 Open Access
 Total Downloads : 272
 Authors : Le Tien Phong, Ngo Duc Minh, Nguyen Van Lien
 Paper ID : IJERTV6IS030468
 Volume & Issue : Volume 06, Issue 03 (March 2017)
 Published (First Online): 01042017
 ISSN (Online) : 22780181
 Publisher Name : IJERT
 License: This work is licensed under a Creative Commons Attribution 4.0 International License
Improving Efficiency and Response of Photovoltaic Power Generation with DC/DC Buck Converter
Le Tien Phong
Electrical Faculty
Thai Nguyen University of Technology Thai Nguyen, Viet Nam
Nguyen Van Lien
Electrical Institue
Ngo Duc Minh
Electrical Faculty
Thai Nguyen University of Technology Thai Nguyen, Viet Nam
Ha Noi University of Technology and Science Ha Noi, Viet Nam
AbstractThis paper presents two new methods using the same structure to control photovoltaic power generation. They are combined the iterative and bisectional technique with average voltage control called IBAVC method and sliding mode control called IBSMC method to capture and maintain the operation point of PVg at maximum power point with a DC/DC buck converter. The iterative and bisectional technique in maximum power point tracker is used to identify parameters at maximum power point that provides the destination for controllers basing on the analysis of moving statement of operation points, a system of equations to describe the change of its parameters and informations about intensity of solar irradiance and temperature on this generation. Simulation results show that IBAVC and IB SMC methods can bring the highest efficiency (approximately 100%). They also represents static and dynamic responses better than tradditional control methods and when it operating this generation under variable weather conditions.
Index Terms Average voltage control, iterative and bisectional technique, maximum power point, maximum power point tracker, photovoltaic power generation, sliding mode control.

INTRODUCTION
Basically, all efforts to increase efficiency of photovoltaic power generation (PVg) up to more some percentages by manufacturing meet difficuties because of limiting material and production engineering. The special characteristic of PVg is that always exists an operation state corresponding with the available maximum power. For a fixed power implement, the amount of power generating from PVg depends on value of intensity of solar irradiance (G), temperature on PVg (T) and electrical load (characterized by impedance of load gload). So, maximum power point (MPP) can be reached by combining control techniques with a maximum power point tracker (MPPT) to drive voltage, current or power at input power converters to desired values.
Average voltage control (AVC), sliding mode control (SMC) and AI (Artificial Intelligence) are often used as control techniques in systems exploiting PVg. For AVC technique, PVg is considered as a voltage source and controlled by double feedback control loops (current and voltage loops) to place output voltage of PVg at desired voltage [1], [2], [3]. For
SMC technique, destinations at any condition for PVg are often voltage, power, impedance and they are aslo sliding surfaces for controllers [411]. Above techniques only help controllers change load for PVg, so efficiency and responses in the process of exploiting PVg depend on characteristics of MPPT. Another control technique, only using AI (Artificial Intelligence), a pyranometer (PYR) and a temperature sensor (TempS), needs much time to collect data, recalculates parameters of controller corresponding to any type of PVg and require a large memory to save data acquisition [12]. Because of above reason, AVC and SMC are more popular than AI to control PVg.
Simultioneously, traditional techniques for MPPT are classified into online and offline groups. Online techniques actively change control pulse before having considerations about MPP whereas offline techniques calculate parameters at MPP in internal controllers before creating control pulse.
For online techniques, SC (ShortCircuit Current) or OV (OpenCircuit Voltage) technique causes shortcircuit or open circuit to measure value of shortcircuit current (ISC) or open circuit voltage (VOC) [13], [14]; P&O (Perturb and Observe) and INC (Incremental Conductance) try to reach to MPP by changing d (pulse control step) continuously [13], [15], [16], [17]. Another approach to find MPP is that combines P&O with AI to reduce d when the operation point is near MPP [18]. Because of being a weak generation when operating at far STC (Standard Test Condition), controllers using above techniques always make perturbation, power loss, and easily to have wrong evaluations about MPP.
For offline techniques, CV (Constant Voltage) is the simplest technique due to using only voltage sensor [13], Temp (temperature) technique only uses a temperature sensor (TempS) [19]. They also provide unexactly about MPP when real weather operation is far STC. Ref. [20] proposed another technique, called OG (Optimal Gradient), to find MPP but it has to use the simple model for PVg to reduce calculation quantity for the controller and TempS, pyranometer (PYR). Common idea for offline technique is to set a fixed value for controllers and maintain the operation point at that value to reduce pertubation in control circuit. Basing on above idea, IB
technique was introduced as an offline technique to identify exact parameters at MPP for any types of PVg and any weather conditions in own controller using the information about G, T and parameters of PVg provided by manufacturers [21]. Nowadays, PYR and TempS are more sensitive, more suitable, cheaper and more popular, so IB technique is easier to apply in system exploiting PVg.
To improve efficiency and response of PVg, it needs to be
the electric grid to have a balance power between input and output for DC/DC converter. Because of this reason, voltage at DCbus is held at a fixed value by load side.

