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Design and Performance Analysis of QZSI Implemented in Grid Integrated PV System
1B. Kavya Santhoshi, 2 K.Mohana Sundaram
1Research Scholar, Department of Electrical and Electronics Engineering, Anna University, Chennai, India.E - mail: [email protected] 2Professor, Department of Electrical and Electronics Engineering, Vel Tech Multi Tech Dr.
Rangarajan Dr. Sakunthala Engineering College, Chennai,India.
E-mail: [email protected]
Abstract
Considering today’s world energy scenario, PV based power generation system plays a
vital role throughout the world. This necessitates gazing towards the design of suitable
converter for feeding PV power to grid. As numerous converters/PV inverters are so far
discussed, flexibility of the quasi impedance source inverter (QZSI) for changing
irradiance and then its boost factor control topology has made it more suitable for grid
system. Thus this work presents a novel of qZSI for grid-linked PV arrangement with
suitable control technique. The Magnetically Coupled Boost (MCB) control technique
minimizes the low order ripples and stress in voltage across the switches and thereby
enriches the performance of the qZSI. Fuzzy logic control (FLC) is implemented to have
the DC-link voltage under control. Both Sinusoidal PWM (SPWM) and Space vector
PWM (SVPWM) techniques are tailored for generating switching pulse for the inverter.
SVPWM results show superiority compared to SPWM. Finally, the performance of the
proposed controller technique under constant irradiance condition is simulated with
MATLAB and the results are summarized as a comparative analysis.
Keywords: Grid connected PV, PWM, Quasi Z Source Inverter, Solar.
1 Introduction Nowadays, diminishing fossil results in increased installation of Renewable
energy system (RES) based power generating stations. While considering the power
generation using PV system, power converters plays a vital role in it [1]. The converters
employed in PV systems are categorized as either single/two stage inverters. Among
those, the former offers a feasible and economical solution due to its compact nature,
reliability and lower price. Conversely, its topology must be tailored so as to couple
,312-331, Alpha Publishers
This is an Open Access publication. © 2019 the Author(s). All rights reserved.
Journal of Green Engineering (JGE)
Volume-9, Issue-3, October 2019
Journal of Green Engineering, Vol. 9_3
313 B. Kavya Santhoshi et. al.
with PV system. As a result, the size of the inverter gets increased [2]. But the
application of two stage converters reduces Kilo-volt-ampere (KVA) rating of inverter
and enhances the boost operation for an extensive choice of input voltage. However, the
number of switching devices is more, causing high switching loss. So the efficiency
becomes poor. In order to overcome this aforementioned drawback, an impedance
source inverter (ZSI) was introduced with a single stage topology to get buck & boost
conversion. This will easily manage the variations the PV system without overloading
the inverter [3]. However, in order to enrich, the operation of ZSI, qZSI is introduced
with some attractive changes and is made more suitable for PV application. Thus the
advantages of qZSI over PV system are as follows [4]
1) As it draws a constant current (CC) from PV, no extra filtering action (capacitor
filter) is needed.
2) The rating of the components implemented in qZSI is very low as compared to
ZSI
3) It reduces the ripple in the PV system.
Thueyushan et al (2014) formulated a qZSI with cascaded multilevel inverter
implemented in grid connection for a single phase PV system. Li et al (2013) formulated
a qZSI for distribution and generation system. All these studies exhibit various topology
of qZSI for different applications. Hence, the foremost contribution of the following
work is to formulate the dynamic model and to design a control topology for qZSI to
achieve PV-grid synchronization. The novel SVPWM technique is implemented to
control the qZSI. In this topology, FLC is utilized to regulate the boost factor to keep
up a constant DC link voltage. Proposed work is finally verified using MATLAB
simulation.
2 Related Works Since 20th century, ZSIs have gained popularity. In the year 2006, Miaosen
Shen et al, in his paper, elaborated two methods for achieving boosted voltage gain
without causing low frequency ripple [6]. Switching frequency is the key component to
control ZSI. This work was most suited for variable speed applications although there
was an increased stress in voltage across the switches. In 2010, Gajanayake et al
introduced four novel topologies using converters [3]. The broad classification of them
is based on whether the boost in output is obtained with the help of diode or capacitor.
