SlideShare a Scribd company logo
1 of 12
Download to read offline
International Journal of Electrical and Computer Engineering (IJECE)
Vol. 10, No. 5, October 2020, pp. 4592~4603
ISSN: 2088-8708, DOI: 10.11591/ijece.v10i5.pp4592-4603  4592
Journal homepage: http://ijece.iaescore.com/index.php/IJECE
Control of the powerquality for a DFIG powered
by multilevel inverters
Hachemi Hachemi1
, Ahmed Allali2
, Belkacem Belkacem3
1,2
University of Science and Technology of Oran Mohamed Boudiaf,
LDDEE, Laboratoire de Développement durable de l’Energie Electrique, Algeria
3
Institut de Maintenance et de Sécurité Industrielle, Université d'Oran, Algeria
Article Info ABSTRACT
Article history:
Received Aug 23, 2019
Revised Feb 24, 2020
Accepted Mar 25, 2020
This paper treats the modeling, and the control of a wind power system based
on a doubly fed induction generator DFIG, the stator is directly connected to
the grid, while the rotor is powered by multilevel inverters. In order to get
a decoupled system of controlfor an independently transits of active and reactive
power, a vector control method based on stator flux orientation SFOC is
considered: Direct vector control based on PI controllers. Cascaded H-bridge
CHBI multilevel inverters are used in the rotor circuit to study its effect on
supply power quality. All simulation models are built in MATLAB/Simulink
software. Results and waveforms clearly show the effectiveness of vector
control strategy. Finally, performances of the system will tested and compared for
each levels of inverter.
Keywords:
Doubly fed induction generator
DFIG
H-BRIDGE
Multi-levels inverters
PI controllers
Stator flux orientation SFOC
Copyright © 2020Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Hachemi Hachemi,
University of Science and Technology of Oran Mohamed Boudiaf,
El Mnaouar، BP 1505, Bir El Djir 31000, Algeria.
Email: h.hachemi@yahoo.fr
1. INTRODUCTION
The generation of electricity that comes from nuclear power and fossil natural resources, pose
continued problems whose importance is growing over the years; as the nuclear untreatable waste and
disappearance expected in the 21st
century, for major source of fossil energy. Environmental constraints on
atmospheric emissions of greenhouse gases has led researchers a way of generating clean, economic and
sustainable electricity [1].
Various studies carried out in this context have shown that far-reaching changes are essential in energy
strategies to ensure better management of the production, transformation, distribution and use of energy [2].
From this perspective, controlling energy in a broad sense constitutes an important challenge in the development of
sustainable energy. Energy efficiency and renewable energies are therefore interesting avenues for more
sustainable energy development and are considered to be among the most environmentally friendly components,
particularly in the fight against climate change [3]. Thus, the modes of production based on the transformation of
renewable energy (solar, wind ...) are expected to be increasingly used in the context of sustainable development,
and thanks to recent developments of power electronics and micro processing.
The production area of variable speed wind energy has in recent years a boom. A great attention is
paid today to doubly fed machine DFIM for various applications suchas generator for wind energy.
This interest is mainly due to the fact of accessibility for its rotor and therefore the possibility of supplying
a converter as well as the stat side gold on the rotor side.
Power-electronic converters have been developed for integrating wind power with the electric grid.
The use of power-electronic converters allows for variable-speed operation of the wind turbine, and enhanced
Int J Elec & Comp Eng ISSN: 2088-8708 
Control of the powerquality for a DFIG powered by multilevel inverters (Hachemi Hachemi)
4593
power extraction. In variable-speed operation, a control method designed to extract maximum power from
the wind turbine and provide constant grid voltage and frequency is required [4].
In this paper, a variable-speed wind turbine is considered with DFIG and a multilevel cascaded
H-Bridge Inverter CHBI. Multilevel inverters are AC-DC-AC converters, well suited for medium and
high-power applications [5] due to their ability to meet the increasing demand of power ratings and power
quality associated with reduced harmonic distortion, lower electromagnetic interference, and higher
efficiencies when compared with the conventional two or three level topology [6]. The increasing number of
voltage levels lead to the production of high-power quality waveforms [7], causing the total harmonic
distortion THD to be lower. Multilevel converters are a good tradeoff solution between performance and cost
in wind high-power systems [8].
The most typical connection diagram of this DFIG is to connect stator directly to the grid, while the rotor
is supplied through a controlled power converter. This solution is more attractive for all applications where speed
variations are limited around the synchronous speed because this area operating presents low slip, and therefore
the converter associated with the rotor has to be treated only for a fraction of 20 to 30 % of the nominal
conversion system power; this means that the losses in the converter are reduced (power supplied to the rotor
is low) and the cost thereof is reduced. That is why we find this machine in high power variable speed and
constant frequency for production systems. A second reason is the possibility of controlling the active and
reactive power in the stator via the control of the power converter [9].
Further variable speed wind turbine is modeled to find a relationship between the electromagnetic
torque and the mechanical wind speed. After describing mechanical and electrical model of the DFIG in
section 3, a vector control method based on stator flux orientation SFOC is considered: direct vector control
based on PI controllers. The sinus pulse wave modulation (SPWM) control strategyfor multilevel invertersis
given in section 4. Finally, simulation and results are presented; performances of the system are then evaluated.
2. WIND TURBINE MODEL
Mechanical power available on the shaft of a wind turbine is expressed by [10]:
𝑃𝑣 =
1
2
𝜌𝑆𝑣𝑣
3
=
1
2
𝜌𝜋𝑅2
𝑣𝑣
3 (1)
where:
ρ :air density (1.25 Kg/m3
);
R : Blade length in meters;
Vv : wind velocity in m/s.
The aerodynamic power extracted from wind turbine canbe calculated as:
𝑃𝑇𝑢𝑟𝑏 = 𝐶 𝑝 𝑃𝑣 =
1
2
𝜌𝑆𝑣𝑣
3
=
1
2
𝜌𝜋𝑅2
𝑣𝑣
3
. 𝐶 𝑝(𝜆, 𝛽) (2)
𝜆 =
Ω 𝑇𝑢𝑟𝑏. 𝑅
𝑣𝑣
(3)
where:
Cp : Power coefficient;
β : Pitch angle (deg);
λ :Tip speed ratio;
ΩTurb : Turbine speed (rd/s).
No wind turbine could convert more than 59 % of the kinetic energy of the wind into mechanical
energy turning a rotor [11]. This is known as the Betz limit, and it is the theoretical maximum coefficient of
power for any wind turbine: Cpmax= 16/27 ≈ 0.593. The multiplier is mathematically modeled by
the following equations:
{
𝑇 𝑚 =
𝑇𝑇𝑢𝑟𝑏
𝐺
Ω 𝑇𝑢𝑟𝑏 =
Ω 𝑚
𝐺
𝐽 𝑇 =
𝐽 𝑇𝑢𝑟𝑏
𝐺2 + 𝐽 𝑔
𝑇𝑇𝑢𝑟𝑏 =
𝑃 𝑇𝑢𝑟𝑏
Ω 𝑇𝑢𝑟𝑏
(4)
 ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 5, October 2020 : 4592 - 4603
4594
where:
Ωturb, Ωm: Turbine speed respectively before and afterthe multiplier;Tturb: aerodynamic torque; Tm: torque after
the multiplier; G: Gear ratio; Jg: Generator inertia; JT: Total inertia; JTurb: Turbine inertia.
The fundamental equation of dynamics to determine the evolution of the mechanical speed from
the total mechanical torque 𝑇 𝑚𝑒𝑐 applied to the rotor:
𝐽 𝑇
𝑑Ω 𝑚𝑒𝑐
𝑑𝑡
= 𝑇 𝑚𝑒𝑐 = 𝑇 𝑚 − 𝑇𝑒𝑚 − 𝐶𝑓Ω 𝑚𝑒𝑐 (5)
where:
Tem : Electromagnetic torque; Cf: Viscous friction coefficient.
2.1. Modeling of the DFIG, Park’s model
The d-q axis representation of DFIG is used for modeling, considering flux as variable based on
Park's model. All rotor quantities are referred to stator side. The DFIG model represented by voltage (6).
The stator and rotor side flux linkage equations are given as [12-14]:
{
𝑉𝑠𝑑 = 𝑅𝑠 𝐼𝑠𝑑 +
𝑑Ф 𝑠𝑑
𝑑𝑡
− 𝜔𝑠Ф 𝑠𝑞
𝑉𝑠𝑞 = 𝑅𝑠 𝐼𝑠𝑞 +
𝑑Ф 𝑠𝑞
𝑑𝑡
+ 𝜔𝑠Ф 𝑠𝑑
𝑉𝑟𝑑 = 𝑅 𝑟 𝐼𝑟𝑑 +
𝑑Ф 𝑟𝑑
𝑑𝑡
− (𝜔𝑠 − 𝜔𝑟)Ф 𝑟𝑞
𝑉𝑟𝑞 = 𝑅 𝑟 𝐼𝑟𝑞 +
𝑑Ф 𝑟𝑞
𝑑𝑡
+ (𝜔𝑠 − 𝜔𝑟)Ф 𝑟𝑑
(6)
The stator and rotor flux can be expressed as:
{
Ф 𝑠𝑑 = 𝐿 𝑠 𝐼𝑠𝑑 + 𝐿 𝑚 𝐼𝑟𝑑
Ф 𝑠𝑞 = 𝐿 𝑠 𝐼𝑠𝑞 + 𝐿 𝑚 𝐼𝑟𝑞
Ф 𝑟𝑑 = 𝐿 𝑟 𝐼𝑟𝑑 + 𝐿 𝑚 𝐼𝑠𝑑
Ф 𝑟𝑞 = 𝐿 𝑟 𝐼𝑟𝑞 + 𝐿 𝑚 𝐼𝑠𝑞
(7)
Electromagnetic torque is also expressed in terms of currents and flux:
𝐶𝑒𝑚 = 𝑝
𝐿 𝑚
𝐿 𝑠
(Ф 𝑠𝑑 𝐼𝑞𝑟 − Ф 𝑠𝑞 𝐼 𝑑𝑟) (8)
where:
Rs, Rr, are respectively the stator and rotor resistances; Ls, Lr: inductances of the stator and rotor windings;
Lmis the mutual inductance; Vds, Vqs, Vdret Vqr: Direct and quadrate components of the space phasors of
the stator and rotor voltages; Ids, Iqs, Idr, Iqr: Direct and quadrate components of the space phasors of
the stator and rotor currents; φds, φqs, φdret φqr: Direct and quadrate components of the space phasors of
the stator and rotor flux respectively;
ɷs: Rotational speed of the synchronous reference frame;
ɷr: Rotor speed,
p: Number of pair poles.
Active and reactive powers at the stator (Ps, Qs), and the rotor (Pr, Qr) are defined as [15-16]:
{
𝑃𝑠 = 𝑉𝑠𝑑 𝐼𝑠𝑑 + 𝑉𝑠𝑞 𝐼𝑠𝑞
𝑄𝑠 = 𝑉𝑠𝑞 𝐼𝑠𝑑 − 𝑉𝑠𝑑 𝐼𝑠𝑞
𝑃𝑟 = 𝑉𝑑𝑟 𝐼 𝑑𝑟 + 𝑉𝑞𝑟 𝐼𝑞𝑟
𝑄 𝑟 = 𝑉𝑞𝑟 𝐼 𝑑𝑟 − 𝑉𝑑𝑟 𝐼𝑞𝑟
(9)
2.2. Control strategy of the DFIG
Once the DFIG is connected to an existing grid, the transit of active and reactive powers must be
controlled separately. To obtain a decoupled powers control of DFIG, the method based on field orientation
Int J Elec & Comp Eng ISSN: 2088-8708 
Control of the powerquality for a DFIG powered by multilevel inverters (Hachemi Hachemi)
4595
can be regarded as the efficient one. The principle of this method consists to orientate the stator flux in such
a way that the stator flux vector points into d-axis direction; this approach is realized by setting the quadratic
component of the stator flux to the null value, detailed representation is show in Figure 1 [17, 18].
Figure 1. Stator flux orientation
The stator fluxes of (6) will be simplified as follows:
{
Ф 𝑠𝑑 = 𝐿 𝑠 𝐼𝑠𝑑 + 𝐿 𝑚 𝐼𝑟𝑑 = Ф 𝑠
Ф 𝑠𝑞 = 𝐿 𝑠 𝐼𝑠𝑞 + 𝐿 𝑚 𝐼𝑟𝑞 = 0
(10)
The stator resistance will be neglected, for medium power machines used in WECS; the stator
voltage vector is consequently in quadrate advance in comparison with the stator flux vector.
{
𝑉𝑠𝑑 = 0
𝑉𝑠𝑞 = 𝜔𝑠Ф 𝑠 = 𝑉𝑠
(11)
Using (10), we can establish the connection between the rotor and stator currents:
{
𝐼𝑠𝑑 = −
𝐿 𝑚
𝐿 𝑠
𝐼𝑟𝑑 +
∅ 𝑠
𝐿 𝑠
𝐼𝑠𝑞 = −
𝐿 𝑚
𝐿 𝑠
𝐼𝑟𝑞
(12)
Using (11) and (12), the stator active and reactive power and rotor voltage are given by:
{
𝑃𝑠 = 𝑉𝑠 𝐼𝑠𝑞 = −𝑉𝑠
𝐿 𝑚
𝐿 𝑠
𝐼𝑟𝑞
𝑄𝑠 = 𝑉𝑠 𝐼𝑠𝑑 = −𝑉𝑠
𝐿 𝑚
𝐿 𝑠
𝐼𝑟𝑑 +
𝑉𝑠
2
𝐿 𝑠 𝑤𝑠
(13)
For controlling the DFIG, established expressions showing the relationship between current and
rotor voltages will be applied to it.
{
𝑉𝑟𝑑 = 𝑅 𝑟 𝐼𝑟𝑑 + (𝐿 𝑟 −
𝐿 𝑚
2
𝐿 𝑠
)
𝑑𝐼𝑟𝑑
𝑑𝑡
− 𝑔𝑤𝑠 (𝐿 𝑟 −
𝐿 𝑚
2
𝐿 𝑠
) 𝐼𝑟𝑞
𝑉𝑟𝑞 = 𝑅 𝑟 𝐼𝑟𝑞 + (𝐿 𝑟 −
𝐿 𝑚
2
𝐿 𝑠
)
𝑑𝐼𝑟𝑞
𝑑𝑡
+ 𝑔𝑤𝑠 (𝐿 𝑟 −
𝐿 𝑚
2
𝐿 𝑠
) 𝐼𝑟𝑑 + 𝑔
𝐿 𝑚 𝑉𝑠
𝐿 𝑠
(14)
By considering σ as the cross coupling term, (14) can be rewrite as:
 ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 5, October 2020 : 4592 - 4603
4596
{
𝑉𝑟𝑑 = 𝑅 𝑟 𝐼𝑟𝑑 + 𝐿 𝑟 𝜎
𝑑𝐼𝑟𝑑
𝑑𝑡
− 𝑔𝜎𝑤 𝜎 𝐿 𝑟 𝐼𝑟𝑞
𝑉𝑟𝑞 = 𝑅 𝑟 𝐼𝑟𝑞 + 𝐿 𝑟 𝜎
𝑑𝐼𝑟𝑞
𝑑𝑡
+ 𝑔𝜎𝑤𝑠 𝐿 𝑟 𝐼𝑟𝑑 + 𝑔
𝐿 𝑚 𝑉𝑠
𝐿 𝑠
𝜎 = 1 −
𝐿 𝑚
2
𝐿 𝑟 𝐿 𝑠
(15)
The block diagram representing the internal model of the system is shown in Figure 2. Field oriented
control of the DFIG can then be applied with the active and reactive power considered as variables
to be controlled. The input blocks relating 𝑉𝑟𝑑 to 𝑉𝑟𝑞 represent the simplified rotor converter model.
Knowing (13) and (15), it is then possible to synthesize the regulators [19].
Figure 2. Block diagram of the system to regulate
In order to improve the last command, we will introduce an additional control loop at the currents to
eliminate the static error while preserving the dynamics of the system, then, two additional PI controllers are
added to regulate the active and reactive powers. So, we need sixcurrents sensors, three to control the rotor
currents (iar, ibr and icr) and three associated with three voltage sensors to measure the stator powers Ps and Qs.
The active power PI controller regulates the rotor current reference iqr from the error between the active
power measured Ps and the desired active power Pref. Furthermore, the reactive power PI controller regulates
the rotor current reference idr from the error between the reactive power measured Qs and the desired reactive
power Qref. The closed loop control of active and reactive powers is presented in Figure 3:
Figure 3. Closed loop control of active and reactive powers
Int J Elec & Comp Eng ISSN: 2088-8708 
Control of the powerquality for a DFIG powered by multilevel inverters (Hachemi Hachemi)
4597
3. CASCADED H-BRIDGE INVERTER CHBI THEORY
