105 CHAPTER 5 ANN CONTROLLLER BASED SHUNT ACTIVE FILTER FOR STATIC AND DYNAMIC LOADS 5.1 Introduction The investigations in Chapter 4 show that analog Icoscontroller based shunt active filter is effective in harmonic and reactive power compensation under dynamic and steady state load conditions. The performance of Icosalgorithm based analog controller for shunt active filter was verified by simulation and experimental results. However analog controller circuits have several limitations. To avoid these limitations, a digital controller for active filter is initiated. A review of various digital control techniques developed is given in section 2.9. Of all digital control techniques, author is of the opinion that ANN based controller has superior performance. In chapter 3, design and performance of ANN based controller for adaptive shunt passive filter is given. It has given good performance over fixed element passive filter. The author is of the opinion that ANN based controller can be adopted for shunt active filter as well. The design, fabrication and performance evaluation of ANN controller based shunt active filter for static and dynamic load conditions is given in this chapter. The results of ANN controller based shunt active filter are compared with the adaptive shunt passive filter and analog controller based shunt active filter, which are explained in chapter 3 and chapter 4 respectively. 5.2 ANN controller based shunt active filter The harmonic levels or THD has an implicit relation to the instantaneous real power demand, instantaneous reactive power demand, instantaneous source current and instantaneous compensation current to be injected by active filter. The exact relation between these parameters is complex and cannot find a uniform rule to suit the different load characteristics under generalized operating conditions. In recent years, it has been found that ANN are well suited as computational tools for solving certain classes of complex problems, where the output variable must be correctly predicted from a knowledge base of input and output variable values [59 – 62]. The design, development and testing of ANN controller based shunt active filter are explained in coming sections. Neural network
Transcript
105
CHAPTER 5
ANN CONTROLLLER BASED SHUNT ACTIVE FILTER FOR STATIC AND DYNAMIC LOADS
5.1 Introduction
The investigations in Chapter 4 show that analog Icos controller based shunt active filter
is effective in harmonic and reactive power compensation under dynamic and steady state
load conditions. The performance of Icos algorithm based analog controller for shunt
active filter was verified by simulation and experimental results. However analog controller
circuits have several limitations. To avoid these limitations, a digital controller for active
filter is initiated. A review of various digital control techniques developed is given in
section 2.9. Of all digital control techniques, author is of the opinion that ANN based
controller has superior performance. In chapter 3, design and performance of ANN based
controller for adaptive shunt passive filter is given. It has given good performance over
fixed element passive filter. The author is of the opinion that ANN based controller can be
adopted for shunt active filter as well. The design, fabrication and performance evaluation
of ANN controller based shunt active filter for static and dynamic load conditions is given
in this chapter. The results of ANN controller based shunt active filter are compared with
the adaptive shunt passive filter and analog controller based shunt active filter, which are
explained in chapter 3 and chapter 4 respectively.
5.2 ANN controller based shunt active filter
The harmonic levels or THD has an implicit relation to the instantaneous real power
demand, instantaneous reactive power demand, instantaneous source current and
instantaneous compensation current to be injected by active filter. The exact relation
between these parameters is complex and cannot find a uniform rule to suit the different
load characteristics under generalized operating conditions. In recent years, it has been
found that ANN are well suited as computational tools for solving certain classes of
complex problems, where the output variable must be correctly predicted from a knowledge
base of input and output variable values [59 – 62]. The design, development and testing of
ANN controller based shunt active filter are explained in coming sections. Neural network
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architecture is designed such that it is very close to the minimal architecture needed for
approximating the target function satisfactorily.
The development and testing of the effectiveness of ANN controller based shunt active
filter under steady state and dynamic conditions are explained in next section.
5.3 Steady state harmonics – Simulation analysis
The performance of ANN controller based shunt active filter is tested in simulation for the
three phase thyristor converter load.
5.3.1 Test system I -Three phase thyristor converter fed R-L load
The test system I, mentioned in 3.3., is taken for simulation study - three phase ac mains
feeds power through three phase thyristor converter to R – L load of 1.8+j8.84 p.u.(Base V
= 400V, Base kV = 15kVA). The source impedance is taken as 0.03 + j0.04 p.u. The
schematic diagram of the test system is given in Figure 3.1. The harmonic analysis of this
nonlinear load for different firing angles was conducted under balanced/unbalanced system
conditions as explained in section 4.3.1.1 and results are tabulated in Tables 4.1 - 4.3.