Further, topologies include continuous current producing converter topology and
discontinuous current producing converter topology. All four have been developed from
QZSIs. The primary benefit of using QZSI is the lower voltage stress on capacitor
compared to other topologies.
In the year 2011, Yandong Chen et al proposed the concept of dual-loop control
strategy for power in a grid connected system [2]. Only single phase systems were
considered. The aim was to achieve Power control with nil error and it was successful.
The use of LCL filter increased the component count but helped to reduce the THD in
output current fed to current. In this paper, an attempt to reduce THD with the help of
LC filter alone is made thus reducing the filtering component. In the same year, Yuan
Li et al presented the modeling of QZSI for distributed generation (DG) and elaborated
the associated control issues [16]. Based on the small signal analysis carried out,
dynamical characteristics of QZSI were investigated. Both open loop and closed loop
control methods were depicted. Since M and D are linked, a constant capacitor voltage
control scheme was introduced as two separate stages of control. In this work, this
inference is taken and the control methods have been incorporated. Based on the choice
Design and Performance Analysis of QZSI Implemented in Grid Integrated PV System
314
of capacitor voltage, lesser stress on switching devices was achieved. In 2013, Baoming
Ge et al proposed a unique single stage PV system incorporating energy storage and
providing a constant dc link peak voltage [11]. The power compensation has been
improved. Also, constant dc link peak voltage was obtained and maximum power due
to use of MPPT was accomplished. This power was injected to grid after mitigating the
stochastic fluctuations.
X. Zong et al, in 2015, proposed an important study based on IEEE standard for
limiting harmonic injection in grid [7]. The harmonics were calculated using Harmonic
Admittance Matrix otherwise known as frequency coupled matrix (FCM). The limit on
the ideal value of current alone was considered and the method of obtaining minimal
harmonics by measurement using FCM was illustrated. But the algorithm was complex
and due to digital methods of calculating harmonics, the tedious procedure did not seek
attention. Hadeed Ahmed Sher et al, in 2016, proposed a PV system with high tracking
efficiency [1]. He used short current pulse and P & O for achieving maximum power.
The converter used was a modified flyback inverter but the main drawback was that the
converter operated in discontinuous mode. For the proposed work P & O method has
been utilized and QZSI has been used for achieving boost voltage. In 2017, Vivek
Nandan Lal et al presented control and his analysis on a single stage grid-PV system
[8]. In this paper, a high power PV system using three phase converter was considered.
Due to modified control strategy compensation of dip in grid voltage was achieved. The
reactive power injection capability was also improvised. A modified voltage controller
was proposed with feedback linearization. P & Q were controlled by use of dq
components of grid current. From this inference, in the proposed work, dq components
were used for control instead of three phase quantities. In 2019, Kavya Santhoshi et al
provided a critical review on different topologies of inverters used in grid-tied pv
systems and the associated grid standards, grid codes, popular intelligent algorithms
used and reactive power injection to grid [18]. Among these the topologies were keenly
studied and q-zsi inverter is chosen for this work due to its numerous advantages.
Keeping in mind, grid codes and standards mentioned in the paper, this work aims at
providing lesser harmonics at the output for smooth power injection to grid.
3 Proposed Q-ZSI with Grid Integrated PV Scheme The topology of the circuit for proposed work is revealed in figure 1. The
system has a PV arrangement, qZSI, LC filter and utility for testing. In this proposed
system, Perturb & Observe (PO) method of Maximum power point tracking (MPPT) is
executed for standardizing the power from PV. A 500 W grid structure is considered for
performance evaluation using MATLAB Simulink.
3.1 Design of PV system - Modeling of PV Array
PV cells joined in series & Parallel combinations forms a PV array. Figure 2
depicts the Model of a PV cell using semiconductor (Diode). Solar cell representation
is with a current source and an inverted diode [8].
Here, the shunt resistance is neglected. Thus, the diode and series resistance forms
a PV model and the output current for the above circuit is derived as follows.
