International Journal of Mechatronics, Electrical and Computer Technology
Vol. 4( 12) , J ul, 2014 , pp. 1095-1107 , ISSN: 2 305-0543
Available online at: http://www.aeuso.org
© A ustrian E-Journals of Universal Scientif ic Organization
--------------------------------------------------Application and Comparison of Two Intelligent Control Algorithms on
Grid-connected Wind Turbine for Maximum Power Point Tracking
R. Babajanipoor and S. Asghar Gholamian
Babol Noshirvani University of Technology
*Corresponding Author's E-mail: gholamian@nit.ac.ir
Abstract
In this paper, two algorithms Fuzzy control and Perturbation and observation (p &O) for
maximum power tracking has been used on wind turbine with permanent magnet
synchronous generator (PMSG). PMSG is connected to the grid by a voltage source inverter
system. Permanent magnet synchronous generator wind turbine system can compensate the
reactive power and inject the maximum active power of wind turbine into the grid. The
control algorithm is based on the theory of instantaneous reactive power and switching
inverter is based on adaptive hysteresis cycle until Variable switching frequency problem of
fixed-band hysteresis cycle has been resolved and has the ability to produce a constant
switching frequency. Transient and steady state response of the system under different wind
speeds have been studied and the simulation results on MATLAB software is discussed in the
article.
Keywords: Wind turbine, PMSG, Fuzzy control, Perturbation
1. Introduction
Nowadays the use of wind turbines has been widely in feed of loads connected grid and
loads apart of grid. Although the cost of installing wind turbine system is less than solar
systems, however using the appropriate power converter more reduced system cost so that
with wind speed changes the power achieved is maximum. Variable speed system delivers 20
to 30 percent more energy than fixed-speed system grid and reduces vibration and improves
reactive power. In the past years due to the advantages of permanent magnet generators
1095
International Journal of Mechatronics, Electrical and Computer Technology
Vol. 4( 12) , J ul, 2014 , pp. 1095-1107 , ISSN: 2 305-0543
Available online at: http://www.aeuso.org
© A ustrian E-Journals of Universal Scientif ic Organization
--------------------------------------------------including size and low weight, high efficiency and gearbox removal using this type of wind
turbine generators developed [1]. Extract the maximum active power from the wind turbine
and deliver Proper energy to the grid are two very important in wind turbine systems. Given
these objectives the best structure for power conversion in wind turbine is AC-DC-AC.
Different methods have been presented for maximum power control that almost all efficient
methods use rotor speed feedback. This article compares the intelligent algorithms
“observation and perturbation, fuzzy control” in order to track the maximum power point and
injected power control into grid has been studied and at the end simulation results are given
[2]. General schematic of Wind turbine with permanent magnet synchronous generator
system is shown in fig1. This structure contains a diode full-wave rectifier, dc-dc boost
converter and three phase inverter. With inverter appropriate keying system can compensate
the reactive power and inject the active power to grid [3].
Figure1: overview of wind turbine system connected to grid
Wind turbine output power can be expressed as follows:
1096
International Journal of Mechatronics, Electrical and Computer Technology
Vol. 4( 12) , Jul, 2014 , pp. 1095-1107 , ISSN: 2 305-0543
Available online at: http://www.aeuso.org
© A ustrian E-Journals of Universal Scientif ic Organization
--------------------------------------------------(1)
is the mechanical power generated by the turbine rotor to primary power of wind that called
power coefficient and is a nonlinear function of
and
[4].
Similarly,
ρ (Kg / m ^ 3) = air density
R (m) = radius of the wind turbine blade
V (m / s) = wind speed
= Blade pitch angle
= the tip speed ratio
(2)
[
In the above equation
that maximizes
(radian / second) is the angular velocity of wind turbine. There is an optimal
and P [5].
