CHAPTER 4
SHUNT HYBRID ACTIVE FILTER
USING AI TECHNIQUES
4.1 INTRODUCTION
The design ramification and immense cost of losses of the conventional passive filters,
as well as their restricted potential to minimize inter-harmonics and non-characteristic
harmonics has encouraged the advancement of harmonic compensation by means of
power electronic devices commonly referred to as Active Filters. Typically shunt AF
consists of a three phase voltage source inverter with capacitor on dc side. For large
power applications, it is difficult to implement a low loss and a low cost PWM
converter. When this equipment is connected in shunt to the ac source impedance it is
possible to improve the compensation characteristics of the passive filters in parallel
connection [62, 55].This forms the transformer-less Parallel Hybrid Active Filter
(PHAF). The aim of PHAF is to mitigate the problems associated with SAF and
passive filters and to complement and enhance their performance by adding active or
passive components to their structure [39]. Shunt Hybrid Active Filter is constituted
by Active Filter connected in shunt and shunt connected with three phase single tuned
second order low pass LC filter for 5th harmonic frequency with rectifier load. The
Active Filtering System is based on Synchronous Reference Frame control strategy.
This chapter describes the 5th harmonic compensation using the combination of
passive filter and Active Filters connected in shunt to the distribution load. The
compensation principle, design and Hybrid Shunt Active Filter are discussed in detail.
This chapter is devoted to the comparison analysis and implementation of intelligent
controllers like PI controller, Fuzzy logic controller and neural network based Shunt
Hybrid Active Filter (SHAF) with non-linear load to minimize the source current
harmonics and provide reactive power compensation. The implementation is
demonstrated through MATLAB Simulated Environment.
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4.2 SHUNT HYBRID ACTIVE FILTER
4.2.1 Principle of Operation
A Shunt Hybrid Active Filter topology named transformer less hybrid filter was
proposed which uses a single LC passive filter for each phase and a small rated
voltage source converter based active power filter [4.4]. The series connection
between the LC passive filter and the voltage source converter is connected parallel to
the load without using any matching transformer. Hybrid filters provide cost-effective
harmonic compensation particularly for high-power nonlinear load [111]. The active
filter is controlled to act as a harmonic compensator for the load by confining all the
harmonic currents into the passive filter. This eliminates the possibility of series and
parallel resonance [151, 62]. Thus only the fundamental frequency component of the
load is to be supplied by the ac mains.
Fig 4.1Schematic Block Diagram of Shunt Hybrid Active Filter
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Fig 4.1 shows schematic block diagram of the Shunt Hybrid Active Filters with
nonlinear load drawing non-sinusoidal current. The system consists of active filter in
shunt with passive filter. The Shunt Hybrid Active Filter works such that ac mains
current is created to have only fundamental frequency component, by absorbing
harmonics all the way through passive filters. The active filter performs as a harmonic
voltage source, compensates voltage drop in passive filter at harmonic frequencies at
PCC, thereby creating a short circuit across passive filter at harmonic frequency [125].
4.2.2 Design Parameters of Shunt Hybrid Active Filters
The design procedure of transformerless Shunt Hybrid Active Filter implicates the
design of the Active Filter and the design of the passive filter. The design parameter
of the Shunt Active Filter has been explained in Chapter 3. The R, L, C values are
determined on the basis of the filter type and the following parameters

Reactive power at nominal voltage

Tuning frequency

Quality factor
The fundamental shunt passive filtering law is to catch the selective harmonic currents
in LC circuits, tuned up to the harmonic filtering frequency to be eliminated from
power system The L,C components of the passive filter is calculated by considering
the harmonic content of the load. Therefore, tuning frequency of the passive filter is
selected to be the foremost dominant harmonic component of the nonlinear load.
The primary step to design a single tuned filter is to first define the size of the
capacitor with a reasonable power factor at the operating line voltage.
X
c

V
2
L L
(4.1)
kVAR. filter
Once the size of the capacitor is defined with a realistic power factor at the operating
line voltage, the reactance value can be calculated by using (4.2) where filter kVAR
signifies the reactive power capacity of the filter and VL-L stands for the line to line
rated voltage of the filter.
