JOURNAL OF SCIENCE & TECHNOLOGY * No. 79B - 2010
DERTERMINA OF COMPENSATING CURRENT FOR A SINGLE-PHASE ACTIVE POWER FILTER USING ADAPTIVE NEURAL NETWORK
XAC DINH DONG DIEN BLJ CHO B O LOC TICH Cl.lC MCJl PHA SU'DUNG MANG NO RON. THJCl 1 NGHI
Son.TNguyen, Tuan.A Phung, Khang.TNguyen, Thanh. VNguyen Hanoi I'nivcrsitv of Science and Technology
ABSTRACT
This paper presents a process of controlling an active power filter for single phase. The active filter is based on a single phase inverter with four controllable switches, a standard H inverter The AC side of the inverter is connected in parallel with an AC controller as the non-linear load through a smoothing inductor The DC side of the inverter is connected to a filter capacitor The control module consists of two parts: the first part is responsible for calculating the compensating current for the filter using an adaptive linear neural network and the second part is developed for stabilizing DC bus voltage and shaping the current via the inductor. The adaptive neural network is trained using modified W-H learning algorithm. The system is modeled in Matlab Simulink and simulation results prove that the injected harmonics are greatly reduced.
TOM T A T
Bai bdo nay tnnh bay quy tnnh diiu khiin bd loc tich cwc mdt pha. Bd loc tich cwc dwgc dwa tren mot bd nghich Iwu mdt pha v&i bdn khda diiu khiin dwgc hay cdn goi Id bd nghich Iwu H chuin.
Phia xoay chiiu ciia bd nghich Iwu dwgc ndi song song v&i mdt bd diiu dp xoay chiiu mdt pha qua mdt cudn khdng loc. Phia mdt chiiu ciia bd nghich Iwu dwgc ndi v&i mdt tu loc. Khdi diiu khiin bao gdm hai phin: Phin thir nhit Idm nhiem vu tinh toan ddng dien bu cua bd loc sir dung mdt mang na ron tuyin tinh thich nghi vd phin thir hai lam nhiem vu dn dinh dien dp phia mdt chiiu va nin ddng dien phia xoay chiiu cua bd loc theo ddng dien bu tinh toan a phin thir nhit. Mang na ron tuyin tinh thich nghi dwgc huin luyen bing thudn todn hoc W-H cai tiin. Todn bd qud trinh lam viec cua bd loc tich cwc dwgc md hinh hda trong Matlab Simulink va kit qua md phdng cho thiy cdc thanh phin hai giam ddng ki khi sir dung bd loc tich cwc.
I. INTRODUCTION
The widespread use of power electronic equipment causes the distortion of power lines or non-sinusoidal voltage and current simply because those equipment work as non-linear load. The distortion of the line current causes harmonic components. On the other hand, harmonics causes unwanted losses, equipment vibration, interfere of measurement devices.
One of the solutions for eliminating the harmonic components is using active power filters connected in paralell with non-linear loads. The function of the active filter is generating the compensating current for eliminating harmonics. The compensafing current is the invert current of the load current [1-3].
There are several methods for harmonic analyzing such as Fast Fourier Transform
(FFT), instantaneous power theory, synchronous d-q coordinates. In FFT. e.xact calculation requires two sampling cycles: one cycle for acquiring data and another cycle for analyzing data. For other methods, realizations are complicated [4].
The use of an adaptive linear neural network can be seen as the fast method of calculating harmonics. In this paper, the harmonic components are eliminated by using an adaptive linear neural network. The main advantage of this method is that harmonic components can be extracted within one sampling cycle
The paper is organized as follows. Part II presents the determination of the compensating current based on the adaptive linear neural network with modified Widrow-Hoff (W-H) learning algorithm. In part III, the control 61
JOURNAL OF SC lENCE & T E C H N O I A M , Y * i>o. / v u - 2uiu
algorithm of the compensating current and dc bus voltage is described. Part IV shows steps of simulation and related results. Finally, Part V is the conclusion of this research.
IL DETERMING TIIE COMPENSATINC;
CIRREM USING AN ADAPTIVE LINEAR NEURAL NETWORK
As wc know, a non-sinusoidal current can be expressed as follows:
i{t)^Y.'^os{na)t-(p„) (I)
Where (0~2/rf with / is the lrec|ucney of power source and (p„ is the phase angle of the n-harmonic component.
Equation (1) can be rc-wriUcn as follows:
.V
i(t) = Y,\_-'l.(^os{na)t)-\-B,,s'm(ncot)~\ (2)
/ i = i
where A,, = X„cos{(p^,), B„ = X„sm{(p„).
