Elektrotehniški vestnik 84(5): 235-240, 2017 Original scientific paper
A direct power control of the doubly-fed induction generator based on the SVM Strategy
Sarra Massoum7, Abdelkader Meroufel7, Ahmed Massoum7, Patrice Wira2
1Djillali Liabes University, Sidi Bel Abbes, Algeria 2Haute Alsace University, Mulhouse, France E-mail: ahmassoum@yahoo.fr
Abstract. This paper proposes a direct power control scheme for the doubly-fed induction generator (DFIG) for variable speed wind-power generation. The machine is connected as a generator. Its rotor is fed by a two-level inverter. We propose to control the DFIG with a technique based on the direct power control (DPC) performances.
A combination of a space-vector modulation (SVM) technique and active and reactive power controllers is made to replace hysteresis controllers used in the classic DPC drive resulting in a fixed switching frequency of the power converter.
The performances obtained by using this control strategy are shown under MATLAB Simulink. Keywords: DPC, SVM, DFIG, Wind turbine
Neposreden nadzor moči pri dvojno napajanem asinhronskem generatorju na podlagi strategije SVM
V prispevku je predstavljen neposreden nadzor moči pri dvojno napajanem asinhronskem generatorju pri vetrnih elektrarnah. Pri nadzoru moči smo uporabili kombinacijo prostorsko-vektorske modulacije in aktivnih ter reaktivnih močnostnih krmilnikov za zamenjavo krmilnikov s histerezo, ki se uporabljajo pri klasičnem neposrednem nadzoru moči. Zmogljivost predlaganega pristopa smo preverili v okolju MATLAB Simulink.
1 Introduction
In the Direct Torque Control (DTC) of an induction machine, the control strategy is based on the selection of appropriate stator voltage vectors in order to maintain the torque and the stator flux within their hysteresis bands [1]. The direct power control (DPC) is based on the well know a DTC for induction machines.
The recent advances in the power semiconductor and microprocessor technology have made possible to use advanced control techniques for the Doubly Fed Induction Generator (DFIG). The basic idea of the DPC approach is a direct control of the active and reactive power without any internal control loop or PWM modulator. The switching states are selected via a switching table and the states are chosen based on the instantaneous error between the estimated and the desired active and reactive-power of the DFIG drive systems [2]. In this paper, a DPC strategy is proposed to control the doubly fed induction generator using a two-level inverter. The DPC performances can be ensured by using a
Switching Table (ST) to select the switching voltage vector. The inverter connected to the DFIG must provide the necessary complementary frequency in order to maintain a constant stator frequency
2 Wind Turbine Characteristic
The wind Electric Conversion System (WECS) is a good solution to electrify isolated locations which are far from the power distribution network. Due to the increasing concern about the clean environment and the depletion of natural resources, such as fossil fuels and nuclear fusion materials, much of the novel research is mainly focused on obtaining electricity from nonconventional energy sources. The WECSs are recently getting a lot of attention, for being cost-viable, inexhaustible, environmentally clean and safe renewable energy sources compared to the thermal and nuclear power generation systems [3].
A wind turbine can be characterized by a nondimensional curve of power coefficient Cp as a function of Tip-Speed Ratio (TSR) X, where, X is given in terms of rotor speed, mm (rad/s), wind speed, V (m/s), and rotor radius, R (m) as [3]:
X =
V
The wind turbine power coefficient, Cp is dependent upon X. If the pitch angle, p is incorporated, Cp becomes a function of X and p, i.e. Cp = f(X, p). The power
Received 11 June 2017 Accepted 17 November 2017
236
MASSOUM, MEROUFEL, MASSOUM, WIRA
coefficient as a function of X and ß can be expressed as [2]:
Cp(X,ß) = 0.518 16 - 0.4ß- 5 e

(1)
+ 0.006&
Where: 1
0.035
0
10
15
Speed ratio
Figurel. Power coefficient.
