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978-981-10-4286-7 29

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Comparison Between PI Controller
and Fuzzy Logic-Based Control
Strategies for Harmonic Reduction
in Grid-Integrated Wind Energy
Conversion System
Ramji Tiwari, N. Ramesh Babu, R. Arunkrishna
and P. Sanjeevikumar
Abstract In this paper, a novel fuzzy logic-based control (FLC) strategy is
developed to perform multi-function strategy for smooth and controlled operation
of three-phase renewable energy system (RES)-based wind energy conversion
system (WECS) with grid integration. The inverter acts as an converter to infuse the
power obtained from the wind energy and as a active power filter to compensate
reactive power demand and load current harmonics. The control strategies in
accordance with 3-phase 4-wire unbalanced load tend to appear as a balanced linear
load system at grid. The control strategy is developed and validated using
MATLAB/Simulink. The proposed controller is compared with PI-based controller
and validate that the proposed FLC provide better efficiency by reducing
harmonics.
Keywords WECS Distributed generation PMSG Proportional–integral
controller Fuzzy logic controller Harmonic reduction
R. Tiwari N. Ramesh Babu (&) R. Arunkrishna
School of Electrical Engineering, Vellore Institute of Technology (VIT) University,
Vellore, India
e-mail: nrameshbabu@vit.ac.in
R. Tiwari
e-mail: ramji.tiwari2015@vit.ac.in
R. Arunkrishna
e-mail: r.arunkrishna10@gmail.com
P. Sanjeevikumar
Department of Electrical and Electronics Engineering, University of Johannesburg,
Auckland, Johannesburg, South Africa
e-mail: sanjeevi_12@yahoo.co.in
© Springer Nature Singapore Pte Ltd. 2018
S. SenGupta et al. (eds.), Advances in Smart Grid and Renewable Energy,
Lecture Notes in Electrical Engineering 435, https://doi.org/10.1007/978-981-10-4286-7_29
297
298
R. Tiwari et al.
1 Introduction
The constant development of electric utilities and depletion of fossil fuel are
becoming major concern of maintaining energy demand. Currently, fossil fuel-based
generation shares a large portion of global energy demand, but simultaneously
increasing the air pollution and global warming concern. Thus, to overcome the all
above major concern, renewable energy-based power generation is gaining more
interest in all countries. To promote renewable energy and to accelerate the interest
among private institute, government is providing many incentives [1].
The distributed generation (DG) should follow a grid code to integrate the
renewable energy source (RES) at distribution level. RES such as solar, wind, tidal
are the major sources of renewable energy. Among RES, wind-based energy
generation is the most preferred energy source for its cost-effective production. The
major threat of RES is the stability, nonlinearity, voltage regulation and power
quality issue. Thus, an advance control strategy is required to overcome the issue
and enhance the system operation for grid integration. However, power electronics
converter and the nonlinear load create the harmonic current which causes issue in
power stability [2].
A considerable amount of harmonic current is being injected into power system
by the nonlinear load. Thus, the harmonic current in the power system causes
voltage distortions which increases the loss in line and decrease the power factor.
The current harmonic in the system add up arithmetically at the neutral bus till 1.73
times of the phase magnitude thus causes heating of the transformers and cables.
This may reduce the energy efficiency and damage the electronic equipment [3].
The LC filter is the traditional method to reduce the current harmonics because
of the simplicity and reduced cost. But, they have an disadvantage of large size,
inductor turns ratio and risk of resonance [4, 5]. So in order to remove the harmonic
from the power network, an active filter is developed which has dynamic response
for the power quality problem. [6]
In this paper, author compares the control strategy based on PI and fuzzy logic
which incorporates the features of active power filters for interfacing the renewable
to the grid. The control strategy can mitigate the unbalance voltage disturbance
caused due to injection of harmonic current into the grid. The active power filter is
used to compensate the current imbalance and reactive power demand. The neutral
current compensation of 3-phase 4-wire system is performed using the control
strategy implemented for grid-interfacing inverter.
2 System Description
The proposed system consists of wind energy conversion system interconnected
with DC-link and the grid through inverter. The voltage source inverter (VSI) is the
key element of the distributed generation (DG) as it interfaces the WECS to grid
Comparison Between PI Controller and Fuzzy Logic-Based Control …
299
Fig. 1 Schematic of WECS-based distributed generation system
and supplies the generated power to the utility [7]. As shown in Fig. 1, 3-phase
4-wire inverter is used in this paper for interfacing the WECS to the grid. The
proposed system consists of a diode rectifier followed by the boost converter before
interfacing with the grid. The variable speed wind turbine is highly nonlinear in
nature. Thus, the power obtained from the WECS needs to be smoothened before
connected to the DC-link. The dc capacitor is connected to decouple the WECS
from the grid to perform independent control on the either side.