The digital controller generates the pulses to the switching devices of shunt active filter. It
takes source voltages, load currents and filter compensation currents in the three phases as
the input quantities (represents input layer of 9 neurons) and PWM pulses to six IGBTs of
inverter as the output quantities (represents output layer of 6 neurons).The procedure of
development of ANN Controller is explained in the following section.
5.3.2 Development of ANN controller
For different values of firing angles (α = 0, 30 and 45), the samples of three phase
instantaneous source voltages, fundamental load currents and, compensation currents are
taken and used as training data. The reference compensation current samples are collected
by means of analog controller circuit. The reference and actual compensation currents are
used to generate the switching pulses to IGBTS of three phase inverter. A few samples of
training data are shown in Table 5.1.
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Table 5.1 Samples of training data for ANN Controller with shunt active filter
The back propagation neural network was trained with MATLAB using 500 training
patterns to achieve the performance goal of 0.001 and 2500 epochs. Levenberg-Marquardt
algorithm is used for training. The weights and biases of networks are adjusted to minimize
the sum squared error of the network. ANN comprises two layers: the input layer (6
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neurons), output layer (3 neurons) and hidden layer (6 neurons). The structure of ANN
network is shown in Figure 5.1. The operation of ANN Network is verified with 50 training
data, by computing output variables of ANN network at each load condition, using the
equation (3.4). The performance characteristics of neural network training are shown in
Figure 5.2.
Figure 5.1 Structure of neural network for controlling shunt active filter
Figure 5.2 Performance plot of training neural network for controlling shunt active filter
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The ANN controller is generated using ‘gensim’ function in neural network toolbox and is
used for controlling the shunt active filter. The ANN controller is simulated as an
embedded MATLAB function using Simulink toolbox and its performance is tested as
explained in the following section.
5.3.3 Performance of ANN controller based active filter – Simulation analysis
The simulation model of the test system with shunt active filter is shown in Figure 5.3. The
10kVA three phase IGBT based VSI inverter (3 kHz switching frequency) with 24mF DC
bus capacitor and 10mH coupling inductor is used as the shunt active filter.
Selection of filter element is done on the basis of dt
diF as mentioned in 4.4.1.1.
Figure 5.3 Simulation model of the test system I with ANN controller based shunt active filter
Three phase thyristor converter fed R-L Load (test system I) is the nonlinear load and it is
simulated under
(i) balanced source, balanced nonlinear load
(ii) unbalanced source, balanced nonlinear load (iii) balanced source, unbalanced nonlinear load conditions (specified in 4.3.1.1).
The three phase unbalanced star connected resistive load forms the unbalanced load. The
ANN controller based shunt active filter is installed in the system. The resulting source
voltage, load current, filter current and source current waveforms under all conditions are
shown in Figure 5.4 to Figure 5.6. The results are summarized in Table 5.2.
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Figure 5.4 Simulation analysis - Source voltages, Load currents, Filter currents and Source currents waveforms for 3 thyristor converter fed R – L load (α = 0) under balanced system conditions with ANN controller based shunt active filter
Figure 5.5 Simulation analysis - Source voltages, Load currents, Filter currents and Source currents waveforms for 3 thyristor converter fed R – L load (α = 0) under unbalanced source with ANN controller based shunt active filter
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Figure 5.6 Simulation analysis - Source voltages, Load currents, Filter currents and Source currents waveforms for 3 thyristor converter fed R – L load (α = 0) under unbalanced load with ANN controller based shunt active filter
Table 5.2 Simulation analysis – Fundamental component of source currents and THD in source currents for thyristor converter load ( = 0) with ANN controller based shunt active filter
Table 5.2 shows the fundamental component of source currents and THD in source currents
in the three-phase system with ANN controller based shunt active filter. Table 5.3 tabulates
the corresponding filter compensation currents.
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In order to confirm the effectiveness of ANN controller based shunt active filter at different
degrees of harmonic generation, simulations are repeated with firing angles set to 30and
60 under the three system conditions mentioned in 4.3.1.1. For firing angle of 30,
corresponding waveforms are plotted in Figure 5.7 to Figure 5.9. The fundamental
components of source currents and THD in source currents are shown in Table 5.4.
Corresponding compensation currents are shown in Table 5.5.