– sc dI I I (1)
/
1 1Vdv kT
d JI Io eq (2)
Where
Io1 - Reverse saturation current of diode,
315 B. Kavya Santhoshi et. al.
q - Charge of an Electron,
Vdv –Diode Voltage,
k - (1.38 * 10-19 J/K) -Boltzmann constant
TJ - Temperature at the Junction (K)
Using the equations 1 and 2, I can be written as
/
1 – 1 qVdv kT
sc o JI I I e (3)
It can also be written as,
( )/
1 – ( 1)q V IRs nkT
sc o JI I I e
(4)
I – PV Current,
V - PV voltage,
N - Ideality Factor of a Diode.
From the above equations, it is concluded that the variations in the weather
condition (i.e. Changes in the temperature) will affect the productivity of PV. Therefore,
MPPT is implemented so as to achieve maximum power from PV [9,10].
Figure 1. PV powered q-ZSI fed grid system circuitry
Figure 2. Model of a PV cell using semiconductor (Diode)
Design and Performance Analysis of QZSI Implemented in Grid Integrated PV System
316
3.2 MPPT Algorithm P&O technique for MPPT tracking is used and the same is depicted in figure 3.
According to this algorithm, the increase in operating voltage of an array results in
increased output power and vice versa. If the power increases, the next perturbation
should proceed in the exiting direction or else if it is reversed, it will be in the opposite
direction to that of present position.
Figure 3. Algorithm of Perturbation & Observation
3.3 QZSI Network
QZSI circuit is different from conventional ZSI. It has an LC and diode network
configuration [12]. The dc-link voltage gets boosted and shoot through protection is
given to the circuit [5,17] and the same is depicted in figure 4.
NO YES
YES NO NO YES
YES
ΔV>0 ΔV>0
Inputs: V(t), I(t), V(t-Δt), I(t-Δt) P(t)
& P(t- Δt) calculated from the inputs
ΔV=V(t)- V(t- Δt)
ΔP=P(t) – P(t- Δt)
ΔP=0
ΔP>0
Decrease
Vref
Increase
Vref
Decrease
Vref
Increase
Vref
Return
Stop
Start
317 B. Kavya Santhoshi et. al.
Figure 4. QZSI circuit
3.3.1 Operating Principle of qZSI Thus approaches of operation of qZSI are as follows.
(1) Non-shoot through mode (active mode). (NSTM)
(2) Shoot through mode (STM)
NSTM
Figure 5 depicts the equivalent circuit of non-shoot through mode. Under this, switching
arrangement of VSI and qZSI are analogous. The dc voltage is fed to inverter acting as
a conventional VSI[6].
Figure 5. Equivalent circuit of QZSI in Active mode
In the STM, for the short period, switches present in the same phase of the inverter
remains ‘ON’. With LC, the switches are not short circuited and thus the voltage gets
boosted up[13]. Thus, the boosted dc link voltage depends upon the boost factor. This
boost factor may be influenced by the shoot through ratio for specified Ma and the
equivalent circuit STM is shown in figure 6
Design and Performance Analysis of QZSI Implemented in Grid Integrated PV System
318
Figure 6. Equivalent circuit of QZSI in Shoot through Mode
With the following assumptions,
T – One complete switching cycle
T0 – period of STM
T1 – period of NSTM
Hence,
Total T =T0 +T1
Shoot-through duty ratio, D =T0 /T1.
During T1
𝑉𝐿1 = 𝑉𝑖𝑛 − 𝑉𝑐1, 𝑉𝐿2 = −𝑉𝑐2 (5)
During T0,
𝑉𝐿1 = 𝑉𝑐2 + 𝑉𝑖𝑛, 𝑉𝐿2 = 𝑉𝑐1 (6)
𝑉𝑃𝑁 = 0, 𝑉𝑑𝑖𝑜𝑑𝑒 = 𝑉𝑐1 + 𝑉𝑐2 (7)
At steady state condition, the average VL becomes zero.