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In single-tuned filter, the reactance of inductor is equal to that of capacitor at resonant
frequency ‘f’.
f 
1
2
(4.2)
LC
f
f
Other parameter included in filter design is resistance value of filter R which can be
determined by defining the sharpness of filter Q, also termed as Quality factor.
Q
LC
f
f
(4.3)
R
Thus, basic principle of shunt passive filter is to trap harmonic currents in LC circuits,
tuned to the harmonic filtering frequency, and to minimize source current distortion.
In the proposed Shunt Hybrid Active Filter, shunt passive filters are tuned to absorb
5th harmonic currents. Hence burden on Shunt Active Filter is reduced as other higher
order harmonics are to be suppressed by Shunt Active Filter. This reduces the rating of
SAF and source needs to supply only fundamental component of load current.
4.2.3 Control Strategy
Synchronous Reference Frame (SRF) theory is implemented to calculate the
compensating current reference signal. In this control strategy, three phase load
current is transformed into d-q stationary reference frame using Parks Transformation.
By means of this transformation, fundamental component appears as DC quantities
and all other harmonics are transformed as non-dc quantities. Since these quantities
are not required hence these can be filter out using low pass filter. Thus, only the low
frequency fundamental components will be passed through and harmonic components
will be stopped. The active power loss is obtained from comparing the Vdc reference
voltage and DC capacitor voltage. This error signal after passing through various
controllers like PI controller, Fuzzy logic controller and Neural Network controller is
added to obtain the reference DC component, the reference compensating signal in d-q
reference frame. Similarly the reactive component of the control signal is added for
fixed reactive power compensation. The extracted dc components are transformed
back into a–b–c coordinates to obtain the reference compensating current. Hysteresis
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current control is employed independently for each phase to generate the switching
signals for three-phase voltage source inverter. The input to the Hysteresis Current
Controller is the error difference between the reference compensating current and the
load current.
The detailed description of the control scheme is explained in chapter 3 section 3.7. To
compensate for the inverter losses different controllers like PI, Fuzzy and neural
controller are applied to regulate the DC bus voltage. Hence the significant reduction
in the 5th harmonic component and other higher order harmonics can be seen which
subsequently minimizes the THD of source current.
4.2.3.1 Design of Fuzzy Controller
Fuzzy Logic control is a technique to embody human-like thinking into a control
system. A fuzzy controller can be designed to emulate human deductive thinking to
infer from the past experience. The triangular shaped membership functions are
considered for the input variables error ‘e’ (v*dc-vdc), change in error (de/dt) and
output variable representing the active power loss. Seven membership functions
namely NL (Negative Large), NM (Negative Medium), NS (Negative Small), Z
(Zero), PS (Positive Small), PM (Positive Medium), PS (Positive Small) have been
chosen for input and output variables. Firstly all seven variables are normalized with
in the membership function range Fig 4.2 and4.3 shows the membership function for
input and output variables. In the second stage, the fuzzy variables are processed by an
interface which executes 49 control rules. Table 4.1 show the fuzzy rules formulated
for the Shunt Hybrid Active Filter using Fuzzy Controller. In third stage as
defuzzification and denormalization, the fuzzy variables are converted back to crisp
variables. The peak value of reference currents is estimated by regulating the DC link
voltage using fuzzy logic controller. The error and change in error are considered as
the input variables and current loss ( iloss ) as output variable. When the proposed fuzzy
based shunt hybrid active filter is curved with Synchronous Reference Frame method,
the most dominant harmonics of the load are greatly reduced.
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Fig 4.2 Membership Function for Input Variable
Fig 4.3 Membership Function for Output Variable
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Table 4.1 Fuzzy Rules Formulated for Shunt Hybrid Active Filter
using Fuzzy Controller
4.2.3.2 Design of Neural Network Controller
Neural Networks offer an unconventional methodology for power quality solution. A
Multilayer Perceptron Neural Network trained with back-propagation training
algorithm is analyzed to recognize the harmonic characteristics of the nonlinear load.
The difference between the DC bus voltage and the capacitor voltage is given to the
neural controller to maintain the DC bus voltage constant equal to 750V. The network
is designed with three layers, the input layer with 1, the hidden layer with 30, and the
output layer with 1 neuron, respectively. ’tansig’ transfer functions between layers,
'trainlm’ and 1000 the number of epochs is considered for simulation.
