Abstract: Widespread applications of power electronic-based loads continue to increase concerns over harmonic distortion. The Current harmonics produced by non-linear loads result in voltage distortion and leads to various power quality problems. Moreover these non-linear loads are not fixed and change randomly. However classic filters may not have satisfactory performance in such fast varying conditions. This project presents a fuzzy and nuero controlled shunt active power filter used to compensate for harmonic distortion in three-phase four-wire systems. The shunt active filter employs a simple method for the calculation of the reference compensation current based on Fast Fourier Transform. This presented filter is able to operate in both balanced and unbalanced load and also for variable load conditions. A fuzzy and nuero based current controller strategy is used to regulate the filter current and hence ensure harmonic free supply current. The validity of the approach presented in harmonic mitigation is verified via simulation results of the proposed test system under different loading conditions.
Keywords-PI controller, Fuzzy controller, ANN controller, Power factor correction, Reactive power correction, Power quality improvement.
I.INTRODUCTION
In a modern electrical distribution system, there has been a sudden increase of nonlinear loads, such as power supplies, rectifier equipment, domestic appliances, adjustable speed drives (ASD), etc. Power quality distortion has become a serious problem in electrical power systems due to the increase of nonlinear loads drawing non-sinusoidal currents. As the number of these loads increased, harmonics currents generated by these loads may become very significant. These harmonics can lead to a variety of different power system problems including the distorted voltage waveforms, equipment overheating, malfunction in system protection, excessive neutral currents, light flicker, inaccurate power flow metering, etc. They also reduce efficiency by drawing reactive current component from the distribution network. To reduce harmonic distortion and power factor improvement, capacitors are employed as passive filters. But they have the drawback of bulky size, component aging, resonance and fixed compensation performance.
Active filters have been widely used for harmonic mitigation as well as reactive power compensation, load balancing, voltage regulation, and voltage flicker
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B.Suresh Kumar and V.Lalitha are with EEE Department, CBIT, Hyderabad. (Mail:[email protected]) Dr.K.RameshReddy is with EEE Department, GNITS, Hyderabad. (Mail: [email protected])
Compensation. In three-phase four-wire systems with nonlinear loads a high level of harmonic currents has been enrolled both in the three line conductors and more significantly in the neutral wire. Unbalanced loads also results in further declination of the supply quality. Various harmonic mitigation techniques have been proposed to reduce the effect of harmonics. These techniques include phase multiplication, passive filters, active power filters (APFs), and harmonic injection. One of the most popular APFs is the shunt active power filter. It is mainly a current source, connected in parallel with the non-linear loads. Conventionally, a shunt APF is controlled in such a way as to inject harmonic and reactive compensation currents based on calculated reference currents. The injected currents are meant to cancel the harmonic and reactive currents drawn by the nonlinear loads.
II. Basic compensation principle
Fig.1 shows the basic compensation principle of the shunt APF. A current controlled voltage source inverter with necessary passive components is used as an APF [8]. It is controlled to draw/supply a compensated current from/to the utility, such that it eliminates reactive and harmonic currents of the non-linear load. Thus, the resulting total current drawn from the ac mains is sinusoidal. Ideally, the APF [6] needs to generate just enough reactive and harmonic current to compensate the non-linear loads in the line.
Fig: 1. Basic compensation principle of shunt APF
Fig: 2.Basic compensation principle of shunt APF
Control system description for Shunt APF:
The control system for shunt APF could be divided into two main stages. In the first stage the reference compensating current has to be determined, while in the second stage the derivation of the switching function for the filter inverter circuit is computed.
Reference Compensation Current Calculation:
The reference compensation current is determined mainly using the information about both the fundamental and the harmonic content of the measured load current. Several methods have been proposed in the literature for reference compensation current computation. These methods depend on either time domain or frequency domain analysis. In this paper the method utilized for reference compensation current calculation depends on Fast Fourier Transform (FFT), sort of frequency domain analysis. FFT is used to extract the magnitude of the fundamental component of the load current from which the reference compensation current will be computed.
The following equations describe the procedure used for reference compensation current calculations.
The load current is a periodic function and according to Fourier series
Where
Thus, the fundamental component magnitude of load current
The amplitude of the reference supply current is given by
Where idc is the current responsible for compensating of the dc losses due to the change in the dc capacitor voltage. Then taking the sine wave template from the supply voltage, the reference supply current will be
And From equation (1) & (4)
Therefore
Fig.3 summarizes the control strategy for shunt active power filter.
Fig: 3. The control strategy for Shunt Active Power Filter
III. PI controller
PI controller has been in use for the last few decades. It performs satisfactorily during transient under limited operating range. Also steady state performance is excellent. Implementation in analog or digital hardware is inexpensive and straight forward. Since PI controller is based on linear model, response for large signal disturbance is poor. The gains Kp and Ki are constants and they are fine tuned for specific operating condition.
