2011 IEEE First Confcrencc on Clean Energy and Technology CET
A Study of Maximum Power Point Tracking Algorithms for Wind Energy System Majid A. Abdullah, A.H.M. Yatim, Chee Wei, Tan Department of Energy Conversion Universiti Teknologi Malaysia Johor 8ahru, Malaysia aaamaj
[email protected] configurations of power electronic converters and electrical generators for variable speed wind turbine systems.
Abstract- This paper reviews and studies the state-of the-art of available maximum power point tracking (MPPT) algorithms.
Due to the nature of the wind that is instantaneously changing,
Among the electric generators, permanent magnet synchronous generator (PMSG) is preferred due to its high efficiency, reliability, power density; gearless construction, light weight, and self-excitation features [3-6]. Controlling the PMSG to achieve the maximum power point (MPP) can be done by varying its load. In this regard, a boost converter is one of the possible solutions, where, by controlling the duty cycle of the converter the apparent load seen by the generator will be adjusted and thus, its output voltage and shaft speed. In addition to that, operating the boost converter in discontinuous conduction mode (OCM) and applying a power factor correction (PFC) technique contributes in total harmonic distortion (THD) reduction and increases the power factor (PF) of the wind power generator [7-8].
hence, there is only one optimal generator speed is desirable at one time that ensures the maximum energy is harvested from the available wind. Therefore, it is essential to include a controller that is able to track the maximum peak regardless of any wind speed. The available maximum power point tracking (MPPT) algorithms can be classified according to the control variable, namely with and without sensor, and also the technique used to locate the maximum peak. A comparison has been made on the performance of the selected MPPT algorithms on the basis of various speed responses and the ability to achieve the maximum energy
yield.
simulating
The
wind
tracking
energy
performance
system
using
is
performed
by
MATLAB/Simulink
simulation package. Besides that, a brief and critical discussion is made on the differences of available MPPT algorithms for wind energy system. Finally, a conclusion is drawn.
In order to determine the optimal operating point of the wind turbine, a maximum power point tracking (MPPT) algorithm is essential to be included in the system. Several MPPT algorithms have been proposed in the literature. Reference [9] has reviewed and criticized many published MPPT algorithms and concluded that the two methods described in [10] and [11] are the best solution due to their adaptive tracking and self tuning capability. References [1214] have compared some of the available MPPT for PMSG based wind energy conversion system. This paper reviews the fundamentals of the available MPPT algorithms for wind energy system. In addition, a comparison of simulation results is made on the three selected MPPT techniques. Finally, a critical discussion is made and a conclusion is drawn.
Keywords- MPPT; Wind energy system; PMSG; Boost converter
I.
INTRODUCTION
Wind energy system has gained vast populations in the past decade as one of the renewable energy sources due to the possibility of depletion of conventional energy sources and its high cost as well as its negative effects on the environment. wind energy is preferred because it is clean, pollution-free, exhaustible and secure. Therefore, a wind energy generation system could be one of the significant candidates as an alternative energy source for the future. The amount of mechanical energy that can be extracted from the wind is not solely depending on the wind speed, but also governed by the ratio of the rotational speed to wind speed. There is a specific optimal ratio for each wind turbine,
II.
which is called the optimal tip speed ratio (TSR) or -top!' at
which the extracted power is maximum. As the wind speed is instantaneously varying, it is essential for the rotational speed to be variable to maintain the equality of the TSR to the optimal one at all times. In the operation of variable speed condition a power electronic converter is essential to convert the variable-voltage-variable-frequency of the generator into a fixed-voltage-fixed-frequency that is suitable for the grid. References [1-2] have discussed the different possible
Uncontrolled
DC Boost
Figure I. A brief block diagram of the proposed PMSG wind energy system
The authors would like to thank the Ministry of Higher Education, MOHE Malaysia for the financial support and Universiti Teknologi Malaysia, UTM Skudai for providing the facilities to conduct this research.
978-1-4577-13 54-5/11/$26.002011 © IEEE
S YSTEM OVERVIEW
Fig. I illustrates the schematic diagram of the proposed wind turbine system. The system supplies a resistive load and consists of wind turbine rotor, PMSG, rectifier and a boost converter.
321
2011 IEEE First Conference on Clean Energy and Technology CET
Wind turbine converts the wind energy at its input to a mechanical energy at the output, which in tum, runs a generator to generate electrical energy. The mechanical power generated by wind turbine can be expressed as [15]:
Pm
=
1
-
2
2 3 pnR V C /A,P)
maximum point,
2000 �
V;v is the wind speed (m/ S ), and C p is the coefficient
-
�
"
of performance.
