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Implementation of Generalized Photovoltaic
System with Maximum Power Point Tracking
Syed Bilal Javed2, Anzar Mahmood1,∗, Rida Abid2, Khurram Shehzad2,
Muhammad Shabir Mirza1, Rafiah Sarfraz2
1Department of Electrical (Power) Engineering,
Mirpur University of Science and Technology (MUST), Mirpur, Azad Kashmir
2EE,COMSATS Institute of Information Technology Islamabad, Pakistan
∗Corresponding Author: Email: anzar.pe@must.edu.pk, anzarmhamood@gmail.com, Ph: +92-331-5079549
Abstract—Renewable Energy (RE) resources have vast
sustainable potential to meet the increasing global energy
demand. Photovoltaic (PV) is one of the most promising RE
technologies. Most of the PV systems use specific PV model
with fixed parameters. This paper presents a PV system
consisting of PV model having generic parameters, PV
array, Maximum Power Point Tracking (MPPT), DC/DC
converter, DC/AC inverter and synchronization with grid
in Matlab/Simulink. There are many MPPT techniques
which are used to track the maximum power point of PV
systems. We have implemented Perturb and Observe (P&O)
algorithm for MPPT. The maximum power point of PV
keeps on changing with varying environmental conditions
such as solar irradiance and cell temperature. The MPPT
extracts maximum power point of PV array and feed it to
the load via boost converter. The PV array characteristics
and MPPT performance under abrupt change of weather
conditions are analysed. Finally, the synchronisation of
inverter with grid has been implemented with feedback
system. Simulation results prove the effectiveness of the
proposed method.
Index Terms—Renewable Energy; Photovoltaic; MPPT;
Boost Converter; Perturb and Observe (P&O); Space
Vector Pulse Width Modulation (SVPWM)
I. INTRODUCTION AND LITERATURE REVIEW
Rapidly increasing electricity demand and atmo-
spheric variations have increased the importance
of Renewable Energy Resources (RERs) for sus-
tainable development. RERs are based on natural sources
like wind, sunlight, tides etc. These are economical and
viable with less carbon emissions and can be certainly
replenished [1], [2]. Among several RERs, the solar
radiant energy is an abundant and easily available source.
Solar energy has offered favourable outcomes to solve
power sector problems [3], [4]. Solar energy depends on
the climatic conditions like temperature, solar irradiation
etc. and consequently it varies continuously. This makes
the nature of solar energy intermittent [5].
The output characteristics of Photovolatic (PV) modules
depend on solar irradiation and cell temperature [6]. PV
modules have nonlinear electrical characteristics hence
designing and simulation of the system need reliable PV
modeling. Many PV system models have been proposed
in order to improve efficiency and performance of the
system [7]. R. Falinirina proposed a system with em-
phasis on PV system, modelling and simulation of PV
array, Maximum Power Point Tracking (MPPT) control
and DC/DC converter [8]. Performance of the proposed
system has been analysed and evaluated using Matlab.
However, synchronisation with the grid has not been
implemented. Lipika et al. have proposed another system
performance of PV module that is optimized Perturb and
Observe (P&O) method using buck boost converter [9].
N. Agarwal presented Matlab/Simulink based model to
study the case for adaptation of solar energy. Authors
have implemented two different types of MPPT con-
trollers to compare effectiveness of both the controllers
for PV systems. The proposed system has numerous
advantages: simple, reliable, permits simulation of cells
etc. and it also analyses incompatible panels which
operate under different conditions [10].
This paper presents a PV system consisting of PV
model having generic parameters, PV array, P&O algo-
rithm based MPPT, DC/DC converter, DC/AC inverter
and synchronization with grid in Matlab/Simulink. Mat-
lab/Simulink provides an intelligent, modular and graph-
ical simulation environment for the constantly varying
analysis of Power systems. It also helps in the designing
and simulation of power system. Our system proposes
an improved PV system as compared to the work of
Falinirina in [8]. This work includes PV modeling with
generic parameters. The generic PV model provides a
user friendly interface to define various PV parameters.
This capability enables the users to analyse the PV
system having any kind of PV modules. Furthermore,
DC to DC converter along with the MPPT controller
has also been implemented. Results show that MPPT
in PV module successfully tracks the maximum power
point of PV array under abrupt changes of solar ir-
radiance, temperature and variable load. Our second
major contribution is the implementation of PV system
978-1-4799-6089-7/14/$31.00 c
2014 IEEE
2nd International Multi-Disciplinary Conference (IMDC-2016), UoL, Gujrat Campus, Pakistan
synchronization with grid. We have implemented three
phase inverter and synchronized it with grid using Space
Vector Pulse Width Modulation (SVPWM) technique.
