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AbstractWireless sensor network (WSN) has got

increasingly in-depth study and application because of its small

size, flexible layout, strong reliability and other advantages, but

in the mean time the life of a wireless sensor node is heavily

dependent on the power supply batteries. This paper studies the

design of a wireless sensor node which is powered by a micro

wind turbine generator. It adopts an optimal power

management to make the node working neutrally: never dies out

of energy. This management consists of an AC-DC converter, an

energy storage element and a maximum power transfer

tracking (MPTT) circuit to sustain the operation of wireless

sensor node over a wide range wind conditions. Extensive

experimental results show that through the proposed power

management, wind energy conversion efficiency improves to

80%, and the harvested power increases three times than

before. Thus this wind powered wireless sensor node could workindependently and has a good application prospect.

I. INTRODUCTIONHE limited available lifetime is a key bottleneck for most

battery equipped wireless sensor networks. Low power

research to maximize the battery lifetime before

replacing it has been a critical undertaking. Therefore,

harvesting energy from the environment has been widely

recognized as a promising approach to ensure the

sustainability of the network. For an energy harvesting WSN

(EH-WSN), the sensor nodes are integrated with an

energy-harvesting unit that harvest energy from the wind,

vibration, solar, etc [1]. Wind energy harvesting isparticularly attractive because of the ubiquitous availability

of wind power and its relatively high power density. This

paper proposes a novel wind energy transferring circuit and

energy management strategy.

So far, several researches have been conducted to address

the problem of MPPT in the wind-powered WSN, Tan and

Panda [2],[3] had successfully implemented a small-scale

WSN powered by micro wind turbine generator used for

forest fire monitoring, and Carli et al. [4] had presented a

design methodology to get maximum conversion efficiency

over a wide range of operating conditions. The key

underlying schemes for those works are maximum power

transfer tracking (MPTT) technique and energy storage

management (Li-Ion battery and supercapacitor). MPTT,

which is based on the maximum power point tracking

(MPPT) technique, not only considers the energy extracted

Manuscript received December 30, 2012.

Y Wu, corresponding author, is with the Automation college, NanjingUniversity of Aeronautics and Astronautics, Nanjing, 210016, PRC (phone:

025-84892766, e-mail: bonnywu2005@yahoo.com.cn)

W Liu is with the Automation college, Nanjing University of Aeronauticsand Astronautics, Nanjing, 210016, PRC (e-mail: wenboliu@nuaa.edu.cn)

Y Zhu is with the electrical department, Suzhou University of Science andTechnology, Suzhou, 215009, PRC (e-mail: zhuyongjun_001@163.com).

from the PV panel, but also the conversion efficiency of the

dc-dc converter, is the latest research result [5]. For the

energy storage element, to date, batteries are the primary

type. However, supercapacitor-only supplies and hybrid

power sources have also emerged in a range of applications

[6], [7], and different energy management strategies have

been designed based on their own storage structures [8], [9].

In this paper, we present a low-power wind energy

harvesting system for wireless sensor node. The proposed

system adopts dynamic MPTT and is able to control the

energy flows automatically. A buck-boost converter is

employed for the power conditioning. A low-power

microcontroller (MCU) is used to manipulate the energy

management for optimal utilizing the energy harvested. And

that it has connected with a RF transceiver to make up awireless sensor node.

The remainder of this paper is organized as follows.

Section 2 presents and describes the overview of the proposed

system. Section 3 analyzes the working principles and energy

management strategy. Section 4 shows the experimental

results including the component level and system level

performance. Section 5 concludes the paper.

II.WIND HARVESTING SYSTEM DESIGNThe proposed system for wind energy harvesting is shown

in Fig.1. In general, the requirements of implementing the

system involving wind turbine generator (WTG),

supercapacitor, and dcdc converter are listed as follows:1)MPTT for the WTG;

2) Ability to charge the supercapacitor independent of the

load; and

3) Capability of the supercapacitor to support the load

when wind is not present or sufficient.