Figure 5.7 Simulation analysis - Source voltages, Load currents, Filter currents and Source currents waveforms for 3 thyristor converter fed R – L load (α =30) under balanced system conditions with ANN controller based shunt active filter
Figure 5.8 Simulation analysis - Source voltages, Load currents, Filter currents and Source currents waveforms for 3 thyristor converter fed R – L load (α = 30) under unbalanced source with ANN controller based shunt active filter
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Figure 5.9 Simulation analysis - Source voltages, Load currents, Filter currents and Source currents waveforms for 3 thyristor converter fed R – L load (α = 30) under unbalanced load with ANN controller based shunt active filter
Table 5.4 Simulation analysis – Fundamental component of source currents and THD in source currents for thyristor converter load ( =30) with ANN controller based shunt active filter
For firing angle 60, the corresponding waveforms are shown in Figure 5.10 to Figure 5.12.
Table 5.6 tabulates the fundamental component of source currents and THD in source
currents with ANN controller based shunt active filter. Corresponding filter injection
currents are given in Table 5.7.
Figure 5.10 Simulation analysis - Source voltages, Load currents, Filter currents and Source currents waveforms for 3 thyristor converter fed R – L load (α = 60) under balanced system conditions with ANN controller based shunt active filter
Figure 5.11 Simulation analysis - Source voltages, Load currents, Filter currents and Source currents waveforms for 3 thyristor converter fed R – L load (α = 60) under unbalanced source with ANN controller based shunt active filter
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Figure 5.12 Simulation analysis - Source voltages, Load currents, Filter currents and Source currents waveforms for 3 thyristor converter fed R – L load (α = 60) under unbalanced load with ANN controller based shunt active filter
Table 5.6 Simulation analysis – Fundamental component of source currents and THD in source currents for thyristor converter load ( = 60) with ANN controller based shunt active filter
The simulation results are verified experimentally as explained in section 5.4.
5.4 Steady state harmonic analysis - Experimental verification
The performance of the ANN based digital controller is checked under balanced source and
balanced nonlinear load conditions as specified in section 4.3.1.1. To reduce the complexity
of the test system, three phase 400V,50Hz supply connected to thyristor converter fed 3kW
resistive load(Test system III), is selected for experimental verification. The experimental
procedure is as follows:
5.4.1 Framing Artificial Neural Network
Using power analyser (Fluke 434B), the samples of three phase source voltages,
fundamental load currents, and corresponding compensation currents are observed
experimentally for different firing angles. These data are used for training ANN as
explained in section 3.6.3. The proposed ANN used here comprises two layers: the input
layer (6 neurons), the output layer (3 neurons) and the hidden layer (9 neurons). The
weights and biases of each layer are obtained from the equivalent Simulink model. Using
equation (3.4), ANN is programmed and implemented using dsPIC30F4011
microcontroller. The development of ANN Controller is explained in section 5.4.2.
5.4.2 Development of ANN controller for shunt active filter
The switching control of shunt active filter is provided with the help of dsPIC 30F4011
microcontroller. The main operations carried out by the digital controller are explained as
follows:
Step1: Sensing source voltages and load currents:
Three phase load currents and filter compensation currents are sensed with the help of
Hall Effect current transducer LA-25NP. Its response time is less than 1s, maxdt
di =
50A/s and frequency bandwidth is (DC – 150 kHz). The three phase source voltages are
sensed by means of Hall Effect voltage transducer LV – 20P with response time of 40s.
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Step2: Digitising input quantities:
Two AD 7863s are used for digitising three phase analog source voltages, load currents and
filter compensation currents. AD 7863 is a bipolar ADC used for the conversion of analog
quantities to corresponding digital values. The basic setup for interfacing AD 7863 and
dsPIC30F4011 is shown in Figure 5.13.Time taken for sensing one set of input samples,
digital conversion, program execution and generation of switching signals is observed as
330s. Hence sampling frequency of 3 kHz is considered.
Figure 5.13 Setup for ANN controller implementation
Step 3: Extraction of fundamental component of load current:
The fundamental components of three phase load currents are extracted with the help of the
biquad filter. Biquad filter is implemented in terms of the transfer function given in
equation (3.8) to (3.12)
Step 4: Switching signals to IGBTs of shunt active filter
The samples of three phase source voltages and fundamental components of load currents
are given as inputs to ANN Network. ANN Network is programmed using equation
(3.4).The output of ANN Network is the reference compensation currents. The reference
compensation currents are compared with actual compensation currents to generate
switching pulses. These switching pulses are amplified and given to IGBTs in shunt active
filter. Three phase 20kVA, 20 kHz PWM voltage source inverter assembly, which consists
of a three phase IGBT based inverter along with large DC link capacitor, is used as the
shunt active filter. DC link capacitor of 1650mF / 800V is used to maintain steady DC bus
voltage required by inverter.