Several multilevel topologies used for grid connection have been proposed in [20, 21]. Multilevel
converter structures have three major classifications; neutral point clamped (NPCor diode clamped), flying
capacitor (FC or capacitor clamped), and cascaded H-bridge inverter CHBI, with isolated DC source Figure 4.
Compared with the latter two, the multilevel CHBI has many distinct advantages:
 Switch devices required are less under the same switching frequency and level number.
 The harmonic content is lower in the output voltage for a given switching frequency.
 Modularized circuit layout and packaging is possible because each cell has the same structure, and there
are no extra clamping diodes as in the case of diode clamped topology, or voltage balancing capacitors as
in the case of the capacitor clamped topology [22].
.
Vdc
S1
S2
S3
S4
Vout
+
-
Figure 4. Single phase H-bridge inverter
3.1. Theory of cascaded H-Bridge multilevel inverter
The cascaded H bridge multilevel inverter circuit consists of individual H-bridge cells which are fed
by individual dc supply. Each H-bridge cell contains four switches. In this topology, IGBT is used as switch
because of its low switching losses. Each H-bridge generates three different output voltages, +Vdc, 0 and –Vdc
using various combinations of switching with the four switches [22, 23]. The switching tableof the three level
CHB is given in Table 1.
Table 1. Switching table for 3-level CHB inverter
S1 S2 S3 S4 Output Voltage
1 0 0 1 Vdc
0 1 1 0 -Vdc
0 0 0 0 0
Cascaded multilevel inverter is the cascade connection of N H-bridge inverters. Each H-bridge
inverter has the same configuration as a typical single-phase full-bridge inverter. In this topology the number
of phase voltage levels at the converter terminals is 2N+1, where N is the number ofcells or dc link voltages.
The IGBT switches have low block voltage and high switching frequency. Consider the seven level inverter;
it requires 12 IGBT switches and three dc sources. The power circuit ofinverter is shown in Figure 5.
By closing the appropriate switches, each H-bridge inverter can produce three different voltages: +Vdc, 0 and -Vdc.
It is also possible to modularize circuit layout and packaging because each level has the same structure, and
there are no extra clamping diodes or voltage balancing capacitors. The number of switches is reduced using
the newtopology [24, 25].
 ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 5, October 2020 : 4592 - 4603
4598
S1
S2
S3 S4
Vdc
+
-
S1
S2
S3 S4
Vdc
+
-
S1
S2
S3 S4
Vdc
+
-
S1
S2
S3 S4
Vdc
+
-
S1
S2
S3 S4
Vdc
+
-
S1
S2
S3 S4
Vdc
+
-
S1
S2
S3 S4
Vdc
+
-
S1
S2
S3 S4
Vdc
+
-
S1
S2
S3 S4
Vdc
+
-
Vc
Vb
Va
Vc
N
Figure 5. Cascaded H-bridge 7-level inverter
4. SIMULATION RESULTS
The system based on a variable speed wind turbine with a doubly fed induction generator DFIG.
The simulation is carried out using the MatLab/Simulink software. The DFIG is connected directly to
the network through the stator, and controlled by its rotor through a three level CHBI. Simulation results are
presented in Figure 6 to Figure 14. They show performances of our system.
Figure 6. Wind speed Figure 7. Electromagnetic torque
Figure 8. Isd current Figure 9. Isq current
Int J Elec & Comp Eng ISSN: 2088-8708 
Control of the powerquality for a DFIG powered by multilevel inverters (Hachemi Hachemi)
4599
Figure 10. Ird current Figure 11. Irq current
Figure 12. Active power Figure 13. Reactive power
Figure 14. Stator currents
 ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 5, October 2020 : 4592 - 4603
4600
To control the power exchanged between the stator and the network, one uses the vector control
with direct stator flux shown in Figure 15. Simulation results are obtained under various stator active and
reactive power steps. The both control strategies with 5 levels CHBI, and 13 levels CHBI separately,
are simulated, tested and compared in terms of power reference tracking. We initial simulation at first, with
an active power step Psref= -5KW. At time t = 0.5s to 2s an application of the echelon of active power
Psref = - 10KW, and after time t = 2s to 3s we return at step Psref = -5KW. The reactive power step is
changed from Qsref = -1 to -4 KVAR at the instant t = 1 s and again from -4 to -1 KVAR at the instant
t = 1.5 s; a last variation of the reactive power step at the instant t = 2.5 is applied from Qsref =.-1 KVAR.
Simulation results are shown in Figure 16 to Figure 19.
It can be seen that multilevel CHBI can control the active and reactive powers of DFIG with a very
fast time response. However, the ripples in powers are more significant from control with 5 levels CHBI.
To observe the effectiveness of the proposed control strategy, we increased levels of CHBI gradually up to
13 levels. In order to produce quality energy, it is apparent that the control with 13 levels CHBI,
harmonics are almost eliminated. Thus, we estimate that these powers injected into the network will have no
significant impact.
Figure 15. Block diagram of DFIG power control Si tu peux le changer sous forme de bloc c’est mieux
ZOOM
Figure 16. Reel and reference active power with 5 levels CHBI
Int J Elec & Comp Eng ISSN: 2088-8708 
Control of the powerquality for a DFIG powered by multilevel inverters (Hachemi Hachemi)
4601
ZOOM
Figure 17. Reel and reference reactive power with 5 levels CHBI
ZOOM
Figure 18. Reel and reference active power with 13 levels CHBI
ZOOM
Figure 19. Reel and reference reactive power with 13 levels CHBI
 ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 5, October 2020 : 4592 - 4603
4602
5. CONCLUSION
The aim of this work is to model and control the doubly fed induction generator DFIG based wind
energy conversion system powered by multitier inverters with cascaded H-Bridge structure, to increase
the power transferred to the network. In this context, a control of the powers of the wind system was carried out.
For adjusting the energy quality supplied by the DFIG, vector control by orientation of the stator flow that
makes the system similar to that of the DC machine was applied. To be able to directly control the active and
reactive DFIG power through multi-level inverters; our strategy was to apply vector control, with
a configuration of H. BRIDGE inverters; and then increase their levels, in order to improve the quality of
the energy delivered by the DFIG; we thus determined the most efficient system for the different
configurations proposed.The global model of our system is at first established. Furthermore, a vector control
strategy of the DFIG to perform power reference tracking to machine parameters variation. The structure
using the DFIG has a best advantage in terms of high power output, in variable speed operation, while
reducing the size of the static converters. Despite this, the use of multilevel converters seems necessary
especially for high power wind turbines. These converters increase the power transmitted to the power grid
by reducing the current ripple and the harmonic content of the output voltages. This increase is done by
means of the voltage, which makes it possible to reduce the losses of power in the lines.The results show that,
using multilevels CHBI, the quality of produced energy is improved, in fact the harmonics that decrease
the efficiency of the system are extremely diminished.
REFERENCES
[1] A. Dendouga, “Contrôle des puissances active et réactive de la machine asynchrone à double alimentation,”
Thèse de doctorat, Université de Batna, 2010.
[2] Patrick Piro, "Guide des énergies vertes pour la maison," Livre éditions : Terre vivante, L'écologie pratique, 2006.
[3] “Evolution et tendances de la demande mondiale en énergie,” [Online]. Available:
http://web.archive.org/web/20080509052730/www.lenergiecreative.com/ (section “énergie et planète”).
[4] Baroudi, J. A, Dinavahi, V and Knight, A. M, “A review of power converter topologies forwind generators,” Renew
Energy, vol. 32, no. 14, pp. 2369-2385, 2007
[5] Lai, J. S and Peng F. Z., “Multilevel converters. A new breed of power converters,” IEEE Transactions on industry
applications, vol. 32, no. 3, pp. 509-517, 1996
[6] Abbes, M, Belhadj, J and Bennani, A. B. A, “Design and control of a direct drive wind turbine equipped with
multilevel converters,” Renew Energy, vol. 35, no. 5, pp. 936-945, 2010.
[7] Babaei. E, Hosseini. S. H, Gharehpetian. G. B, Haque. M. T and Sabahi. M., “Reduction of dc voltage sources and
switches in asymmetrical multilevel converters using a novel topology,” Electric Power Systems Research, vol. 77,
no. 8, pp. 1073-85, 2007.
[8] R. Melício a, V. M. F. Mendes. B and J. P. S. Catalão, “Power converter topologies for wind energy conversion
systems: Integrated modeling, control strategy and performance simulation,” Renewable Energy, vol. 35,
pp. 2165-2174, 2010.
[9] B.Belkacem, A.K. Lahouari, M. Rahli, “SPWM and SVPWM control of a three level voltage inverter dedicated to
a variable speed wind turbine,” Journal of Power Technologies, vol. 97, no. 3, pp. 190-200, 2017.
[10] F. Poitiers, M. Machmoum, R. Le Doeufi and M. E. Zaim, “Control of a doubly-fed induction generator for wind
energy conversion systems,” IEEE Trans Renewable Energy, vol. 3, no. 3, pp. 373-378, 2001.
[11] H. S. Hamad, A. Hussein Ali, A. A. Abdulrazzaq, “An adaptable different-levels cascaded h-bridge inverter
analysis for PV grid-connected systems,” International Journal of Power Electronics and Drive Systems (IJPEDS),
vol. 10, no. 2, 2019.
[12] B. Hamane. M. L. Doumbia, M. Bouhamida, and M. Benghanem, “Control of Wind Turbine Based on DFIG Using
Fuzzy-PI and Sliding Mode Controllers,” Ninth International Conference on Ecological Vehicles and Renewable
Energies, pp. 1-8, 2014.
[13] A. G. Ram, S. and A. Lincoln, “Fuzzy adaptive PI controller for single input single output non-linear system,”
ARPN Journal of Engineering and Applied, Sciences, vol. 7, no. 10, pp. 1273-1280, 2012.
[14] T. Mesbahi, T. Ghennam and E. M. Berkouk, “A Doubly Fed Induction Generator for wind stand-alone power
applications (Simulation and experimental validation),” Electrical Machines (ICEM), 2012 XXth International
Conference on, pp. 2028-2033, 2012.
[15] R. Sadaoui, "Analyse et commande de la machine asynchrone à double alimentation," Université du Québec
à Trois-Rivières Service de la bibliothèque, 2013.
[16] Shanzhi Li, Haoping Wang, Yang Tian, Abdel Aitouch, John Klein, “Direct power control of DFIG wind turbine systems
based on an intelligent proportional-integral sliding mode control,” ISA Transactions, vol. 64, pp. 431-439, 2016.
[17] K. Kerrouche, A. Mezouar and L. Boumedien, “A simple and efficient maximized power control of DFIG Variable
Speed Wind Turbine,” Proceedings of the 3rd International Conference on Systems and Control, 2013.
[18] A. Bouharchouche, E. M. Berkouk, T. Ghennam and B. Tabbache, “Modeling and control of a Doubly fed
induction generator with battery supercapacitor hybrid energy storage for wind power applications,”
2013 Fourth International Conference on Power Engineering, Energy and Electrical Drives, pp. 1392 -1397, 2013.
Int J Elec & Comp Eng ISSN: 2088-8708 
Control of the powerquality for a DFIG powered by multilevel inverters (Hachemi Hachemi)
4603
[19] B. Hamane, M. L. Doumbia, M. Bouhamida and M. Benghanem, “Direct active and reactive power control of
DFIG based WECS using PI and sliding mode controllers,” ECON 2014-40th Annual Conference of the IEEE
Industrial Electronics Society, pp. 2050-2055, 2014.
[20] A. Leredde, "Etude, Commande et Mise en Œuvre de Nouvelles Structures Multiniveaux," Thèse de doctorat de
l’Institut National Polytechnique de Toulouse (INP Toulouse), 2011.
[21] D. Floricau and G. Gateau "New Multilevel Converter for Industrial Medium-Voltage Applications,"
Journal Przeglad Elektrotechniczny (Electrical Review), pp. 26-30, 2009.
[22] F. Z. Peng, J. W. Mckeever and D. J. Adams, “A power line conditioner using cascade multilevel inverters for
distribution systems,” IEEE Transactions on Industry Applications, vol. 34, no. 6, pp. 1293-1298, 1998.
[23] A. Shamsul Rahimi A. Subki, and all, “Hardware implementation of single phase three-level cascaded h-bridge
multilevel inverter using sinusoidal pulse width modulation,” vol. 10, no. 2, 2019.
[24] J. S. Mariéthoz, "Etude formelle pour la synthèse de convertisseurs multiniveaux asymétriques: Topologies,
modulation et commande," Thèse de Doctorat, Ecole Polytechnique Fédérale de Lausanne, 2005.
[25] A. Mahrous, M. K. Metwaly and N. Elkalashy, “Performance investigation of multi-level inverter for DFIG during
grid autoreclosure operation,” International Journal of Power Electronics and Drive Systems (IJPEDS), vol. 10,
no. 1, pp. 454-462, 2019.