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4.3 SYSTEM CONFIGURATION
A three-phase source is supplied by a sinusoidal balanced three-phase 415 V source
having 50 Hz frequency with a source inductance of 2 mH and a source resistance of
0.2Ω. The Active Filter consists of an IGBT three-leg bridge. One 2200 µF capacitors
is connected at the dc side. The reference voltage at the capacitors is 750 V. A smallrated filter has been included to minimize the switching ripples at the inverter output.
The load used in simulating the system is three phase unbalance nonlinear load.
Passive filter arrangement provides reactive VAR compensation at the fundamental
frequency tuned for the most dominant harmonic frequency of 250 Hz (5th harmonic
order). The value of Quality Factor is considered as 50.The component values for the
passive filter network and other parameters of the system are given in Table 4.2.
Table 4.2 Parameters of the System Considered for Shunt Hybrid
Active Filters
Parameters
Numerical Values
Supply voltage
415V (L-L), 50 Hz
Load:
(i) Linear: phase a= 25Ω
Phase b=10 Ω and 80mH
Phase c =10 Ω and 80 mH
(ii) Nonlinear: Three phase full bridge
rectifier drawing 15A
Shunt Active Filter:
Interfacing Inductance
Lf = 5mH
DC bus capacitance
2200e-6F.
Referenced Dc voltage
750 V
Tuned Passive Filter
C5=40e-6 F; L5=10mH; R=0.04
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4.4 SIMULATION RESULTS
The performance of the proposed scheme is evaluated for its application to
unbalanced non-linear load for different configurations of filters viz passive filters,
pure Shunt Active Filter, Shunt Hybrid Active Filter, Fuzzy based Shunt Hybrid Filter
and Neural Network based Shunt Hybrid Active Filter. In the present study the 5th
tuned branches of passive filter are considered. Resonance problem occurs at fifth
harmonic frequency when passive filter operates alone. The hybrid filter produces the
resonance caused by capacitors in the passive filters with source side inductive
impedance and amplification phenomenon at fifth harmonic frequency disappears.
4.4.1 Performance of Shunt Hybrid Active Filter using PI Controller
A Shunt Hybrid Active Filter consists of low rating Shunt Active Filter and a shunt
connected passive filter tuned at 5th frequency. It is used to reduce the total harmonic
distortion and the 5th harmonic component of fundamental frequency. An unbalanced
load with highly nonlinear characteristics is considered for the simulation. The source
current is same as the load current when the compensator is not connected. The SRF
control strategy is used which provides high resistance at the fundamental frequency
and also zero impedance is presented to harmonic current flowing in to the passive
filter [152]. The total harmonic distortion of the source current with hybrid active
filtering using PI controller for the three phases ,phase a, phase b and phase c are
2.43%,2.42% and 2.35% as shown in Fig 4.4. The dynamic performance of the Shunt
Hybrid Active Filter under non-linear unbalanced load condition with filtering is
shown in Fig 4.5.The source voltage, source current, load current, compensating
current, are depicted in the dynamic performance. Fig 4.6 and Fig 4.7 shows the DC
capacitor voltage of Shunt Hybrid Active Filter using PI controller and load reactive
power and source reactive power respectively.
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Fig 4.4(a) FFT of Source Current for Phase a with Shunt Hybrid Active Filter
using PI Controller
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Fig 4.4(b) FFT of Source Current for Phase b with Shunt Hybrid Active Filter
using PI Controller
169
Fig 4.4(c) FFT of Source Current for Phase c with Shunt Hybrid Active Filter
using PI Controller
170
Fig 4.5 Dynamic performance of Shunt Hybrid Active Filter using PI Controller
171
Fig 4.6 DC Capacitor Voltage of Shunt Hybrid Active Filter using PI Controller
Fig 4.7 Load Reactive Power and Source Reactive Power of Shunt Hybrid Active Filter
using PI Controller
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4.4.2
Performance of Shunt Active Filter using Fuzzy Controller
Fig 4.8 shows the FFT analysis of source current by Shunt Hybrid Active Filter using
Fuzzy controller for phase ‘a’ THD is 2.06%. For phase ‘b’ it is 2.38% and for phase ‘c’
2.38%.The source voltage, source current, load current, compensating current, are
depicted in the dynamic performance as shown in Fig 4.9.Fig 4.10 shows the DC
capacitor voltage of Shunt Hybrid Active Filter using Fuzzy controller. Fig 4.11 shows
the load reactive power and source reactive power for Shunt Hybrid Active Filter using
Fuzzy controller.