Modelling PVg
PVg is described as the equivalent circuit in Fig. 2 [13], [15], [17].
A +
driven to new MPP immediately when having any change of (G, T) and maintain at MPP when not having any change of (G, T). To do this idea, two new methods are proposed in this paper to control PVg, called IBAVC and IBSMC. Although using the same structure, IBAVC method combines the IB
Iph Id
–
+ Diode
Ip RS
Rp
ipv
vpv
–
technique with AVC technique whereas IBSMC method combines the IB technique with SMC technique. Due to above purposes, the rest of the paper is organized as follows: Section II is for the system structure and modelling. Section III
Fig. 2. Equivalent circuit of PVg
Write Kirchhoff law equation at node A:
introduces IB technique to identify MPP. Section IV designs
vpv ipvRs
vpv ipvRs
controllers. Section V provides an illustrative example to show the effectiveness of proposed methods and Section IV presents some conclusions where the significant points and remarks of the paper are summarized.


SYSTEM STRUCTURE AND MODELLING
A. System structure
ipv Iph I0 exp 1
nV R
t p
Instantaneous power generating from PVg:
ppv vpvipv
The system structure is described in Fig. 1.
Sun
where: RS is series resistor; Rp is parallel resistor; I0 is reserve saturation current; Iph is photogenerated current; I0 is saturation current; Vt is thermal voltage of PVg; n is diode
PVg
Solar irradiance
PYR
TempS
+
–
vpv
ipv
DCbus Vdc
DC/DC
buck converter
Control signal
+
Load side
–
ideality factor.
Representing equation (1) and (2), we have vpvipv, vpvppv curves corresponding with each value of couple (G, T). Each cuve always exists a peak point called MPP and it divides two curves into two sides as Fig. 3.
Measurement m +
unit –
Controller
i p
ipv dipv 0
MPP
ipv dipv 0
G T
MPPT
mref
(0, ISC)
vpv
dvpv
vpv
dvpv
i = a.v + b
Fig. 1. System structure
where:
Impp
Linearized point
pv pv
vpvppv curve
Measurement unit collects all information about G from PYR, temperature on PVg from TempS, instantaneous current and voltage of PVg from sensors placed at output terminals.
vpvipv curve
Fig. 3. vpvipv and vpvppv curves of PVg
Vmpp
v
(VOC, 0)
MPPT uses the IB technique to calculate desired values (voltage vmpp, current impp or power Pmpp at MPP) at instantaneous time.
In fact, datasheet for each PVg only presents some basic parameters that are: short circuit current ISC, open circuit
voltage V , voltage and current at MPP (V , I ) at STC,
OC mpp mpp
The controller uses informations about m from measurement unit and mref from MPPT to evaluate and decide pulse control. For AVC controller, mref is Vmpp. For SMC controller, sliding surface is chosen because power at MPP is the destination that needs to reach at any time, so mref is Pmpp.
The DC/DC buck converter is a nonisolated converter and its output voltage is smaller than its input voltage. To operate PVg at MPP, input voltage and current of this converter is regulated corresponding with them at MPP. Moreover, to operate PVg at MPP, load side at DCbus needs to be linked to an energy storage or a DC/AC converter that is connected to
temperature coefficient of voltage CTV, current CTI and power CTP. Unknown parameters not presenting such as Iph, I0, Vt, RS, Rp can be calculated by NewtonRaphson algorithm [21].
When G and T vary in real conditions, parameters of PVg are changed by (3) [21].
Iph
G,T
G Gstc
{Iphstc1 CTI (T Tstc)}
step and bisectional technique by observing the movement of operation points in a vpvppv curve as presented in Fig. 5
(continuous arrow for present direction, dash arrow for next
G
ISC G,T ISCstc G