More Related Content

What's hot

Controlling Flicker Caused Due to Power Fluctuations by Using Individual Pitc...
Controlling Flicker Caused Due to Power Fluctuations by Using Individual Pitc...Controlling Flicker Caused Due to Power Fluctuations by Using Individual Pitc...
Controlling Flicker Caused Due to Power Fluctuations by Using Individual Pitc...IRJET Journal
 
Transient analysis and modeling of wind generator during power and grid volta...
Transient analysis and modeling of wind generator during power and grid volta...Transient analysis and modeling of wind generator during power and grid volta...
Transient analysis and modeling of wind generator during power and grid volta...IAEME Publication
 
Analysis of PMSG in Wind Integration using T Source Inverter with Simple Boos...
Analysis of PMSG in Wind Integration using T Source Inverter with Simple Boos...Analysis of PMSG in Wind Integration using T Source Inverter with Simple Boos...
Analysis of PMSG in Wind Integration using T Source Inverter with Simple Boos...IJTET Journal
 
Wind Energy Conversion System Using PMSG with T-Source Three Phase Matrix Con...
Wind Energy Conversion System Using PMSG with T-Source Three Phase Matrix Con...Wind Energy Conversion System Using PMSG with T-Source Three Phase Matrix Con...
Wind Energy Conversion System Using PMSG with T-Source Three Phase Matrix Con...IJTET Journal
 
Intelligent Control for Doubly Fed Induction Generator Connected to the Elect...
Intelligent Control for Doubly Fed Induction Generator Connected to the Elect...Intelligent Control for Doubly Fed Induction Generator Connected to the Elect...
Intelligent Control for Doubly Fed Induction Generator Connected to the Elect...IJPEDS-IAES
 
Power Control of Wind Turbine Based on Fuzzy Sliding-Mode Control
Power Control of Wind Turbine Based on Fuzzy Sliding-Mode ControlPower Control of Wind Turbine Based on Fuzzy Sliding-Mode Control
Power Control of Wind Turbine Based on Fuzzy Sliding-Mode ControlIJPEDS-IAES
 
Independent Control of Active and Reactive Powers of a DFIG Based Wind Energy...
Independent Control of Active and Reactive Powers of a DFIG Based Wind Energy...Independent Control of Active and Reactive Powers of a DFIG Based Wind Energy...
Independent Control of Active and Reactive Powers of a DFIG Based Wind Energy...IJERA Editor
 
Wind and solar integrated to smart grid using islanding operation
Wind and solar integrated to smart grid using islanding operationWind and solar integrated to smart grid using islanding operation
Wind and solar integrated to smart grid using islanding operationiaemedu
 
Dynamic responses improvement of grid connected wpgs using flc in high wind s...
Dynamic responses improvement of grid connected wpgs using flc in high wind s...Dynamic responses improvement of grid connected wpgs using flc in high wind s...
Dynamic responses improvement of grid connected wpgs using flc in high wind s...ijscmcj
 
Active and Reactive Power Control of a Doubly Fed Induction Generator
Active and Reactive Power Control of a Doubly Fed Induction GeneratorActive and Reactive Power Control of a Doubly Fed Induction Generator
Active and Reactive Power Control of a Doubly Fed Induction GeneratorIJPEDS-IAES
 
Modeling and performance analysis of a small scale direct driven pmsg based w...
Modeling and performance analysis of a small scale direct driven pmsg based w...Modeling and performance analysis of a small scale direct driven pmsg based w...
Modeling and performance analysis of a small scale direct driven pmsg based w...Alexander Decker
 
Modeling and Control of a Doubly-Fed Induction Generator for Wind Turbine-Gen...
Modeling and Control of a Doubly-Fed Induction Generator for Wind Turbine-Gen...Modeling and Control of a Doubly-Fed Induction Generator for Wind Turbine-Gen...
Modeling and Control of a Doubly-Fed Induction Generator for Wind Turbine-Gen...IJPEDS-IAES
 
Analysis of wind turbine driven permanent magnet synchronous generator under ...
Analysis of wind turbine driven permanent magnet synchronous generator under ...Analysis of wind turbine driven permanent magnet synchronous generator under ...
Analysis of wind turbine driven permanent magnet synchronous generator under ...Alexander Decker
 

What's hot (19)

Controlling Flicker Caused Due to Power Fluctuations by Using Individual Pitc...
Controlling Flicker Caused Due to Power Fluctuations by Using Individual Pitc...Controlling Flicker Caused Due to Power Fluctuations by Using Individual Pitc...
Controlling Flicker Caused Due to Power Fluctuations by Using Individual Pitc...
 
Performance enhancements of DFIG wind turbine using fuzzy-feedback linearizat...
Performance enhancements of DFIG wind turbine using fuzzy-feedback linearizat...Performance enhancements of DFIG wind turbine using fuzzy-feedback linearizat...
Performance enhancements of DFIG wind turbine using fuzzy-feedback linearizat...
 
Performance of a vector control for DFIG driven by wind turbine: real time si...
Performance of a vector control for DFIG driven by wind turbine: real time si...Performance of a vector control for DFIG driven by wind turbine: real time si...
Performance of a vector control for DFIG driven by wind turbine: real time si...
 
Transient analysis and modeling of wind generator during power and grid volta...
Transient analysis and modeling of wind generator during power and grid volta...Transient analysis and modeling of wind generator during power and grid volta...
Transient analysis and modeling of wind generator during power and grid volta...
 