..
_____
0
15 0
w
I-
extraction efficiency of the wind turbine [16). It is a nonlinear function of both tip speed ratio, A and the blade pitch angle, f3. While its maximum theoretical value is approximately 0.59, it is practically between 0.4 and 0.45 [2]. The tip speed ratio is a variable expressing the ratio of the linear speed of the tip of blades to the rotational speed of wind turbine [15).
OJ",R V",
Generator Speed (rad/sec)
III.
(2)
A.
C p made in the previous studies. This paper defines C p as [5]:
1
0.035 3 1 + ,8
A + 0.08,8
MPPT TECHNIQUES
Tip Speed Ratio Control
The optimal TSR for a given wind turbine is constant regardless of the wind speed. If the TSR is maintained constantly at its optimal value, this ensures that the energy extracted is in its maximum operating point too. Therefore, this method seeks to force the energy conversion system to work at this point continuously by comparing it with the actual value and feeding this difference to the controller. That, in tum, changes the speed of the generator to reduce this error. The optimal point of the TSR can be determined experimentally or theoretically and stored as a reference. This method is simple, however, it requires the measurement of wind speed consistently and accurately which complicates its use in the reality, as well as increases the system cost [17-19). The block diagram of the tip speed ratio control method is shown in Fig. 4.
There are many different versions of fitted equations for
----- ----
500
Figure 3. Characteristics of turbine power as a function of the rotor speed for a series of wind speeds.
where OJm is the mechanical angular velocity of the rotor measured in rad/s.
Ai
· . · . _ _ _ _ _ _ _ _ _ _ _ L _ _ _ _ _ ______ ___ · . · . · .
� 1000
The turbine power coefficient, C p' describes the power
=
the C p is
2500 .---�---�--����
(1 )
where p is the air density (kg /m ), R is the turbine rotor
A
where
maximum. Continuous operation of wind turbine at this point guarantees the maximum available power can be harvested from the available wind at any speed, as shown in Fig. 3.
3
(m),
the Aopl'
denoted by
(4)
O , 5 r-----�--�-�----_, a.
U
Q; � 0
a.
'0
�
'--___ s_ lo ...;.p_ e_--'
Universal Bridge speed Lradfs]
Figure 9. The simulated system diagram.
Figure 8. Wind turbine output power and torque characteristics with MPP tracking process [30].
E.
The obtained performance with the different methods is shown in Fig. 10 and the results are also summarized in Table I. According to the plot and results analysis, the OTC controller is the fastest in achieving the steady-state and also in the recovery time upon wind speed change. In addition, the OTC
Other methods
Many of the problems associated with the aforementioned methods have been solved by means of artificial intelligence control and hybrid methods. According to [34], fuzzy logic control methods have the advantages of fast convergence, parameter insensitivity, and accepting noisy and inaccurate signa\. They can also be used to obtain an optimal step size for conventional HCS method, as in [35]. Wind speed measurement and its associated drawbacks have been solved by using neural network technique to estimate the wind speed depending on actual machine torque and speed [22, 36].The proposed control structure, Wilcoxon radial basis function network (WRBFN)-based with HCS MPPT strategy and modified particle swarm optimization (MPSO) algorithm, in [37] diminish the effect of the wind turbine inertia on HCS method performance.
method is able to reach the highest value of Cp and maintained
the same value after the wind speed change. It is followed by the P&O in input voltage method which took approximately double the time to reach the steady-state, with Cp average of
0.4607. The slowest and less efficient one is the P&O in duty cycle method, where the response time is eight times the first method, 0.02142. After being 0.46 before the wind speed step change, Cpmax decreased to 0.42 when the step change
occurred. Since the used perturbation and observation methods are the conventional ones, with fixed step-size, the ripples of
Cp changed under wind speed variations.
Hybrid method is the combination of two methods from the aforementioned ones; to exploit the advantages of one technique to overcome the disadvantage of the other. An example of this methods is that in [11] where OTC method is merged with HCS to solve the two problems associated with the conventional HCS, the speed-efficiency trade-off and the wrong directionality under rapid wind change. Another example is combining PSF control and HCS in [26] to develop a sensorless and flexible method which is also applicable for all wind turbine levels. IV.
