Energy Efficient Communication Networks Design ... - Semantic Scholar

Energy Efficient Communication Networks Design for Demand Response in Smart Grid

Lei Zheng1, Simon Parkinson2, Dan Wang2, Lin Cai1, and Curran Crawford2 1Dept.

of Electrical & Computer Engineering, 2Institute for Integrated Energy Systems, Dept. of Mech. Eng., University of Victoria, Victoria, BC, Canada

LOGO

Outline I. Background & Motivations II. Main Contributions III. Future Topics IV. Conclusion

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Outline I. Background & Motivations   

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

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I. Background & Motivations Demand Response (DR)  Stable power system operation depends on constant balance between supply and demand；

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 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;

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I. Background & Motivations DR Control Strategy in Smart Grid

Fig.1 DR Control Strategy in Smart Grid

 Intelligence of Smart grid needs reliable communications. Open topic: How much will communications performance impact DR in Smart Grid? 5

I. Background & Motivations The main motivations  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.

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Outline I. Background & Motivations II. Main Contributions 

Impact of Communication on DR Control Strategy

Packet loss

in Communication Networks

Energy Efficient Communication

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Network Design

II. Contribution-I Introduction 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

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II. Contribution-I Impact of Packet Loss in Communications  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.

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II. Contribution-I Model-Driven Simulations  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 Table.1 Parameters in Model-driven Simulations thermostats. 10

II. Contribution-I Simulation Results - I

Fig.2 Model inputs and uncontrolled heat pump load subject to the outdoor temperature regime Fig.3 The effects of packet loss on the performance of the aggregate load controller. given in the bottom pane. 11

II. Contribution-I Simulation Results - I 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. Fig.4 The effects of packet loss on the total demand and response error. 12

II. Contribution-II About Communication Networks  Grid Network Topology

– Clustering-based hierarchical scalable network – L × L 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

Fig.5 Grid Network Topology. 13

II. Contribution-II Packet Loss Performance  End-to-End Packet-Loss-Ratio  Bit-Error-Rate (BER) under different PHY options

 Two-way Path-Loss Model

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II. Contribution-II Simulation Results - II

Fig.6 End-to-end PLR with different PHY options.

Fig.7 Impact of DA location on end-to-end PLR. 15

II. Contribution-III Communication Energy Consumption  Number of Hops (x i , yi ) - coordination of node i; (x c , yc ) - coordination of data aggregator.

 Distribution of Energy Consumption If ni == 0, P{E i = P t } = 1; If ni == 1, P{E i = kP t } =  Pi a , k = 1 ;  q 1 − Pi , k = 2

If ni == 1, P{E i = kP t } =  Pi a  r a − P P ( 1 i )  Η (i ) k −1 r r a P ∏ − − P P ( 1 )( 1 Η ( k −1) Η ( k −l ) i ) l =2   k −1 r a ∏ − − P P ( 1 )( 1 Η ( k −l ) i )  l = 2 16

, k = 1; , k = 2; , 2 < k ≤ ni ; , k = ni + 1.

II. Contribution-III Energy Efficient Network 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

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II. Contribution-III Simulation Results - III

Fig.9 The optimal designed communications networks.

Fig.8 Impact of DA location on mean energy consumption. 18

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

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III. Future Topics Topics  Fixed cluster-header -> Random cluster-header;  Analysis Model； Considering Geometric Distribution of nodes distance 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.

 Delay considering two “Range”: Transmission Range & Interference Range

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

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IV. Conclusions  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. 22

Reference [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. 23

Questions/Comments?

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