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The program for step 1 to step 4 is coded in embedded C language and compiled with the
help of MPLABC30 compiler and downloaded to dsPIC 30F4011 microcontroller. The
experimental results with the insertion of ANN controller based shunt active filter are
discussed in section 5.4.3.
5.4.3 Hardware implementation of ANN controller for shunt active filter
The shunt active filter with ANN based digital controller is inserted in the test system II
described in 3.4. The performance of the filter is tested under three different load
conditions. The corresponding source current harmonic spectra show variation in source
current THD and individual harmonics with firing angle of thyristor converter. The
experimental results for three settings of firing angle ( = 0, 30, and 45) are shown
below:
Case (i) Thyristor converter firing angle α = 0
The ANN controller receives the samples of three phase source voltages and fundamental
load currents and controls the shunt active filter. The source voltage, source current and
filter current waveforms are shown in Figure 5.14. Source current harmonic distortions are
also measured with the help of Power Analyser (Fluke 434B).It is shown in Figure 5.15.
(a)Without filter (b) With ANN controller based shunt active filter Figure 5.14(a) Experimental results - Source voltage and Source current waveforms for 3 thyristor converter load ( = 0)(test system II) under balanced system conditions without and with ANN controller based shunt active filter
Figure 5.14 (b) Experimental results - Source voltage and Filter current waveforms for 3 thyristor converter load ( = 0) (test system II) under balanced system conditions with ANN controller based shunt active filter
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(a)Without filter (b) With ANN controller based shunt active filter
Figure 5.15 Experimental results - Source current harmonic spectra for 3 thyristor converter load (=0) (test system II) under balanced system conditions without and with
ANN controller based active filter Case (ii) Thyristor converter firing angle α = 30
For another setting of firing angle at α = 30 also, ANN based shunt active filter is tested.
The source voltage and source current waveforms are shown in Figure 5.16. The
corresponding harmonic spectra are shown in Figure 5.17.
(a)Without filter (b) With ANN controller for shunt active filter Figure 5.16 Experimental results - Source voltage and Source current waveforms for 3 thyristor converter load ( =30) (test system II) under balanced system conditions without and with ANN controller based shunt active filter
(a)Without filter (b) With ANN Controller for shunt active filter
Figure 5.17 Experimental results - Source current harmonic spectra for 3 thyristor converter load (=30) (test system II) under balanced system conditions without and with ANN controller based shunt active filter
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Case (iii) Thyristor converter firing angle α = 45
Firing angle of thyristor converter is changed to 45 and to meet harmonic and reactive
compensation, 5F – 60mH is inserted by the controller. The corresponding source voltage
and source current waveforms are shown in Figure 5.18. Source current harmonic spectra
are shown in Figure 5.19.
(a)Without filter (b) With ANN controller based shunt active filter Figure 5.18 Experimental results - Source voltage and Source current waveforms for 3 thyristor converter load ( = 45) (test system II) under balanced system conditions without and with ANN controller based shunt active filter
(a)Without filter (b) With ANN controller based shunt active filter
Figure 5.19 Experimental results - Source current harmonic spectra for 3 thyristor converter load (=45) (test system II) under balanced system conditions without and with ANN controller based active filter
The above simulation and experimental results show that the ANN based digital controller
reduces harmonic distortion in the source currents and reactive power drawn from supply
under steady state load conditions. However, ANN controller takes almost 2 cycles for
effective compensation. In order to evaluate its performance, the controller must be tried on
dynamic load, which is explained in next section.
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5.5 Dynamic state harmonics - Simulation analysis
The effectiveness of ANN controller based shunt active filter under dynamic conditions is
also studied by simulation and laboratory testing. For dynamic state harmonic analysis, the
following loads are considered.
(i) DC motor fed through three phase thyristor converter
(ii) Three phase induction motor driven by thyristor phase controller
5.5.1 DC motor fed through three phase thyristor converter
Test system mentioned in 4.5.1 is used in this case. For convenience, the specifications are
mentioned repeatedly. Three phase 400V AC 50Hz voltage source is connected through
three phase thyristor converter to separately excited 5HP, 1750 RPM DC motor (test
system IV). Field winding is supplied from 220V DC field voltage source. The
effectiveness of ANN controller based shunt active filter is tested as explained in next
section.