The Cp = f (X, p) curves for some p values are shown in Figure 1. It can be seen that as p increases, Cp decreases too, thus reducing the power generated by the wind turbine, knowing the speed of the turbine the aerodynamic torque is determined by:
.....3 )Y i '
c = P-
Qt
Cp (pSV3
2
Q
'turb
(2)
The multiplier is mathematically modelled using the following equations:
G„ =■
Gt
Qt =■
G
G±
G
(3)
(4)
The connection between the turbine and the electric part of the wind is represented here by the equation of the shaft:
_ Jt
J + Jg	(5)
The mechanical torque applied to the rotor:
jdQ = c = c -c -Ct
J dt Cmec Cg Cem cf
(6)
And we have that:
^^ = ffQ g
3 A DFIG Dynamic model
(7)
X X + 0.08P p3 +1
Figure 1 shows simulation results in MATLAB/Simulink of evolution of power coefficient C a function of relative speed I for different pitch angles p.
0.6 0.5 0.4 0.3 0.2 0.1 0 -0.1
In order to investigate the DFIG behavior, a dynamic equation needs to be considered. From the point of view of the control, the d-q representation of an induction machine leads to control flexibility. The DFIG dynamic behavior in a synchronous reference frame can be represented by the Park's equations, provided all the rotor quantities are referred to the stator side. The stator and rotor voltages are expressed as follows [3] [4] [5]:
Vds = RI
s ds
d® ds n ^ +-dL-0 s ® as
dt s as
d®
V = R I +-a—-0 ® ,
r as	as ^ s^ds
Vdr = Rrldr + — ~0,®
(8)
dt d®
r qr
V„„ = RrInr +—— -0 r ® dr
qr	qr
dt
® * = LsIch + MIdr
® = LI + MI
^ as s* as ar
ds
® dr = LrIdr + M
® = LI + MI
ar r ar	as
(9)
The electromagnetic torque, the active and reactive power equations for DFIG may be written as:
Cem = Cr + fQ + J
dQ dt
(10)
This can be expressed as a function of stator fluxes and rotor currents:
Cem m asIdr ® dsIdr )
L c
(11)
4 Control Strategy of the Doubly-Fed Induction Generator
The doubly-fed electric machines are electric motors or electric generators with windings on both the stationary and rotating parts, where both windings transfer a significant power between the shaft and the electric system. The doubly-fed machines are useful in applications that require a variable speed of the machine shaft for a fixed power system frequency. As the penetration of large-scale wind turbines into electric-power grids continue to increase, electric system operators are placing greater demands on the wind turbine power plants.
For obvious reasons of simplifications, the d-q reference frame related to the stator spinning-field pattern and the stator flux aligned on the d-axis are
1
5
\
y
A DIRECT POWER CONTROL OF THE DOUBLY-FED INDUCTION GENERATOR BASED ON THE SVM STRATEGY
237
adopted. Moreover, the stator resistance can be neglected since it is a realistic assumption for the generators used in the wind turbine [3] [4]
DFIG is controlled by the rotor voltages via an inverter. It is an independent control of the active and reactive power. In the d-q reference frame, in an asynchronous generator stator, the active power Ps and reactive power Qs are:
Q -vsfiqr +
Lc
iL
Ls ras
(12)
Vdr	dr ^
( ^ ^ V Ls yy
Lr -
dl
dr
dt
-g
( (M 2^
(13)
Lr -
V Ls yy
ra s1 qr
Vqr	qr
( (M 2^
V Ls y
Lr -
dl
dr
dt
-g
M2
Lr -
V Ls y y
ra sIqr + g
V
(14)
L ra is the stator reactance. Equations showing the relationship between the rotor currents and voltages are established and will be applied to control the generator.
r ■ M ®ra = CT Lr'ra	® s
Ls
® rß = CT Lr'rß
Vs
® =J
S
(16)
ra.