2. Fuzzy Control Method
In this method the controller measures output current and output voltage of dc-dc converter and send
to fuzzy controller. Fuzzy systems by analyzing input signal and comparing the with a duty cycle (D)
send switching command .Controllers with voltage changes
(voltage after rectifier) control the turbine
rotor speed and tracks maximum power point . Figure 2 shows the block diagram of this controller. [6-7]
Figure 2: Block diagram of the fuzzy controller
1097
International Journal of Mechatronics, Electrical and Computer Technology
Vol. 4( 12) , Jul, 2014 , pp. 1095-1107 , ISSN: 2 305-0543
Available online at: http://www.aeuso.org
© A ustrian E-Journals of Universal Scientif ic Organization
--------------------------------------------------3. Observation and perturbation method
According to the algorithm P&O if the power increased by increasing voltage the search continues in the
same direction otherwise search direction is reversed. To obtain maximum power from wind systems the
following relationship must be established.
(3)
First select the desired value for the reference voltage to start the search process. Then the controller
measure valuevoltage and current of rectifier and calculate the power. Then reference voltage rises
value so that
(4)
(5)
If, the system has not reached to maximum power point and voltage reference should continue to rise as
and this power value compared with the previous power.
If P k < P k-1 , reference voltage must be reduced as much as
flowchart in Figure 3 is shown. [7-9]
1098
. Maximum power point tracking
International Journal of Mechatronics, Electrical and Computer Technology
Vol. 4( 12) , J ul, 2014 , pp. 1095-1107 , ISSN: 2 305-0543
Available online at: http://www.aeuso.org
© A ustrian E-Journals of Universal Scientif ic Organization
---------------------------------------------------
Figure 3: observations and perturbation Flowchart of the maximum power point tracking
4. Inverter control scheme
The control scheme proposed in this paper based on the instantaneous power theory to
produce suitable reference current. In first load current and voltage in common connection
point grid with load measured and then transferred to reference frame d-q. Reference values
of load current and voltage obtained from the following relationships. [10-11]
(10)
1099
International Journal of Mechatronics, Electrical and Computer Technology
Vol. 4( 12) , J ul, 2014 , pp. 1095-1107 , ISSN: 2 305-0543
Available online at: http://www.aeuso.org
© A ustrian E-Journals of Universal Scientif ic Organization
--------------------------------------------------√
√
(11)
(12)
√
√
(13)
Similarly, the active power and Instantaneous reactive power in α-
coordinates through
the following equations are obtained:
[ ]
[
̅
̃
(14)
̅
̃
(15)
] .[
]
(16)
The reference current in a-b-c coordinates can be written as follows:
√
[
.[ ]
]= √
[
√
(17)
]
Since DC voltage supply of inverter may vary so with increasing voltage and Fixed-band
hysteresis cycle increase frequency switching. To solve this problem adaptive hysteresis
band method is used. In this method, adaptive hysteresis band is modulated as a function of
system parameters. As a result, the switching frequency is kept in constant amount [12].
HB =
[
]
(18)
5. Simulation
To evaluate the performance of the proposed strategy, a three-phase three-wire network
selected to simulate. A three-phase voltage source with a frequency of 60 Hz feed a threephase inductance resistance load.
System parameters are given in table1.
1100
International Journal of Mechatronics, Electrical and Computer Technology
Vol. 4( 12) , J ul, 2014 , pp. 1095-1107 , ISSN: 2 305-0543
Available online at: http://www.aeuso.org
© A ustrian E-Journals of Universal Scientif ic Organization
--------------------------------------------------Table1: Proposed system Specifications
Switching frequency
12 kHz
resistance Connected to the load
1 Ohm
inductance Connected to the load
2 mH
Resistance connected to the inverter
0.064 mOhm
Inductance connected to the inverter
2.08 mH
Base frequency
60 Hz
DC link capacitor
3 mF
Grid voltage
230 V
In this simulation wind speed in is considered in three steps. The wind speed at the moment
and
has changed (figure 4) and from 10(m/s) to 16(m/s) increased and
then reduced to 13(m/s).