CTI (T Tstc)
direction), IB technique was proposed to identify MPP. It has
stc
T
two stages: the first one is that moves forward normally and the second one is that bisects as represented in Fig. 6. To excute
G,T T
Vt Vtstc
stc
this technique at any weather condition, it need to use system
G of equations (3), calculate all unknown parameters of PVg and
VOC G,T VOCstc1 CTV (T Tstc) Vt ln G
stc
use information about G, T [21]. The algorithm using IB
R p G,T R pstc
Gstc
G
technique to identify MPP for PVg at any weather condition is presented in Fig. 7 [20]
RS
G,T
RSstc
p
(i+2)
pv
(i+1)
(i+2)
p
pv
or p (i+1)
where, values of symbols having stc are defined in STC,
n is a nonlinear function and can be defined by each structure of PVg.
ppv
p
(i) pv
pv
a. Case 1 (p (i)
p (i+2)
(i+1)
< p
pv
pv
p
(i) pv
pv
< p (i+2))
p
(i+2)
C. DC/DC buck converter
A DC/DC buck converter can be modeled in small signal
p
(i) pv
pv
p
(i+1)
pv or
p
(i) pv
(i+1) ppv
pv
state or in switching state. Its electric circuit and equivalent
b. Case 2 (p (i)<p
(i+1), p (i+1)=p (i+2)) c. Case 3 (p (i)<p (i+1), p (i+1)>p (i+2))
circuit in above states are represented in Fig. 4 [1], [2], [3],
pv pv pv pv
pv pv pv pv
[22].Fig. 5. Moving statement of operation points
B SW
+
R, L
DCbus +
ppv
move forward normally
bisect
PVg
C Diode
–

Electric circuit
~
D – + +
ipv
~
C Vdc
–
R, L
~
iL
1
2
V V/2
Fig. 6. The process of identifying MPP using IB technique
vpv
PVg
~
vpv
~ ~ iL d
C
Vpvd
~vdc
–
C Vdc
Start
Enter parameters of PVg
(i)
pv
Calculate value of ppv
Set initial value of v (i)

Equivalent circuit in small signal state
ipv
B iL iC
R, L
ipv
iC
iL R, L
v (i+2) = v (i) + 2V
pv pv
v (i+1) = v (i) + V
i=i+1
N
PVg
vpv
C Vdc
PVg
vpv C
Vdc
pv pv
pv pv
Calculate i (i+1), i (i+2)
p (i+3)max{p (i), p (i)
, p (i+2)}<

Equivalent circuit when SW on

Equivalent circuit when SW off
pv pv
p (i+1), p (i+2)
pv pv
pv +1
pv
Y
i=i+1
Stop
Fig. 4. Modelling a DC/DC buck converter
pv
(i+3) =
vpv
Where, small signal state is to obtain a smallsignal transfer function and switching states is to write system of state equations. In Fig. 4, symbols having ~ are defined in small
(i) (i+1) Y
p = p
pv pv
v (i+2)+0.5V
N
p (i)< p (i+1) N
Pmpp=p (i+2)
pv
pv
Vmpp=v (i+2)
(i+3)
Calculate ppv
signal state or small variation of variables when pulse control
changes, Vdc is output voltage of converter held at fixed value, Vpv=Vdc/D and Ipv are average values (D is voltage
pv
Y (i+1)
pv
pv pv
v (i+3)=v (i+1)0.5V
Y
pv pv
v (i+3)=v (i+1)+0.5V
(i+2) N
transformation ratio corresponding with continuous state).
ppv
< ppv



MPPT
pv
Because of the complexity of equation (1), Vmpp and Impp cant be identified by solving equation dppv/dvpv=0. Using
Fig. 7. Algorithm using IB technique to find MPP
where: V is value of voltage step.
detective technique for identifying couple of (v
(i), i(i)) at ith
To ensure the convergence for this algorithm, V should be chosen smaller than (VOC – Vmpp). Advantages of this technique are that can apply for any type of PVg and calculate parameters at MPP in selfprocessor very fast whenever having any change of (G, T).
Current controller Gci:
Gci
Kip