Fig. 11, the
TABLE l. SIMULATED RESULTS: POWER COEFFICIENT AVERAGE VALUES,RESPONSE TIMES,RECOVERY TIMES; ENERGY AND EFFECIENCY. Response
S IMULATlON RESULTS A ND D ISCUSSIONS
Melhod
The performance of three MPPT control methods has been simulated and compared using MATLAB/Simulink simulation package. The simulated system diagram is shown in Fig. 9. The studied MPPT methods are: OTC, P&O of the duty cycle of the boost converter, and P&O of the input voltage of the boost converter. All the simulations were carried out with system parameters as [5]. The load resistance, R is 20 n for all simulations. The step-sizes in P&O of the duty cycle and the
324
Median
time
Recovery time
(.....)
(sec.)
Energy
(W)
Efficiency
("/0)
(relierence)
0.48
--
--
784.5
--
OTC
0.4789
0.02488
0.0006
665.9
90.66
P&O or input voltage
0.4607
0.053
0.0014
645.9
87.94
P&O orduly-cycle
0.3956
0.2142
0.022
597.4
81.33
Max. theoretical value
input voltage were fixed at 0.5 x 1 0-3 and 0.001, respectively.
978-1-4577-13 54-5/11/$26.002011 © IEEE
In
generator's output power for each method is depicted. While the generator's output power for the first two methods stabilized at the same time, 0.025 sec., it needed 0.175 sec more time for the third one. Taking the maximum mechanical input energy of the generator as a reference and measuring the electrical energy output of the generator under the selected methods, the efficiencies can be calculated, as listed in Table I.
2011 IEEE First Conference on Clean Energy and Technology CET
average value of Cp and held it at its maximum even with
6_5 r--,---,-----,
-"J "
i
il ""'"
wind speed change_ Nevertheless, its dependency on the wind turbine characteristics makes it inflexible_ On the other hand, P&O method is flexible and simple in implementation, but it is less efficient and has a difficulty in determining the optimum step-size_ Comparing the perturbation in duty cycle, perturbation of the input voltage to get a reference voltage is better, as there is a controller to force the input voltage to track the reference_ Finding out an adaptive step-size algorithms and combining two or more of the available methods will improve the performance and overcome some of the obstacles of the current methods_
------- ------- ------- ------- --------t---;--....,...-�--�____i 5_5
-0
---_._. -------
. _ . _---
------- -------
-------
r--_:_-�-__::_-_:_-� .-----.
�
, , , , , . _-----------,-------- ------- _ ...
.
;
:
�
. -------- ------. - ---- . - . -----, , , , , ,
4 _ 5 L-----,---L-------:--'-----..L._-----: _-,-L_-,---L_--,---L -'-:-,-----,---l:-:----,L---:-' -0_55 0.48 0.49 0_5 0_51 0_ 52 0_53 0_ 54 0.45 0.46 0.47
Time (Sec.)
Coefficient of Power (Cp) 05 r-,---,---,
REFERENCES
I, ,I 't I' I' I, (I "It I, It I ' I ,I , I' 'I I ' , I I, I ' I I, I I 'I ' I / I I II , I I I, I I, I I " I, ,I ' I I, , I, I I I, II " I,I 'I ,I ' II I' II 'J " ,I 'J
I
I
I
' / I,
'I I, 'I I,
0.32
I I
�I
I' ,I I' ,I I'
I
I
I t, '/ I, 'I I, •
'
(
I
.1 I' ,I I'
I!
t I
I I ' I I, 'I I.