Fig 4.8 (a) FFT of Source Current for Phase a with Shunt Hybrid Active Filter using
Fuzzy Controller
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Fig 4.8 (b) FFT of Source Current for Phase b with Shunt Hybrid Active Filter using
Fuzzy Controller
174
Fig 4.8 (c) FFT of Source Current for Phase c with Shunt Hybrid Active Filter using
Fuzzy Controller
175
Fig 4.9 Dynamic Performance of Shunt Hybrid Active Filter using Fuzzy Controller
176
Fig 4.10 DC Capacitor Voltage of Shunt Hybrid Active Filter using Fuzzy Controller
Fig 4.11 Load Reactive Power and Source Reactive Power of Shunt Hybrid Active Filter
using Fuzzy Controller
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4.4.3 Performance of Shunt Active Filter Using Neural Network Controller
The total harmonic distortion of the source current with hybrid active filtering using
ANN controller for the three phases ,phase a, phase b and phase c are 2.05%,2.20% and
2.22% as shown in Fig 4.12. The dynamic performance of the Shunt Hybrid Active Filter
under non-linear unbalanced load condition with filtering is shown in Fig 4.13.The source
voltage, source current, load current, compensating current, are depicted in the dynamic
performance. Fig 4.14 and Fig 4.15 shows the DC capacitor voltage of Shunt Hybrid
Active Filter using ANN controller and load reactive power and source reactive power
respectively.
Fig 4.12 (a) FFT of Source Current after Filtering for Phase a using ANN Controller
178
Fig 4.12 (b) FFT of Source Current after Filtering for Phase b using ANN Controller
179
Fig 4.12 (c) FFT of Source Current after Filtering for Phase c using ANN Controller
180
Fig 4.13 Dynamic performance of Shunt Hybrid Active Filter using ANN Controller
181
Fig 4.14 DC Capacitor voltage of Shunt Hybrid Active Filter using ANN Controller
Fig 4.15 Load Reactive Power and Source Reactive Power of Shunt Hybrid Active
Filter using ANN Controller
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4.4.4 Comparison of Different Controllers
The performance of the presented SRF control strategy is evaluated by using
comparison of pure Shunt Active Filter and Shunt Hybrid Filter. The three phase
unbalance nonlinear load 2 considered in Chapter 3 contains 5th harmonic content as
the most prominent factor which causes the distortion in the source current. Hence
the passive elements of the hybrid filter are tuned for the resonance frequency of
250Hz. The VA rating required for the inverter in the hybrid filter is much lesser
than that required in a pure shunt active filter.
The apparent power rating of nonlinear load is given by
VA rating= 3 V Srms  I Lrms
where VSrms and ILrms are the RMS value of source voltage taken as 415 V and load
current taken as 22 A.
Thus the rating of load (nonlinear load 2 considered in chapter 3) is approximated to
27.5 kVA.
The VA rating required of the inverter in Shunt Active Filter is given by
VA rating= 3 
V
dc
2

I
FMAX
2
where I FMAX is the maximum filter current
The maximum filter current observed in implementing Shunt Active Filter is 7.4 A.
Thus the rating of Shunt Active Filter is approximated to 4.8 kVA.
The maximum filter current observed in implementing Shunt Hybrid Active Filter is
3 A. Thus the rating of Shunt Active Filter is approximated to 2 kVA.
The apparent ratio of the Shunt Active Filter and Shunt Hybrid Active Filter shows
the VA rating has been greatly reduced by 60%.
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The Shunt Hybrid Active Filter is modeled and the various controllers have been
applied to reduce the THD of the source current and compensate the reactive power.
The Shunt Hybrid Active Filter is designed to minimize the 5th harmonic of the
source current. Hence the implemented AI techniques also facilitate to reduce the
harmonic content of the source current at frequencies higher than fundamental
frequency. A comparative analysis of the THD and RMS values of the source current
for all three phases using different controllers have presented in Table 4.3. The
harmonic content of the load current and supply current in percentage of
fundamental current for phase a, phase b, phase c are given in Table 4.4,Table 4.5
and Table 4.6 respectively.