Kii
s


DESIGN CONTROLLER
where, Kip
T1 2K T
, Kii
1
2K T

AVC Controller
The structure of AVC controller is presented in Fig. 8 [1], [2], [3].
1 2 1 2
Linearize at stable point (MPP), we have the relation of vpv and ipv:
PWM
BB DC/DC
buck
V + iLref + d iL
mpp
–
Gcu Gci
–
vpv
where,
ipv avpv b
Fig. 8. Control structure of BSAVC method
The relationships of quantities in Fig 4b are described by
I0
Vmpp ImppRS 1
di

exp
V nV R
system of equations (4):
a pv
t t p 0
dvpv
I R Vmpp ImppRS R
~ ~ ~ ~
mpp
1 0
Vt
S exp
nVt
S
R p
vpv Vpv vpv,ipv Ipv ipv,iL IL iL , d D d
where, d is duty cycle of pulse control.
Impp aVmpp b
Substituting equation (12) into equation (6) and using
Write Kirchhoff laws at DCbus side and bus B in Fig. 4b:
Laplace transform and conditions: ILD Ipv aVpv b ,~ ~ 0 , ~ 0 ,we have voltage transfer function:
L diL
dt
vpvd

Vdc
iLd d
~vpv

D / a

iC ipv
iLd
Gui ~
iL
1 C s a
Substituting equation (4) into equation (5) and using Laplace
~ ~ Opencurrent control loop at MPP:
transform and conditions: Vdc=DVpvRIL, vpvd 0 , we have:
~ ~ ~
G D / a 1 K2
dt
(R sL) iL Vpvd vpvD
1 C s 1 L Ls
(1 T3s)(1 T4s)
For current control loop, we have
~vpv 0 and current
a VpvKpi
transfer function is:
Gid
~
~
iL
d
Vpv R sL
where, K2= D/a, T3= – C/a, T4=L/(Vmpp.Kpi) Voltage controller Gcu:
u
G K Kpu cu pu T s
PWM pulse transfer function for current loop:
PWM
G 1
where, Kup
T3
2K T
, Kui
1
2K T
1 0.5TSs
2 4 2 4
where: TS=1/fS is time of pulse cycle. Opencurrent control loop at MPP:
Under variable weather conditions, AVC controller needs to recalculate Kip, Kii of Gci, Kup, Kui of Gcu basing on values of Vmpp and Impp at each new MPP provided by IB technique, so it is also an adaptive controller.
Gih
GidG
P WM
K1
(1 T1s)(1 T2s)


SMC controller

System of state equations
Write Kirchhoff laws in two cases of SW on (u=1) and SW
where, K1=Vmpp/R, T1=L/R, T2=TS/2.
off (u=0) [22]:
dvpv
C dt
ipv iL u
Because of (22), convergent.

0
and the sliding mode process is
di
RiL L L Vdc vpvu

When the operation is at the right side of MPP and needs to move MPP, we have (23) [4], [13], [17]:

dt
Rewrite system of equations (17), we have system of state
dvpv 0, ipv dipv 0, p P 0
equations (18):
dt vpv
dvpv
pv mpp
x ipv x 2 u
Because of (23),
SS 0
and the sliding mode process is
1 C C
x 2 dc iL 1 u
V R x
L L L
convergent.
4) Equivalent control signal:
Equivalent control signal u

is the equivalance between
where, x= [x1 x2] = [vpv iL] is state vector,
eq
an infinite frequency switched control input (0, 1) and a smooth feedback control. ueq(t) is considered as a smooth
f (x)
ipv
C
is drift vector field,
feedback control law to maintain ideal state trajectory along S
[23]. Value of ueq(t) is determined by (24):Vdc R x L S
L
L 2
0 ueq (t) f 1
LgS
x2
where:
g(x)
C
is control input vector field.
x1
L
Lf S
S f (x) is deriavation of S in the direction of f(x);
xT


Sliding surface
Because of the purpose that reaches to MPP (mref = Pmpp) at any time, we choose the following sliding surface (20):
L S S g(x) is deriavation of S in the direction of g(x).
g xT
Applying for DC/DC buck converter, we have:
S ppv Pmpp
1
x 2
ipv
where, Pmpp is value of power at MPP (result of IB algorithm) needing to reach at that time (considered as a constant at each
LgS
C ipv x1 x
time).
ipv
ipv
1

Stability analysis

According to Lyapunov theory, sliding process will be stable
Lf S C ipv x1 x
if S.S 0 [22]. We have:
S d(ppv Pmpp ) S dvpv v
ipv dipv
From (25) and (26), ueq(t) is determined by (27):
ipv
dt
dt
so,
v
pv
pv
dvpv
5) Control strategy
ueq (t)
i
L
dt
S.S dvpv v
ipv dipv

P )
Control strategy for IBSMC method is reprented in Fig. 9.
dvpv
v
pv
pv
(ppv
mpp