Analysis of PMSG in Wind Integration using T Source Inverter with Simple Boos...
Analysis of PMSG in Wind Integration using T Source Inverter with Simple Boos...Analysis of PMSG in Wind Integration using T Source Inverter with Simple Boos...
Analysis of PMSG in Wind Integration using T Source Inverter with Simple Boos...
 
Wind Energy Conversion System Using PMSG with T-Source Three Phase Matrix Con...
Wind Energy Conversion System Using PMSG with T-Source Three Phase Matrix Con...Wind Energy Conversion System Using PMSG with T-Source Three Phase Matrix Con...
Wind Energy Conversion System Using PMSG with T-Source Three Phase Matrix Con...
 
Generator and grid side converter control for wind energy conversion system
Generator and grid side converter control for wind energy conversion systemGenerator and grid side converter control for wind energy conversion system
Generator and grid side converter control for wind energy conversion system
 
Intelligent Control for Doubly Fed Induction Generator Connected to the Elect...
Intelligent Control for Doubly Fed Induction Generator Connected to the Elect...Intelligent Control for Doubly Fed Induction Generator Connected to the Elect...
Intelligent Control for Doubly Fed Induction Generator Connected to the Elect...
 
Power Control of Wind Turbine Based on Fuzzy Sliding-Mode Control
Power Control of Wind Turbine Based on Fuzzy Sliding-Mode ControlPower Control of Wind Turbine Based on Fuzzy Sliding-Mode Control
Power Control of Wind Turbine Based on Fuzzy Sliding-Mode Control
 
Independent Control of Active and Reactive Powers of a DFIG Based Wind Energy...
Independent Control of Active and Reactive Powers of a DFIG Based Wind Energy...Independent Control of Active and Reactive Powers of a DFIG Based Wind Energy...
Independent Control of Active and Reactive Powers of a DFIG Based Wind Energy...
 
Wind and solar integrated to smart grid using islanding operation
Wind and solar integrated to smart grid using islanding operationWind and solar integrated to smart grid using islanding operation
Wind and solar integrated to smart grid using islanding operation
 
Dynamic responses improvement of grid connected wpgs using flc in high wind s...
Dynamic responses improvement of grid connected wpgs using flc in high wind s...Dynamic responses improvement of grid connected wpgs using flc in high wind s...
Dynamic responses improvement of grid connected wpgs using flc in high wind s...
 
Australia 1
Australia 1Australia 1
Australia 1
 
Improved Performance of DFIG-generators for Wind Turbines Variable-speed
Improved Performance of DFIG-generators for Wind Turbines Variable-speedImproved Performance of DFIG-generators for Wind Turbines Variable-speed
Improved Performance of DFIG-generators for Wind Turbines Variable-speed
 
Active and Reactive Power Control of a Doubly Fed Induction Generator
Active and Reactive Power Control of a Doubly Fed Induction GeneratorActive and Reactive Power Control of a Doubly Fed Induction Generator
Active and Reactive Power Control of a Doubly Fed Induction Generator
 
Modeling and performance analysis of a small scale direct driven pmsg based w...
Modeling and performance analysis of a small scale direct driven pmsg based w...Modeling and performance analysis of a small scale direct driven pmsg based w...
Modeling and performance analysis of a small scale direct driven pmsg based w...
 
Modeling and Control of a Doubly-Fed Induction Generator for Wind Turbine-Gen...
Modeling and Control of a Doubly-Fed Induction Generator for Wind Turbine-Gen...Modeling and Control of a Doubly-Fed Induction Generator for Wind Turbine-Gen...
Modeling and Control of a Doubly-Fed Induction Generator for Wind Turbine-Gen...
 
Analysis of wind turbine driven permanent magnet synchronous generator under ...
Analysis of wind turbine driven permanent magnet synchronous generator under ...Analysis of wind turbine driven permanent magnet synchronous generator under ...
Analysis of wind turbine driven permanent magnet synchronous generator under ...
 
Control of PMSG based variable speed wind energy conversion system connected ...
Control of PMSG based variable speed wind energy conversion system connected ...Control of PMSG based variable speed wind energy conversion system connected ...
Control of PMSG based variable speed wind energy conversion system connected ...
 

Similar to Control of the powerquality for a DFIG powered by multilevel inverters

Performance Analysis of DFIG Wind Turbine
Performance Analysis of DFIG Wind TurbinePerformance Analysis of DFIG Wind Turbine
Performance Analysis of DFIG Wind Turbinepaperpublications3
 
Performance Analysis of DFIG Wind Turbine
Performance Analysis of DFIG Wind TurbinePerformance Analysis of DFIG Wind Turbine
Performance Analysis of DFIG Wind Turbinepaperpublications3
 
Improved Control Strategy for Low Voltage Ride Through Capability of DFIG wit...
Improved Control Strategy for Low Voltage Ride Through Capability of DFIG wit...Improved Control Strategy for Low Voltage Ride Through Capability of DFIG wit...
Improved Control Strategy for Low Voltage Ride Through Capability of DFIG wit...ecij
 
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy Conversion
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy ConversionIndirect Control of a Doubly-Fed Induction Machine for Wind Energy Conversion
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy ConversionIAES-IJPEDS
 
11.modeling and performance analysis of a small scale direct driven pmsg base...
11.modeling and performance analysis of a small scale direct driven pmsg base...11.modeling and performance analysis of a small scale direct driven pmsg base...
11.modeling and performance analysis of a small scale direct driven pmsg base...Alexander Decker
 
DYNAMIC RESPONSES IMPROVEMENT OF GRID CONNECTED WPGS USING FLC IN HIGH WIND S...
DYNAMIC RESPONSES IMPROVEMENT OF GRID CONNECTED WPGS USING FLC IN HIGH WIND S...DYNAMIC RESPONSES IMPROVEMENT OF GRID CONNECTED WPGS USING FLC IN HIGH WIND S...
DYNAMIC RESPONSES IMPROVEMENT OF GRID CONNECTED WPGS USING FLC IN HIGH WIND S...ijscmcjournal
 
ENHANCED CONTROL OF DFIG IN WIND ENERGY CONVERSION SYSTEM
ENHANCED CONTROL OF DFIG IN WIND ENERGY CONVERSION SYSTEMENHANCED CONTROL OF DFIG IN WIND ENERGY CONVERSION SYSTEM
ENHANCED CONTROL OF DFIG IN WIND ENERGY CONVERSION SYSTEMIjorat1
 
Optimized servo-speed control of wind turbine coupled to doubly fed inductio...
Optimized servo-speed control of wind turbine coupled to  doubly fed inductio...Optimized servo-speed control of wind turbine coupled to  doubly fed inductio...
Optimized servo-speed control of wind turbine coupled to doubly fed inductio...IJECEIAES
 
Integration of a Wind Turbine Based Doubly Fed Induction Generator Using STAT...
Integration of a Wind Turbine Based Doubly Fed Induction Generator Using STAT...Integration of a Wind Turbine Based Doubly Fed Induction Generator Using STAT...
Integration of a Wind Turbine Based Doubly Fed Induction Generator Using STAT...IJERA Editor
 
Enhanced Crowbar Protection for Fault Ride through Capability of Wind Generat...
Enhanced Crowbar Protection for Fault Ride through Capability of Wind Generat...Enhanced Crowbar Protection for Fault Ride through Capability of Wind Generat...
Enhanced Crowbar Protection for Fault Ride through Capability of Wind Generat...IAES-IJPEDS
 
A Fuzzy Logic Control Strategy for Doubly Fed Induction Generator for Improve...
A Fuzzy Logic Control Strategy for Doubly Fed Induction Generator for Improve...A Fuzzy Logic Control Strategy for Doubly Fed Induction Generator for Improve...
A Fuzzy Logic Control Strategy for Doubly Fed Induction Generator for Improve...IAES-IJPEDS
 
Real time simulation of nonlinear generalized predictive control for wind ene...
Real time simulation of nonlinear generalized predictive control for wind ene...Real time simulation of nonlinear generalized predictive control for wind ene...
Real time simulation of nonlinear generalized predictive control for wind ene...ISA Interchange
 
Load Frequency Control of DFIG-isolated and Grid Connected Mode
Load Frequency Control of DFIG-isolated and Grid Connected ModeLoad Frequency Control of DFIG-isolated and Grid Connected Mode
Load Frequency Control of DFIG-isolated and Grid Connected ModeIJAPEJOURNAL
 
Modeling and simulation of dfig to grid connected wind power generation using...
Modeling and simulation of dfig to grid connected wind power generation using...Modeling and simulation of dfig to grid connected wind power generation using...
Modeling and simulation of dfig to grid connected wind power generation using...IAEME Publication
 

Similar to Control of the powerquality for a DFIG powered by multilevel inverters (20)

Evaluation of Synchronization and MPPT Algorithms in a DFIG Wind Turbine Cont...
Evaluation of Synchronization and MPPT Algorithms in a DFIG Wind Turbine Cont...Evaluation of Synchronization and MPPT Algorithms in a DFIG Wind Turbine Cont...
Evaluation of Synchronization and MPPT Algorithms in a DFIG Wind Turbine Cont...
 
G010234652
G010234652G010234652
G010234652
 
Performance Analysis of DFIG Wind Turbine
Performance Analysis of DFIG Wind TurbinePerformance Analysis of DFIG Wind Turbine
Performance Analysis of DFIG Wind Turbine
 
Performance Analysis of DFIG Wind Turbine
Performance Analysis of DFIG Wind TurbinePerformance Analysis of DFIG Wind Turbine
Performance Analysis of DFIG Wind Turbine
 
Maximum Power Point Tracking of Wind Turbine Conversion Chain Variable Speed ...
Maximum Power Point Tracking of Wind Turbine Conversion Chain Variable Speed ...Maximum Power Point Tracking of Wind Turbine Conversion Chain Variable Speed ...
Maximum Power Point Tracking of Wind Turbine Conversion Chain Variable Speed ...
 
Improved Control Strategy for Low Voltage Ride Through Capability of DFIG wit...
Improved Control Strategy for Low Voltage Ride Through Capability of DFIG wit...Improved Control Strategy for Low Voltage Ride Through Capability of DFIG wit...
Improved Control Strategy for Low Voltage Ride Through Capability of DFIG wit...
 
Nonlinear control of grid-connected wind energy conversion system without mec...
Nonlinear control of grid-connected wind energy conversion system without mec...Nonlinear control of grid-connected wind energy conversion system without mec...
Nonlinear control of grid-connected wind energy conversion system without mec...
 
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy Conversion
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy ConversionIndirect Control of a Doubly-Fed Induction Machine for Wind Energy Conversion
Indirect Control of a Doubly-Fed Induction Machine for Wind Energy Conversion
 
D03701028034
D03701028034D03701028034
D03701028034
 
11.modeling and performance analysis of a small scale direct driven pmsg base...
11.modeling and performance analysis of a small scale direct driven pmsg base...11.modeling and performance analysis of a small scale direct driven pmsg base...
11.modeling and performance analysis of a small scale direct driven pmsg base...
 
DYNAMIC RESPONSES IMPROVEMENT OF GRID CONNECTED WPGS USING FLC IN HIGH WIND S...
DYNAMIC RESPONSES IMPROVEMENT OF GRID CONNECTED WPGS USING FLC IN HIGH WIND S...DYNAMIC RESPONSES IMPROVEMENT OF GRID CONNECTED WPGS USING FLC IN HIGH WIND S...
DYNAMIC RESPONSES IMPROVEMENT OF GRID CONNECTED WPGS USING FLC IN HIGH WIND S...
 
Performance analysis and enhancement of direct power control of DFIG based wi...
Performance analysis and enhancement of direct power control of DFIG based wi...Performance analysis and enhancement of direct power control of DFIG based wi...
Performance analysis and enhancement of direct power control of DFIG based wi...
 