Wind speed(m/s)
18
16
14
12
10
8
0
0.2
0.4
0.6
Time(s)
0.8
1
1.2
Figure 4: Wind speed profile
With wind speed changes control system perform switching operation so wind turbine
connected to grid extract maximum power. The main characteristic In order to determine
1101
International Journal of Mechatronics, Electrical and Computer Technology
Vol. 4( 12) , J ul, 2014 , pp. 1095-1107 , ISSN: 2 305-0543
Available online at: http://www.aeuso.org
© A ustrian E-Journals of Universal Scientif ic Organization
--------------------------------------------------the optimum system performance in optimal state and extract maximum power is power
coefficient (
) in at different moments of the system. This characteristic for the three
algorithms used is shown in figure (5).
(a)
(b)
Figure 5: (a) Power coefficient for Fuzzy control, (b) Observation and perturbation
In Figure (5) observed that in different wind speed for fuzzy control power coefficient has
less fluctuation and more accuracy. In fuzzy control with a step change in wind speed
power coefficient vary rapidly and reach to maximum value but this variation in
1102
International Journal of Mechatronics, Electrical and Computer Technology
Vol. 4( 12) , J ul, 2014 , pp. 1095-1107 , ISSN: 2 305-0543
Available online at: http://www.aeuso.org
© A ustrian E-Journals of Universal Scientif ic Organization
--------------------------------------------------Incremental conducting method and observation and perturbation method is not fund. As is
clear in steady state with fuzzy control system has very good performance and the
percentage of error is very small. But this error for IC and P&O algorithm is more in steady
state. Also fuzzy control and P &o algorithm reach to steady state sooner than IC algorithm.
Grid current
200
100
0
-100
-200
0.6
0.7
0.8
0.9
Time(s)
1
1.1
1.2
(a)
Grid current
200
100
0
-100
-200
0.6
0.7
0.8
0.9
Time(s)
1
1.1
1.2
(b)
Figure 6: (a) current injection to grid for Fuzzy control, (b) Observation and perturbation
1103
International Journal of Mechatronics, Electrical and Computer Technology
Vol. 4( 12) , J ul, 2014 , pp. 1095-1107 , ISSN: 2 305-0543
Available online at: http://www.aeuso.org
© A ustrian E-Journals of Universal Scientif ic Organization
---------------------------------------------------
Load current
200
100
0
-100
-200
0.6
0.65
0.7
0.75
0.8
0.85
Time(s)
0.9
0.95
1
0.9
0.95
1
(a)
Load current
200
100
0
-100
-200
0.6
0.65
0.7
0.75
0.8 0.85
Time(s)
(b)
Figure7: (a) current injection to load for Fuzzy control, (b) Observation and
perturbation
Load current and grid current in figure 6 and 7 are shown. Since the phase of load current is
equal to voltage phase so the reactive power injection to grid is zero and just active power
inject to grid. Characteristic of injection current to load using three control method is quite
similar and have THD=0.01%. But grid current using fuzzy control has THD=2.4% and for
IC algorithm has THD=2.47% and for P &O has THD=2.59%. Since this difference is very
small can be said system performance in inject current to grid is suitable for three method.
1104
International Journal of Mechatronics, Electrical and Computer Technology
Vol. 4( 12) , J ul, 2014 , pp. 1095-1107 , ISSN: 2 305-0543
Available online at: http://www.aeuso.org
© A ustrian E-Journals of Universal Scientif ic Organization
---------------------------------------------------
PQ(Grid)
3
x 10
4
2
1
0
0
0.2
0.4
0.6
Time(s)
0.8
1
1.2
(a)
PQ(Grid)
3
x 10
4
2
1
0
0
0.2
0.4
0.6
Time(s)
0.8
1
1.2
(b)
Figure 8: (a) active and reactive injection to grid for Fuzzy control, (b) Observation and
perturbation
Figure8 show the active and reactive power injected to grid with using suitable reference
current. In every three method the reactive power injected to grid is zero but in fuzzy
control the active power ripple has less than two other.
