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APSAEM12 Journal of the Japan Society of Applied Electromagnetics and Mechanics Vol.21, No.3 (2013)

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Improving Stability for Independent Power Control of Wind-Turbine Doubly Fed Induction Generator during Grid Unbalance With Pi-Fuzzy Controller

Truc Pham-Dinh *1 and Hai Nguyen-Thanh *2

This paper presents modified SFOC control of Doubly Fed Induction Generator (DFIG) wind turbine during grid unbalance for improved stability by using hybrid PI-Fuzzy controllers and eliminating negative sequence components. The system consists of a common induction generator with slip ring and power electronic converters at both stator and rotor sides. The modifications are applied to rotor side converter for active and reactive power controls of wind turbine. The turbine, generator and control units are also described. The investigation is based on MATLAB/SIMULINK. Simulation results show improved stability of active and reactive powers delivered by DFIG.

Keywords: DFIG; grid unbalance; PI-Fuzzy; wind turbine.(Received: 31 May 2012, Revised: 4 June 2013)

1. Introduction

Doubly fed induction generators have been the popular choice in wind power generation due to the low rating of power electronic circuit connected to the rotor side of the generator and the grid [1]. The active and reactive powers delivered by DFIG can be controlled independently by Stator Flux oriented Control which is designed for operation with balanced grid voltage [2]. However, most of the grids experience the problems of voltage unbalance, which raise the winding temperature and cause pulsation of torque and power [3]. This paper will investigate the stabilities of active and reactive powers during transient unbalance of grid voltage for traditional and modified stator flux oriented controls of DFIG. The modifications are hybrid PI-Fuzzy controller and Sequence Component controller. The grid unbal-ance is modelled with a reduction of 25 % of voltage in one phase. Wind speed is varied randomly during the process.

2. Mathematical Model of Wind Turbine

The model of wind turbine and its formula of shaft torque, turbine torque, power transferred to generator and related parameters are presented in this session. Fig.1 illustrates the mechanical system of wind turbine which is often used in large wind turbine systems.

Fig. 1. Mechanical model of wind turbine [9].

The power extracted from the wind is:

),(21 3 �� pwturb CAvP � (1)

Where:� = 31.22 (kg/m3)� air densityA=R2��(m2) the cross-sectional area through

which the wind passes.R(m): length of turbine’s blades.vw (m/s):the wind speed normal to the cross-

session area ACp (��: the aerodynamic efficiency which depends on the tip spe��to Betz’s efficiency, the maximum theoretical efficiency is 59.3% [10].

ieCi

p��

��

5.12

54.011622.0),(�

��

��

�� (2)

��the outer tip of the blade is moving divided by the wind speed

w

turb

vR�

� � (3)

_______________________Correspondence: Truc Pham-Dinh, Faculty of Electrical and

Electronic Engineering, Ho Chi Minh City University of Technology, 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnamemail: [email protected]

*1 Ho Chi Minh City University of Technology*2 Le Hong Phong High School, Ho Chi Minh City

Regular Paper

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日本 AEM 学会誌　Vol. 21, No.3 (2013)

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��turb (rad/s)�is the angular velocity of turbine. The turbine efficiency Cp is the function of tip-speed ratio ��

3. Control Methods and Modifications

Structure of control method for DFIG is shown in Fig. 2, converters on grid side and rotor side of DFIG are controlled by stator flux oriented control to achieve the independent control of active and reactive powers. Modification of the control system by using hybrid PI-Fuzzy controller has provided better performance of the generated powers [5]. However, this is only verified with balanced grid voltage. To improve stability of the powers, inclusion of sequence component controller with Notch filter has been suggested by [6] and pre-sented in Fig. 3 to eliminate negative sequence compo-nents.

An investigation on DFIG model and system behav-iour based on SFOC under unbalanced grid voltage conditions has been provided in [7]. As indicated in [8],in contrast to SFOC, stator voltage orientation (SVO) results in the system stability and damping being inde-pendent of the rotor current. Thus in this section a modified DFIG model based on SVO is presented.

Fig. 2. ��-connected DFIG-based wind generator [4].

Fig. 3. The proposed current control scheme for the RSC of a DFIG using PI+Fuzzy controller [6].

Fig. 4 shows the spatial relationships between the �� s reference �� r refer-��r, and the dq+ and dq� ��s��s, respectively. As shown, the d+

-axis of the dq+

reference frame is fixed to the positive sequence stator voltage V+

sd+. According to Fig. 4, the transformations ��s��r and dq+ and dq� reference frames are given by the following equation [6;7;8].

