International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 6 (2016) pp 3761-3767
© Research India Publications. http://www.ripublication.com
3761
Simulation and Implementation of Perturb and observe Fuzzy
based DC-DC Converter in PV-Battery Hybrid System
Lakshman Rao S. Paragond
Assistant Professor, Department of Electrical & Electronics Engineering, Manipal Institute of Technology (MIT), Manipal, Karnataka, India.
Dr. Ciji Pearl Kurian SMIEE
Professor, Department of Electrical & Electronics Engineering, Manipal Institute of Technology (MIT), Manipal, Karnataka, India.
Dr. B. K. Singh Professor, Department of Electrical & Electronics Engineering,
Manipal Institute of Technology (MIT), Manipal, Karnataka, India.
Mr. Aswanth V
PG Student, Department of Electrical & Electronics Engineering, Manipal Institute of Technology (MIT), Manipal, Karnataka, India.
Abstract
This paper explains Design, simulation and implementation of
Perturb and Observe (P&O) Fuzzy Based control of DC-DC
Converter in Photo-Voltaic (PV) System. A standalone PV
system connected to a Boost converter with a resistive load
and Maximum Power Point Tracking (MPPT) is modeled and
implemented. A battery is used for storage purpose. The
simulations were done in MATLAB/SIMULINK
Environment. A prototype of BOOST converter with
conventional P&O Method is developed. Performance
Analysis of P&O and Fuzzy based MPPT is done.
Keywords: PV, MPPT, Perturb and Observe (P&O), Fuzzy
logic Control, Boost converter.
Introduction Fossil fuels like petrol, diesel, coal etc. are the main sources of
world energy at present. The exhaust nature of the fossil fuels
and their adverse effect on nature are the primary concern.
World is depending more and more on renewable energy
sources due to their abundant availability less impact factor on
environment pollution. The Availability of solar energy all
over the world and its setup cost compared to other types of
renewable energies makes it attractive. Resources are focusing
on low cost models for the extraction of solar energy. The total
power demand of entire world is estimated to be 30 Giga tons
of oil equivalent by 2050. To avoid energy crisis, the solar
energy 460wm-2 which is available for conversion is to be
utilized to the maximum.Even 1% utilization of the total solar
energy available can greatly reduce the energy crises[1]
The solar panel output depends on the light falling on the
panels, time of the day, panel position and orientation. If these
factors are kept constant, the power output depends on the load
connected [2]. (ICT), Fuzzy logic Control (FLC), Perturb and
observation method (P&O), Hill Climbing method, neural
network based MPPT, Linear current control based MPPT,
Temperature based MPPT, Array reconfiguration based
MPPT.
Among these theperturb and observation technique and fuzzy
logic control are employed in our simulation model such that a
resistive load of about 90Ω is connected, its output voltage is
compared and checked with the hardware output. The lead acid
battery is also simulated and its appropriate % State of Charge
(SOC), voltage, current is provided for actual reference.
In the proposed PV-Battery hybrid systems the stand alone PV
panel is connected to an Energy storage system or lead acid
battery such that the excess energy is stored and can be used as
backup during black out conditions or line fault conditions.
System Configuration The basic block diagram of PV-Battery system connected to a
load through BOOST converter implementing an MPPT
algorithm as shown in Figure 1.The system is designed to
operate in MPPT mode transferring maximum power
available from the PV panel and transferring it to the load
under all operating conditions. The 36 solar cells are
connected in series and the PV panel output is 20 watts.The
function of the BOOST
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 6 (2016) pp 3761-3767
© Research India Publications. http://www.ripublication.com
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Figure 1: General Block Diagram
To improve the efficiency of the PV modules a MPPT
technique is proposed. MPPT it is meant to draw maximum
power from PV panels irrespective of temperature, irradiance
and load conditions. Many MPPT algorithms are available and
some of them are mentioned such as Incremental conductance
algorithm converter is to match the internal resistance of the
PV and to that of the load such that a suitable PWM output is
generated from the MPPT algorithm to drive the BOOST
converter and such that the excess energy is stored in the lead
acid battery.