When the operation is at the left side of MPP and needs to move MPP, we have (22) [4] , [13], [17]:
dvpv 0, ipv dipv 0, p P 0
dt vpv
dvpv
pv mpp
Measure G, T
Start
Two offline techniques (CV, Temp) and two online techniques (OV, P&O) using AVC controllers are used to evaluate proposed control methods. Control parameters for above methods are represented in TABLE III.
MPPT (IB algorithm)
TABLE III. CONTROL PARAMETERS OF CVAVC, TEMPAVC,
Control method
Control parameters
CVAVC
VmppCV=24.2 V; Kip = 0.2075; Kii = 4.149;
Kup = 1.004; Kui = 222.2 (Fixed values)
TempAVC (Adaptive controller)
Vmpptemp=Vmppstc(1+Ctv(T25))
OVAVC
(Adaptive controller)
VmppOV=0.8VOCG,T; Sample time: 0.4 s
Closecircuit time: 0.3 s; Opencircuit time:
0.1 s
P&O
Width pulse control step: d=0.2%
OVAVC, P&O
Pmpp
Determine ueq(t) (SMC technique)
Send control pulse to SW
Measure vpv, ipv Calculate ppv=vpvipv
ppv=Pmpp N
Y
Hold ueq(t)=ueqmpp at ppv=Pmpp
Change G, T? Y
N
Electric energy A(t) each second received from PVg in range time (0t) is calculated by (29) and efficiency H% for each control method is calculated by (30):
Y Continue? N Stop t
Fig. 9. Control strategy for IBSMC method


SIMULATION
A(t) ppv (t)dt
0

Simulation parameters
Parameters of converter, DCbus, and switching frequency are represented in TABLE I. Parameters of PVg type

Simulation results
H%
A(t) 100%
Ampp
MF165EB3 are represented in TABLE II and n(T) is defined by (28).
TABLE I. PARAMETERS OF CONVERTER, DCbus AND SWITCHING FREQUENCY
To see static and dynamic repsonses and received energy of PVg, a sample scenario for weather condition is considered when T=400C and the variation of G is represented in Fig. 10.
G (W/m2)
1000
900
800
TABLE II. PARAMETERS OF MF165EB3 AT STC
0 0.5 1 1.5 2 2.5 3
Symbol
Value
DC/DC buck converter
R ()
0.01
L (H)
5.103
C (F)
103
Voltage at DCbus
Vdc (V)
12
Switching frequency
fS (kHz)
50
Time (s)
Fig. 10. The variation of G in sample scenario
Fig. 11 presents the process of moving operation points in v i plane when controller of methods (except OVAVC method) change control pusle to track MPP in above scenario.
Type of parameters
Symbol
Value
Known parameters provided by manufacturers
ISC (A)
7.36
VOC (V)
30.4
Vmpp (V)
24.2
Impp (A
6.83
CTI (%/0C)
0.057
CTV (%/0C)
0.346
CTP (%/0C)
0.478
Unknown parameters calculated by NewtonRaphson algorithm
Iph (A)
7.3616
I0 (A)
1.03.107
Vt (V)
1.6814
RS ()
0.2511
Rp ()
1172.1
i MPP850
gK
MPP1000
K
gmpp1000 gmpp800
gL
i v curve
L pv pv
850
ipvvpv curve800
n(T) 1 0.008017 (T T
) 9
(T T )2
MPP800
22.37V 22.4V 22.55V
ipvvpv curve1000
v
stc
400000
stc
Fig. 11. Process of moving operation points in vi plane (T=400C, G varies)
In Fig. 11, starting from MPP850 and G increases from 850 W/m2 to 1000W/m2 in Fig. 13, MPP850 is moved to K in vpvipv curve1000 (gload1=gK) because controllers continue to hold input voltage of the converter at 22.4V. After MPPT provides new value of voltage at MPP1000 (22.55V), controllers change control pulse to move K to MPP1000 (changes gK to gload2=gmpp1000=0.3). At the time of decreasing irradiance from 1000 W/m2 to 800 W/m2, MPP1000 is immediately moved to L, so controllers continue to change control pulse to hold input voltage of the converter at 22.37V and move L to MPP800
100
90
80
H (%)
70
60
50
40
30
20
25 30 35 40 45 0
50 55 60 65
(changes gL to gload3= gmpp800=0.247).
Fig. 12 shows Ppv(t), Pmpp, A(t) for above methods: IB SMC, IBAVC, CVAVC, TempAVC, OVAVC, P&O.
150
T ( C)
a. G=1000 W/m2, T increases from 25 0C to 65 0C.
100
80
IBSMC
100
50
0
A=3*136.2 Ws 60
ppv(t)
Pmpp(t) A(t)
H (%)
40
20
0 0.5 1 1.5 2 2.5 3
150
IBAVC
100
50
0
150
A=3*135.9 Ws
0 0.5 1 1.5 2 2.5 3
0
25 30 35 40 45 T ( 0C)