I+dq = I ��e�� I�dq = I ��e�� (4)

I+dq = I�dq e�� I�dq = I+

dq e�� (5)

I+dq = I�� e�� I�dq = I (�� e�� . (6)

ddsdq

sdq s sdq s sdq

��

�� V R I j

�(7)

I��+ = I��++ + I��+- = I��++ + I�� -- e-�� . (8)

I��+ = I��++ + I��+- = I��++ + I�� -- e-�� . (9)

Active and reactive power of stator:

P��+ ��

++�� + - V��

+��+� (10)

Q��+ ��

++�� + - V��

+��+� (11)

PI-Fuzzy controllers as shown in Fig. 5 are used to control the errors between the required and actual values of both the active power and reactive power delivered to the grid by the generator. The parameters of the PI-Fuzzy are adjusted by the fuzzy rules to obtain the best output to drive the errors to zero. The outputs of these controllers are commanded values of d-q components of rotor current in the stator flux oriented reference frame. These commanded values of currents are used to regu-late the RSC for provision of the rotor phase voltage to DFIG.

Fig. 4. Relationships between ��s��r and dq+and dq� reference frames.


427(95)

Fig. 5. PI- Fuzzy Controller.

Table 1 Rule Base of Kp [5]

Table 2 Rule Base of Ti [5]

The fuzzy rules for parameters of PI-FUZZY con-trollers are presented in table 1 and table 2. The rules are developed by trial and error method. LN, SN, ZE, SP, and LP represents large negative, small negative, zero, small positive, large positive. S, M, H are for small, medium, high.

The triangular membership functions of inputs and outputs of PI-Fuzzy controller are shown in Figs. 6 and7.

Fig. 6. Membership functions of two inputs of fuzzy bloc.

Fig. 7. Membership functions of two outputs of fuzzy bloc.

Table 3 Parameters of DFIG 2.3MWParameter Symbol ValueStator inductance LS 159.2 (�H)Rotor inductance Lr 159.2 (�H)Magnetic inductance Lm 5.096 (mH)Stator resistance RS 4 (��)Rotor resistance Rr 4 (��)Number of pole pairs P 2Frequency of the electric system �S 100��rad/s)Inertia J 93.22 (kg.m2)

Inertia of Rotor Jrot4.17×106

(kg.m2)

4. Simulation and Results

Simulation of proposed control method for a 2.3 MW DFIG is carried out, parameters of the generator are shown in table 3. The grid voltage unbalance hap-pens after 35 seconds, the commanded values of reac-tive power and active power change at 50s and 60s respectively. Comparisons of average values of the powers in steady state with different controllers are presented in table 4 and 5. Both actual values and percentage of references are shown. The randomly variable wind speed is shown in Fig. 8. DFIG’s rotor speed is shown in Fig 9. Grid voltage unbalance which happens after 35 s is shown in Fig. 10.

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Fig. 8. Random variation of wind speed.

0 10 20 30 40 50 60-500

0

500

1000

1500

2000

Time [s]

Var

iatio

n of

rot

or s

peed

(nr

)

Fig. 9. Variation of rotor speed.

34.9 34.92 34.94 34.96 34.98 35 35.02 35.04 35.06 35.08 35.1-800

-600

-400

-200

0

200

400

600

800

Time [s]

Vabcs

[V

]

Fig. 10. The grid voltage unbalance happens after 35 seconds.

Table 4 Average Value of Ps in Steady State for 3 Control-lers

��

PI PI-FUZZY PI-��

MW %* MW %* MW %*

Balanced 0.976 2.38 0.976 2.41 0.975 2.53

Unbalanced 0.905 9.52 0.92 8.00 0.925 7.50

(*)%= 100s ref s

s ref

P PP

�

Table 5 Average Value of Qs In Steady State for 3 Controllers.��

PI PI-FUZZY PI-��

MVAR %** MVAR %** MVAR %**

Balance 0.491 1.71 0.502 -0.39 0.502 -0.37

Unbalance 0.440 12.1 0.481 3.7 0.482 3.62

(**)%= 100s ref s

s ref

Q QQ

�

32 34 36 38-2500

-2000

-1500

-1000

-500

0

500

1000

1500

2000

2500

Time [s]

Iabc

r [A

]

With PI & Notch Filter

32 34 36 38-2500

-2000

-1500

-1000

-500

0

500

1000

1500

2000

2500With PI-F & without Notch Filter

Time [s]32 34 36 38

-2500

-2000

-1500

-1000

-500

0

500

1000

1500

2000

2500With PI & without Notch Filter

Time [s]

Fig. 11. Phase rotor current of DFIG.

20 40 60 800.6

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6PI-F & with Notch Filter

Time [s]

Ps

[MW

]

20 40 60 800.6

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6PI-F & without Notch Filter

Time [s]20 40 60 80

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6PI & without Notch Filter

Time [s]

Fig. 12. Active output power of DFIG.