CT = 1 -
M 2
Ls Lr
Adaptation of these equations to the simplified assumptions gives
Ps and Qs can be reformulated by inducing angle 5 between the stator and rotor vectors as follows:
Ps =-
M
CTLsLr
ras ®s ®r sin8
Qs =
= - y
ss ctls
^ M | . _ . ^ — ®r cos8- ®s
Lin	Is
V Lr	y
(17)
The derivation of the two equations in (10) gives: . dj®r|sin®r)
dPs	Lm ra
dt	ctLsL
dQs	Mra s
dt	CTLsLr
1° s
s| dt d (j® r| cos 8)
(18)
dt
The stator active and reactive powers can then be varied by changing the angle between the rotor and stator vectors:
5 DPC Principle
The DTC method is basically a performance-enhanced scalar control method. The main features of a DTC are direct control of the flux and torque by the selecting an optimal inverter switching vector.
The basic principle of DPC was proposed by Noguchi and is based on the well-know a DTC for induction machines. In DPC, the active and reactive powers replace the torque and flux amplitude used as a controlled output in DTC. The basic concept consists of selecting the appropriate switching states from a switching table based on the errors, which are limited by a hysteresis band, present in the active and reactive powers [6] [7] [8] [9].
The measured values of powers Ps and Qs are estimated from the following relations where powers can be written in terms of the two rotor flux components in the (ar-Pr) frame.
Ps =-
M
CTLsLr
V ® R
' s^rß
Qs =
V
®-
VsM _ s ®
V ctls	CTLsLr
(15)
Where:
6 DPC BASED ON THE SVM STRATEGY
The space vector modulation (SVM) is an algorithm to control the pulse width modulation (PWM). It is used to create of alternating current (AC) waveform. It is most commonly used in inverters and three-phase ac-powered motors. There are various types of SVM that result in different quality and computational requirements. One active area of development is in the reduction of the total harmonic distortion (THD) created by the rapid switching inherent to these algorithms [10].
238
MASSOUM, MEROUFEL, MASSOUM, WIRA
In order to obtain a smooth operation at a constant switching frequency, direct power control is combined with the SVM strategy based on the principles of the classical DPC method
Elaboration of the switching table of the control structure is based on the outputs of the Rp and Rq controllers and rotor-flux position 5 .
Table 1 gives a clear idea of the switching sequences of all the states of the inverter.
x 105
Table 1. Switching table
Rq
Rp
Rotor Flux sector
		1			-1	
	1	0	-1	1	0	-1
1	V5	V7	V3	V6	Vo	V2
2	V6	Vo	V4	V,	V7	V3
3	Vi	V7	V5	V2	Vo	V4
4	V2	Vo	V6	V3	V7	V5
5	V3	V7	V,	V4	Vo	V6
6	V4	Vo	V2	V5	V7	Vi
A schematic diagram of the proposed DPC for a DFIG system is shown in Fig. 3. The controller contains two PI controllers, one for the active power and one for the reactive power, as well as SVM unit.
o a.
a
á -10
o <
-15-
Psref Ps
0.2
0.4 0.6 Time (s)
0.8
1.5
x 106
ra
s
0.5
o ra
0
01
-0.5
-1.5
Qsref Qs

0.2
0.4 0.6 Time (s)
0.8
Figure 4. Active and reactive power (DPC).
4000
< 2000
Figure 3. Conventional switching table based on DPC for DFIG.
7 Simulation Results
The proposed DPC scheme is implemented with Matlab/Simulink in order to evaluate its performances. DFIG used for the simulations has the following parameters:
P = 2kw, Vn = 230V, f = 50Hz, Rs = 0.455 Q, Rr = 0.19Q, Ls = 0.07 H, Lr = 0,213Q, M = 0,034H, J = 0.3125kg .m 2, Kf = 0.001Nm.s / rad, p = 2
£ -2000
-4000
4000
< 2000
■S -2000
w
-4000
0.2
0.4 0.6 Time (s)
0.8
0.2 0.4 0.6 Time (s)
0.8
Figure 5. Rotor and stator currents (DPC).
