations
• III. Future Topics

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 We have first investigated the impact of packet losses on DR control accuracy through model-based simulations, which confirm the importance of limiting the PLR to ensure control effectiveness.  Based on the results, we have modeled and analyzed the packet loss performance of communication networks by using a clustering-based grid network topology .  And discussed the optimal network design considering both of the QoS requirement of DR and the energy consumption for communications.

• IV. Conclusions

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[ 1] S. Parkinson, D. Wang, C. Crawford, and N. Djilali. Comfortconstrained distributed heat pump management. Accepted: Proc. of IEEE ICSGCE 2011, 2011. [ 3] H. Farhangi. The path of the smart grid. Power and Energy Magazine, IEEE, 8(1): 18 –28, january-february 2010. [ 6] D. Callaway. Tapping the energy storage potential in electric loads to deliver load following and regulation, with application to wind energy. Energ. Convers. and Manag., 50(9): 1389–1400, 2009. [ 7] A. Kashyap and D. Callaway. Controlling distributed energy constrained resources for power system ancillary services. In Proc. of IEEE PMAPS, pages 407–412, 2010. [ 8] D. Niyato, P. Wang, E. Hossain, and Z. Han. Impact of packet loss on power demand estimation and power supply cost in smart grid. In Proc.of IEEE WCNC, pages 6–10, 2011. [ 9] IEEE standard for information technology- telecommunications and information exchange between systems- local and metropolitan area networks- specific requirements part 15.4: Wireless medium access control (mac) and physical layer (phy) specifications for low-rate wireless personal area networks (wpans). IEEE Std 802.15.4-2006 (Revision of IEEE Std 802.15.4-2003), pages 1 –305, 2006.

Reference

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Questions/ Com m ents?

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