X^ = yJA^, -I- Bl and (p^ = arctan
Equation (2) can be re-written with the product of two vectors:
cos [cot) /•(/) = [A 5, ••• A„ 5„]
SI in(a)/) cos [ncol) s'm [ncot)
(3)
or i{t) = W'x{t) Where: ^ ' = [ 4 5,
cos [cot) s'm[cot)
(4)
x ( / ) =
cos (not) sin (ncot)
A, B,,] (5)
(6)
At discrete time / = kT with /: = 1,2,3,...and 7' is the sampling interval, equation (3) becomes:
i{kT) = \A, IJ, • A„ B„]
cos {(okT) s'm[a)kT)
(7) cos (ncvkT) s'\n [ncokT)
In (7), o) and 7'arc known, coefficients //|,7i| Ar^^r ^^^ unknown and need to be determined. Therefore, we have the topology of an adaptive linear neural network for calculating //,,/i,...., ,4„,/i„ as shown in Fig.l.
In Fig.l, l{kT) is the sampled signal of the load current and / {kT) is the estimated current of the neural network output. The error signal is defined as follows:
e(kT) = i(kT)-i^{kT) (8) The error signal ^-'{kT) is used to update
vector \V at sampling times {kT) using (Widrow-HofO algorithm. Vector W at sampling time (A: + l ) . H^. , is update according to vector W at sampling time {k).
]V.
' f ; . = ' ' * + ^ ^
^k V ;
(9) According to [5], tW-H algorithm can be adjusted as follows:
' ' ; . ! = " . +
T-^\ Yk
(IQ) Where
v^ =0,5.v,^/7(.vJ + 0,5x, (11) Where or^ is the learning rate at the sampling
time k and calculated as follows:
a,=a,+c,e,-^c,{e,-e,_,) (12) In equation (12), aQ,c, and c^ are
coefficients. Obviously, a^ depends on e^ and the change of error e^ - e^ , In other words,
a^ is the adaptive learning rate.
62
JOURNAL OF SCIENCE & TECHNOLOGY * No. 79B - 2010
\todifwJn'-ll Icarnini; algarilhm
Figure I. The adaptive linear neural network for determining the compensating current
In the deteiMTiination progress of the compensating current, we only have to consider the fundamental active current (frequency 50 Hz). Therefore, coefficient 5, is only considered. The compensating current is then computed as follows
il{t) = B,sm{cot)-l{t) (13) In discrete fime, equafion (13) becomes
ll{kT) = B,sm{ojkT)-i{kT) (14) Equafion (14) is the equation for .determining the compensating current of the
acfive filter.
III. CONTROLLING THE COMPENSATING CURRENT AND
S T A B L I Z I N G THE DC BUS VOLTAGE After determining the compensating current, the next step is choosing the control strategy for four DFET switches of the H- bridge as shown in Figure.2. In order to exactly compensate hamionics anytime, the dc bus voltage has to be always higher the maximum value of the source voltage.
The procedure of controlling the compensating current via the inductor and stabilizing the dc bus voltage is shown in Figure.3. Two outputs Q and Q are used to control switches 5", and S2. Two switches S^
and S^ open or close according to signs of the source voltage. In particular, .V, closes when the source voltage is positive and .S', closes when the source voltage is negative.
' 113 '' -'
0"
Figure 2. The active filter amnected in parallel with a non-linear, which an Ai' controller
''.+-
PIcontroller
Ft.dback of the current via m iU'Ttor L
.+
CLK Q
v..
Fccdbcikofthe voltage c^'ssii^
capacitor C
Adaptive
neural network fulse general Z'"
Fepdback of:he load CU.'TC
Figure 3. The diagram of controlling the compensating current and stabilizing the dc bus voltage.