As can be seen below, Fig.1 shows a diagram of the wind

energy harvesting wireless sensor node. The system adopts a

buck-boost converter, connected in series to the load, which is

able to step up or down the input voltage. A 10F, 2.7V

supercapacitor is chosen as the energy storage element due to

its virtually unlimited life cycles and simple charge

mechanism. A low-power MCU MSP430 from Texas

Instruments implements the MPTT algorithm and powermanagement. And a conventional PWM controller is used to

drive the buck-boost converter when MCU is in sleep mode;

in addition a switch circuit is chosen to gating the driving

signal as well.

Generally the load (mainly the RF transceiver and MCU) is

powered by the WTG. At the same time, the remaining power

is transferred to the supercapacitor through the buck-boost

converter, so the supercapacitor is charged. On the contrary,

when wind power is insufficient to supply, discharging

operation is performed, supercapacitor will handle the load

Design of a Wind Energy Harvesting Wireless Sensor Node

Yin Wu, Wenbo Liu and Yongjun Zhu

T

Third International Conference on Information Science and Technology

March 23-25, 2013; Yangzhou, Jiangsu, China

978-1-4673-2764-0/13/$31.00 2013 IEEE 1494

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requirement independently without the WTG. Hence, charge

or discharge operations are determined by the specific

running conditions of wind and load. Moreover, MPTT

algorithm can be achieved by controlling the duty ratio of the

buck-boost converter, and it is running periodically to save

power: For the environmental conditions such as temperature

and weather change relatively slow compared with the

processor speed.

Fig. 1. Diagram of the proposed system

III. PRINCIPLE OF SYSTEM OPERATIONA. Wind Turbine Generator

We use a plastic seven bladed horizontal axis wind turbine

here, which has a radius of 5 cm and an AC peak voltage of

7V when the wind speed is 5m/s. From [4] we know that for a

fixed wind speed, there is a load value that maximizes the

power generated by the WTG. So we tested our WTG under

different wind speed, and recorded the corresponding output

power that at the rectifier output port in Figure 2:

As can bee seen in Fig.2, maximum output power of WTG

is achieved when load impedance is 500. And the local

average wind speed is 3.62m/s in April and May in Nanjing,

China [10], so the output power of proposed WTG could be

10.89mW if load value meets 500. Moreover we find thatwhen the external load resistance matches 500, the

harvested power is always maximized for any incoming wind

speed. Notice that germanium diode is chosen to make up the

rectifier due to its ultralow forward voltage drop.

B.Power Management UnitThe PMU runs a continuously matching between the

source (WTG) impedance and the load (energy storage,

PMU, and sensor node) impedance to achieve optimal power

conversion efficiency. The purpose of PMU circuit is to make

a constant input resistance of about 500 while harvesting

the energy into the supercapacitor. As in this paper we chose a

buck-boost converter to achieve this purpose. The circuit is

operating in a discontinuous current mode, as shown in

Figure 3. The drive signal of MOSFET is controlled by MCU.

As demonstrated by classic text-books on power

electronics [11], we have the following expression:22

)1/(/ DDRRIO

= (1)

WhereO

R is the load impedance,I

R is the internal

impedance of WTG, D is the duty ratio of buck-boost. Thus

by adjusting D and OR , we could get the maximum harvestedpower when

IR meets 500.

C.Energy Management StrategyIn this paper,

WinV ,

SCV ,

WinE ,

MinE and

SCE represent the

voltage of WTG and supercapacitor, the energy output of

WTG, the minimum energy requirement for system startup

and the energy stored in the supercapacitor, respectively.

First, after the installation of the system, WTG has the ability

to harvest energy to supply buck-boost converter, whenWin

E

is greater thanMin

E , buck-boost converter is turned on and the

supercapacitor is being charged. At this time, the buck-boost

converter is mainly used to power PWM controller and the

switch circuits (the dashed line in Fig.1). Only whenSC

V

exceeds 1V, supercapacitor could discharge to support the

load. Note that DC-DC regulator regulates the voltage of

supercapacitor into 3.3V to power electric load: MCU, RF

transceiver, et al. Then MCU starts running MPTT algorithm.

Notice it must be discharged for protection wheneverSC

V

exceeds 2.5V. If wind power decreases, supercapacitor would

power the whole system until running out. Whole diagram of

power management is shown is Fig.4.