Rest of the paper is organized as follows. Proposed model
has been elaborated in section II. Results and discussion
are described in section III while conclusions are drawn
in section IV.
II. THE PROPOSED MODEL
This section is dedicated for details of proposed PV
system. Our proposed system consists of five major
modules: PV array model, DC-DC converter, MPPT
controller, DC-AC inverter and synchronization mod-
ule. Synchronization module comprises SVPWM, Phase
Locked Loop (PLL) and voltage measurement sub mod-
ules. Block diagram of the proposed system is shown
in Fig. 1. PV panel takes the solar irradiance and
temperature as input and produces current and voltage.
MPPT controller tracks the maximum power point of PV
panel using P&O algorithm. DC-DC converter boosts up
the output voltage and DC-AC inverter converts the DC
output into AC. The synchronization module is used to
synchronize the DC-AC inverter output with grid. PLL
block generates a reference signal having same frequency
and angle as that of the grid. SVPWM is a modulation
technique that generates the controlled gating signals for
the inverter [8].
A. Photovoltaic Array Modelling
A PV cell is a p-n semiconductor device that converts
sunlight into DC current (electricity) using PV effect.
Large number of PV cells are connected in series and
parallel combination according to energy requirements.
This arrangement is known as PV module. A PV array
is defined as group of numerous PV modules connected
in series (responsible to increase the array voltage) and
parallel connections (responsible to increase current in
the array) [11]. The equivalent circuit of a PV cell is a
current source in parallel with an inverted diode, parallel
or shunt resistor and a series resistor as shown in Fig. 2
[9].
Shunt resistor RPcharacterizes leakage current of diode
and series resistance RSrepresents internal losses due to
current flow. Performance of PV cells depend on two
main factors i.e. temperature and irradiance. Following
equations (1) to (4) represent the behaviour of PV device
[12].
I=IPV −ID,(1)
Where, ID=Io[exp[q∗v
a∗k∗t]−1](2)
So, I=IPV −Io[exp[q∗v
a∗k∗t]−1](3)
Fig. 2: Single Diode Model of a PV Device
I=IPV −Io[exp[V+Rs
a∗Vt ]] −V+1Rs
Rp .(4)
Where,
I: Solar Cell Current (A)
IPV: Current Generated by Incident Light (A)
ID: Diode Current
q: Electron Charge
k: Boltzmann Constant
T[K]: Temperature of P-N Junction.
a: Diode Constant.
Vt: Thermal Voltage of Array.
RS: Equivalent Series Resistance.
RP: Equivalent Parallel Resistance.
IO: Diode Saturation Current (A)
Complete system shown in Fig. 1 has been modelled in
Simulink, MATLAB R2012a. Various modules of pro-
posed PV system are discussed in subsequent sections.
Block diagram of solar PV panel is shown in Fig. 3.
Temperature and solar irradiation are the inputs of solar
PV panel [9], [12]. In order to make the nature of PV
panel generic, it is needed to create a mask of the module
for user inputs. Mask created for this purpose is shown in
Fig. 4. PV module depends on the following parameters:
Ns: Number of Cells in Series
Npp: Number of Modules in Parallel
Nss: Number of Modules in Series
a: 1.3977, Diode Constant
Iscn: Nominal Short-Circuit Voltage
Kp: Voltage Temperature Constant
Ki: Current Temperature Coefficient
Vmp: Voltage Maximum Power at STC
Imp: Current at Maximum Power at STC
Mask shown in Fig. 4 depicts the parameters for BP
MSX 120 array PV model, parameters are taken from
its data sheet [13]. However, these parameters can be
modified for any other PV panel. Some of the modules
are explained in subsequent sections.
B. MPPT Control Algorithm
Power generated from a PV system primarily relies
on weather conditions, for instance temperature and solar
Fig. 1: Block Diagram of Solar PV System
Fig. 3: Block Diagram of PV Module
irradiances. Low efficiency and high cost of a PV system
demands that it must be operated at Maximum Power
Point (MPP). The MPP of a PV system changes with
atmospheric conditions or load variations. A typical solar
panel converts only 30-40% of the incident solar irradi-
ation into electrical energy [14]. A number of MPPT
methods have been developed to enhance the efficiency
of PV system. The PV model output characteristics are
nonlinear with altered solar irradiance and temperature.
Moreover, the solar irradiation is uncertain and it varies
the MPP of PV module. Thus, a MPPT method is
required to operate the PV module on its MPP. There
are many techniques for MPPT, the most popular tech-
niques are [15]: P&O, Fuzzy Logic Control, Incremental
Conductance, Neural Network Control etc.