3 Analysis of Wind Energy-Based Conversion System
The WECS system comprises of wind turbine and permanent magnet-based synchronous generator (PMSG). The wind turbine produces the torque which is converted into electric power by the PMSG. The power and torque equation of WECS
is determined by the following equation,
1
3
Pm ¼ Cp ðb; kÞ qpR2 Vwind
2
Tm ¼
Pm
k
ð1Þ
ð2Þ
where b (blade pitch angle) and k (tip speed ratio) are the variables of Cp (rotor
power coefficient), q implies the air density, R refers to the radius of wind turbine
blade, and wind speed is represented as Vwind [8].
300
R. Tiwari et al.
The electromagnetic torque generated from the rotor of PMSG is given by the
equations
Te ¼ 1:5
i
Ph
wp isq þ isd isq Lsd Lsq
2
ð3Þ
where the dq axis current and voltages are represented as isd ; isq ; usd and usq ,
respectively, and angular frequency of the generator is defined by xs . Inductances
of the generator are denoted as Lsd and Lsq . wp is the permanent flux, Rsa refers to
the resistance of the stator, and P refers to number of poles [9].
4 Control Strategy
Figure 2 shows the control diagram of grid interconnected with 3-phase 4-wire
system. The neutral current of the load is stabilised using the fourth leg of the
inverter. The main aim of the proposed topology is to stabilise the power transferred
to the grid. The inverter supplies the fundamental active power to the grid by
reducing the harmonics and the neutral current [10].
This control strategy is used to generate the duty ratio for the inverter using
injected power and DC voltage as the input parameter. The DC-link voltage provides the data of the injected power to the grid from the WECS. The multiplication
of active current (Im) component with unit grid vector (Ua, Ub, Uc) constitutes to
Fig. 2 Control technique for generating pulses
Comparison Between PI Controller and Fuzzy Logic-Based Control …
301
reference grid currents ðIa ; Ib ; Ic Þ, and the neutral reference is set to null. The unit
vectors of the grid can be given as follows
Ua ¼ sinðhÞ
2p
Ub ¼ sin h 3
2p
Uc ¼ sin h þ
3
ð4Þ
ð5Þ
ð6Þ
The instantaneous values of grid current reference are given as
Ia ¼ Im Ua
ð7Þ
Ib ¼ Im Ub
ð8Þ
Ic ¼ Im Uc
ð9Þ
The neutral conductor connected to load generates the neutral current. Neutral
current is compensated using the fourth leg of the grid-interfacing inverter. The
reference neutral current ðIn Þ is considered to be zero as shown in Eq. 10. Neutral
current should not be drawn from the grid.
In ¼ 0
ð10Þ
The above analysis is given to the controller in order to obtain the switching
pulses for the gate drivers for the grid-interfacing inverters.
(A) PI controller
In PI-based control technique, the reference voltage and the DC voltage across the
converter are analysed to generate an error signal. The obtained error signal is then
fetched to the PI controller in order to generate the output signal [11]. The obtained
PI output signal is then fed to the PWM generator where the signal is compared
with the triangular wave to deliver the pulses in form of duty cycle which controls
the inverter switch in such a way that the DC-link is maintained constant under
rapid variation of wind speed. [12]. The equation used for PI controller is
D ðsÞ ¼ Kp þ Ki = s E ðsÞ
ð11Þ
where Kp and Ki are the proportional and integral parameter of PI controller. E ðsÞ is
the error signal of obtained voltage and desired voltage, and D ðsÞ represents the
duty cycle generated by the PI controller. The DC-link voltage error is given by
Eq. 12.
302
R. Tiwari et al.
E ðsÞ ¼ Vdc
Vdc
ð12Þ
The output of PI controller is expressed as
Im ¼ Im þ Kp Vdc
Vdc þ Ki E ðsÞ
ð13Þ
where, value of Kp is calculated as 10 and Ki as 0.05.
(B) Fuzzy logic controller
PI controller fails to determine the change in rise and fall of the error and only
capable to react to the instantaneous value of error. Thus, they are not suitable for
nonlinear system like wind energy. To overcome this problem, FLC is implemented
which has an advantage of overcoming the nonlinearity of system, fast convergence. FLC works on the principle of three steps in order; they are Fuzzification,
inference system and Defuzzification [13]. The rules are framed from the former
knowledge of the system. The error signal obtained from the difference between the
obtained with respect to desired value and change in error signal are considered as
the input for the FLC. The output of the controller is the duty cycle for inverted.
The efficiency of FLC is purely depending upon the user’s knowledge about the
system and the framing right computation error.
Table 1 presents rules set used for FLC used in this topology. The rules are
framed in seven levels, namely Negative large (NL), Negative medium (NM),
Negative small (NS), Zero (ZE), Positive small (PS), Positive medium (PM) and
Positive large (PL). Inference mechanism is basically defined by membership
functions which show the relevance of rules from Table 1. Methods, Minimum
(min) and Maximum (max), are defined for the implication and aggregation,
respectively, whereas, centroid is used for the Defuzzification processing.