"
� ; �I !; I,;
J,
"
[1) J_ A Baroudi,V_ Dinavahi,and A M_ Knight, "A review of power converter topologies for wind generators," Renewable Energy, vol. 32, pp_ 2369-2385,2007_
,
[2) C. Zhe, J M_ Guerrero, and F. Blaabjerg, "A Review of the State of the Art of Power Electronics for Wind Turbines," Power Electronics, IEEE Transactions on, vol. 24,pp_ 1859-1875,2009_
:� I; II ;1, I� , ;� , I' i! il
- - - - P&O
[3) M_ G_ Molina, E C. dos Santos, and M_ Pacas, "Advanced power conditioning system for grid integration of direct-driven PMSG wind turbines," in Energy Conversion Congress and Exposition (ECCE), 2010 IEEE, 2010,pp_ 3366-3373_
Duty Cytle Control
[4) S_ Li, T. A Haskew, and L. Xu, "Conventional and novel control designs for direct driven PMSG wind turbines," Electric Power Systems Research,vol. 80,pp_ 328-338,2010_
- - P&O Input Voltage Control
-- OTC Control
[5) H_ E_ Mena Lopez, "Maximum power tracking control scheme for wind generator systems," Master Thesis,Texas A&M University,Dec 2007
Tim'lsec)
[6) S_ M_ Muyeen, R Takahashi, T. Murata, and J Tamura, "A Variable Speed Wind Turbine Control Strategy to Meet Wind Farm Grid Code Requirements," Power Systems, IEEE Transactions on, vol. 25, pp_ 331340,2010_
Figure 10_ Simulation results for a step change in wind speed (a) Wind speed (b) Power Coefficient, Cp _
1000
------- P&O Duty Cycle Control
- - P&O Input Voltage Control
900
-- OTC Control -- Theoritical maximum
800
�
700
� "-
600
i
[7) 0_ Carranza, G_ Garcen'!, E_ Figueres, and L_ G_ Gonzalez, " Peak current mode control of three-phase boost rectifiers in discontinuous conduction mode for small wind power generators," Elsevier, Applied Energy, vol. 87,pp_ 2728-2736, August 2010_
Electrical Power
r;=�===::'::::==�==�:::;-lI1l\f"-r-TTTIl
[8) Y_ M_ Kawale and S_ Dutt, "Comparative Study of Converter Topologies Used for PMSG Based Wind Power Generation," in Computer and Electrical Engineering, 2009_ ICCEE '09_ Second International Conference on, 2009,pp_ 367-371.
power
"
[9) S_ M_ Raza Kazmi, H. Goto, G_ Hai-Jiao, and 0_ Ichinokura, "Review and critical analysis of the research papers published till date on maximum power point tracking in wind energy conversion system," in Energy Conversion Congress and Exposition (ECCE), 2010 IEEE, 2010, pp_ 40754082_
"
0; w 400 300
[10) J_ Hui and A Bakhshai, "A new adaptive control algorithm for maximum power point tracking for wind energy conversion systems," in Power Electronics Specialists Conference, 2008_ PESC 2008_ IEEE, 2008,pp_ 4003-4007_
"" "
1
[11) S_ M_ R Kazmi, H_ Goto, G_ Hai-Jiao, and 0_ Ichinokura, "A Novel Algorithm for Fast and Efficient Speed-Sensorless Maximum Power Point Tracking in Wind Energy Conversion Systems," Industrial Electronics, IEEE Transactions on, vol. 58,pp_ 29-36,201 L
200 L---�--�---L----L---�--� a 4S 046
Figure 11_ The output power response produced by the PMSG generator.
Y_
[12) J_ Brahmi, L_ Krichen, and A Ouali, "A comparative study between three sensorless control strategies for PMSG in wind energy conversion system," Applied Energy, vol. 86,pp_ 1565-1573,2009_
C ONCLUSION
[13) AJ Mahdi, WH Tang, Jiang L ,and W_ QH, "A Comparative study on variable-speed operations of a wind generation system using vector control," in International Conference On Renewable Energies And Power Quality, The 10th International Conference On Renewable Energies And Power Quality,University of Granada_Granada,Spain,2010,pp_ 1-6_
This paper discusses and reviews the available MPPT algorithms_ In addition, simulation and comparison of selected three control methods in terms of the efficiency and speed of response were made_ Simulation results demonstrate superiority of OTC method; where it obtained the maximum
978-1-4577-13 54-5/11/$26,002011 © IEEE
325
2011 IEEE First Conference on Clean Energy and Technology CET
[34] M. G. Simoes, B. K. Bose, and R. J Spiegel, "Design and performance evaluation of a fuzzy-logic-based variable-speed wind generation system," Industry Applications, IEEE Transactions on, vol. 33, pp. 956-965, 1997.
[14] A. Mirecki, X. Roboam, and F. Richardeau, "Comparative study of maximum power strategy in wind turbines," in Industrial Electronics, 2004 IEEE International Symposium on, 2004,pp. 993-998 vol. 2. [15] L. L. Freris, Wind Energy Conversion System. London, u.K.: Prentice Hall,1990.
[35] Q.-N. Trinh and H-H Lee, "Fuzzy Logic Controller for Maximum Power Tracking in PMSG-Based Wind Power Systems," in Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. vol. 6216, D.-S. Huang, X. Zhang, C. Reyes Garcia, and L. Zhang,Eds.,ed: Springer Berlin / Heidelberg,2010,pp. 543-553.
