Realization Of Energy Harvesting Wireless Sensor Network (Eh Wsn) With Special Focus On The Energy Harvesting Systems Tan Yen Kheng

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Realization of Energy HarvestingRealization of Energy HarvestingRealization of Energy Harvesting Realization of Energy Harvesting Wireless Sensor Network (EHWireless Sensor Network (EH--WSN) WSN) -- with special focus on the energy with special focus on the energy

harvesting systemsharvesting systems

Presented by

Yen Kheng Tan and A/Professor S.K. PandaDepartment of Electrical & Computer Engineering

National University of Singapore (NUS)[email protected]

Research MotivationsUbiquitous/Pervasive computing (Invisible/Disappearing)– As people find more ways to incorporate these inexpensive, p p y p p ,

flexible and infinitely customizable devices into their lives, the computers themselves will gradually "disappear" into the fabric of our lives (http://www.microsoft.com/presspass/ofnote/11-02worldin2003.mspx)

– “Will we be surrounded by computers by 2010? Yes, but we won’t know it.” Bill Gates in ‘The Economist’, 2002

Realization Of Energy Harvesting Wireless Sensor Network (EH-WSN) - with special focus on the energy harvesting systemsRealization Of Energy Harvesting Wireless Sensor Network (EH-WSN) - with special focus on the energy harvesting systems

HealthcareBio-medicalEnvironmentMilitary

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Research Motivations (cont’d)Energy Harvesting/Scavenging Technology– “The pervasiveness and near-invisibility of computing will be p y p g

helped along by new technologies such as … inductively powered computers that rely on heat and motion from their environment to run without batteries.”

Bill Gates in ‘The Economist’, 2002– “The importance of energy harvesting has motivated the

German federal government to include the topic in its €500 million (about S$1 billion) research support program.”


EE Times article, 2007

Goal: To investigate energy harvesting technologies that can power tiny pervasive computing devices indefinitely in a smart environment

Architecture of Smart Environment


Reference: D.J. Cook and S.K. Das, ”Wireless Sensor Networks, Smart Environments: Technologies, Protocols and Applications”, John Wiley, New York, 2004.

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Sensor node has limited energy supplyHard to replace/recharge nodes’ batteries once deployed, due toQ

Design Challenges in Conventional WSN

- Number of nodes in network is high- Deployed in large area and difficult locations like hostile

environments, forests, inside walls, etc- Nodes are ad hoc deployed and distributed- No human intervention to interrupt nodes’ operations

=> Restricted resources available for collecting and relaying dataConfigure and/or reconfigure sensor nodes into network

Realization Of Energy Harvesting Wireless Sensor Network (EH-WSN) - with special focus on the energy harvesting systems

Network and communication topology of WSN changes frequently- Addition of more nodes, failure of nodes, etc

Tradeoff between Energy and Quality of ServiceLimited finite energy and demand for QoS

=> Prolong network lifetime by sacrificing application requirements such as delay, throughput, reliability, etc

Q

Q

Energy related matter in WSN- Power management for sensor node

Research Issues in WSN

g- Energy efficient protocols in medium access control (MAC) and

routing layersNetwork performance- Quality of Service (QoS) e.g. data throughput, reliability,

propagation delay, etc- Network security

Sensor network deployment


- Sensor network deployment- Real-time location estimation

WSN performances highly dependent on energy supply=> Higher performances demand more energy supply

=> Bottleneck of Conventional WSN is ENERGY

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Compare battery estimated life of a Crossbow sensor node operating at 1 % and 4 % duty cycles

Typical Power Consumption of a Wireless Sensor Node

Duty cycle = 1 %


Duty cycle = 4 %

Longer operational lifetime => Require more energy supply => Higher energy storage capacity => Larger battery size

Wireless Sensor Network (WSN) onlyEnergy Harvesting Wireless Sensor Network (EH-WSN)Energy Harvesting in Wireless Sensor Network

Finite energy source such as batteries

Energy manage-

ment circuit

Sensor nodes in WSN

Energy Harvest

-ing

Batteries => finite energy supply => limited WSN lifetime– Network failure occurs after some nodes go into idle state– Nodes go into idle state after energy supply exhausted

??? + Batteries => sustainable WSN lifetime$Realization Of Energy Harvesting Wireless Sensor Network (EH-WSN) - with special focus on the energy harvesting systemsRealization Of Energy Harvesting Wireless Sensor Network (EH-WSN) - with special focus on the energy harvesting systems

EH + Batteries => prolong energy supply => sustainable WSN lifetime– Recharge batteries in sensor nodes using EH– Prolong WSN operational lifetime or even infinite life span$

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Power Aware EH-WSN Considerations


Adapted from MIT, Chandrakasan et al.