Fig. 4. Energy management block diagram.

When MCU prepares to sleep, it orders the PWM

controller to generate the pulses, since the average current

Fig. 3. Mppt circuit with supercapacitor.

Fig. 2. Output power of WTG VS. Load impedance.

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dissipated by the MCU is approximately an order of

magnitude higher than the latter [12].

IV. EXPERIMENTAL RESULTSTo verify the feasibility and measure the performance of

proposed wind powered WSN, we prototyped the system and

experimented it from the early April to May, placed in the

No.29, Yudao Street, Nanjing, China (32 degrees north

latitude and 118.8 degrees east longitude). Experimentalresults are presented in this section.

All the circuit parameters should be carefully chosen to

minimize the energy loss of components. The main

components and circuit parameters used are listed in Table 1.

First, we evaluate the function ability of proposed MPTT

algorithm: we connect a 1.2K resistor to the output of

buck-boost converter as electric load without subsequent

supercapacitor et al. when the environment wind speed is 2-6

m/s. Thus based on (1), we can operate MPTT algorithm by

adjusting the duty ratio of buck-boost converter. Result shows

that when the wind speed is 3.62m/s, energy conversion

efficiency is:

%80)/(/ 2 ===InInOOutInOut

IVRVPP

Another investigation being carried out is to determine the

power consumption of the associated control, sensing, and

PWM generation electronic circuits and its significance as

compared to the harvested power. Based on the voltage and

current requirements of each individual component in the

sensing and processing circuits, the total power consumption

of the electronic circuits is calculated to be:

mWPPPPPWMocessSenseConsume

681.0Pr

=++=

Taking into account both the power loss of MPTT and

energy management, respectively the performancecomparison of wind-harvesting system with MPTT andwithout MPTT is tabulated in the bar chart shown in Fig. 5.

Where the left column represents the power harvested

without MPTT; the right column in black represents thepower harvested with MPTT and energy management,

especially the white part is the power losses. We can see that

the right column is significant improved to nearly three times

than the left. So it is of great use to implant MPTT and energymanagement into wind-harvesting WSN.

Next we use supercapacitor as energy storage to test the

charging characteristics. We record and compare the voltage

of supercapacitor when MPTT turns on and off.In Fig.6 it shows that the voltage of supercapacitor

increases to 1.94V with MPTT after 500s, while without

MPTT the voltage is only 0.62V. Hence, this exhibits the

superior performance of the wind-harvesting system withMPTT scheme over its counterpart under dynamic load

condition.

At last, we conduct a short term experiment with the whole

wind powered wireless senor node: it is placed on the roof of

a teaching building for one week, and transmitted a

predefined data to the sink under a 10% duty cycle (6 secondsper minute). We record the residual energy in the

supercapacitor as shown in Fig.7 and it can be seen that the

energy of supercapacitor never goes down to zero and couldbe charged up quickly. The result proves that the windpowered wireless sensor node presented in this paper could

work well-balanced and self-sustainable.

V.CONCLUSIONSThis paper has investigated an energy harvesting and

Fig. 5. Performance comparison between the Wind-harvesting system

without MPPT and with MPPT plus its associated losses for variousincoming wind speeds.

Fig. 6. Performance of wind-harvesting system with MPTT and

without MPTT for charging a supercapacitor.

Fig. 7. Residual energy of supercapacitor.

TABLEI

COMPONENTS AND CIRCUIT PARAMETERS

Components Details

Supercapacitor 10F, 2.7V

PWM Controller UCC2808-2 (TI)

MCU MSP430F2247(TI)

RF Transceiver CC2520(TI)

Regulator LTC3525D-3.3

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management architecture that utilizes supercapacitor asenergy storage for a wind-harvesting wireless sensor node. Anovel configuration is proposed to provide independent

supercapacitor charging, MPTT function and energy transfer

management. For this configuration, a buck-boost converter

is proposed and tested. And the energy transfer controlstrategy is analyzed. A complete system is constructed and

measured to confirm the feasibility of the proposed approach.

Currently, we are working on a hybrid energy harvestingsystem platform which contains solar, wind and vibrationenergy et al.

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