IV. Fuzzy Logic Controller
In recent times Fuzzy logic controllers have generated a good deal of interest in certain applications. The advantages of FLC over the conventional controllers are: it doesn't need accurate mathematical model, it can work with imprecise inputs, it can handle non linearity and it is more robust than conventional nonlinear controllers.
FLC in power electronics have been designed by trial and error. Power converters are inherently nonlinear. The causes of non linearity in the power converters include variable structure within a single switching period, saturating inductances, voltage clamping etc, with the advent of resonant converters, power converters are getting complicated, resulting in complex mathematical models. The FLC seems to be a viable controller for Power Electronic
applications.FLC is feasible and has good potential for power electronic circuits.
Fuzzy logic control is a new addition to control theory. Its design philosophy deviates from all the previous methods by accommodating expert knowledge in controller design. Fuzzy Logic control is derived from fuzzy set theory introduced by Zadeh in 1965. In Fuzzy set theory, the transition between membership and non membership can be gradual. Therefore, boundaries of fuzzy sets can be vague and ambiguous, making it useful for approximate systems.
FLC is an attractive choice when precise mathematical formulations are not possible. It can work with less precise inputs. It doesn't need fast processors. It needs less data storage in the form of membership functions and rules than conventional look up table for nonlinear controllers. It is more robust than other nonlinear controllers.
Reference input is compared with the regulated output to produce an error. The error is fed to Fuzzy Logic Controller [1], which performs calculations to generate output. This is called fuzzy inference process and requires three basic steps. The FLC has three functional blocks for calculation and two data base. The functional blocks in FLC are: Fuzzifier, Rule evaluator and Defuzzifier. The two databases are Rule base and Database. The functional block diagram of FLC is shown in fig4.
Fig: 4. internal structure of FLC
The desired switching signals for the filter inverter circuit are determined according to the error in the filter current using fuzzy logic controller. The parameters for the fuzzy logic current controller used in this paper are as follows: The design uses centroid defuzzification method. There are two inputs: error and its derivative and one output, which is the command signal to the PWM of the filter inverter. The two input uses Gaussian membership functions while the output use triangle membership function. The fuzzy rules are given in the table1, and the formation is shown in fig5.
Table:1.Fuzzy Rules Representation Table
Error
de/dt
Negative
Zero
Positive
Negative
Big Negative
Positive
Big Positive
Zero
Big Negative
Zero
Big Positive
Positive
Big Negative
Negative
Big Positive
Fig: 5. Fuzzy Rules formation
V. Neural Controller
This paper proposes the use of an artificial neural network (ANN) technique. This neural controller is trained with the Levenberg-Marquardt feed forward back propagation algorithm.The proposed method uses ANN algorithm to compute the harmonic current and reactive power for the nonlinear loads. With the use of this ANN controller, the shunt active filter can be made adaptive to variations in nonlinear load currents. It can also compensate for unbalanced nonlinear load currents. It can also correct power factor of the supply side near to unity. It also has the capability to regulate the dc capacitor voltage at the desired level. Computer simulations are carried out to verify an active filter performance. Fig.8.Shows the general structure of back propagation layered neural network.
The neural controller uses feed forward back propagation algorithm. The inputs to the neural controller are the filter error and its derivative and output is the conduction time of the switches.
These inputs and outputs obtained are given to neural network tool box where the training process takes place using back propagation algorithm (training of the data until minimum error is obtained) and the outputs are given as pulses to IGBT's in the shunt active filter. In the shunt active filter which acts as a voltage source converter the capacitor voltage is maintained constant and the inductor current is made equal in magnitude but opposite in phase to that of the load current consisting of harmonics. So, the harmonics injected by the load current in the supply current are cancelled by the negative harmonics injected by the filter output current thereby, resulting in the harmonic reduction [7].
The following diagrams fig.6. Represent the FFT analysis for different loads with different control schemes for shunt active filter.
Fig.7. Simulink model of shunt active power filter using PI,FUZZY and ANN controllers with balanced, unbalanced and variable nonlinear models.