0
0
0
0
0
A DIRECT POWER CONTROL OF THE DOUBLY-FED INDUCTION GENERATOR BASED ON THE SVM STRATEGY
239
o
.x 105
If-10
>
■+J
o
< -15
-20
1.5 F"
.x 10"
-o 1 -ra
f 0.5-
a)
5
o. 0-
|	-0.5-
ra
a)
*	-1-
Psref Ps
0.2
0.4 0.6 Time (s)
0.8
Qsref Qs
Figure 4 shows that the active and reactive powers are decoupled from each other in the proposed DPC control process with a rapid time response, without overshoot and with a minimal static error, but with a significant chattering for all the parameters (Fig. 5).
The performance of the DTC-SVM can be seen in the maintaining of a perfect decoupling of the powers and a net reduction of chattering for the different parameters (Fig.6, Fig.7)
8 Conclusion
This paper presents a direct power control for a doubly fed induction generator that can achieve a high accuracy and fast dynamic power response. The direct power control scheme helps protecting the rotor-side converter because there is no overshoot in the rotor current. The direct power control guarantees the active and the reactive power to reach their desired reference values and as satisfactory decoupling between the two stator powers.
The DTC-SVM gives a perfect decoupling of the powers and a net reduction of chattering for the different parameters of the machine parameters variations.
References
-1.5L
0.2
0.4 0.6 Time (s)
0.8
Figure 6. Active and reactive power (DPC-SVM).
4000 f
& 2000 ■
V>.
■2000 -
-4000L
4000 r
0.2
0.4 0.6 Time (s)
0.8
S 2000 "
J3 c
£ g
o o
Hi -20001-
f>
-4000
■llïl
0.2 0.4 0.6 0.8 Time (s)
Figure 7. Rotor and stator currents (DPC-SVM).
[1]	S. Vaez-Zadeh and G.H. Mazarei. "On-line determination of optimal hysteresis band amplitudes in direct torque control of induction motor drives", IJE Transactions A: Basics,15, pp. 309338, 2002.
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[9]	Sung-Tak Jou, Sol-Bin Lee, Yong-Bae Park and Kyo-Beum Lee. "Direct Power Control of a DFIG in Wind Turbines to Improve Dynamic Responses", Journal of Power Electronics, 9, pp. 782790, 2009.
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Sarra Massoum is working towards her PhD degree from the Electrical Engineering at the University of Sidi Bel-Abbes (Algeria). She is a member of the ICEPS (Intelligent Control Electrical Power System) Laboratory. Her research interests are robust control of electrical machines.
Abdelkader Meroufel received his BS and M.Sc degrees in Electrical ingeneering from the USTOran University (Algeria) in 1979, and in 1990 respectively, and his PhD degree from the Electrical Engeneering Institute of University of Sidi Bel-Abbes (Algeria) in 2004. He is currently a Professor of electrical engineering at this University. He is a member of the ICEPS (Intelligent Control Electrical Power System) Laboratory. His research interests are in robust control of electrical machines.
Patrice Wira received his MSc degree and PhD degrees in Electrical Engineering from the University of Haute Alsace, Mulhouse, France, in 1997 and 2002, respectively. In 2009 he was accreditated to supervise research (the French Habilitation Diriger des Recherches) in computer sciences at the same university. He was an associate professor with the MIPS Laboratory (Laboratoire Modlisation, Intelligence, Processus, Systeme) at the same university. Since 2011, he has been a full professor. He is the author or coauthor of more than 20 technical papers covering his research interests from artificial neural networks applied to modelling and simulation of complex automation systems, to neuro-control approaches and other adaptive control systems.
Ahmed Massoum was born in 1959 in M'sirda Fouaga, Tlemcen, Algeria. He received his BS degree in electrical engineering from the Electrical Engineering Institute (INELEC) of Boumerdes 1985 and the MS degree from the Electrical Engineering Institute of Sidi Bel-Abbes University in 2004 where he is currently Professor of electrical engineering. He is a member in Intelligent Control Electrical Power System Laboratory (ICEPS).