ENHANCED CONTROL OF DFIG IN WIND ENERGY CONVERSION SYSTEM
ENHANCED CONTROL OF DFIG IN WIND ENERGY CONVERSION SYSTEMENHANCED CONTROL OF DFIG IN WIND ENERGY CONVERSION SYSTEM
ENHANCED CONTROL OF DFIG IN WIND ENERGY CONVERSION SYSTEM
 
Optimized servo-speed control of wind turbine coupled to doubly fed inductio...
Optimized servo-speed control of wind turbine coupled to  doubly fed inductio...Optimized servo-speed control of wind turbine coupled to  doubly fed inductio...
Optimized servo-speed control of wind turbine coupled to doubly fed inductio...
 
Integration of a Wind Turbine Based Doubly Fed Induction Generator Using STAT...
Integration of a Wind Turbine Based Doubly Fed Induction Generator Using STAT...Integration of a Wind Turbine Based Doubly Fed Induction Generator Using STAT...
Integration of a Wind Turbine Based Doubly Fed Induction Generator Using STAT...
 
Enhanced Crowbar Protection for Fault Ride through Capability of Wind Generat...
Enhanced Crowbar Protection for Fault Ride through Capability of Wind Generat...Enhanced Crowbar Protection for Fault Ride through Capability of Wind Generat...
Enhanced Crowbar Protection for Fault Ride through Capability of Wind Generat...
 
A Fuzzy Logic Control Strategy for Doubly Fed Induction Generator for Improve...
A Fuzzy Logic Control Strategy for Doubly Fed Induction Generator for Improve...A Fuzzy Logic Control Strategy for Doubly Fed Induction Generator for Improve...
A Fuzzy Logic Control Strategy for Doubly Fed Induction Generator for Improve...
 
Real time simulation of nonlinear generalized predictive control for wind ene...
Real time simulation of nonlinear generalized predictive control for wind ene...Real time simulation of nonlinear generalized predictive control for wind ene...
Real time simulation of nonlinear generalized predictive control for wind ene...
 
Load Frequency Control of DFIG-isolated and Grid Connected Mode
Load Frequency Control of DFIG-isolated and Grid Connected ModeLoad Frequency Control of DFIG-isolated and Grid Connected Mode
Load Frequency Control of DFIG-isolated and Grid Connected Mode
 
Modeling and simulation of dfig to grid connected wind power generation using...
Modeling and simulation of dfig to grid connected wind power generation using...Modeling and simulation of dfig to grid connected wind power generation using...
Modeling and simulation of dfig to grid connected wind power generation using...
 

More from IJECEIAES

Cloud service ranking with an integration of k-means algorithm and decision-m...
Cloud service ranking with an integration of k-means algorithm and decision-m...Cloud service ranking with an integration of k-means algorithm and decision-m...
Cloud service ranking with an integration of k-means algorithm and decision-m...IJECEIAES
 
Prediction of the risk of developing heart disease using logistic regression
Prediction of the risk of developing heart disease using logistic regressionPrediction of the risk of developing heart disease using logistic regression
Prediction of the risk of developing heart disease using logistic regressionIJECEIAES
 
Predictive analysis of terrorist activities in Thailand's Southern provinces:...
Predictive analysis of terrorist activities in Thailand's Southern provinces:...Predictive analysis of terrorist activities in Thailand's Southern provinces:...
Predictive analysis of terrorist activities in Thailand's Southern provinces:...IJECEIAES
 
Optimal model of vehicular ad-hoc network assisted by unmanned aerial vehicl...
Optimal model of vehicular ad-hoc network assisted by  unmanned aerial vehicl...Optimal model of vehicular ad-hoc network assisted by  unmanned aerial vehicl...
Optimal model of vehicular ad-hoc network assisted by unmanned aerial vehicl...IJECEIAES
 
Improving cyberbullying detection through multi-level machine learning
Improving cyberbullying detection through multi-level machine learningImproving cyberbullying detection through multi-level machine learning
Improving cyberbullying detection through multi-level machine learningIJECEIAES
 
Comparison of time series temperature prediction with autoregressive integrat...
Comparison of time series temperature prediction with autoregressive integrat...Comparison of time series temperature prediction with autoregressive integrat...
Comparison of time series temperature prediction with autoregressive integrat...IJECEIAES
 
Strengthening data integrity in academic document recording with blockchain a...
Strengthening data integrity in academic document recording with blockchain a...Strengthening data integrity in academic document recording with blockchain a...
Strengthening data integrity in academic document recording with blockchain a...IJECEIAES
 
Design of storage benchmark kit framework for supporting the file storage ret...
Design of storage benchmark kit framework for supporting the file storage ret...Design of storage benchmark kit framework for supporting the file storage ret...
Design of storage benchmark kit framework for supporting the file storage ret...IJECEIAES
 
Detection of diseases in rice leaf using convolutional neural network with tr...
Detection of diseases in rice leaf using convolutional neural network with tr...Detection of diseases in rice leaf using convolutional neural network with tr...
Detection of diseases in rice leaf using convolutional neural network with tr...IJECEIAES
 
A systematic review of in-memory database over multi-tenancy
A systematic review of in-memory database over multi-tenancyA systematic review of in-memory database over multi-tenancy
A systematic review of in-memory database over multi-tenancyIJECEIAES
 
Agriculture crop yield prediction using inertia based cat swarm optimization
Agriculture crop yield prediction using inertia based cat swarm optimizationAgriculture crop yield prediction using inertia based cat swarm optimization
Agriculture crop yield prediction using inertia based cat swarm optimizationIJECEIAES
 
Three layer hybrid learning to improve intrusion detection system performance
Three layer hybrid learning to improve intrusion detection system performanceThree layer hybrid learning to improve intrusion detection system performance
Three layer hybrid learning to improve intrusion detection system performanceIJECEIAES
 
Non-binary codes approach on the performance of short-packet full-duplex tran...
Non-binary codes approach on the performance of short-packet full-duplex tran...Non-binary codes approach on the performance of short-packet full-duplex tran...
Non-binary codes approach on the performance of short-packet full-duplex tran...IJECEIAES
 
Improved design and performance of the global rectenna system for wireless po...
Improved design and performance of the global rectenna system for wireless po...Improved design and performance of the global rectenna system for wireless po...
Improved design and performance of the global rectenna system for wireless po...IJECEIAES
 
Advanced hybrid algorithms for precise multipath channel estimation in next-g...
Advanced hybrid algorithms for precise multipath channel estimation in next-g...Advanced hybrid algorithms for precise multipath channel estimation in next-g...
Advanced hybrid algorithms for precise multipath channel estimation in next-g...IJECEIAES
 
Performance analysis of 2D optical code division multiple access through unde...
Performance analysis of 2D optical code division multiple access through unde...Performance analysis of 2D optical code division multiple access through unde...
Performance analysis of 2D optical code division multiple access through unde...IJECEIAES
 
On performance analysis of non-orthogonal multiple access downlink for cellul...
On performance analysis of non-orthogonal multiple access downlink for cellul...On performance analysis of non-orthogonal multiple access downlink for cellul...
On performance analysis of non-orthogonal multiple access downlink for cellul...IJECEIAES
 
Phase delay through slot-line beam switching microstrip patch array antenna d...
Phase delay through slot-line beam switching microstrip patch array antenna d...Phase delay through slot-line beam switching microstrip patch array antenna d...
Phase delay through slot-line beam switching microstrip patch array antenna d...IJECEIAES
 
A simple feed orthogonal excitation X-band dual circular polarized microstrip...
A simple feed orthogonal excitation X-band dual circular polarized microstrip...A simple feed orthogonal excitation X-band dual circular polarized microstrip...
A simple feed orthogonal excitation X-band dual circular polarized microstrip...IJECEIAES
 
A taxonomy on power optimization techniques for fifthgeneration heterogenous ...
A taxonomy on power optimization techniques for fifthgeneration heterogenous ...A taxonomy on power optimization techniques for fifthgeneration heterogenous ...
A taxonomy on power optimization techniques for fifthgeneration heterogenous ...IJECEIAES
 

More from IJECEIAES (20)

Cloud service ranking with an integration of k-means algorithm and decision-m...
Cloud service ranking with an integration of k-means algorithm and decision-m...Cloud service ranking with an integration of k-means algorithm and decision-m...
Cloud service ranking with an integration of k-means algorithm and decision-m...
 
Prediction of the risk of developing heart disease using logistic regression
Prediction of the risk of developing heart disease using logistic regressionPrediction of the risk of developing heart disease using logistic regression
Prediction of the risk of developing heart disease using logistic regression
 
Predictive analysis of terrorist activities in Thailand's Southern provinces:...
Predictive analysis of terrorist activities in Thailand's Southern provinces:...Predictive analysis of terrorist activities in Thailand's Southern provinces:...
Predictive analysis of terrorist activities in Thailand's Southern provinces:...
 
Optimal model of vehicular ad-hoc network assisted by unmanned aerial vehicl...
Optimal model of vehicular ad-hoc network assisted by  unmanned aerial vehicl...Optimal model of vehicular ad-hoc network assisted by  unmanned aerial vehicl...
Optimal model of vehicular ad-hoc network assisted by unmanned aerial vehicl...
 
Improving cyberbullying detection through multi-level machine learning
Improving cyberbullying detection through multi-level machine learningImproving cyberbullying detection through multi-level machine learning
Improving cyberbullying detection through multi-level machine learning
 
Comparison of time series temperature prediction with autoregressive integrat...
Comparison of time series temperature prediction with autoregressive integrat...Comparison of time series temperature prediction with autoregressive integrat...
Comparison of time series temperature prediction with autoregressive integrat...
 
Strengthening data integrity in academic document recording with blockchain a...
Strengthening data integrity in academic document recording with blockchain a...Strengthening data integrity in academic document recording with blockchain a...
Strengthening data integrity in academic document recording with blockchain a...
 
Design of storage benchmark kit framework for supporting the file storage ret...
Design of storage benchmark kit framework for supporting the file storage ret...Design of storage benchmark kit framework for supporting the file storage ret...
Design of storage benchmark kit framework for supporting the file storage ret...
 
Detection of diseases in rice leaf using convolutional neural network with tr...
Detection of diseases in rice leaf using convolutional neural network with tr...Detection of diseases in rice leaf using convolutional neural network with tr...
Detection of diseases in rice leaf using convolutional neural network with tr...
 
A systematic review of in-memory database over multi-tenancy
A systematic review of in-memory database over multi-tenancyA systematic review of in-memory database over multi-tenancy
A systematic review of in-memory database over multi-tenancy
 
Agriculture crop yield prediction using inertia based cat swarm optimization
Agriculture crop yield prediction using inertia based cat swarm optimizationAgriculture crop yield prediction using inertia based cat swarm optimization
Agriculture crop yield prediction using inertia based cat swarm optimization
 
Three layer hybrid learning to improve intrusion detection system performance
Three layer hybrid learning to improve intrusion detection system performanceThree layer hybrid learning to improve intrusion detection system performance
Three layer hybrid learning to improve intrusion detection system performance
 
Non-binary codes approach on the performance of short-packet full-duplex tran...
Non-binary codes approach on the performance of short-packet full-duplex tran...Non-binary codes approach on the performance of short-packet full-duplex tran...
Non-binary codes approach on the performance of short-packet full-duplex tran...
 
Improved design and performance of the global rectenna system for wireless po...
Improved design and performance of the global rectenna system for wireless po...Improved design and performance of the global rectenna system for wireless po...
Improved design and performance of the global rectenna system for wireless po...
 
Advanced hybrid algorithms for precise multipath channel estimation in next-g...
Advanced hybrid algorithms for precise multipath channel estimation in next-g...Advanced hybrid algorithms for precise multipath channel estimation in next-g...
Advanced hybrid algorithms for precise multipath channel estimation in next-g...
 