Research Issues in EH-WSN1. Quality of service (QoS) under constrained energy supply

– Trade-off between energy consumption in sensor node & gy pQoS in WSN

– Determine optimal operating point e.g. optimal sleep and wakeup strategy => achieve highest system utility

2. Optimization of energy usage based on EH device behaviour– Harvested energy largely depend on ambient conditions– Optimize energy usage to satisfy QoS constraints under


p gy g y Qvarying energy supply

3. Cross-layer optimization– Energy optimization in WSN using EH in cross-layer fashion

e.g. energy-aware routing and MAC protocols 4. Integration with new wireless technologies

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Design and Development of EH-WSNObjective: Integrate energy harvesting systems into wireless sensor nodes target for specific applicationsg p pp– Investigate on various energy harvesting (EH) sources– Model and characterize the performances of energy

harvesters– Develop suitable power/energy management circuits

between energy harvester and load– Validate EH sensor nodes in practical applications


p pp

Finite energy source such as batteries

Power/ Energy

manage-ment

circuits

Sensor nodes in EH-WSN

Energy harvest

-ing sources

i.e. wind

Energy harvest

ers

Energy Harvesting Sources and their Energy Harvesters


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Existing Research WorksEH-WSN research– Indoor Solar EH (SEH) wireless sensor node for smartIndoor Solar EH (SEH) wireless sensor node for smart

environment– Outdoor Solar EH for military portable computing system– Vibration EH (VEH) wireless sensor node for condition

based maintenance of large equipment– Thermal EH (TEH) from human warmth for wireless

body area network


body area network– Wind EH (WEH) wireless sensor node for remote

sensing and management of disastersOther energy related research– Wireless energy transfer

Indoor SEH Wireless Sensor NodeExample of indoor testbed in Pavoda Cables

Issue on battery duration for non–cabled nodes→ even worst for large numbers of nodes (100-1000)

Introduce indoor solar energy

Michele Zorzi, 2008


gyharvesting for indoor nodesBulky size and heavy weightLarge area required by nonocrystaline solar panels

Dallas IEEE, 2007

Solar panels

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Indoor SEH Wireless Sensor Node (cont’d) Resistance Emulation using DCM boost converter to achieve MPPT during impedance matchingg p g


+

-

sTtv )(1

sTti )(1

2/411

2/411

M ratio, Conversion2

e

g

g

RRVV

KdVVM

++=

++==

ss

e

Ts

T

fdL

TdLdR

tvTtdtiss

22

1

2

1

e

22)(

)(2

)()(

R Resistor, Emulated

==

=

Indoor Solar powered sensor node

Battery-powered sensor node

Voltage waveforms of DCM DC-DC boost converterIndoor SEH Wireless Sensor Node (cont’d)

Vinductor (C3)

Vsolar (C4)PFM from VCO (C1)

1

2


DCM boost DC-DC converterVswitch (C2)1 2

3

3

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Evaluate power harvested from solar panel with MPPT for various loading conditions (Vref = 0.93 V)

Indoor SEH Wireless Sensor Node (cont’d)

Rload VloadPharvested

w/emulator@Rload

Pharvestedw/Rload

Difference in harvested power

180 Ω 1.510 V 12.67 mW 8 mW 58.4 %

270 Ω 1.836 V 12.48 mW 6 mW 108 %

470 Ω 2.412 V 12.38 mW 3 mW 312.7 %

680 Ω 2 907 V 12 43 mW 2 mW 521 5 %


Significant increase in power harvested with resistor emulator Rload // Re matches with Rsolar → fs changes, Re changes

680 Ω 2.907 V 12.43 mW 2 mW 521.5 %

1200 Ω 4.1 V 14.00 mW 1 mW 1300 %

3900 Ω 6.906 V 12.23 mW 0.32 mW 3721.9 %

Q

Outdoor SEH Portable Computing SystemDeployment testbed and experimental results


Experimental TestbedCourtesy of DSO & NUS research team

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Primary Circuit Secondary Circuit

Maximize VEH Using SCE TechniqueIllustration of synchronous charge extraction circuit

Piezoelectric generator

Switch S closed


Primary Circuit: Accumulated charges extracted from piezoelectric generator transferred to transformer, L

Secondary: Open-circuitCircuit

Switch S OpenPrimary Circuit: Open-circuit & generated charges accumulated in generator