5.5.1.1 Performance of ANN controller for shunt active filter –Simulation analysis
The effect of change in triggering angle of thyristor converter on harmonic compensation
characteristics of the ANN controller based shunt active filter is studied. The reduction in
the firing angle caused reduction in armature voltage drop and hence reduction in the load
current and source current. The corresponding waveforms are also recorded. These
instantaneous source voltages, load currents and compensation currents are sampled and
used for training ANN as explained in section 5.3.2. The ANN controller based shunt
active filter was simulated using MATLAB/SIMULINK and used in the system to
compensate for harmonics and reactive power under dynamic states.
The simulation analysis is conducted as explained below:
Initially the firing angle of thyristor converter is changed from α = 30 to α = 45 and
corresponding dynamic and steady state responses without and with ANN controlled shunt
active filter were observed under balanced source conditions specified in 4.3.1.1. Later,
triggering angle is changed from 30⁰ to 60⁰ and corresponding responses were also
observed. The significant parameters - fundamental component of source current, and THD
in source current – under steady state conditions are tabulated in Table 5.8 (base kVA =
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5kVA, base kV = 400V). Figure 5.20, and Figure 5.21 show source voltage, load current
and source current for phase a with the installation of ANN controller based shunt active
filter under dynamic conditions. However, on observing the waveforms, one can conclude
that filter current waveform is adjusted in every cycle so that source current is sinusoidal.
Table 5.8 Simulation analysis - Fundamental source current, and THD in source current for DC drive load without and with ANN controlled shunt active filter – Steady state conditions Firing angle
α
Filter status
Fundamental component of source current (p.u.) THD in source current (%)
Phase a Phase b Phase c Phase a Phase b Phase c
45⁰ without filter 0.68 0.68 0.68 27.59 27.59 27.59
with ANN controlled shunt active filer 0.48 0.48 0.48 4.98 4.99 4.98
60⁰
without filter 0.45 0.45 0.45 40.31 40.31 40.31
with ANN controlled shunt active filer 0.225 0.225 0.225 4.96 4.96 4.96
Figure 5.20 Simulation analysis – Source voltage, Load current, Filter current, and Source current waveforms for DC motor drive load(Case I) under balanced system with ANN controller based shunt active filter – dynamic conditions
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Figure 5.21 Simulation analysis – Source voltage, Load current, Filter current, and Source current waveforms for DC motor drive load(Case II) under balanced system with ANN controller based shunt active filter – dynamic conditions
5.5.2 Induction motor drive
Test system mentioned in 4.5.2 is used in this case. A three phase 400V,50Hz balanced
source connected to AC Voltage regulator fed induction motor (415V, 4.8A, 2.2kW) is
selected as the nonlinear load(test system V). The source impedance is selected as 0.05 p.u.
The specifications of the induction motor drive system used for testing the performance of
the ANN controller based shunt active filter are given in Appendix 1. The induction motor
drive system is controlled by AC phase controller. The simulation studies for checking the
performance of ANN controller based shunt active filter is described in section 5.5.2.1.
5.5.2.1 Performance of ANN controlled shunt active filter – Simulation analysis
The simulation analysis is conducted as explained below:
Initially the firing angle of thyristor converter is changed from α = 30 to α = 45 and
corresponding dynamic and steady state responses without and with ANN controlled shunt
active filter were observed under balanced source conditions specified in 4.3.1.1. Later,
triggering angle is changed from 30⁰ to 60⁰ and corresponding responses were also
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observed. The significant parameters - fundamental source current, and THD in source
current – under steady state conditions are tabulated in Table 5.9 (base kVA = 2.5kVA ,
base kV = 400V). Figure 5.22, and Figure 5.23 show source voltage, load current and
source current for phase a with the installation of ANN controller based shunt active filter
under dynamic conditions. The performance of ANN controller based shunt active filter is
verified with the sinusoidal source currents in phase with source voltage.