Modelling of PV System Diode model of a PV cell
Figure 2. Shows the diode model of Pv system based on general
equations (3) and the corresponding Simulink model is given
figure 3.
Figure 2: Diode model of PV System
The equations related to two diode modeling of PV cell are
explained [3].The output current of the PV cells given by
equation (1)-(4)
𝐼𝑑1 = 𝐼01 [exp (𝑉+𝐼𝑅𝑠
𝛼1𝑉𝑇1) − 1] (1)
𝐼𝑑2 = 𝐼02[exp(𝑉+𝐼𝑅𝑠
𝛼2𝑉𝑇2)-1] (2)
For the diode D1 and D2 reverse saturation currents are Io1 and
I02 respective The thermal voltages of diodes are 𝑉𝑇1and
𝑉𝑇2. 𝐼𝐷1 is diode current due to diffusion loses in PV cell and
𝐼𝐷2 corresponds to diode current due to recombination loses in
PV cell.𝑅𝑠is series resistance due to material contacts and
other miscellaneous loses.𝑅𝑝is the parallel Resistance due to
leakage current to ground.
The Photo-current 𝐼𝑃𝐻 is given by
𝐼𝑃𝐻 = (𝐼𝑃𝑉𝑆𝑇𝐶 +𝐾1∆𝑇)𝐺
𝐺𝑆𝑇𝐶 (3)
𝐼𝑃𝑉𝑠𝑡𝑐 is the light generated current at STC. ∆T=T-𝑇𝑆𝑇𝐶
(In Kelvin, 𝑇𝑆𝑇𝐶=25C, G is the solar irradiance on the surface
of the PV cell in 𝑊
𝑚2 and 𝐺𝑆𝑇𝐶 irradiance at STC (1000𝑊
𝑚2).The
constant K1 is the short circuit current coefficient in 𝑚𝐴
𝐾 which
is provided by the manufacturer. The diode saturation current
with variation in temperature is given by
𝐼𝑜 = (𝐼𝑆𝐶,𝑆𝑇𝐶 + ∆Tk1)/exp[𝑉𝑂𝐶𝑆𝑇𝐶 +𝐾𝑣∆𝑇
𝛼𝑉𝑇] − 1
(4)
𝐾𝑣 Is the open circuit voltage coefficient in 𝑚𝑉𝐾 provided in
the data sheet.𝑉𝑜𝑐𝑆𝑇𝐶 is the open circuit voltage of PV cell at
STC.𝐼𝑆𝑇𝐶 is the short circuit current of PV cell at STC.
Figure 3: Two diode Simulink model of PV System.
Perturb and Observation (MPPT)
Inputs given to the P&O MPPT algorithm are the output
currents and output voltage from the PV panel which also
happens to be the input current and input voltage to the DC-
DC Boost converter. In this conventional Perturb and
Observation Technique shown in Figure 4 contains power
which is the product of voltage and current of the converter,
every increment or decrement of the power in the Power-
Voltage curve is tracked until maximum power point is
obtained. For instance the current value of power is compared
with the previous value and the value of 𝑉𝑟𝑒𝑓 is incremented or
decremented until the entire loop is returned to the beginning
when the Power is checked once again from its previous value.
Figure 4: Flowchart of P&O MPPT algorithm.
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 6 (2016) pp 3761-3767
© Research India Publications. http://www.ripublication.com
3763
Fuzzylogic control.
The three basic components of a typical FLC are fuzzification
module, defuzzification module, inference engine The Figure
5 as shown the basic flowchart of FLC.
𝑃(𝑘) = 𝑉(𝑘) ∗ 𝑖(𝑘) (5)
𝐸(𝑘) =𝑃(𝑘)−𝑃(𝑘−1)
𝑉(𝑘)−𝑉(𝑘−1)=
∆𝑝
∆𝑣 (6)
∆𝐸(𝑘) = 𝐸(𝑘) − 1 (7)
Figure 5 explains the concept of the control system. The
objective of the system to push the operating point towards the
point 𝑃𝑚𝑎𝑥 using controller. The advantage of the fuzzy control
is that it is robust, fast and responds instantaneously to
atmospheric changes. The inputs to the fuzzy logic system will
be error (E) and change in error(C).The output will be the
change in Duty cycle (∆d) at sampling instant (k) [3].