P&O is the most frequently used method because
of implementation ease and low cost. It operates by
adjusting the PV array operating voltage, and analysing
the PV output power with the earlier one. The power
Fig. 4: Mask for Generalize PV Module
decreases (increases) with decrease (increase) in voltage
when going on left of MPP. The power increases (de-
creases) with decrease (increase) in voltage when going
on right of MPP. Consequently, if there is a rise in
power, the successive perturbation must keep the same to
acquire the MPP. Similarly, if there is a fall in power, the
perturbation must be reversed. The P&O algorithm needs
two measurements: the voltage (Vpv)and the current (Ipv)
[9].
C. SVPWM Technique
Space Vector Modulation (SVM) is the modulation
technique that was developed as vector approach to
Pulse Width Modulation (PWM). It was developed to be
used in three phase inverters. This technique generates
Sine waveform having less harmonic distortion and
produces high voltage. This quality makes it the best
to use in power electronics. The main objective of
any modulation approach is to get maximum variable
output with minimum harmonics [16]. In context of
SVM technique, consider a three phase half-bridge
voltage source inverter [16], three voltages, each phase
to centre-tap voltages can have only two possible values,
namely +Vdc/2 or −Vdc/2, respectively. There are three
switches corresponding to three phases, so at any time
instant, inverter has eight possible states. If upper switch
of the leg is on, it is indicated by the state 1. Similarly,
if lower switch of a particular leg is on, it is indicated
by state 0. As there are 3 legs, so there are 8 possible
switching combinations. Line to neutral voltages can be
found using the following three equations:
Van = [2Vao −Vco −Vbo]/3 (5)
Vbn = [2Vbo −Vao −Vco]/3 (6)
Vcn = [2Vco −Vao −Vbo]/3 (7)
Summary of these states and line to neutral voltage
applied accordingly is shown in Table I [16], [17].
So there are six active states of inverter and the rest
two are zero states. The line to neutral voltages, i.e. Van,
Vbn and Vcn, are 120◦apart. Two phase equivalent of the
line to neutral voltages is written as follows.
Vref =Vds +jVqs (8)
By using Clark’s transformation, the value of Vds and Vqs
is obtained. From equation (8), the magnitude and phase
of the voltage Vref can be determined. When plotting
the magnitude and phase, the space vector magnitude
and position corresponding to each switching state is
determined as shown in Fig.5. Each of the vectors such
as V100, V110 etc., shown in the diagram represents six
voltage steps developed by inverter with zero voltages
V000 and V111 located at origin. The inverter switches
are in a steady state at each of these states. A switching
pattern must be devised that produces a voltage which
transitions in between these states and not only at the
six vectors states, in order to develop a sine wave at the
motor. This effectively produces a continuous rotating
vector Vref , which transitions smoothly from state to
Fig. 5: Space Vector Corresponding to Each Switching States
[16]
state.
A vector is produced that transitions smoothly between
sectors using the appropriate PWM signals and hence
provide sinusoidal line to line voltages which is
equivalent to the input reference voltage. Thus, by
using space vector modulation technique, the output
voltages of the inverter are almost equal to the input
reference voltages. The reference voltage is sampled at a
particular frequency to obtain such output voltages. The
output voltage will be closer to the reference voltage if
the sampling frequency is greater but as the sampling
frequency increase, the switching frequency also
increases which further results in increased switching
loss. So an optimum sampling frequency should be
selected to overcome this problem. A formula must
be derived to obtain the PWM time intervals for each
sector. By sampling the reference voltages, the time
for which active vectors are switched and sector in
which these vectors are switched is obtained. The
time and sector can be found from the magnitude and
the position of reference voltages. The symbols T1
and T2, respectively represents the time periods for
which the active vector along the lagging edge and the
leading edge are switched for the understanding of the
reference voltage space vector in a given sampling time
period. Ts is the symbol that represents the sampling
time period. The time T1 and T2 can be obtained, by
applying volt-sec balance in vector form. The volt-sec
balance along ds and qs axis is written as following
from equation (8):
Vref ∗Ts∗cos(α) = [(V1∗T1∗cos(0))+(V2∗T2∗cos(60))]
(9)
Vref ∗Ts∗sin(α) = [(V1∗T1∗sin(0))+(V2∗T2∗sin(60))]
(10)
Where, Vs is the magnitude of the reference voltage and
V1 &V2 are the magnitude of the sector voltages that is
equal to DC link voltage, Vdc. The αis the position of
TABLE I: Inverter Switching States
States ON Switches Van Vbn Vcn Space Voltage Vectors
0 462 0 0 0 V0(000)
1 162 2(VDC/3) -(VDC/3) -(VDC/3) V1(100)
2 132 (VDC/3) (VDC/3) -2(VDC/3) V2(110)
3 432 -(VDC/3) 2(VDC/3) -(VDC/3) V3(010)
4 435 -2(VDC/3) (VDC/3) (VDC/3) V4(011)
5 465 -(VDC/3) -(VDC/3) 2(VDC/3) V5(001)
6 165 (VDC/3) -2(VDC/3) (VDC/3) V6(101)
7 135 0 0 0 V7(111)
reference vector w.r.t the beginning of sector where the
reference vector’s tip lies. Rearragning equations 8 and
9, the switching time T1 and T2 is found and is stated as:
T1={[Vs∗Ts∗sin(60 −α)]/(Vdc ∗sin(60))}(11)
T2={[Vs∗Ts∗sinα]/(Vdc∗sin(60))}(12)
The sampling time is as follows:
Ts= (T1+T2+T0)(13)
In equation (13), T0 is the time for which the null vectors
(0 and 7) are switched on.