Secondary: Stored energy in L Circuit gets released to

Cr & RL

Maximize VEH Using SCE Technique (cont’d)Piezoelectric generator

Vibration energy source

Vibration energy source

Shaker

SCEC

Latching CircuitAllows applications with higher power consumptions to be operated intermittently, rather than continuously

Bootstrap CircuitAccumulates sufficient energy in storage cap, which then provide the initial startup power to the control circuit.Buck ConverterRegulates the output voltage @5V


Power consumption of control circuit ~300 μW (60μA @5V)

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Maximize VEH Using SCE Technique (cont’d)Performance of SCE technique

Theoretical results 8.8 mW


Y.K. Tan, J.Y. Lee and S.K. Panda, “Maximize Piezoelectric Energy Harvesting Using Synchronous Electric Charge Extraction Technique For Powering Autonomous Wireless Transmitter”, IEEE International Conference on Sustainable Energy Technologies (ICSET 2008), 1254-1259, 2008.

Simulation resultsExperimental results 5.6 mW

6.7 mW

TEH from Human Warmth for WBANOverview of WBAN and its TEH system


Human wrist

TEH system

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TEH from Human Warmth for WBAN (cont’d)Circuit design and video demonstration


D.C. Hoang, Y.K. Tan and S.K. Panda, “Thermal Energy Harvesting From Human Warmth For Wireless Body Area Network In Medical Healthcare System”, The 8th IEEE International Conference on Power Electronics and Drive Systems, 2009, in-progress

System-level problems to be addressed- Fluctuating wind energy source → load energy requirement

WEH Wireless Sensor Node

Fluctuating wind energy source load energy requirement- Min and max wind speeds available → voltage regulation and

energy storage- Portability of wind energy harvester system → size and

weight- Energy consumed by wind speed sensing and wireless

communicating hem

e 2

hem

e 1

Wind turbine

Power management


Motivation- Self-sufficient and sustainable by wind energy source- Compact and miniature wind energy harvester

=>Two WEH schemes implemented to power remote area wind speed sensor in disaster management application

ScSc

and RF transmitter circuits

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Video demonstrations on the wind turbine and wind piezoharvesting systems$

WEH Wireless Sensor Node (cont’d)

g y

Scheme 1: Wind turbine Scheme 2: Wind piezo


Y.K. Tan & S.K. Panda, “A Novel Piezoelectric Based Wind Energy Harvester for Low-power Autonomous Wind Speed Sensor”, 33th Annual IEEE Conference of Industrial Electronics Society, pp.2175-2180, 2007.

R.J. Ang, Y.K. Tan & S.K. Panda, “Energy harvesting for autonomous wind sensor in remote area”, 33th Annual IEEE Conference of Industrial Electronics Society, pp.2104-2109, 2007.

Magnetic energy harvesting based on Ampere’s law and Faraday’s law

MEH through Inductive Coupling for WSN

y

AC power source

Gauss meter

Magnetic energy


Y.K. Tan, S.C. Xie and S.K. Panda, “Stray Magnetic Energy Harvesting in Power Lines through Inductive Coupling for Wireless Sensor Nodes”, The Proceedings for the 2008 nanoPower Forum (nPF’08), Darnell Group, Irvine, Costa Mesa, California, 2008.

Resistor load bank

Magnetic energy harvesting circuit

Magnetic energy harvesting circuit

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Wireless Transmission of Power with Magnetic Resonance

Source Transmitting Receiving Load

Efficiency (%) vs Inductance (H)

50

60

70

80

y(%

)

Coilg

Coilg

Coil Coil

Efficiency (%) vs Capacitance (F)

10

20

30

40

50

60

70

80

Effic

ienc

y (%

)

0

10

20

30

40

1.00E-07

1.00E-06

1.00E-05

1.00E-04

1.00E-03

1.00E-02

1.00E-01

1.00E+00

Inductance (H)

Effic

ienc

y


Transmitting end

Receiving end

01.00E-15 1.00E-13 1.00E-11 1.00E-09 1.00E-07 1.00E-05 1.00E-03

Capacitance (F)

Efficiency (%) vs Conductor radius (m)

0102030405060708090

100

0 0.002 0.004 0.006 0.008 0.01Conductor radius (m)

Effic

ienc

y (%

)

Efficiency (%) vs Distance (m)

0

20

40

60

80

100

120

0 0.5 1 1.5 2 2.5Distance (m)

Effic

ienc

y (%

)

Case Study ExampleWind Energy Harvesting Wireless Sensor Node

Modeling and Analysis– Modeling and Analysis– Design considerations– Implementation and hardware prototype– Live Demonstration


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Fire behavior on the Bor Forest Island under the FIRESCAN fire research program