G=600 W/m2, T increases from 25 0C to 65 0C.
100
80
50 55 60 65
CVAVC
100
50
0
A=3*127.2 Ws
60 IBSMC
H (%)
IBAVC
40 P&O
OVAVC
20 CVAVC
150
0 0.5 1 1.5 2 2.5 3 TempAVC
0
25 30 35 40 45 T ( 0C)
50 55 60 65
TempAVC
100
50
0
150
OVAVC
100
50
A=3*135.3 Ws
0 0.5 1 1.5 2 2.5 3
A=3*95.9 Ws

G=200 W/m2, T increases from 25 0C to 65 0C.
Fig. 13. A(t) curves corresponding with three irradiance levels
IB technique uses both a PYR and a TempS, so it can provide information exactly about MPP at any time. Because of this reason, IBSMC and IBAVC methods always have the highest dynamic response to track MPP very well whenever it has any change of weather condition and the highest static
0
150
P&O
100
50
0 0.5 1 1.5 2 2.5 3
A=3*131 Ws
response to uphold the operation of PVg at MPP (power curve is always flat) when it doesnt have any change of weather condition. Moreover, these methods also cause very small perturbation and provied the highest efficiency.
IBSMC and IBAVC methods also have a significant meaning in combining calculation technique and control
0
0 0.5 1 1.5 Time [s] 2 2.5 3
Fig. 12. ppv(t), Pmpp, A(t) curves (T=400C, G varies)
Fig. 13 illustrates efficient curves received by using above methods and corresponding with G=1000 W/m2, G=600 W/m2 and G=200 W/m2 when T increases from 25 0C to 65 0C. From Fig. 11, Fig. 13, we can see that techniques not using TempS such as OV, CV, P&O always exist some disadvantages: making perturbation in the circuit, causing power loss at the time looking for MPP, operating far MPP and providing medium or low efficiency when weather condition is far STC. If using a TempS, TempAVC provides reference value of voltage to the controller quite near voltage at real MPP, flat power curve and track MPP quite well at near STC, so it can use it in some simple application.
techniques through DC/DC converters to help them be easier in real applications with simple microprocessors than traditional techniques. At the same time, they can help us exploit all available energy of PVg at any time to overcome high cost and low efficiency when we use PVg in long time.


CONCLUSION
In this paper, we have presented two new methods to control PVg. They are IBAVC combining the IB technique with AVC technique and IBSMC combining IB technique with SMC technique. They use information providing the IB technique, so they use adaptive controllers changing control parameters corresponding with various weather conditions.
Because of using a PYR, TempS, voltage and current sensors, controllers can identify parameters at MPP before creating control pulse, proposed methods overcome disadvantages of previous control methods using online and offline techniques to find MPP. They help controllers improve efficiency (approximately 100%), static and dynamic responses when exloiting PVg.
Simulation results show that the proposed control methods are new approaches to improve the ability to exploit PVg, reduce power loss and perturbation in control circuit and can apply for any structure of PVg. Up to now, PYR and TempS become more popular, it is easier to execute these control methods. IBSMC method brings higher efficiency a bit than IBVAC method and provides a dependable tool to test behaviors of PVg in theory. Otherwise, IBSMC method requires more highly sensitive and accurate measurement units, so IBVAC method is more suitable and easier to execute in real applications than IBSMC method.
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Le Tien Phong, born in 1982, received the M.Sc. degree in 2010 in Electrical Engineering from Ha Noi University of Technology and Science and working in Thai Nguyen University of Technolgy now. Interested research fields: renewable energy, control electrical energy conversions.
Ngo Duc Minh, born in 1960, received the PhD. degree in Automation from Ha Noi University of Technology and Science in 2010 and working in Thai Nguyen University of Technolgy now. His research interests include active filter, FACTS BESS, control of power system, distribution grid, renewable energy.
Asc. Prof. Nguyen Van Lien, born in 1949, received the PhD. degree in Power electronic and electric drive in Slovaque university, working in Ha Noi University of Technology and Science now. His research interests include position and motion control, Controlling energy conversion systems in the electric power system and network.