1105
International Journal of Mechatronics, Electrical and Computer Technology
Vol. 4( 12) , J ul, 2014 , pp. 1095-1107 , ISSN: 2 305-0543
Available online at: http://www.aeuso.org
© A ustrian E-Journals of Universal Scientif ic Organization
--------------------------------------------------Conclusion
In this paper presented a wind turbine system -connected grid not only able to inject
active power to the grid, but also compensate the reactive power of load. This process is
done with generating suitable reference current by instantaneous power theory. This paper
shows adaptive hysteresis band control is suitable for control the inverter connected to the
grid. In addition system control with fuzzy controller has appropriate respond compare to
other method. The results show IC algorithm is suitable for wind turbine in low wind speed.
Simulation results show that this system can deliver the generated maximum power by
wind turbine and compensate the reactive power of load. This system delivering maximum
power and filtering function simultaneously .Therefore, it is economically advantageous.
References
[1]. A. M eharrar; M . Tioursi, M . Hatti, A. Boudghène Stambouli." A variable speed wind generator maximum
power tracking based on adaptative neuro-fuzzy inference system". Expert Systems with Applications 38 (2011)
7659–7664.
[2]. M . Arifujjaman, M . Iqbal and J.E. Quaicoe, “M aximum power extraction from a small wind turbine
emulator using a dc-dc converter controlled by a microcontroller.” International Conference on Electrical and
Computer Engineering, pp. 213-216, 2006
[3]. B.K. Bose, “An adaptive hysteresis band current control technique of a voltage feed PWM inverter for
machine drive system”, IEEE Trans.Ind Ind. Electron. 37 (5) (1990) 402–406.
[4]. Aryuanto Soetedjo, Abraham Lomi, Widodo Puji M ulayanto,” M odeling of Wind Energy System with
M PPT Control” International Conference on Electrical Engineering and Informatics17-19 July 2011, Bandung,
Indonesia.
[5]. I.Syed M eer Kulam Ali P.Aravindan Dr.M .Y.Sanavullah,” M PPT BASED PERM ANENT M AGNET
SYNCHRONOUS GENERATOR FOR WIND ENERGY CONVERSION SYSTEM ”, International Journal of
Communications and Engineering Volume 04– No.4, Issue: 02 M arch2012.
[6]. N. Yamamura, M . Ishida, and T. Hori, “A simple wind power generating system with permanent magnet
type synchronous generator”, IEEE International Conf. on Power Electronics and Drive Systems, PEDS ‟ 99,
Hong Kong , July 1999.
1106
International Journal of Mechatronics, Electrical and Computer Technology
Vol. 4( 12) , J ul, 2014 , pp. 1095-1107 , ISSN: 2 305-0543
Available online at: http://www.aeuso.org
© A ustrian E-Journals of Universal Scientif ic Organization
--------------------------------------------------[7]. E. Koutroulis, and K. Kalaitzakis, “Design of a maximum power tracking system for Wind-EnergyConversion applications”, IEEE Trans.on Industrial Electronics, Vol. 53, no. 2, pp. 486-494, April 2006.
[8]. S.M orimoto, H. Nakayama, M . Sanada, andY. Takeda, “Sensorless output maximization control for
variablespeed wind generation system using IPM SG,” IEEE Trans. Ind. Appl., vol. 41, no. 1, pp. 60–67,
Jan./Feb. 2005.
[9]. M . Kesraoui , N. Korichi , A. Belkadi ,” M aximum power point tracker of wind energy conversion system,”
Renewable Energy 36 (2011) 2655e2662,ELSEVIER
[10]. J. Afonso, . Couto and J. M artins , “Active Filters with Control Based on the p -q Theory,” IEEE Industrial
Electronics Society Newsletter,pp. 5-10, Sept. 2000.
[11]. Georgios Tsengenes, Thomas Nathenas , Georgios Adamidis,” A three-level space vector modulated grid
connected inverter with control scheme based on instantaneous power theory,” Simulation M odelling Practice
and Theory 25 (2012) 134–147,ELSEVIER.
[12]. Satyaranjan Jena, B.Chitti Babu, S.R.Samantaray and M ohamayee M ohapatra, “Comparative Study
Between Adaptive Hysteresis and SVPWM Current Control for Grid-connected Inverter System” , 2011 IEEE.
1107