(C) Switching control
The switching pattern of the proposed topology is determined using hysteresis
current controller technique as shown in Fig. 2. The significance of the pattern of
switch is determined using the error generated using the FLC or PI controller. The
hysteresis strategy is the major cause for the high harmonic band in the switching
frequency though they are preferred for nonlinear system as they provide better
response and robust for sudden variation [14, 15].
Table 1 Fuzzy logic table
E/CE
NL
NM
NS
ZE
PS
PM
PL
NL
NM
NS
ZE
PS
PM
PL
PS
PM
PL
NL
NM
NS
ZE
PM
PL
NL
NM
NS
ZE
PS
PL
NL
NM
NS
ZE
PS
PM
NL
NM
NS
ZE
PS
PM
PL
NM
NS
ZE
PS
PM
PL
NL
NS
ZE
PS
PM
PL
NL
NM
ZE
PS
PM
PL
NL
NM
NS
Comparison Between PI Controller and Fuzzy Logic-Based Control …
303
5 Simulation Results
The proposed control topology is verified by interfacing the WECS to the 3-phase
4-wire inverter connecting to the grid. An simulation study is analysed using
MATLAB/Simulink. The inverter is controlled actively to achieve balanced sinusoidal grid voltage despite of varying wind speed. Capacitor at DC-link is used to
connect the inverter with the WECS. The harmonics and reactive power of the
3-phase 4-wire system need to compensate using the suitable control strategy to
follow the grid regulations.
The grid side voltage is set as 360 V as shown in Fig. 3. The grid current,
unbalanced load current and inverter current for the PI-based controller are shown
in Figs. 4, 5 and 6, respectively. At t = 0.1, the inverter tends to inject active power
to the grid. It can be clearly seen that in Fig. 6 load current takes time to settle when
PI controller used.
Voltage(v)
400
200
0
-200
-400
0
0.05
0.1
0.15
0.2
0.05
0.1
0.15
0.2
0.25
0.3
Time(sec)
0.35
0.4
0.45
0.5
0.3
0.35
0.4
0.45
0.5
0.3
0.35
0.4
0.45
0.5
Fig. 3 Grid voltage
Current(A)
20
10
0
-10
-20
0
0.25
Time(sec)
Fig. 4 Grid current (PI-based control strategy)
Current(A)
20
10
0
-10
-20
0
0.05
0.1
0.15
0.2
0.25
Time (sec)
Fig. 5 Load current (PI-based control strategy)
304
R. Tiwari et al.
Current(A)
10
5
0
-5
-10
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.3
0.35
0.4
0.45
0.5
0.3
0.35
0.4
0.45
0.5
0.3
0.35
0.4
0.45
0.5
Time(sec)
Fig. 6 Inverter current (PI-based control strategy)
Current(A)
20
10
0
-10
-20
0
0.05
0.1
0.15
0.2
0.25
Time(sec)
Fig. 7 Grid current (FLC-based control strategy)
Current(A)
20
10
0
-10
-20
0
0.05
0.1
0.15
0.2
0.25
Time(sec)
Fig. 8 Load current (FLC-based control strategy)
Current(A)
40
20
0
-20
-40
0
0.05
0.1
0.15
0.2
0.25
Time(sec)
Fig. 9 Inverter current (FLC-based control strategy)
The waveforms for grid current, unbalanced load current and the inverter current
for FLC-based control strategy are shown in Figs. 7, 8 and 9. The FLC requires
only few times when compared to PI controller to compensate the load current. The
harmonics induced by the PI controller is high when compared to the FLC-based
controller.
Comparison Between PI Controller and Fuzzy Logic-Based Control …
305
Form the results, it can analysed that FLC-based control strategy provide better
stabilisation of the load current and elimination of harmonics when compared with
the PI-based control strategy.
6 Conclusion
The paper presents a comparative analysis of PI- and FLC-based control strategies
for active grid-interfacing inverter to compensate the harmonic produced by nonlinear system. A 3-phase 4-wire-based DG system is interfaced with the grid
inverter which is utilised effectively without disturbing the normal operation of
active power transfer. The inverter can be used for multi-objective function, such as
to inject active power generated from wind energy to the grid and to compensate the
harmonics and the current distortion produced due to nonlinearity of the system.
Thus, this will eliminate the need of separate filter used for power condition
operation. The neutral current is prevented to flow into grid by the fourth leg of the
inverter thus by reducing the damage. The quality of power is increased reducing
the harmonic content from the load current.
The comparison between two control strategies is analysed and it is clear that
FLC-based control system provides dynamic response and has higher efficiency
than the PI-based control technique. FLC-based system provides robustness toward
the nonlinearity of the system. The current harmonics, unbalance current and the
load reactive power are compensated effectively using the combination of FLC
control strategy for 3-phase 4-wire grid-integrated inverter.
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