20 40 60 800

0.2

0.4

0.6

0.8

1

1.2

1.4

Time [s]

Qs

[MV

AR

]

PI-F & with Notch Filter

20 40 60 800

0.2

0.4

0.6

0.8

1

1.2

1.4PI-F & without Notch Filter

Time [s]20 40 60 800

0.2

0.4

0.6

0.8

1

1.2

1.4PI & without Notch Filter

Time [s]

Fig. 13. Reactive output power of DFIG.

The simulation results with different controllers are shown in Figs. 11 to 14; for rotor currents, active and reactive powers, and generator’s torque respectively.


429(97)

20 40 60 80-20000

-15000

-10000

-5000

0

5000PI-F & with Notch Filter

TIME [S]

Te

20 40 60 80-20000

-15000

-10000

-5000

0

5000PI-F & without Notch Filter

TIME [S]20 40 60 80

-20000

-15000

-10000

-5000

0

5000PI & without Notch Filter

TIME [S]

Fig. 14. Torque of DFIG.

5. Discussion

The generator’s rotor speed fluctuates significantly when and after the voltage unbalance happens as shown in Figs. 9 and 10. The phase rotor currents are slightly distorted when grid unbalance happens as shown in Fig.11. The inclusion of Notch filter for elimination of negative phase sequence does not change significantly the waveform of rotor phase current.

However, Notch filter causes significant effects onactive power delivered to the grid during unbalance as shown in Fig. 12 and highlighted in table 4. After the grid unbalance happens, the active power still follows the commanded value, but with fluctuation. The combi-nation of the PI-Fuzzy controller and Notch filter improves the response of active power by reducing the fluctuation. The steady state error of active power during voltage unbalance is also cut down to 7.5 % of reference value from 9.52 % when the filter and the hybrid controller are not used.

Similarly, the combination also reduces fluctuation in reactive power responses due to voltage unbalance as shown in Fig. 13 and summarized in table 5. The steady state error in reactive power response has been reduced to 3.6 % of reference value with the incorporation of the controller and the filter. The PI-Fuzzy controller and Notch filter do not result in improvement of generator’s torque responses as shown in Fig. 14.

6. Conclusion

The inclusion of hybrid PI-Fuzzy controller and Notch filter for sequence component controlling have improved the stability of active and reactive powers delivered to the grid by DFIG during grid voltage unbalance. High fluctuations are observed in both active and reactive powers, discrepancies between the active power and reactive power average values and reference values have been significantly reduced. The further improvement for reduction of power ripples and steady-state discrepancy should be suggested.

References

[1] T. Ackermann, Wind power in power systems, John Wiley and Sons, USA, 2003.

[2] W. Leonhard, Control of electric drives, Springer-Verlag, 3rd edition, USA, 2001.

[3] E. Muljadi, D, Yildirim, T. Batan and C. P. Butterfield, “Understand the Unbalanced-Voltage Problem in Wind Turbine Generation,” IEEE Indust. Appl. Conf., Phoenix, USA, pp.1359-1365, 1999.

[4] M. M. Baggu, “Advanced Control Techniques for Doubly Fed Induction Generator – Based Wind Turbine Convert-ers to Improve Low Voltage Ride- Throught during Sys-tem Imbalances,” Ph. D. Thesis, Missouri University of Sci. and Tech., 2009.

[5] T. Pham-Dinh, H. Pham-Trung and H. Le-Thanh, “PI-Fuzzy Controller for Doubly Fed Induction Generator Wind Turbine,” Proc. ASEAN Symp. Automatic Control ASAC 2011, Vietnam, pp.79-81, 2011.

[6] V. T. Phan, H. H. Lee and T. W. Chun, “An Effective Rotor Current Controller for Unbalanced Stand – alone DFIG Systems in the Rotor Reference Frame,” J. Power Electrion., Vol. 10, No. 6, pp. 194-202, 2010.

[7] L. Xu and Y. Wang, “Dynamic Modeling and Control of DFIG Based Wind Turbines under Unbalanced Network Conditions,” IEEE Trans. Power Sys., Vol. 22, No. 1, pp. 314-323, 2007.

[8] A. Peterson, L. Harnefors and T. Thiringer, “Comparison between Stator-Flux and Gridflux Oriented Rotor Current Control of Doubly-Fed Induction Generators,” 35th Annual IEEE Power Electron. Specialist Conf., Vol. 1, 20–25, pp. 482-486, 2004.

[9] P. Sorensen, D. A. Hansen, P. Christensen, M. Mieritz, J. Bech, B. Bak-Jensen and H. Nielsen, Simulation and Veri-fication of Transient Events in Large Wind Power Installa-tion, Project Report, Risø National Laboratory, Roskilde, Norway, 2003.

[10] M. G. Masters, Renewable and Efficient Electric Power Systems, John Wiley and Sons, Inc., Publication, 2004.

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