Table 5.9 Simulation analysis - Fundamental Source current, and THD in source current for induction motor drive load without and with ANN controlled shunt active filter – Steady state conditions Firing angle
α
Filter status
Fundamental component of source current (p.u.) THD in source current (%)
Phase a Phase b Phase c Phase a Phase b Phase c
45⁰ without filter 0.73 0.73 0.73 37.59 37.59 37.59
with ANN controlled shunt active filer 0.516 0.516 0.516 4.87 4.87 4.87
60⁰ without filter 0.61 0.61 0.61 47.13 47.13 47.13
with ANN controlled shunt active filer 0.305 0.305 0.305 4.35 4.35 4.35
Figure 5.22 Simulation analysis – Source voltage, Load current, Filter current, Source current waveforms for induction motor drive load (Case I) under balanced system with ANN controller based shunt active filter –dynamic conditions
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Figure 5.23 Simulation analysis – Source voltage, Load current, Filter current, Source current waveforms for induction motor drive load (Case II) under balanced system with ANN controller based shunt active filter – dynamic conditions
5.6 Dynamic state harmonics - Experimental verification
5.6.1 DC motor fed through three phase thyristor converter
The performance of the ANN controller based shunt active filter under dynamic conditions
is experimentally verified in the laboratory with seperately excited DC motor having the
same specifications as the one used for simulation studies(test system IV).When subjected
to change in the firing angle of thyristor converter from α = 30⁰ to α = 60⁰, the source
current varies in magnitude and is distorted as shown in Figure 5.24(a).The three phase
ANN controller based shunt active filter is implemented in the laboratory as explained in
section 5.4. The active filter helps in harmonic reduction and reactive power compensation
as seen in Figure 5.24(b).
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(a) Without Filter (b) With ANN Controller based shunt active filter
Figure 5.24 Experimental results – Source current waveforms for DC drive load (Case I) under balanced system conditions without and with ANN controller based shunt active filter– dynamic conditions
5.6.2 Three phase induction motor driven by thyristor phase controller
The effectiveness of the ANN controller based shunt active filter is checked with the three
phase induction motor drive of identical rating as the one used for simulation studies (same
as specified in the section 4.5.2-test system V). The induction motor drive system is set up
in the laboratory. When the firing angle of phase controller is varied from α = 0 to α = 60,
the source current varies in magnitude and is distorted as shown in Figure 5.25 (a). The
ANN controller based shunt active filter, is used for source current harmonic mitigation.
With the addition of the shunt active filter, the source current harmonics are reduced as
seen in Figure 5.25 (b).The performance of the shunt active filter is satisfactory.
(a)Without filter (b) With ANN controller based shunt active filter Figure 5.25 Experimental results - Source current waveforms for the induction motor drive load (Case II) under balanced system without and with ANN Controller based shunt active filter – dynamic conditions
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5.7 Discussion The author verified the performance of the ANN controller based shunt active filter with
balanced/unbalanced system under steady state and dynamic conditions. Having seen the
performance, the author felt it is necessary to compare the simulation results of various
types of filters used in the work. This is to examine whether ANN controlled shunt active
filter is superior to other type of filters. A filter having capabilities of harmonic mitigation
and reactive power compensation, with reduced active filter rating, are the objectives of
research work. Therefore, author selected the comparison parameters as
(i) fundamental source currents, (ii) reactive power drawn from supply, (iii) source power
factor, and (iv) active filter current.
The performance of three phase ac source feeding nonlinear load without any filter is
compared with
(i) conventional shunt passive filter with 5th and 7th harmonic compensators
(ii) adaptive shunt passive filter with ANN controller
(iii) shunt active filter with analog Icos controller
(iv) shunt active filter controlled by ANN controller
For comparative study, three phase thyristor converter fed R-L load (test system I) is taken
as non-linear load. Table 5.10 shows comparative study of significant parameters for
thyristor converter load (α = 0, 30, and 60) under balanced system conditions.
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Table 5.10 (a) Simulation analysis – Fund. Source current, reactive power drawn from supply, source power factor, THD in source current, etc. for thyristor converter fed R-L load ( = 0) without filter, with fixed element passive filter, with adaptive shunt passive filter, with analog Icos controller based shunt active filter and with ANN controller based shunt active filter -under balanced steady state conditions.
