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Simulation and Experiment of a Fuzzy Logic Based MPPT

Controller for a Small Wind Turbine System

Diana Petrila, Nicolae Muntean

Politehnica University of Timisoara, Bd. Vasile Parvan, no. 2, 300223, Timisoara, Romania

Abstract. This paper describes the development of a fuzzy logic based maximum power point tracking (MPPT) strategyfor a variable speed wind turbine system (VSWT). For this scope, a fuzzy logic controller (FLC) was described,

simulated and tested on a real time hardware in the loop wind turbine emulator. Simulation and experimental resultsshow that the controller is able to track the maximum power point for various wind conditions and validate the proposedcontrol strategy.

Keywords: Small wind turbine system, maximum power point tracking, hardware in the loop wind turbine emulator,fuzzy logic controller.

INTRODUCTION

Variable speed fixed-pitch wind turbine systems become very popular because generally, they are more efficient

in small-scale applications, compared to constant speed, and less expensive than variable-pitch wind turbine

systems. Usually, the main characteristics of the variable speed fixed-pitch wind turbine systems are: direct coupling

with the electric generator and the possibility to use a maximum power point tracking strategy for optimum systemoperation, without an anemometer or other transducers [1] [3].

In this paper the structure of the studied wind turbine system, the designed control strategy, and finally digital

simulation results are presented. The theoretical aspects are validated with real time experimental results obtained

with the proposed controller [4].

SYSTEM OVERVIEW

The analyzed system (Fig. 1) consists of a permanent magnet synchronous generator (PMSG) driven by fixedpitch wind turbine, a diode bridge rectifier (DB), a hybrid DC-DC converter (HDC) - the element that regulates the

turbine speed through the controlled PMSG current, and the load.

To test the designed FLC MPPT strategy, a hardware emulator was needed, which contains: a dSPACE control

board, a voltage source inverter with direct torque control (DTC), a three phase induction machine with a gearbox(GB) the wind turbine equivalent, and a permanent magnet synchronous generator (PMSG). The hybrid DC-DC

converter (HDC) and the resistive load is added for the scope (Fig. 2) [5].

FIGURE 1. Wind turbine control system structure.

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FIGURE 2. Hardware in the loop wind turbine emulator configuration.

The wind turbine output torque Twt and power Pwt varies with the wind speed:

ARvCT Twt2)(

2

1 (1)

where the tip-speed ratio is defined as:

v

R (2)

and A: blade swept area [m2]; : specific density of air [kg/m3]; v: wind speed [m/s]; R: radius of the turbine blade[m]; : rotating speed [rad/s]; CT: wind turbine torque coefficient; expression (3) was obtained from the wind

turbine test.

5.2

0 baCC TT (3)

where a, b, CT0 are the constants for the nominal tip-speed ratio 0.The dynamic equation of motion is:

dt

dJTT gwt

(4)

where Twt: wind turbine torque [Nm]; Tg: PMSG torque [ Nm]; J: inertia of the wind turbine system (which is equal

with the wind turbine inertia -Jwt, plus the PMSG inertia -Jg).

The PMSG model includes also the rectifier model:

0)]2([)(22

dondcvfpfpsPMp VVkRIILp (5)

where pp: pole pairs; PM: PM flux [Wb]; Rs: stator resistance []; Ls: stator inductance [H];Vdon: diode voltage drop

[V]; Cf: filter capacitance [F]; kv=3/.

A hybrid DC-DC converter is used to control the power delivered to the load [6]. The HDC input-to-output

voltage ratio is:

rectout VD

DV

2(6)

whereVout: output voltage [V]; Vrect: input (rectifiedPMSG) voltage [V];D: duty cycle.To extract the maximum available power from the wind it must be obtained the optimum rotating speed of the

wind turbine and the generator torque must be changed. HDC works as a current controller, i.e. the converter

controls the PMSGoutput current through the DB, in order to change the PMSG torque Tg.In the steady state, if the operating point is on the left side of the maximum power point on the power versus

rotating speed curve, to attain the optimum power operating point, the MPPT FLC has to decrease the reference

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current and, as a result, the rotating speed increases. In this way the operating point will move to the right to a higher

power point. In the other case, when the operating point is on the right side of the maximum power point, thereference current needs to be increased. In this way the speed will decrease and the operating point will move to the

left, to a higher power point.

For low power VSWT, working almost continuously in transient regimes, the energy stored by the rotor inertia is

considerable and the controller must be able to account for it

Theinput variables of the proposed MPPT FLC are: change in mechanical power (Pm), change in rotating speed() and the sign of Pm/. The output variable is the change in HDC reference current (I*). The considered

mechanical power (Pm) it is composed by:

dt

dJPP gm

(7)

where Pg: PMSG mechanical (input) power [W].These input and output variables are normalized in the range of [-1 1], according to the system behavior in order

that the FLC block to be universal for other wind turbine systems. The FLC algorithm is characterized by if then

rules. The fuzzy basic rules, which associates the fuzzy output to the fuzzy input, is derived from the desired system

behavior and the designed control strategy. The rules are designed so that the controller always seeks a maximumpower point, without stopping. More details regarding the controller parameters setting were presented in [4].

SIMULATION AND EXPERIMETAL RESULTS

A digital simulation of the wind turbine system, including the wind turbine mathematical model and electrical

generator mathematical model, was implemented in Matlab/Simulink. The HDC was implemented as an ideal, fast

current source (the measured current will always be equal with the reference current).

Figure 3 shows the step response of the MPPT FLC for a wind speed step variation from 7 to 5 [m/s]. Figure 4shows the power versus rotating speed characteristic for a wind speed step of 7-5-7 [m/s]. This figure also illustrates

the proposed algorithm and that the maximum power point (MPP) is reached for every wind speed. Good

similarities can be observed between simulation and experimental results, which validates the designed MPPT FLC.

0 100 200 300 400 500 6000

5

10

t [s]a.

v[m/s]

0 100 200 300 400 500 6000

5

10

t [s]b.

I*[A]

0 100 200 300 400 500 6000

5

10

t [s]

c.

w[rad/s]

0 100 200 300 400 500 6000

1000

2000

t [s]d.

Pg[W]

Experimental re sults

Simulation results

FIGURE 3. Simulation results compared with experimental results for a wind speed step between 7-5 [m/s]: a) Wind speed; b)Reference current; c) Rotating speed; d) PMSG mechanical power.

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0 1 2 3 4 5 6 7 8 9 100

200

400

600

800

1000

1200

1400

1600

1800

2000

w [rad/s]

P[W]

Pgexperiment

Pgsimulation

Pm

v= 5 [m/s]

(1)

(4)

(5)

(4)

(1)

(2)

(2)

(3)

(2)

(3)

(1)

(3)

MPP

MPP

v= 7 [m/s]

FIGURE 4. Mechanical power (Pm), simulation and experimental PMSG mechanical power versus rotating speed obtained for a

wind speed step of 7-5-7 [m/s].

CONCLUSION

The paper presents a fuzzy logic MPPT control strategy implemented in a small-scale variable speed wind

turbine system. The proposed strategy is validated by simulation and experimental results on real time hardware in

the loop wind turbine emulator.

ACKNOWLEDGMENTS

This work was supported by the strategic grant POSDRU/88/1.5/S/50783 (2009) of the Ministry of Labor,Family and Social Protection, Romania co-financed by the European Social Fund - Investing in people.

REFERENCES

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th

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