IV. SIMILATION AND RESULTS
In this part, the control algorithm of the active filter was tested in Matlab/Simulink environment. The non-linear load is a single- phase AC/AC converter with the real power of
\OkW The AC grid has the voltage of 220K,.^,, and frequency f = 50Hz The real power of the non-linear load is adjusted via the change of the firing angle of the Triac. The acfive filter has the following parameters that can be seen to be reasonable: the inductance
Z = 0,001/7 and the capacitance C = lOOO^F The simulation process consists of two steps. The first step is calculating the compensating current according to different firing angles of triac 30 ,60 ,90 and 120 Figure.4, 5, 6 and 7 are waveforms of the load
JOURNAL OF SCIENCE & TECHNOLOGY * No. 79B - 2010
current, the compensating current and the grid compensation. Table.2 is the statistic of total side current according to different llring angles harmonic distortion (THD) of the source of the triac. fable. 1 is the statistic of the highest current,
values of the source current after the
7£//)/c'.7 The highest values of the source current Table. 2 TIID of the source, current according to after compensation. different working .schemes of the load
Firing angle (a)
30"
60"
90"
The highest values of the source current after
compensation (A) 57.0^
49 30.56
13.95
Firing angle (a )
30"
60"
90"
120"
7"77D (%) without filtering 15.11 37.75 65.07 102.6
THD (%) with fiilterlng
8.17 18.13 33.86 55.68
0 0 01 0 02 0 03 0 04 OOS 0 06 0 07 0 06 0 09 0 1 ttmfl(s)
u '
0 0 01 0.02 0 03 0 04 0 05 0 06 0 07 0 08 0 09 0 1 time(s)
100
0
-100
0 0.01 0 02 0 03 0 0 4 0 05 0 0 6 0 07 0 08 0 0 9 0 1 time(s)
Figure 4. Waveforms of the currents when fiirlng Figure 5. Waveform.^ ot the currents when firing angle of triac a = 30° .• load current (above angle of triac a = 60 . load current (above curve), compensating current (michlle curve) and curve), compensating current (middle curve) and grid side current (below curve). grid side current (below curve).
\j
0 0.01 0 02 0 03 0 04 0 05 0 06 0 07 0 08 0 09 0 1 time{s)
100 r 0
•100
0 0 01 0 02 0 03 0 0 4 0 0 5 0 0 6 0 07 0 0 8 0 0 9 01 time(s)
5 0 , —
5 0 | • • • •: ' : r . 1 5 0 ^ , .—
-50i „L. .,L„ . . L „'.,. . . : . . r.^r.^-^^t7- I ' „ '- 1* . -50 I - i ' —: i - - - 0 0 01 0 02 0.03 0 04 0 05 0 06 0 07 0 08 0 09 0,1
time(s)
i, 1 1 1 i— .
0 0 01 0.02 0 03 0 04 0 05 0 06 0 07 0.08 0.09 0.1 time(s)
'O 0.01 0.02 0.03 0 04 0.05 0 06 0,07 0 08 0 09 0.1 time(s)
0 0 01 0.02 0 03 0.04 0 05 0.06 0.07 0.08 0.09 01 time(s)
Figure 6. Waveforms of the currents when firing figure 7. Waveforms of the currents when firing angle of triac a = 90° load current (above angle of triac a = \20\- load current (above curve), compensating current (middle curve) and curve), compensating current (middle curve) and grid side current (below curve). grid side current (below curve).
J O U R N A L UF SLlti-NL-E & T E C H N O L O G Y * No. 79B - 2010
V. CONCLUSIONS algorithm is easily deployed on different digital The simulation resuhs obtained show that '°"^'"°' 'y^^^'^'" "^^^ ™^ ° ^ * " ^""'"'^^ '^"^'"^"^
the use of an adaptive linear neural network ^^^"'" ^'^^ 'compensation reduces to half of THD trained by the modified W-H algorithm allows °^^'^" '"'"''^'^'''''"'''' ^^^''"' ^''^^''^'^S-
the fast and exact determination of the compensating current. Furthermore, the
REFERENCES
1. A. Dell'Aquila, A. Lecci, M. Liserre, and P Zanchetta; "Design of the optimum duty cycle for a fuzzy controlled active filter''; Proceedings of the 2000 IEEE International Symposium on Industrial Electronics, vol. 1, pp. 78 - 83, 2000.
2. R. Costa-Castello, R. Grino, R. Cardoner, and E. Fossas; "High Performance Control of a Single- Phase Shunt Active Filter''; IEEE International Symposium on Industrial Electronics, pp. 3350 3355,2007.
3. A. Dell'Aquila, A. Lecci, and V G. Monopoli; "Fuzzy controlled active filter driven by an innovative current reference for cost reduction"; Proceedings of the 2002 IEEE International Symposium on Industrial Electronics, vol. 3, pp. 948 - 952, 2002.
4. J.-Q. W. Shu-Guang Sun, Shun-Quan Shi; "Study on Two Detection Methods for Harmonics and Reactive Currents"; Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, Kunming, 12-15 July 2008, pp. 1445 - 1449, 2008.
5. P Salmeron and J. R. Vazquez; "Practical Design of a Three-Phase Active Power-Line Conditioner Controlled by Artificial Neural Networks''; IEEE Transactions on Power Delivery, Vol. 20, No. 2, April 2005, vol. 20, pp. 1037 1044,2005.
Author's address: Nguyen Thanh Son - Tel.: (+844) 3869.2511, email: nts2006(^gmail.com Hanoi University of Science and Technology
No. 1, Dai Co Viet Str., Ha Noi, Viet Nam
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