Performance analysis of 2D optical code division multiple access through unde...
Performance analysis of 2D optical code division multiple access through unde...Performance analysis of 2D optical code division multiple access through unde...
Performance analysis of 2D optical code division multiple access through unde...
 
On performance analysis of non-orthogonal multiple access downlink for cellul...
On performance analysis of non-orthogonal multiple access downlink for cellul...On performance analysis of non-orthogonal multiple access downlink for cellul...
On performance analysis of non-orthogonal multiple access downlink for cellul...
 
Phase delay through slot-line beam switching microstrip patch array antenna d...
Phase delay through slot-line beam switching microstrip patch array antenna d...Phase delay through slot-line beam switching microstrip patch array antenna d...
Phase delay through slot-line beam switching microstrip patch array antenna d...
 
A simple feed orthogonal excitation X-band dual circular polarized microstrip...
A simple feed orthogonal excitation X-band dual circular polarized microstrip...A simple feed orthogonal excitation X-band dual circular polarized microstrip...
A simple feed orthogonal excitation X-band dual circular polarized microstrip...
 
A taxonomy on power optimization techniques for fifthgeneration heterogenous ...
A taxonomy on power optimization techniques for fifthgeneration heterogenous ...A taxonomy on power optimization techniques for fifthgeneration heterogenous ...
A taxonomy on power optimization techniques for fifthgeneration heterogenous ...
 

Recently uploaded

Internship report on mechanical engineering
Internship report on mechanical engineeringInternship report on mechanical engineering
Internship report on mechanical engineeringmalavadedarshan25
 
IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024Mark Billinghurst
 
HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2RajaP95
 
complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...asadnawaz62
 
Electronically Controlled suspensions system .pdf
Electronically Controlled suspensions system .pdfElectronically Controlled suspensions system .pdf
Electronically Controlled suspensions system .pdfme23b1001
 
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130Suhani Kapoor
 
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube ExchangerStudy on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube ExchangerAnamika Sarkar
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024hassan khalil
 
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxMicroscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxpurnimasatapathy1234
 
GDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSCAESB
 
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfCCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfAsst.prof M.Gokilavani
 
Current Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCLCurrent Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCLDeelipZope
 
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptxDecoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptxJoão Esperancinha
 
Sachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective IntroductionSachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective IntroductionDr.Costas Sachpazis
 
Churning of Butter, Factors affecting .
Churning of Butter, Factors affecting  .Churning of Butter, Factors affecting  .
Churning of Butter, Factors affecting .Satyam Kumar
 
Introduction-To-Agricultural-Surveillance-Rover.pptx
Introduction-To-Agricultural-Surveillance-Rover.pptxIntroduction-To-Agricultural-Surveillance-Rover.pptx
Introduction-To-Agricultural-Surveillance-Rover.pptxk795866
 
chaitra-1.pptx fake news detection using machine learning
chaitra-1.pptx  fake news detection using machine learningchaitra-1.pptx  fake news detection using machine learning
chaitra-1.pptx fake news detection using machine learningmisbanausheenparvam
 

Recently uploaded (20)

Internship report on mechanical engineering
Internship report on mechanical engineeringInternship report on mechanical engineering
Internship report on mechanical engineering
 
IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024IVE Industry Focused Event - Defence Sector 2024
IVE Industry Focused Event - Defence Sector 2024
 
HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2HARMONY IN THE HUMAN BEING - Unit-II UHV-2
HARMONY IN THE HUMAN BEING - Unit-II UHV-2
 
complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...complete construction, environmental and economics information of biomass com...
complete construction, environmental and economics information of biomass com...
 
Electronically Controlled suspensions system .pdf
Electronically Controlled suspensions system .pdfElectronically Controlled suspensions system .pdf
Electronically Controlled suspensions system .pdf
 
Design and analysis of solar grass cutter.pdf
Design and analysis of solar grass cutter.pdfDesign and analysis of solar grass cutter.pdf
Design and analysis of solar grass cutter.pdf
 
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
VIP Call Girls Service Hitech City Hyderabad Call +91-8250192130
 
POWER SYSTEMS-1 Complete notes examples
POWER SYSTEMS-1 Complete notes  examplesPOWER SYSTEMS-1 Complete notes  examples
POWER SYSTEMS-1 Complete notes examples
 
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube ExchangerStudy on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
Study on Air-Water & Water-Water Heat Exchange in a Finned Tube Exchanger
 
Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024Architect Hassan Khalil Portfolio for 2024
Architect Hassan Khalil Portfolio for 2024
 
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCRCall Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
Call Us -/9953056974- Call Girls In Vikaspuri-/- Delhi NCR
 
Microscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptxMicroscopic Analysis of Ceramic Materials.pptx
Microscopic Analysis of Ceramic Materials.pptx
 
GDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentationGDSC ASEB Gen AI study jams presentation
GDSC ASEB Gen AI study jams presentation
 
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdfCCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
CCS355 Neural Network & Deep Learning Unit II Notes with Question bank .pdf
 
Current Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCLCurrent Transformer Drawing and GTP for MSETCL
Current Transformer Drawing and GTP for MSETCL
 
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptxDecoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
Decoding Kotlin - Your guide to solving the mysterious in Kotlin.pptx
 
Sachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective IntroductionSachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
Sachpazis Costas: Geotechnical Engineering: A student's Perspective Introduction
 
Churning of Butter, Factors affecting .
Churning of Butter, Factors affecting  .Churning of Butter, Factors affecting  .
Churning of Butter, Factors affecting .
 
Introduction-To-Agricultural-Surveillance-Rover.pptx
Introduction-To-Agricultural-Surveillance-Rover.pptxIntroduction-To-Agricultural-Surveillance-Rover.pptx
Introduction-To-Agricultural-Surveillance-Rover.pptx
 
chaitra-1.pptx fake news detection using machine learning
chaitra-1.pptx  fake news detection using machine learningchaitra-1.pptx  fake news detection using machine learning
chaitra-1.pptx fake news detection using machine learning
 