Wind Speed Distribution

p g

Nominal daily wind speed in the deployment location over a


Nominal daily wind speed in the deployment location over a period of one monthWind speed high, wind energy harvester harvests energy for electronic circuitries and charge supercapacitorWind speed too low, supercapacitor acts like DC power source to power electronic circuitries

Functional Model and Power Equations of Wind Turbine

gearaeromech PP η=AvvFP 1 3== ρ


generatorgearpitchp

generatormechelec

gearpitchp

gearaeromech

CvR

VIPP

CvR

ηηθλρπ

η

ηθλρπ

η

),(21

),(21

32

32

=

==

=

vvvaaaC

CvR

CPP

AvvFP

p

pitchp

pitchpwindaero

Awind

2,)1(4

),(21

),(2

22

32

−=−=

=

=

==

θλρπ

θλ

ρ

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Characteristic of Wind TurbineAC electrical power generated by wind turbine vs voltage and current under varying wind source

MPPT ptMPPT pt

y g


rvwherek

dtdiLRIV s

ssλωφω =++= ,Q

Does not exist any voltage or current reference point for maximum power harvesting over the range of wind speeds

Fixed reference V and I MPPT approaches are not applicable

AC electrical power generated by wind turbine vs load resistance under varying wind source

Characteristic of Wind Turbine (cont’d)

y g


Maximum power extraction at optimal load resistance of 100Ω– Low optimal resistance => high output current EH sourceDeviate away from optimal loading, either very light or heavy loads, will result in significant drop in output power harvested

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Overview of WEH Wireless Sensor Node


Power Power management management

electronic electronic circuitscircuits

Resistance Emulation (RE) is based on the concept of impedance matching

Resistance Emulation Approach

p g

RRR //


LoadconverterbyEmulatedE RRR //=

bb DRRRwhereDR

R

RV

RV

osin

o

in

o

o

in

in

,)1(

12

22

⇒=

⎟⎟⎠

⎞⎜⎜⎝

⎛−

=

=

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Performance of resistance emulator for matching source Rs = 150 Ω with dynamic load (charging supercapacitor)

Performance of Resistance Emulator

s y ( g g p p )

Ropt = 150 Ω Pmppt = 7.5 mW @3.5 m/s

urce

resi

stan

ce (Ω

)

elec

tric

al p

ower

(mW

)


Supercapacitor is initially uncharged, i.e. Rload = 0 ΩAs supercap is charged, Rload changes => dynamic loadRopt = 150 Ω remains and Pmppt = 7.5 mW @3.5 m/s achieved

Sou

DC

eLoad resistance (Ω) Duty cycle

Performance of resistance emulator for matching source Rs = 150 Ω with dynamic load (charging supercapacitor)


s y ( g g p p )

ourc

e vo

ltage

(V)

Load

vol

tage

(V)

VV 1=


As supercap is charged– Vcap increases, but Vsource remains at Vmppt = 1.07 V– Rload changes, D changes to maintain Ropt = 150 Ω

So L

Load voltage (V) Duty cycle

il VD

V)1( −

=

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Performance of WEH w/ and w/o resistance emulator in charging supercapacitor (act like a dynamic load)


g g p p ( y )

w/ MPPT control

Vmax = 2.14 V

w/o MPPT control Vmax = 0.66 V 66.0sec)500()2

sec101514.2sec)500()1

,5.5

)1()(

/

max,

max,

cap

mpptw

cap

cap

t

capcap

VtV

VtV

VVFor

eVtV

τ

τ

==

=

==

=

−=−


constanttimechargingtheisτwhere

sec3911

//

/

mpptowmpptw

mpptow

ττ

τ

<<⇒

=

Demonstrate the effects of MPPT and WEH on the operation of a sensor node i.e. 1 sec per transmission


p p@ 3.6 m/s wind speed

Vo, boost

Vi, boost


Ii, boost

w/o MPPTw/WEH

w/MPPTw/WEH

w/o MPPTw/o WEH

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Live Demonstration


ConclusionsChallenges and research issues in a sustainable WSN – energy supply is the bottleneckWSN energy supply is the bottleneckIntegration of energy harvesting wireless sensor networkDesign considerations for energy harvesting systems in practical applicationsMaximize energy harvesting with dedicated power management solutions


management solutions

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Thank you!

Questions and Answers


National University of SingaporeYen Kheng Tan

[email protected] or [email protected]

Documents

Realization Of Energy Harvesting Wireless Sensor Network (Eh Wsn) With Special Focus On The Energy Harvesting Systems Tan Yen Kheng