𝑉𝑃𝑁 = 𝑉𝑐1 − 𝑉𝐿2 = 𝑉𝑐1 + 𝑉𝑐2, 𝑉𝑑𝑖𝑜𝑑𝑒 = 0 (8)
From (3.1) and (3.3),
{𝑉𝐿1 = 𝑉𝐿1 =𝑇0(𝑉𝑐2+𝑉𝑖𝑛)+𝑇1(𝑉𝑖𝑛−𝑉𝑐1)
𝑇= 0 (9)
{𝑉𝐿2 = 𝑉𝐿2 =𝑇0(𝑉𝑐1)+𝑇1(−𝑉𝑐2)
𝑇= 0 (10)
Thus,
𝑉𝑐1 =𝑇1
𝑇1−𝑇0𝑉𝑖𝑛 𝑉𝑐2 =
𝑇0
𝑇1−𝑇0𝑉𝑖𝑛 (11)
From (5), (6) and (7), the peak dc-link voltage across the inverter is
𝑉𝑃𝑁 = 𝑉𝑐1 + 𝑉𝑐2 =𝑇
𝑇1−𝑇0𝑉𝑖𝑛 =
1
1−2𝑇0𝑇1
𝑉𝑖𝑛 = 𝐵𝑉𝑖𝑛 (12)
where
B -Boost Factor
Then the I avg across the inductors (L1, L2) can be given as
𝐼𝐿1 = 𝐼𝐿2 = 𝐼𝑖𝑛 =𝑃
𝑉𝑖𝑛 (13)
AS per KCL,
𝐼𝑐1 = 𝐼𝑐2 = 𝐼𝑃𝑁 − 𝐼𝐿1 𝐼𝐷 = 2𝐼𝐿1 − 𝐼𝑃𝑁 (14)
319 B. Kavya Santhoshi et. al.
Thus, from the above equation, it is observed that qZSI has more advantageous
over ZSI.
3.3.2 Inductor Design For traditional operating condition, capacitor voltage is same as input oltage,
Hence inductor voltage becomes zero. During STM, inductor current (IL) increases and
hence the VL=VC[14]. Thus the ILavg is depicted as,
𝐼𝐿 =𝑃𝑉𝑑𝑐⁄ (15)
Where
P -Total Power
Vdc - Input Voltage.
The Iavg for the proposed design can be calculated. When both IL and ST are at
their maximum, then it results in high ripple current. However, only 30% of current
ripple through inductor is allowed. Thus the ripple should be below 4A and maximum
current is about 10.67A. Hence, for fs about 10kHz, the VCavg is calculated as
𝑉𝑐 = (1 −𝑇0
𝑇⁄ ) ∗ 𝑉𝑑𝑐/(1 −2𝑇0
𝑇⁄ ) (16)
Thus by replacing the values in this equation, the VCavg and inductance is
calculated
3.3.3
The most important purpose of capacitor is minimization of voltage ripple and
maintaining voltage at the constant value. During ST, the capacitor will charge the
inductor, therefore IL=IC.
The ripple at the capacitor is calculated using
VC = ILavgTS/C (17)
4 Control Scheme Figure 1 has two control variables, namely shoot through duty ratio and
modulation index. The first is for MPPT control and next is for control of grid.
Considering grid, the injected P and Q is measured using d-q components. Thus the
measured voltage and current are the grid side are sent to the voltage controller and thus,
M is calculated. Thus, these two parameters (m and D) combined together and produce
PWM signals.
4.1
FLC is an intelligent control system. In this work, it is used for maintenance of
constant dc link voltage [11]. They are characterized using fixed linguistic statements
which are mainly based on expert knowledge / experience.
Thus, the FLC implemented in this system has,
Implications by means of Mamdani’s ‘min’ operator.
Seven fuzzy sets for each input (e, Δe) and output (Δu) with
triangular membership functions.
Defuzzification with the ‘centroid’ method
Continuous universe of discourse for Fuzzification.
Design of a Capacitor
Design of Fuzzy Controller
Design and Performance Analysis of QZSI Implemented in Grid Integrated PV System
320
Figure 7a, 7b and 7c shows the triangular MF of input & output variables.