Control of the powerquality for a DFIG powered by multilevel inverters

  • 1. International Journal of Electrical and Computer Engineering (IJECE) Vol. 10, No. 5, October 2020, pp. 4592~4603 ISSN: 2088-8708, DOI: 10.11591/ijece.v10i5.pp4592-4603  4592 Journal homepage: http://ijece.iaescore.com/index.php/IJECE Control of the powerquality for a DFIG powered by multilevel inverters Hachemi Hachemi1 , Ahmed Allali2 , Belkacem Belkacem3 1,2 University of Science and Technology of Oran Mohamed Boudiaf, LDDEE, Laboratoire de Développement durable de l’Energie Electrique, Algeria 3 Institut de Maintenance et de Sécurité Industrielle, Université d'Oran, Algeria Article Info ABSTRACT Article history: Received Aug 23, 2019 Revised Feb 24, 2020 Accepted Mar 25, 2020 This paper treats the modeling, and the control of a wind power system based on a doubly fed induction generator DFIG, the stator is directly connected to the grid, while the rotor is powered by multilevel inverters. In order to get a decoupled system of controlfor an independently transits of active and reactive power, a vector control method based on stator flux orientation SFOC is considered: Direct vector control based on PI controllers. Cascaded H-bridge CHBI multilevel inverters are used in the rotor circuit to study its effect on supply power quality. All simulation models are built in MATLAB/Simulink software. Results and waveforms clearly show the effectiveness of vector control strategy. Finally, performances of the system will tested and compared for each levels of inverter. Keywords: Doubly fed induction generator DFIG H-BRIDGE Multi-levels inverters PI controllers Stator flux orientation SFOC Copyright © 2020Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Hachemi Hachemi, University of Science and Technology of Oran Mohamed Boudiaf, El Mnaouar، BP 1505, Bir El Djir 31000, Algeria. Email: h.hachemi@yahoo.fr 1. INTRODUCTION The generation of electricity that comes from nuclear power and fossil natural resources, pose continued problems whose importance is growing over the years; as the nuclear untreatable waste and disappearance expected in the 21st century, for major source of fossil energy. Environmental constraints on atmospheric emissions of greenhouse gases has led researchers a way of generating clean, economic and sustainable electricity [1]. Various studies carried out in this context have shown that far-reaching changes are essential in energy strategies to ensure better management of the production, transformation, distribution and use of energy [2]. From this perspective, controlling energy in a broad sense constitutes an important challenge in the development of sustainable energy. Energy efficiency and renewable energies are therefore interesting avenues for more sustainable energy development and are considered to be among the most environmentally friendly components, particularly in the fight against climate change [3]. Thus, the modes of production based on the transformation of renewable energy (solar, wind ...) are expected to be increasingly used in the context of sustainable development, and thanks to recent developments of power electronics and micro processing. The production area of variable speed wind energy has in recent years a boom. A great attention is paid today to doubly fed machine DFIM for various applications suchas generator for wind energy. This interest is mainly due to the fact of accessibility for its rotor and therefore the possibility of supplying a converter as well as the stat side gold on the rotor side. Power-electronic converters have been developed for integrating wind power with the electric grid. The use of power-electronic converters allows for variable-speed operation of the wind turbine, and enhanced
  • 2. Int J Elec & Comp Eng ISSN: 2088-8708  Control of the powerquality for a DFIG powered by multilevel inverters (Hachemi Hachemi) 4593 power extraction. In variable-speed operation, a control method designed to extract maximum power from the wind turbine and provide constant grid voltage and frequency is required [4]. In this paper, a variable-speed wind turbine is considered with DFIG and a multilevel cascaded H-Bridge Inverter CHBI. Multilevel inverters are AC-DC-AC converters, well suited for medium and high-power applications [5] due to their ability to meet the increasing demand of power ratings and power quality associated with reduced harmonic distortion, lower electromagnetic interference, and higher efficiencies when compared with the conventional two or three level topology [6]. The increasing number of voltage levels lead to the production of high-power quality waveforms [7], causing the total harmonic distortion THD to be lower. Multilevel converters are a good tradeoff solution between performance and cost in wind high-power systems [8]. The most typical connection diagram of this DFIG is to connect stator directly to the grid, while the rotor is supplied through a controlled power converter. This solution is more attractive for all applications where speed variations are limited around the synchronous speed because this area operating presents low slip, and therefore the converter associated with the rotor has to be treated only for a fraction of 20 to 30 % of the nominal conversion system power; this means that the losses in the converter are reduced (power supplied to the rotor is low) and the cost thereof is reduced. That is why we find this machine in high power variable speed and constant frequency for production systems. A second reason is the possibility of controlling the active and reactive power in the stator via the control of the power converter [9]. Further variable speed wind turbine is modeled to find a relationship between the electromagnetic torque and the mechanical wind speed. After describing mechanical and electrical model of the DFIG in section 3, a vector control method based on stator flux orientation SFOC is considered: direct vector control based on PI controllers. The sinus pulse wave modulation (SPWM) control strategyfor multilevel invertersis given in section 4. Finally, simulation and results are presented; performances of the system are then evaluated. 2. WIND TURBINE MODEL Mechanical power available on the shaft of a wind turbine is expressed by [10]: 𝑃𝑣 = 1 2 𝜌𝑆𝑣𝑣 3 = 1 2 𝜌𝜋𝑅2 𝑣𝑣 3 (1) where: ρ :air density (1.25 Kg/m3 ); R : Blade length in meters; Vv : wind velocity in m/s. The aerodynamic power extracted from wind turbine canbe calculated as: 𝑃𝑇𝑢𝑟𝑏 = 𝐶 𝑝 𝑃𝑣 = 1 2 𝜌𝑆𝑣𝑣 3 = 1 2 𝜌𝜋𝑅2 𝑣𝑣 3 . 𝐶 𝑝(𝜆, 𝛽) (2) 𝜆 = Ω 𝑇𝑢𝑟𝑏. 𝑅 𝑣𝑣 (3) where: Cp : Power coefficient; β : Pitch angle (deg); λ :Tip speed ratio; ΩTurb : Turbine speed (rd/s). No wind turbine could convert more than 59 % of the kinetic energy of the wind into mechanical energy turning a rotor [11]. This is known as the Betz limit, and it is the theoretical maximum coefficient of power for any wind turbine: Cpmax= 16/27 ≈ 0.593. The multiplier is mathematically modeled by the following equations: { 𝑇 𝑚 = 𝑇𝑇𝑢𝑟𝑏 𝐺 Ω 𝑇𝑢𝑟𝑏 = Ω 𝑚 𝐺 𝐽 𝑇 = 𝐽 𝑇𝑢𝑟𝑏 𝐺2 + 𝐽 𝑔 𝑇𝑇𝑢𝑟𝑏 = 𝑃 𝑇𝑢𝑟𝑏 Ω 𝑇𝑢𝑟𝑏 (4)
  • 3.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 10, No. 5, October 2020 : 4592 - 4603 4594 where: Ωturb, Ωm: Turbine speed respectively before and afterthe multiplier;Tturb: aerodynamic torque; Tm: torque after the multiplier; G: Gear ratio; Jg: Generator inertia; JT: Total inertia; JTurb: Turbine inertia. The fundamental equation of dynamics to determine the evolution of the mechanical speed from the total mechanical torque 𝑇 𝑚𝑒𝑐 applied to the rotor: 𝐽 𝑇 𝑑Ω 𝑚𝑒𝑐 𝑑𝑡 = 𝑇 𝑚𝑒𝑐 = 𝑇 𝑚 − 𝑇𝑒𝑚 − 𝐶𝑓Ω 𝑚𝑒𝑐 (5) where: Tem : Electromagnetic torque; Cf: Viscous friction coefficient. 2.1. Modeling of the DFIG, Park’s model The d-q axis representation of DFIG is used for modeling, considering flux as variable based on Park's model. All rotor quantities are referred to stator side. The DFIG model represented by voltage (6). The stator and rotor side flux linkage equations are given as [12-14]: { 𝑉𝑠𝑑 = 𝑅𝑠 𝐼𝑠𝑑 + 𝑑Ф 𝑠𝑑 𝑑𝑡 − 𝜔𝑠Ф 𝑠𝑞 𝑉𝑠𝑞 = 𝑅𝑠 𝐼𝑠𝑞 + 𝑑Ф 𝑠𝑞 𝑑𝑡 + 𝜔𝑠Ф 𝑠𝑑 𝑉𝑟𝑑 = 𝑅 𝑟 𝐼𝑟𝑑 + 𝑑Ф 𝑟𝑑 𝑑𝑡 − (𝜔𝑠 − 𝜔𝑟)Ф 𝑟𝑞 𝑉𝑟𝑞 = 𝑅 𝑟 𝐼𝑟𝑞 + 𝑑Ф 𝑟𝑞 𝑑𝑡 + (𝜔𝑠 − 𝜔𝑟)Ф 𝑟𝑑 (6) The stator and rotor flux can be expressed as: { Ф 𝑠𝑑 = 𝐿 𝑠 𝐼𝑠𝑑 + 𝐿 𝑚 𝐼𝑟𝑑 Ф 𝑠𝑞 = 𝐿 𝑠 𝐼𝑠𝑞 + 𝐿 𝑚 𝐼𝑟𝑞 Ф 𝑟𝑑 = 𝐿 𝑟 𝐼𝑟𝑑 + 𝐿 𝑚 𝐼𝑠𝑑 Ф 𝑟𝑞 = 𝐿 𝑟 𝐼𝑟𝑞 + 𝐿 𝑚 𝐼𝑠𝑞 (7) Electromagnetic torque is also expressed in terms of currents and flux: 𝐶𝑒𝑚 = 𝑝 𝐿 𝑚 𝐿 𝑠 (Ф 𝑠𝑑 𝐼𝑞𝑟 − Ф 𝑠𝑞 𝐼 𝑑𝑟) (8) where: Rs, Rr, are respectively the stator and rotor resistances; Ls, Lr: inductances of the stator and rotor windings; Lmis the mutual inductance; Vds, Vqs, Vdret Vqr: Direct and quadrate components of the space phasors of the stator and rotor voltages; Ids, Iqs, Idr, Iqr: Direct and quadrate components of the space phasors of the stator and rotor currents; φds, φqs, φdret φqr: Direct and quadrate components of the space phasors of the stator and rotor flux respectively; ɷs: Rotational speed of the synchronous reference frame; ɷr: Rotor speed, p: Number of pair poles. Active and reactive powers at the stator (Ps, Qs), and the rotor (Pr, Qr) are defined as [15-16]: { 𝑃𝑠 = 𝑉𝑠𝑑 𝐼𝑠𝑑 + 𝑉𝑠𝑞 𝐼𝑠𝑞 𝑄𝑠 = 𝑉𝑠𝑞 𝐼𝑠𝑑 − 𝑉𝑠𝑑 𝐼𝑠𝑞 𝑃𝑟 = 𝑉𝑑𝑟 𝐼 𝑑𝑟 + 𝑉𝑞𝑟 𝐼𝑞𝑟 𝑄 𝑟 = 𝑉𝑞𝑟 𝐼 𝑑𝑟 − 𝑉𝑑𝑟 𝐼𝑞𝑟 (9) 2.2. Control strategy of the DFIG Once the DFIG is connected to an existing grid, the transit of active and reactive powers must be controlled separately. To obtain a decoupled powers control of DFIG, the method based on field orientation
  • 4. Int J Elec & Comp Eng ISSN: 2088-8708  Control of the powerquality for a DFIG powered by multilevel inverters (Hachemi Hachemi) 4595 can be regarded as the efficient one. The principle of this method consists to orientate the stator flux in such a way that the stator flux vector points into d-axis direction; this approach is realized by setting the quadratic component of the stator flux to the null value, detailed representation is show in Figure 1 [17, 18]. Figure 1. Stator flux orientation The stator fluxes of (6) will be simplified as follows: { Ф 𝑠𝑑 = 𝐿 𝑠 𝐼𝑠𝑑 + 𝐿 𝑚 𝐼𝑟𝑑 = Ф 𝑠 Ф 𝑠𝑞 = 𝐿 𝑠 𝐼𝑠𝑞 + 𝐿 𝑚 𝐼𝑟𝑞 = 0 (10) The stator resistance will be neglected, for medium power machines used in WECS; the stator voltage vector is consequently in quadrate advance in comparison with the stator flux vector. { 𝑉𝑠𝑑 = 0 𝑉𝑠𝑞 = 𝜔𝑠Ф 𝑠 = 𝑉𝑠 (11) Using (10), we can establish the connection between the rotor and stator currents: { 𝐼𝑠𝑑 = − 𝐿 𝑚 𝐿 𝑠 𝐼𝑟𝑑 + ∅ 𝑠 𝐿 𝑠 𝐼𝑠𝑞 = − 𝐿 𝑚 𝐿 𝑠 𝐼𝑟𝑞 (12) Using (11) and (12), the stator active and reactive power and rotor voltage are given by: { 𝑃𝑠 = 𝑉𝑠 𝐼𝑠𝑞 = −𝑉𝑠 𝐿 𝑚 𝐿 𝑠 𝐼𝑟𝑞 𝑄𝑠 = 𝑉𝑠 𝐼𝑠𝑑 = −𝑉𝑠 𝐿 𝑚 𝐿 𝑠 𝐼𝑟𝑑 + 𝑉𝑠 2 𝐿 𝑠 𝑤𝑠 (13) For controlling the DFIG, established expressions showing the relationship between current and rotor voltages will be applied to it. { 𝑉𝑟𝑑 = 𝑅 𝑟 𝐼𝑟𝑑 + (𝐿 𝑟 − 𝐿 𝑚 2 𝐿 𝑠 ) 𝑑𝐼𝑟𝑑 𝑑𝑡 − 𝑔𝑤𝑠 (𝐿 𝑟 − 𝐿 𝑚 2 𝐿 𝑠 ) 𝐼𝑟𝑞 𝑉𝑟𝑞 = 𝑅 𝑟 𝐼𝑟𝑞 + (𝐿 𝑟 − 𝐿 𝑚 2 𝐿 𝑠 ) 𝑑𝐼𝑟𝑞 𝑑𝑡 + 𝑔𝑤𝑠 (𝐿 𝑟 − 𝐿 𝑚 2 𝐿 𝑠 ) 𝐼𝑟𝑑 + 𝑔 𝐿 𝑚 𝑉𝑠 𝐿 𝑠 (14) By considering σ as the cross coupling term, (14) can be rewrite as:
  • 5.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 10, No. 5, October 2020 : 4592 - 4603 4596 { 𝑉𝑟𝑑 = 𝑅 𝑟 𝐼𝑟𝑑 + 𝐿 𝑟 𝜎 𝑑𝐼𝑟𝑑 𝑑𝑡 − 𝑔𝜎𝑤 𝜎 𝐿 𝑟 𝐼𝑟𝑞 𝑉𝑟𝑞 = 𝑅 𝑟 𝐼𝑟𝑞 + 𝐿 𝑟 𝜎 𝑑𝐼𝑟𝑞 𝑑𝑡 + 𝑔𝜎𝑤𝑠 𝐿 𝑟 𝐼𝑟𝑑 + 𝑔 𝐿 𝑚 𝑉𝑠 𝐿 𝑠 𝜎 = 1 − 𝐿 𝑚 2 𝐿 𝑟 𝐿 𝑠 (15) The block diagram representing the internal model of the system is shown in Figure 2. Field oriented control of the DFIG can then be applied with the active and reactive power considered as variables to be controlled. The input blocks relating 𝑉𝑟𝑑 to 𝑉𝑟𝑞 represent the simplified rotor converter model. Knowing (13) and (15), it is then possible to synthesize the regulators [19]. Figure 2. Block diagram of the system to regulate In order to improve the last command, we will introduce an additional control loop at the currents to eliminate the static error while preserving the dynamics of the system, then, two additional PI controllers are added to regulate the active and reactive powers. So, we need sixcurrents sensors, three to control the rotor currents (iar, ibr and icr) and three associated with three voltage sensors to measure the stator powers Ps and Qs. The active power PI controller regulates the rotor current reference iqr from the error between the active power measured Ps and the desired active power Pref. Furthermore, the reactive power PI controller regulates the rotor current reference idr from the error between the reactive power measured Qs and the desired reactive power Qref. The closed loop control of active and reactive powers is presented in Figure 3: Figure 3. Closed loop control of active and reactive powers