4.5 CONCLUSION
The implemented control strategy has demonstrated the capability of intelligent
controller for hybrid power filter to minimize the overall THD and the selective
harmonic content of the source current. A complete evaluation between a
conventional PI based Hybrid Active Filter, fuzzy based the Hybrid Filter and ANN
based Hybrid Shunt Active Filter has been presented. Thus FLC and neural network
seems more suitable and flexible for the active filter since it does not need a complex
mathematic model to tune the PI controller gains. The comparison results of the
THD of the load current and source current with different controllers have been
given in Table 4.3. From the results it can be depicted that ANN controller is giving
better performance than other controllers. The results shows that the source current
THD is reduced below IEEE standard (5%) with all the three controllers. After
compensation reactive power is also compensated to make power factor close to
unity. As the source current is becoming sinusoidal after compensation power quality
has been improved.
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Table 4.3 Comparison of THD and RMS Values of the Source Current for All Three
Phases with Shunt Hybrid Active Filter using Different Types of Controllers
Type of
Phase a
Controller
RMS
THD(%) RMS
THD(%) RMS
value
value
value
26.97 14.74
25.57 16.27
20.71 19.66
26.82 6.30
24.45 6.89
20.32 28.73
3.71
4.12
3.67
23.92 2.43
22.38 2.42
23.83 2.35
Fuzzy Based Shunt Hybrid 23.78 2.06
Filter
23.04 2.38
23.9
Neural
Based
Hybrid Filter
22.98 2.20
23.78 2.22
Load Current Without
Phase b
Phase c
THD(%)
Filter
Pure Passive Filter
Pure Shunt Active Filter
PI Based Hybrid Filter
Shunt 23.82 2.05
2.38
Table 4.4 Harmonic Content of Load Current and Supply Current in Percentage of
Fundamental Current for Phase a
Load current Without
Filter
Source current with
Passive Filter
Source current with Pure
Shunt Active Filter
Source current with Shunt
Hybrid Active Filter
Source current with Fuzzy
based Shunt Hybrid
Active Filter
Source current with neural
based Shunt Hybrid
Active Filter
5th
12.76
7th
5.42
11th
3.92
13th
2.23
17th
1.55
19th
0.97
0.61
3.53
2.82
1.65
1.11
0.71
1.11
0.92
1.13
0.19
0.80
0.59
1.09
0.41
0.37
0.22
0.23
0.08
0.31
0.46
0.66
0.18
0.66
0.13
0.68
0.43
0.28
0.12
0.13
0.25
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Table 4.5 Harmonic Content of Load Current and Supply Current in Percentage of
Fundamental Current for Phase b
Load current Without
Filter
Source current with
Passive Filter
Source current with Pure
Shunt Active Filter
Source current with Shunt
Hybrid Active Filter
Source current with Fuzzy
based Shunt Hybrid Active
Filter
Source current with neural
based Shunt Hybrid Active
Filter
5th
14.30
7th
5.46
11th
4.47
13th
2.15
17th
1.76
19th
0.91
0.70
3.53
3.47
1.55
1.37
0.67
1.57
0.51
1.78
0.79
0.44
0.75
1.13
0.30
0.38
0.53
0.28
0.29
0.91
0.12
0.82
0.36
0.78
0.38
0.75
0.50
0.27
0.16
0.09
0.27
Table 4.6 Harmonic Content of Load Current and Supply Current in Percentage of
Fundamental Current for Phase c
5th
7th
11th
13th
17th
19th
Load current Without
Filter
17.01
7.25
5.21
3.02
1.98
1.36
Source current with
Passive Filter
0.80
4.66
3.79
2.29
1.40
1.08
Source current with Pure
Shunt Active Filter
0.96
0.49
0.93
0.58
0.64
0.23
Source current with Shunt 0.95
Hybrid Active Filter
0.51
0.12
0.38
0.31
0.36
Source current with Fuzzy 0.63
based Shunt Hybrid
Active Filter
0.35
0.95
0.44
0.86
0.24
Source current with neural
based Shunt Hybrid
Active Filter
0.52
0.27
0.21
0.08
0.14
0.28
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