Every iteration the duty cycle is updated as per the fuzzy rule
base. Then the next sample of voltage and current is the fuzzy
variables are divided into 5 linguistic hedges: Negative Big
(NB), Negative Small (NS), and Zero (ZE), Positive small
(PS), Positive Big (PB).The membership functions are shown
in Figure 6.
Table 1 shows the fuzzy rule base. The output for each fuzzy
and input is tabulated in the form of a rule base the it uses
Mamdani implication. Now the load requires non fuzzy value
of control, a defuzzification stage is needed, by using the height
method Defuzzification is done
The fuzzy logic is shown to be more stable and reliable than
the perturb and observation method. The results output show
that the fuzzy output is more linear than P&O MPPT.The
results are shown in the Simulation results and validation
section.
Figure 5: Flowchart of Fuzzy logic controller
Figure 6: Membership functions of change in error
Table 1: Fuzzy rule Base
Boost converter design
The Boost converter is designed based on the general
equations in MATLAB/Simulink environment, duty cycle of
the boost converter is changing according to MPPT
𝑉𝑜
𝑉𝑠=
1
1−𝐷 (8)
Simulation Results and Validations This section consists of the simulation and hardware results of
the PV system. In Figure 7. ‘a’ ‘b’ and ‘c’ are shown the PV
output voltage (20V), current and power. In Figure 8. shows
the boost converter output voltage. The output voltage is
fluctuating between 38 to 40 volts. The output power of the
boost converter is varying between 16 watts to 18 watts,
getting these results by using perturb and observed method of
MPPT.
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 6 (2016) pp 3761-3767
© Research India Publications. http://www.ripublication.com
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Figure 7a: PV panel output Voltage
b). PV panel output current
c). Output Power of PV panel
Figure 8a: Boost converter output Voltage
b). Boost converter output power
The Figure. 9a, 9b, and 9c as shown the output voltage, current
and power of the PV panel. The current is fluctuating between
0.6 Amp to 0.8 Amp and corresponding power is 15 to 18
watts. The Figure 10a, 10b and 10c as shown the output
voltage (38V), current (0.42A) and power(16 Watts) of the
boost convert based on the fuzzy based MPPT
Figure 9a: Output Voltage of PV panel
b). Output Current of PV panel
c). Output Power of PV panel
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 6 (2016) pp 3761-3767
© Research India Publications. http://www.ripublication.com
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Figure 10.a: Boost converter output voltage
b). Boost convert output current
c). Boost converter output Power
System connected to battery through MPPT
Simulation of a standalone PV system connected to a lead acid
battery operating in maximum power point is carried out in
SIMULINK/MATLAB environment. The converter operates
in MPPT mode and charges the battery completely. In the
simulation the DC bus is connected to the battery to measure
the battery SOC, voltage and current. The output waveform of
the lead acid battery is shown in Figure 11. The negative
current depicted in the current waveform shows that the
battery is charging under STC i.e at constant temperature of
25°C and irradiation of 1000W/𝑚2.