Vs
170v
Ls
1mH
Lf
4mH
Lr
2mH
Load
Rr=50Ω
Simulation Parameters:
Table: 2. Balanced Load
Table: 3. Unbalanced Load
Vs
170v
Ls
1mH
Lf
4mH
Lr
2mH
Loads
Load1:Rr=50Ω
Load2:R2=15 Ω
Load3:R3=15Ω,
L3=0.1H
Vs
170v
Ls
1mH
Lf
4mH
Lr
1mH
Variable Load
Vdc=120v,R=1Ω,L=20mH
Table: 4.Parameters in case of Variable Load
IL
Vd
Id
Simulation Results
IL
IF
IS
Time (sec)
Fig: 9 Wave forms of balanced non linear load under PI control
IL
IF
IS
Time (sec)
Fig: 10 Wave forms of unbalanced non linear load under PI control
IL
IF
IS
Time (sec)
Fig: 11 Wave forms of variable non linear load under PI control
Time (sec)
Fig: 12 Wave forms of variable non linear load
IL
IF
IS
Time (sec)
Fig: 13 Wave forms of balanced non linear load under FUZZY control
IL
IF
IS
IL
IF
IS
Time (sec)
Fig: 14 Wave forms of unbalanced non linear load under FUZZY control
IL
IF
IS
IL
IF
IS
Time (sec)
Fig: 15 Wave forms of variable non linear load under FUZZY control
IL
IF
IS
Time (sec)
Fig: 16 Wave forms of balanced non linear load under ANN control
Time (sec)
Fig: 17 Wave forms of unbalanced non linear load under ANN control
Time (sec)
Fig: 18 Wave of variable non linear load under ANN control
Table: 5 Results with Balanced load
CONTROLSCHEME
With Filter
With Out
Filter
%THD
P.f
Reactive
Power
%THD
P.f
Reactive
Power
PI control
4.94
0.850
51.12
99.64
0.611
125.9
Fuzzy
control
2.82
0.9727
17.62
94.57
0.6619
125.9
ANN control
1.35
0.992
23.02
94.96
0.662
125.9
Table: 6 Results with Unbalanced load
CONTROLSCHEME
With Filter
With Out
Filter
%THD
P.f
Reactive
Power
%THD
P.f
Reactive
Power
PI control
2.84
0.972
19.38
99.64
0.660
31.67
Fuzzy
control
2.82
0.980
31.33
99.64
0.699
45.56
ANN control
2.84
0.960
34.92
99.64
0.732
31.67
Table: 7 Results with Variable load
CONTROLSCHEME
With Filter
With Out
Filter
%THD
P.f
Reactive
Power
%THD
P.f
Reactive
Power
PI control
2.82
0.923
36.76
99.64
0.652
150
Fuzzy
control
1.56
0.986
45.33
99.64
0.6619
200
ANN control
1.28
0.992
88.60
99.64
0.662
190
VI.CONCLUSIONS
The Fuzzy and ANN controllers of Shunt Active Power filter are designed. The proposed control technique is found satisfactory to mitigate harmonics from utility current especially under variable load condition. Thus, the resulting total current drawn from the ac mains is sinusoidal. Fuzzy and Nuero controller improves the overall control system performance over other conventional controller. The validity of the presented controllers was proved by simulation of a three phase four wire test system under balanced, unbalanced and variable loading conditions. The proposed shunt active filter compensate for balance and unbalanced nonlinear load currents, adapt itself to compensate variations in non linear load currents, and correct power factor of the supply side near to unity. Proposed APF topology limits THD percentage of source current under limits of IEEE-519 standard.THD percentage of source current under PI, Fuzzy and ANN controllers are compared. It has also been observed that reactive power compensation has improved leading to power factor improvement These comparisons conclude that ANN controller is better choice than fuzzy controller.
VII.REFERENCES
[1] B. K. Bose, Expert Systems, Fuzzy Logic and Neural Network Application in Power Electronics and Motion Control. Piscataway, NJ: IEEE Press, 1999, ch.11.
[2] V. S. C. Raviraj and P. C. Sen, "Comparative study of proportional integral,
sliding mode, and fuzzy logic controllers for power converters," IEEE Trans. Ind. Appl., vol. 33, no. 2, pp. 518-524, Mar./Apr. 1997.
[3] C. N. Bhende, S. Mishra, and S. K. Jain, "TS-Fuzzy-Controlled Active Power Filter for Load Compensation", IEEE Transactions on Power Delivery, Vol. 21,No. 3, July. 2006.
[4]"Active filter for power quality improvement by artificial neural networks technique"by M.A.Farahat,A.Zobah,Zagazig University .
[5] G. K. Singh, "Power system harmonics research: a survey" European Transactions on Electrical Power, 2009 Page(s):151 - 172.
[6] A. Emadi, A. Nasiri, S. Bekiarov, Uninterruptible Power Supplies and Active Filters. CRC Press, 2005, ch. 2.
[7] S. Rechka, E. Ngandui, Jianhong Xu; P. Sicard , "A comparative study of harmonic detection algorithms for active filters and hybrid active filters" IEEE 33rd Annual Power Electronics Specialists Conference, 2002. Volume 1, Page(s): 357 - 363.
[8] J. S. Setiadji and H. H. Tumbelaka, "Simulation of Active Filtering Applied to A Computer Centre," Journal Technique Electro, vol. 2, pp 105-109, September 2002.
[9] "Auto Tuned Robust Active Power Filter for Power Quality Improvement under Fast Load Variation" by S. S. Mortazavi, R. Kianinezhad, A. Ghasemi.
[10]"Fuzzy Logic Controlled Shunt Active Power Filter for Three-phase Four-wire Systems with Balanced and Unbalanced Loads" .by Ahmed A. Helal, Nahla E. Zakzouk, and Yasser G. Desouky,world academy of science,2009