Figure 7a. Membership functions of e
Figure 7b. Membership functions of Δe
Figure 7c. Membership functions of Δu
4.2 Generation of PWM Signals Numerous works [15,18,19,and 20] have depicted the use of PWM techniques
for better performance of QZSIs. SVPWM technique is widely used in many
applications as it provides more refined sine wave with less THD. In this technique, 3ϕ
quantities are transformed into 2ϕ quantity using SRFT topology. From these 2ϕ
components, magnitude of reference vector is calculated and PWM signals are
generated.
Thus the realization of SVPWM is carried out using the steps depicted below
1. Determine, an angle (α) ,Vd, Vref and Vq
2. Determine time required for each sector
321 B. Kavya Santhoshi et. al.
3. Finally, Compute switching time of each switch (S1 to S6)
Thus, whenever either upper/lower switch of a specific phase is ON, then it can
be denoted as ‘1’ or ‘-1’. Correspondingly, when the switch is in OFF state, then it can
be considered as ‘0’. Hence, based on these combinations, eight switching vectors, line
to neutral voltage and output line-to-line voltages are produced in SVPWM topology.
5 Simulated Results & Discussion The proposed qZSI is simulated in MATLAB. The Output voltage of PV is fed
to inverter through a z source network. Thus the voltage from the PV is boosted using
shoot-through-mode and it is converted into AC. The output grid voltage and current
are fed back using dq reference frame theory. These signals activated the SVPWM
generator and MOSFET switches are switched ON. Here the filter elements are inductor
and capacitor of ZSI. Thus the obtained output voltage is given to the grid.
Figs. 8a–b show the grid voltage, the grid current and the dc link voltage
respectively. Voltage and current are in phase and hence with the help of the results,
here it is concluded that the PV grid-connected system has a unity power factor. It can
be observed that the distortion is lesser while using fuzzy controller.
Figure. 8a. Simulation results with PI controller
Figure. 8b. Simulation results with fuzzy controller
Design and Performance Analysis of QZSI Implemented in Grid Integrated PV System
322
Table 1. Comparison of Proposed methods based on PWM topology
PWM Method Used Voltage THD
(%)
Current THD
(%)
SPWM (Open loop) 1.84 1.46
SPWM (Closed loop) 1.67 1.61
Table 2. Comparison of Proposed methods based on control scheme
Control Scheme Used Voltage THD
(%)
Current THD
(%)
PI 1.17 1.3
Fuzzy 0.23 1.2
From tables 1 and 2, proposed topology under the control of fuzzy controller
with SVPWM techniques exhibits lower THD and is about 0.23% which satisfied the
IEEE Standard.
According to IEEE standard, the value of THD should be less than 5% for an
inverter output voltage waveform[7].
Figure 9 gives input V and I provided by panel. The voltage is about 11.5 volts
in magnitude and the current is about 4.2 amps. Figures 10-13 show the simulation
results obtained under different schemes as tabulated.
Figure 9. Solar voltage and current
Figures 10 a, 10 b, 10 c and 10 d are simulation results for SPWM under open
loop control. From figure 10 a it can be noted that, the output current obtained is about
3.8 amps. In Figure 10 b, the THD of output current is seen as 1.46%. In figure 10 c the
output voltage is shown and measures around 230 volts. On the other hand, the THD of
output voltage is found to be 1.84% from 10 d. Figures 11 a, 11 b, 11 c and 11 d are
323 B. Kavya Santhoshi et. al.
simulation results for SPWM under closed loop control. In 11 a, the output voltage is
shown and measures around 200 volts. The THD of output voltage under this closed
loop scheme is shown in 11 b. It is about 1.67%. From 11 c, it is evident that
the output current obtained is nearly 4 amps and the THD of output current is 1.61% as
shown in figure 11 d.
Figure 10 a. Output Current measured while using Sine PWM in open loop mode
Figure 10 b. THD of output current measured while using Sine PWM in open loop mode
Figure 10 c. Output Voltage measured while using Sine PWM in open loop mode
Design and Performance Analysis of QZSI Implemented in Grid Integrated PV System
324
Figure 10 d. THD of output voltage measured while using Sine PWM in open loop mode
Figure 11 a. Output voltage measured while using Sine PWM in closed loop mode
Figures 12 a, 12 b, 12 c and 12 d present the simulation results obtained using
SVPWM with PI controller. From 12 a, it can be observed that, the output voltage is
measured as 230 volts. THD of output voltage is 1.17% as shown in 12 b. The output
current reaches a maximum of 10 amps in the beginning and settles at 4 amps. It is
displayed in 12 c. 1.30% is the THD of output current obtained in this scheme. It is
showcased in 12 d. Figures 13 a, 13 b, 13 c and 13 d are the simulation results obtained
by using fuzzy controller. The output voltage in figure 13 a is measured as 330 volts.