D. Inverter Connected to Grid
For grid connected system it is important to synchro-
nize the inverter’s voltage and frequency with the grid.
For this purpose, synchronization between inverter and
the grid has been done via feedback system. Builtin
SIMULINK PLL block has been used. The purpose
of PLL block is to generate grid’s frequency, voltages
and phase angle which is then fed into SVPWM block.
SVPWM block generates signal for inverter hence the
output is synchronized with grid. SVPWM block has
been designed on the basis of model presented in [16].
The inputs of this block are the output from PLL block
and current from the inverter. It generates the switching
signal that is again fed to the inverter. This is how this
model for feedback system is working in grid connected
mode. Simulations of PV array with boost converter
and synchronization of inverter with grid have been
performed. Any type of PV array can be used in the
proposed system by assigning its parameters in the mask
shown in Fig. 4. The BP MSX 120 PV model is used
for simulation. The temperature, irradiance and load are
varied to determine the capability of MPPT to track the
MPP under abrupt change of weather conditions and
variable load.
E. Results and Discussion
The characteristics of BP MSX 120 at STC 25◦C are
briefed in Table II [13]. The BP MSX 120 modules are
connected in series and parallel to make a PV array. A
PV array of 12 KW is made by connecting 10 modules
in series and 10 modules in parallel. The characteristics
of this array have already been depicted in Fig. 4.
TABLE II: BP MSX 120 Parameters Values
BP MSX 120
Short Circuit Current 3.56 A
Current at maximum power point 3.87 A
Voltage at maximum power point 33.7 V
Open Circuit Voltage 42.1 V
Number of cells in series 72
1) The Characteristics of PV Array with Varying
Temperature and Irradiance: The current-voltage (I-V)
and power-voltage (P-V) characteristics of PV array as
a function of temperature and solar irradiance are shown
in Figs. 6 and 7. These curves are nonlinear and signif-
icantly depend on the temperature and solar irradiation.
The I-V & P-V characteristic curves of PV array for
different values of solar irradiance are shown in Fig. 6.
It can be seen that as the irradiation rises, the current
rises more than the voltage and the MPP increases as
well. Fig. 7 explains the P-V & I-V characteristic curves
of PV array at different temperatures. It can be observed
that the increase in temperature results in decreasing the
power and voltage of PV array while the current remains
almost constant. Therefore, temperature does not affect
the current.
III. CONCLUSIONS
In this paper, we have presented a generalized PV
system with MPPT controller, DC-DC converter, inverter
and synchronization module. Resistive load has been
used for simulation studies. The proposed system has
been simulated in Matlab/Simulink. First, the general-
ized PV module is designed for which the parameters
provided in the mask can be modified to use any type
of PV module. The simulations of PV array BP MSX
120 array showed that the simulated model is accurate
because the current voltage characteristics are same as
Fig. 6: BP MSX 120 Array Characteristic Curves as a Function
of Solar Irradiance (G)
Fig. 7: BP MSX 120 Array Characteristic Curves as a Function
of Temperature (T)
given in the data sheet. Then the same PV array with
boost converter is analysed under the abrupt change of
irradiance, temperature and variable resistive load. The
simulation results show that PV output power, voltage
and current vary with the changes of temperature and
irradiance. The change in load does not affect the output
of photovoltaic array. The simulation results also show
that P&O based MPPT algorithm can track the MPP of
the PV under different weather conditions. The proposed
model has been successfully synchronized with grid.
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