  • 6. Int J Elec & Comp Eng ISSN: 2088-8708  Control of the powerquality for a DFIG powered by multilevel inverters (Hachemi Hachemi) 4597 3. CASCADED H-BRIDGE INVERTER CHBI THEORY Several multilevel topologies used for grid connection have been proposed in [20, 21]. Multilevel converter structures have three major classifications; neutral point clamped (NPCor diode clamped), flying capacitor (FC or capacitor clamped), and cascaded H-bridge inverter CHBI, with isolated DC source Figure 4. Compared with the latter two, the multilevel CHBI has many distinct advantages:  Switch devices required are less under the same switching frequency and level number.  The harmonic content is lower in the output voltage for a given switching frequency.  Modularized circuit layout and packaging is possible because each cell has the same structure, and there are no extra clamping diodes as in the case of diode clamped topology, or voltage balancing capacitors as in the case of the capacitor clamped topology [22]. . Vdc S1 S2 S3 S4 Vout + - Figure 4. Single phase H-bridge inverter 3.1. Theory of cascaded H-Bridge multilevel inverter The cascaded H bridge multilevel inverter circuit consists of individual H-bridge cells which are fed by individual dc supply. Each H-bridge cell contains four switches. In this topology, IGBT is used as switch because of its low switching losses. Each H-bridge generates three different output voltages, +Vdc, 0 and –Vdc using various combinations of switching with the four switches [22, 23]. The switching tableof the three level CHB is given in Table 1. Table 1. Switching table for 3-level CHB inverter S1 S2 S3 S4 Output Voltage 1 0 0 1 Vdc 0 1 1 0 -Vdc 0 0 0 0 0 Cascaded multilevel inverter is the cascade connection of N H-bridge inverters. Each H-bridge inverter has the same configuration as a typical single-phase full-bridge inverter. In this topology the number of phase voltage levels at the converter terminals is 2N+1, where N is the number ofcells or dc link voltages. The IGBT switches have low block voltage and high switching frequency. Consider the seven level inverter; it requires 12 IGBT switches and three dc sources. The power circuit ofinverter is shown in Figure 5. By closing the appropriate switches, each H-bridge inverter can produce three different voltages: +Vdc, 0 and -Vdc. It is also possible to modularize circuit layout and packaging because each level has the same structure, and there are no extra clamping diodes or voltage balancing capacitors. The number of switches is reduced using the newtopology [24, 25].
  • 7.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 10, No. 5, October 2020 : 4592 - 4603 4598 S1 S2 S3 S4 Vdc + - S1 S2 S3 S4 Vdc + - S1 S2 S3 S4 Vdc + - S1 S2 S3 S4 Vdc + - S1 S2 S3 S4 Vdc + - S1 S2 S3 S4 Vdc + - S1 S2 S3 S4 Vdc + - S1 S2 S3 S4 Vdc + - S1 S2 S3 S4 Vdc + - Vc Vb Va Vc N Figure 5. Cascaded H-bridge 7-level inverter 4. SIMULATION RESULTS The system based on a variable speed wind turbine with a doubly fed induction generator DFIG. The simulation is carried out using the MatLab/Simulink software. The DFIG is connected directly to the network through the stator, and controlled by its rotor through a three level CHBI. Simulation results are presented in Figure 6 to Figure 14. They show performances of our system. Figure 6. Wind speed Figure 7. Electromagnetic torque Figure 8. Isd current Figure 9. Isq current
  • 8. Int J Elec & Comp Eng ISSN: 2088-8708  Control of the powerquality for a DFIG powered by multilevel inverters (Hachemi Hachemi) 4599 Figure 10. Ird current Figure 11. Irq current Figure 12. Active power Figure 13. Reactive power Figure 14. Stator currents
  • 9.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 10, No. 5, October 2020 : 4592 - 4603 4600 To control the power exchanged between the stator and the network, one uses the vector control with direct stator flux shown in Figure 15. Simulation results are obtained under various stator active and reactive power steps. The both control strategies with 5 levels CHBI, and 13 levels CHBI separately, are simulated, tested and compared in terms of power reference tracking. We initial simulation at first, with an active power step Psref= -5KW. At time t = 0.5s to 2s an application of the echelon of active power Psref = - 10KW, and after time t = 2s to 3s we return at step Psref = -5KW. The reactive power step is changed from Qsref = -1 to -4 KVAR at the instant t = 1 s and again from -4 to -1 KVAR at the instant t = 1.5 s; a last variation of the reactive power step at the instant t = 2.5 is applied from Qsref =.-1 KVAR. Simulation results are shown in Figure 16 to Figure 19. It can be seen that multilevel CHBI can control the active and reactive powers of DFIG with a very fast time response. However, the ripples in powers are more significant from control with 5 levels CHBI. To observe the effectiveness of the proposed control strategy, we increased levels of CHBI gradually up to 13 levels. In order to produce quality energy, it is apparent that the control with 13 levels CHBI, harmonics are almost eliminated. Thus, we estimate that these powers injected into the network will have no significant impact. Figure 15. Block diagram of DFIG power control Si tu peux le changer sous forme de bloc c’est mieux ZOOM Figure 16. Reel and reference active power with 5 levels CHBI
  • 10. Int J Elec & Comp Eng ISSN: 2088-8708  Control of the powerquality for a DFIG powered by multilevel inverters (Hachemi Hachemi) 4601 ZOOM Figure 17. Reel and reference reactive power with 5 levels CHBI ZOOM Figure 18. Reel and reference active power with 13 levels CHBI ZOOM Figure 19. Reel and reference reactive power with 13 levels CHBI
  • 11.  ISSN: 2088-8708 Int J Elec & Comp Eng, Vol. 10, No. 5, October 2020 : 4592 - 4603 4602 5. CONCLUSION The aim of this work is to model and control the doubly fed induction generator DFIG based wind energy conversion system powered by multitier inverters with cascaded H-Bridge structure, to increase the power transferred to the network. In this context, a control of the powers of the wind system was carried out. For adjusting the energy quality supplied by the DFIG, vector control by orientation of the stator flow that makes the system similar to that of the DC machine was applied. To be able to directly control the active and reactive DFIG power through multi-level inverters; our strategy was to apply vector control, with a configuration of H. BRIDGE inverters; and then increase their levels, in order to improve the quality of the energy delivered by the DFIG; we thus determined the most efficient system for the different configurations proposed.The global model of our system is at first established. Furthermore, a vector control strategy of the DFIG to perform power reference tracking to machine parameters variation. The structure using the DFIG has a best advantage in terms of high power output, in variable speed operation, while reducing the size of the static converters. Despite this, the use of multilevel converters seems necessary especially for high power wind turbines. These converters increase the power transmitted to the power grid by reducing the current ripple and the harmonic content of the output voltages. This increase is done by means of the voltage, which makes it possible to reduce the losses of power in the lines.The results show that, using multilevels CHBI, the quality of produced energy is improved, in fact the harmonics that decrease the efficiency of the system are extremely diminished. REFERENCES [1] A. Dendouga, “Contrôle des puissances active et réactive de la machine asynchrone à double alimentation,” Thèse de doctorat, Université de Batna, 2010. [2] Patrick Piro, "Guide des énergies vertes pour la maison," Livre éditions : Terre vivante, L'écologie pratique, 2006. [3] “Evolution et tendances de la demande mondiale en énergie,” [Online]. Available: http://web.archive.org/web/20080509052730/www.lenergiecreative.com/ (section “énergie et planète”). [4] Baroudi, J. A, Dinavahi, V and Knight, A. M, “A review of power converter topologies forwind generators,” Renew Energy, vol. 32, no. 14, pp. 2369-2385, 2007 [5] Lai, J. S and Peng F. Z., “Multilevel converters. A new breed of power converters,” IEEE Transactions on industry applications, vol. 32, no. 3, pp. 509-517, 1996 [6] Abbes, M, Belhadj, J and Bennani, A. B. A, “Design and control of a direct drive wind turbine equipped with multilevel converters,” Renew Energy, vol. 35, no. 5, pp. 936-945, 2010. [7] Babaei. E, Hosseini. S. H, Gharehpetian. G. B, Haque. M. T and Sabahi. M., “Reduction of dc voltage sources and switches in asymmetrical multilevel converters using a novel topology,” Electric Power Systems Research, vol. 77, no. 8, pp. 1073-85, 2007. [8] R. Melício a, V. M. F. Mendes. B and J. P. S. Catalão, “Power converter topologies for wind energy conversion systems: Integrated modeling, control strategy and performance simulation,” Renewable Energy, vol. 35, pp. 2165-2174, 2010. [9] B.Belkacem, A.K. Lahouari, M. Rahli, “SPWM and SVPWM control of a three level voltage inverter dedicated to a variable speed wind turbine,” Journal of Power Technologies, vol. 97, no. 3, pp. 190-200, 2017. [10] F. Poitiers, M. Machmoum, R. Le Doeufi and M. E. Zaim, “Control of a doubly-fed induction generator for wind energy conversion systems,” IEEE Trans Renewable Energy, vol. 3, no. 3, pp. 373-378, 2001. [11] H. S. Hamad, A. Hussein Ali, A. A. Abdulrazzaq, “An adaptable different-levels cascaded h-bridge inverter analysis for PV grid-connected systems,” International Journal of Power Electronics and Drive Systems (IJPEDS), vol. 10, no. 2, 2019. [12] B. Hamane. M. L. Doumbia, M. Bouhamida, and M. Benghanem, “Control of Wind Turbine Based on DFIG Using Fuzzy-PI and Sliding Mode Controllers,” Ninth International Conference on Ecological Vehicles and Renewable Energies, pp. 1-8, 2014. [13] A. G. Ram, S. and A. Lincoln, “Fuzzy adaptive PI controller for single input single output non-linear system,” ARPN Journal of Engineering and Applied, Sciences, vol. 7, no. 10, pp. 1273-1280, 2012. [14] T. Mesbahi, T. Ghennam and E. M. Berkouk, “A Doubly Fed Induction Generator for wind stand-alone power applications (Simulation and experimental validation),” Electrical Machines (ICEM), 2012 XXth International Conference on, pp. 2028-2033, 2012. [15] R. Sadaoui, "Analyse et commande de la machine asynchrone à double alimentation," Université du Québec à Trois-Rivières Service de la bibliothèque, 2013. [16] Shanzhi Li, Haoping Wang, Yang Tian, Abdel Aitouch, John Klein, “Direct power control of DFIG wind turbine systems based on an intelligent proportional-integral sliding mode control,” ISA Transactions, vol. 64, pp. 431-439, 2016. [17] K. Kerrouche, A. Mezouar and L. Boumedien, “A simple and efficient maximized power control of DFIG Variable Speed Wind Turbine,” Proceedings of the 3rd International Conference on Systems and Control, 2013. [18] A. Bouharchouche, E. M. Berkouk, T. Ghennam and B. Tabbache, “Modeling and control of a Doubly fed induction generator with battery supercapacitor hybrid energy storage for wind power applications,” 2013 Fourth International Conference on Power Engineering, Energy and Electrical Drives, pp. 1392 -1397, 2013.
  • 12. Int J Elec & Comp Eng ISSN: 2088-8708  Control of the powerquality for a DFIG powered by multilevel inverters (Hachemi Hachemi) 4603 [19] B. Hamane, M. L. Doumbia, M. Bouhamida and M. Benghanem, “Direct active and reactive power control of DFIG based WECS using PI and sliding mode controllers,” ECON 2014-40th Annual Conference of the IEEE Industrial Electronics Society, pp. 2050-2055, 2014. [20] A. Leredde, "Etude, Commande et Mise en Œuvre de Nouvelles Structures Multiniveaux," Thèse de doctorat de l’Institut National Polytechnique de Toulouse (INP Toulouse), 2011. [21] D. Floricau and G. Gateau "New Multilevel Converter for Industrial Medium-Voltage Applications," Journal Przeglad Elektrotechniczny (Electrical Review), pp. 26-30, 2009. [22] F. Z. Peng, J. W. Mckeever and D. J. Adams, “A power line conditioner using cascade multilevel inverters for distribution systems,” IEEE Transactions on Industry Applications, vol. 34, no. 6, pp. 1293-1298, 1998. [23] A. Shamsul Rahimi A. Subki, and all, “Hardware implementation of single phase three-level cascaded h-bridge multilevel inverter using sinusoidal pulse width modulation,” vol. 10, no. 2, 2019. [24] J. S. Mariéthoz, "Etude formelle pour la synthèse de convertisseurs multiniveaux asymétriques: Topologies, modulation et commande," Thèse de Doctorat, Ecole Polytechnique Fédérale de Lausanne, 2005. [25] A. Mahrous, M. K. Metwaly and N. Elkalashy, “Performance investigation of multi-level inverter for DFIG during grid autoreclosure operation,” International Journal of Power Electronics and Drive Systems (IJPEDS), vol. 10, no. 1, pp. 454-462, 2019.