THD of output voltage measures as low as 0.23 % while using fuzzy controller. From
figures 13 c and 13 d, the output current settles at 4.5 amps after reaching a peak of 5.2
amps initially and 1.20 % is the THD of the output current.
325 B. Kavya Santhoshi et. al.
Figure 11 b. THD of output voltage measured while using Sine PWM in closed loop mode
Figure 11 c. Output current measured while using Sine PWM in closed loop mode
Figure 11 d. THD of output current measured while using Sine PWM in closed loop mode
Design and Performance Analysis of QZSI Implemented in Grid Integrated PV System
326
Figure 12 a. Output voltage measured while using SVPWM with PI controller
Figure 12.b THD of output voltage measured while using SVPWM with PI controller
Figure 12 c. Output current measured while using SVPWM with PI controller
327 B. Kavya Santhoshi et. al.
Figure 12 d. THD of output current measured while using SVPWM with PI controller
Figure 13 a. Output voltage measured while using Fuzzy Controller
Figure 13 b. THD of output voltage measured while using Fuzzy Controller
Design and Performance Analysis of QZSI Implemented in Grid Integrated PV System
328
Figure 13 c. Output current measured while using Fuzzy Controller
Figure 13 d. THD of output current measured while using Fuzzy Controller
Hence, it can be said that SVPWM technique is more suitable in grid
configurations utilizing PV. Simultaneously, on the controller design, fuzzy controller
exhibits faster response compared to other controllers.
6 Conclusion Design and performance analysis of q-ZSI for grid integrated topology under
open and closed loop control is proposed. The main objective of this work is to compare
and conclude the best PWM control for generation of pulses between SPWM and
SVPWM and also the best control strategy between PI and Fuzzy control for grid
connected PV systems. Also, both, open loop and closed loop controls for PI and Fuzzy
have been tested and the harmonics obtained in each method have been carefully
observed and tabulated. The best method was found to be fuzzy for which THD obtained
was 0.23%.When FLC is implemented to control the duty cycle of the STM , BF is also
regulated. Therefore, DC link voltage is kept constant. Also, the P&O method provides
a satisfactory output. From the simulation results, the variations in power factor, real/
reactive power and harmonics are determined. The results of THD measured under
different control schemes are tabulated as a comparative analysis. Therefore, this study
helps researchers to identify the best method of control in grid tied configurations.
329 B. Kavya Santhoshi et. al.
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Biographies
B. Kavya Santhoshi completed B.E in Electrical and Electronics Engineering from
Saveetha Engineering College (Affiliated to Anna University) in 2010. She pursued M.E in
Power electronics and drives from Jeppiaar Engineering College (Affiliated to Anna
University) in the year 2015. She also completed Master of Business Administration in
Human Resource Management from Alagappa University in the year 2012. She was given
a cash award of Rs. 75,000 for her academic excellence during her undergraduate course
and secured university rank in her M.E. Her research interests include Power electronics and
Renewable energy. She is currently pursuing Ph.d under the guidance of Dr. K. Mohana
Sundaram in Anna University.
Dr. K. Mohana Sundaram received B.E degree in Electrical and Electronics Engineering
from University of Madras in 2000 and M.Tech degree in High voltage Engineering from
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331 B. Kavya Santhoshi et. al.
SASTRA University in 2002 and Ph.D degree from Anna University, India in 2014. His
research interests include Intelligent controllers, Power systems, Embedded system and
Power electronics. Currently he is working as a Professor in EEE department at Vel Tech
Multi Tech Dr. Rangarajan Dr. Sakunthala Engineeering College, Tamil Nadu, India.