( a)
(b)
(c)
Figure 11.a: Battery SOC, b) Voltage and c) current when
completely charged
( a)
( b)
Figure 12a: PV output Voltage, b) current of battery during
charging
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 159.9995
60
60.0005
60.001
60.0015
60.002
Time (seconds)
<SO
C (%
)>
Time Series Plot:<SOC (%)>
0 0.02 0.04 0.06 0.08 0.1 0.12
33.5
34
34.5
35
35.5
36
36.5
37
37.5
38
Time (seconds)
<V
olta
ge (
V)>
Time Series Plot:<Voltage (V)>
0 0.02 0.04 0.06 0.08 0.1 0.12
-300
-200
-100
0
100
200
300
Time (seconds)
<C
urre
nt (
A)>
Time Series Plot:<Current (A)>
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10
5
10
15
20
25
Time (seconds)
Voltage
Time Series Plot:
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10
0.2
0.4
0.6
0.8
1
1.2
1.4
Time (seconds)
Curre
nt
Time Series Plot:
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 6 (2016) pp 3761-3767
© Research India Publications. http://www.ripublication.com
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Hardware Prototype:
Figure 13: Hardware setup for MPPT with Boost converter
Figure 14: Duty cycle as during P&O MPPT operation
Figure 15: Output Voltage curve
Figure 16: Output Power curve
Table 2: Hardware results with resistive load (80Ω)
TIME Output
Voltage(Volt)
Resistive
Load(Ohm)
Power(watts)
10AM 15 80 2.81
11AM 20 80 5
12AM 24 80 7.2
1PM 28 80 9.8
2PM 32.4 80 13.1
3PM 27 80 9.11
4PM 18 80 4.05
5PM 14 80 2.45
In boost converter the inductor is designed for 0.5mH and
MOSFET IRFZ44 is used as switch. By using voltage resistive
divider circuit and Hall Effect current sensor to sense the
output voltage and current of the PV panel, Here 20watts PV
panel is used. In hardware design the perturb and observation
method algorithm is coded in MICROCHIP PIC16f877a.
TLP250 is used to provide the control signal between
MOSFET and microcontroller the PWM pulse output is
shown if Figure 14.
Conclusion The paper presents two MPPT methods P&O and FLC whose
simulation results are compared and verified. The FLC based
MPPT method is more accurate compared to P&O method. A
20 Watts hardware prototype is developed of the proposed
P&O system. With an constant load (80 Ohm) the output
power is calculated from 10AM to 5 PM 10th August 2015.
The maximum power is getting 13.1 watts and its related
voltage is 32.4 volt at 2PM.The minimum power getting 2.45
watts its related voltage is 14 Volt at 5pm.
References
[1] Md. Imran Khan, M. Rihanul Islam, Md. Zahanagir
Mozumder and K.M Rahman, “Photovoltaic
Maximum Power Point Tracking Battery Charge
Controlle”1st International Conference on the
Developments in Renewable Energy
Technology(ICDRET).2009.
[2] Mahalakshmi, R., Aswin Kumar A., and Aravind
Kumar. "Design of Fuzzy Logic based Maximum
Power Point Tracking controller for solar array for
cloudy weather conditions" power and energy
systems conference towards sustainable energy,
march 2014.
[3] I.H Atlas and A.M. Sharaf, “A novel maximum
power fuzzy logic Controller for photovoltaic solar
energy systems” Renewable energy, vol.33, no.3,
pp.388-399, 2008.
[4] I.H Atlas and A.M Sharaf, “A generalized direct
approach for designing fuzzy logic controllers in Mat
0
10
20
30
40
10AM 11AM 12AM 1PM 2PM 3PM 4PM 5PM
Output Voltage(Volt)
0
5
10
15
10AM11AM12AM 1PM 2PM 3PM 4PM 5PM
Output Power (watts)
Power(watts)
International Journal of Applied Engineering Research ISSN 0973-4562 Volume 11, Number 6 (2016) pp 3761-3767
© Research India Publications. http://www.ripublication.com
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lab/Simulink GUI Environment”, International
journal of Information technology and Intelligent
Computing, vol. 1, no.4, 2007.
[5] Roman, Cristian, Virgiliu Fireteanu, Jacqueline Etay,
and Yves Fautrelle. "An overview on solar energy,
molten salts and electromagnetic pumping
technologies", 10th International Conference on
Environment and Electrical Engineering, Jan 2011.
[6] Rao, S. P. Lakshman, Ciji Pearl Kurian, B. K. Singh,
Kumar Abhinav, and Gaurav Nandy. "Design and
simulation of grid connected hybrid solar-WECS
using SIMULINK/MATLAB", 2014 International
Conference on Advances in Energy Conversion
∩∩Technologies (ICAECT), 2014.