Filter Configuration
Without filter
With fixed element passive filter
With adaptive shunt passive filter
With analog Icoscontroller based shunt active filter
With ANN controller based shunt active filter
Fundamental source current (p.u) 0.778 0.875 0.784 0.780 0.780
Fundamental frequency reactive power(p.u) drawn from supply
0.0 0.4 0.1 0.0 0.0
Source power factor 0.983 0.888 0.989 almost unity almost unity
THD in source current (%)
18.43% 3.27% 4.08% 1.16% 3.16%
Active filter current (p.u.) NA NA NA 0.12 0.13
Harmonic elimination NA
reduces tuned harmonic components
reduces tuned harmonic components
well within IEEE standard limits
within IEEE standard limits
Size of compensator NA
passive filter is bulky in size. requires no controller circuit
passive filter is bulky in size. requires controller, which occupies less space
active filter requires analog controller, which is large in size.
digital controller used requires less space, more flexible and can be reproduced in large quantities.
Response time (approx.)
NA almost instantaneous two cycles one cycle two cycles
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Table.5.10 (b) Triggering angle of thyristor converter (α = 30)
Filter configuration
Without filter
With fixed element passive filter
With adaptive shunt passive filter
With analog Icoscontroller based shunt active filter
With ANN controller based shunt active filter
Fundamental source current
(p.u) 0.669 0.582 0.579 0.579 0.580
Fundamental frequency reactive
power(p.u) drawn from
supply
0.33 0.07 0.03 0.00 0.00
Source power factor
0.839 0.992 0.995 almost unity almost unity
THD in source current
(%) 25.81% 5.87% 5.34% 1.79% 4.29%
Active filter current (p.u.)
NA NA NA 0.343 0.345
Harmonic elimination
NA
reduces tuned
harmonic
components
reduces
tuned
harmonic
components
well within
IEEE standard
limits
within IEEE
standard
limits
Size of compensator NA
passive filter
is bulky in
size. requires
no controller
circuit
passive filter
is bulky in
size. requires
controller
which
occupies less
space
active filter
requires analog
controller,
which is large
in size.
digital
controller
used requires
less space,
more flexible
and can be
reproduced
in large
quantities.
Response time
(approx.) NA
almost
instantaneous two cycles one cycle two cycles
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Table.5.10(c) Triggering angle of thyristor converter (α = 60)
Filter Configuration
Without filter
With fixed element passive filter
With adaptive shunt passive filter
With analog Icoscontroller based shunt active filter
With ANN controller based shunt active filter
Fundamental source current (p.u)
0.382 0.203 0.193 0.190 0.190
Fundamental frequency reactive power(p.u) drawn from supply
0.33 0.07 0.03 0.00 0.00
Source power factor
0.477 0.935 0.976 almost unity almost unity
THD in source current (%)
43.94% 8.55% 8.21% 2.36% 4.26%
Active filter current (p.u.)
NA NA NA 0.263 0.270
Harmonic elimination
NA
reduces
tuned
harmonic
components
reduces
tuned
harmonic
components
well within
IEEE standard
limits
within IEEE
standard limits
Size of compensator NA
passive filter
is bulky in
size. requires
no controller
circuit
passive filter
is bulky in
size.
requires
controller
which
occupies less
space
active filter
requires
analog
controller,
which is large
in size.
digital
controller used
requires less
space, more
flexible and can
be reproduced
in large
quantities.
Response time (approx.)
NA almost
instantaneous two cycles one cycle two cycles
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Comparing the performances, it is obvious that shunt active filter with Icos controller or
shunt active filter with ANN controller are much better harmonic and reactive
compensation schemes, when compared with the adaptive shunt passive filter. Of the shunt
active filter configurations, the THD of source current with ANN controller based shunt
active filter is higher than the analog Icos controller based shunt active filter, yet THD is
within IEEE Standard limits. Considering the flexibility of the controller used, two filter
configurations - adaptive shunt passive filter and ANN controller based shunt active filter –
are selected for comparison. The three significant parameters, namely, source current,
reactive power drawn from supply and source power factor are compared for these two
filter configurations. The % saving in parameters are defined below:
These parameters are calculated based on the simulation results shown in Table 5.10. The
results are tabulated in Table 5.11.
Table 5.11 Simulation analysis - % reduction in fundamental source current, reactive power drawn from supply and improvement in source power factor with ANN controller based shunt active filter when compared to the adaptive shunt passive filter for thyristor converter load under balanced system conditions
The comparison parameters in equations (5.1) to (5.3) are obtained based on the
experimental results with thyristor converter load. These results are shown in Table 5.12.
Table 5.12 Experimental results - Comparison table – % reduction in fundamental source current, reactive power drawn from supply and improvement in source power factor with ANN controller based shunt active filter compared to adaptive shunt passive filter for thyristor converter load under balanced system conditions