[16] M. J Grimble and M. A. Johnson, Optimal Control of Wind Energy Systems, 2008. [17]
M. R. Patel,Wind and Solar Power Systems: CRC Press, 1999.
[18] Q. Wang, "Maximum wind energy extraction strategies using power electronic converters," PhD. dissertation, University of New Brunswick, Canada,June 2003.
[36] C.- Y Lee, Y-x. Shen, J-c. Cheng, Y-Y Li, and C.-W. Chang, "Neural Networks and Particle Swarm Optimization Based MPPT for Small Wind Power Generator," presented at the World Academy of Science, Engineering and Technology 60 2009,2009.
[19] S. M. Barakati, "Modeling and Controller Design of a Wind Energy Conversion System Including Matrix Converter," PhD. dissertation, Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, Canada,2008.
[37] W.-M. Lin and c.-M. Hong, "Intelligent approach to maximum power point tracking control strategy for variable-speed wind turbine generation system," Energy, vol. 35,pp. 2440-2447,2010.
[20] T. Nakamura, S. Morimoto, M. Sanada,and Y Takeda, "Optimum control of IPMSG for wind generation system," in Power Conversion Conference, 2002. PCC Osaka 2002. Proceedings of the,2002,pp. 1435-1440 vol.3. [21] S. Morimoto, H. Nakayama, M. Sanada, and Y Takeda, "Sensorless output maximization control for variable-speed wind generation system using IPMSG," Industry Applications, IEEE Transactions on, vol. 41, pp. 60-67,2005. [22] M. Pucci and M. Cirrincione, "Neural MPPT Control of Wind Generators With Induction Machines Without Speed Sensors," Industrial Electronics, IEEE Transactions on, vol. 58,pp. 37-47,2011. [23] M. Shirazi, A. H. Viki, and O. Babayi, "A comparative study of maximum power extraction strategies in PMSG wind turbine system," in Electrical Power & Energy Conference (EPEC),2009 IEEE,2009,pp. 1-6. [24] K. Tan and S. Islam, "Optimum control strategies in energy conversion of PMSG wind turbine system without mechanical sensors," Energy Conversion, IEEE Transactions on, vol. 19,pp. 392-399,2004. [25] S. M. Barakati, M. Kazerani, and J D. Aplevich, "Maximum Power Tracking Control for a Wind Turbine System Including a Matrix Converter," Energy Conversion, IEEE Transactions on, vol. 24, pp. 705-713, 2009. [26] W. Quincy and C. Liuchen, "An intelligent maximum power extraction algorithm for inverter-based variable speed wind turbine systems," Power Electronics, IEEE Transactions on, vol. 19,pp. 1242-1249,2004. [27] C. Patsios, A. Chaniotis, M. Rotas, and A. G. Kladas, "A comparison of maximum-power-point tracking control techniques for low power variable-speed wind generators," in Advanced Electromechanical Motion Systems & Electric Drives Joint Symposium, 2009. ELECTROMOTION 2009. 8th International Symposium on, 2009,pp. 1-6. [28] A. C. C. Hua and B. C. H. Cheng, "Design and implementation of power converters for wind energy conversion system," in Power Electronics Conference (IPEC),2010 International, 2010,pp. 323-328. [29] E. Koutroulis and K. Kalaitzakis, "Design of a maximum power tracking system for wind-energy-conversion applications," Industrial Electronics,IEEE Transactions on, vol. 53,pp. 486-494,2006. [30] B. Neammanee, S. Sirisumranukul, and S. Chatratana, "Control Performance Analysis of Feedforward and Maximum Peak Power Tracking for Small-and Medium-Sized Fixed Pitch Wind Turbines," in Control, Automation, Robotics and Vision, 2006. ICARCV '06. 9th International Conference on, 2006,pp. 1-7. [31] M. Kesraoui, N. Korichi, and A. Belkadi, "Maximum power point tracker of wind energy conversion system," Renewable Energy, vol. In Press, Corrected Proof. [32] P. Ching-Tsai and J Yu-Ling, "A Novel Sensorless MPPT Controller for a High-Efficiency Microscale Wind Power Generation System," Energy Conversion,IEEE Transactions on,vol. 25,pp. 207-216,2010. [33] M.-K. Hong and H.-H Lee, "Adaptive maximum power point tracking algorithm for variable speed wind power systems," presented at the Proceedings of the 2010 international conference on Life system modeling and and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part I, Wuxi, China, 2010.
978-1-4577-13 54-5/11/$26.002011 © IEEE
326
