fuzzy logic based maximum power point tracking
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PROJECT REPORT
ONFUZZY LOGIC BASED MAXIMUM POWER POINT
TRACKING
Submitted by:
Krithik Kumar Chandrashekar
Nisarg M. Dave
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Abstract
This project proposes the use of a fuzzy logic based control method for maximum power point
tracking for photovoltaic array. The power output of a solar array under normal operating
considerations is dependent on the temperature and irradiation conditions. Therefore in order
to maximize the amount of power delivered to the battery/load, a control technique must be
employed. Some of the common techniques used for MPPT are Fractional Open circuit current,
Perturb and Observe, Incremental conductance. There are advantages/disadvantages to each of
these techniques .This project makes a comparison with fractional open circuit current MPPT
and one without any MPPT.
Introduction
Photo-Voltaic based methods of power generation have become the crux of future energy
needs, it is quite apparent as to why this has become so , fossil fuels have not only caused
considerable environmental damage but the sources of the fuel have also diminished to a large
extent. Hence the focus has shifted to renewable energies. However renewable energies have
in some cases shown to have little efficiency, it is in these cases that new developments must
be applied to improve the output power thus making renewable energies more viable. One of
the ways to achieve this in solar energy is called maximum power point tracking. A maximum
power point tracker (or MPPT) is a high efficiency DC to DC converter that presents an optimal
electrical load to a solar panel or array and produces a voltage suitable for the load. PV
cells have a single operating point where the values of the current (I) and Voltage (V) of the cell
result in a maximum power output. These values correspond to a particular resistance, which is
equal to V/I as specified by Ohm's Law. A PV cell has an exponential relationship between
current and voltage, and the maximum power point (MPP) occurs at the knee of the curve,
where the resistance is equal to the negative of the differential resistance (V/I = -dV/dI).
Maximum power point trackers utilize some type of control circuit or logic to search for this
point and thus to allow the converter circuit to extract the maximum power available from a
cell.
Recently fuzzy logic controllers have been introduced in the tracking of the MPPT in PV systems.
They have the advantage to be robust and relatively simple to design as they do not require theknowledge of the exact model. They do require in the other hand the complete knowledge of
the operation of the PV system by the designer. A fuzzy logic system may seem as an ideal
choice for MPPT given the non linear nature of the PV characteristics of the solar cell.
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PV Array
Duty Ratio
Voltage Power
Figure 1: Solar Array System
The overall block diagram is illustrated above. Here we can see that between the array and the
battery we have a boost converter with a fuzzy logic controller. The voltage and power from the
array is measured and fed to the controller. Based on the rate of change of error in power and
voltage, the duty ratio is adjusted automatically. The duty ratio is adjusted such that maximum
possible power is delivered to the load; in this case we have the battery.
Application
The application we have chosen is a solar powered street light .The load is a 12V, 60 watt
lamp(s). To size the battery and the panel the following things are taken into consideration
1. Hours of Operation -10hours, 600 watt-hours
2. Days of Backup in case of cloudy weather /rainy days -1 day
DC-DC
CONVERTER
FUZZY LOGIC
CONTROLLER
Battery
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3. Grid connection – Not Present, Off Grid
4. Battery Voltage -12V
5. Number of Sun Hours for Chicago: 4.4 hours
After careful calculation we arrive with the conclusion that battery and solar panels should be
sized as follows.
Battery Size/Capacity-200ah
Solar Array Size-200Watt
Solar Panel Specifications
Current/Voltage/Power ES-A-200-fa3
Pmp
Ptolerance
Pmp, max
Pmp, min
ηmin
Pptc
Vmp
Imp
VocIsc
200
-0/+4.99
204.99
200.00
12.7
180.6
18.10
11.05
22.6011.80
As it can be seen that under standard conditions, the maximum power that can be extracted is
180 watts. However the data sheet of the solar panel1
specifies that the test conditions to be at
a temperature of 20 degree centigrade and 1000 w/m2.
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Battery Specifications
Ritar 12V / 200Ah VLRA Battery
Figure 2: Discharge Characteristics of the Battery
Parameter ValueCells Per Unit
Voltage Per Unit
Capacity
Weight
Max. Discharge Current
Internal Resistance
Operating Temperature Range
Normal Operating Temperature RangeFloat charging Voltage
Recommended Maximum Charging
Current Limit
Equalization and Cycle Service
6
12
200Ah@10hr-rate to 1.75V per cell @25°C
Approx. 60.0 Kg
2000A (5 sec)
Approx. 4 mΩ
Discharge: -20°C ~ 60°C
Charge: 0°C~50°C
Storage: -20°C~60°C
25 C±5C13.6 to 13.8 VDC/unit Average at 25°C
60 A
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DC-DC boost convertor
Figure3: Boost Converter2 Figure 4: Inductor current v/s time
The design of DC-DC boost converter is done to supply the battery for a 12V battery.
Inductance= 0.000128Henry
Capacitor=0.006 farad
Switching Device=MOSFET
Switching Frequency=1 kHz
A boost converter is part of a subset of DC-DC converters called switch-mode converters. The
circuits belonging to this class, including buck, flyback, buck-boost, and push-pull converters are
very similar. They generally perform the conversion by applying a DC voltage across an inductor
or transformer for a period of time which causes current to flow through it and store energy
magnetically, then switching this voltage off and causing the stored energy to be transferred to
the voltage output in a controlled manner.
Applying Kirchhoff’s rules around the loops and rearranging the terms gives an intuitive resultas shown below.
Vout/Vin=1/ (1-D)
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Fuzzy logic controller3
Figure 5: Fuzzy logic controller –look up table
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MPPT attempts to move an operation point of a solar array as close to the maximum power
point or the knee of the I-V curve shown in Figure as possible. Mathematically, this is equivalent
to finding the point where the derivative dP/dV is equal to zero. Alternatively, when
implemented in digital system, output voltage and current at consnsecutive time interval n-1
and n are sampled, to search the peak power point of a solar array, firstly defined as error
function is
E (n) =P (n)-P (n-1) / V (n) - V (n - 1).
Also, the associated change of error is defined as
∆E (n) =E (n)-E (n-1).
The controller works to force the error function, which is the derivative of power with respect
to the measured voltage, and its associated change of error to zero. Thus an optimal operation
point can be obtained. Instead of finding the underlying derivative, MPPT can also be achieved
by means of fuzzy logic. Let us denote a duty ratio of the switch in Fig.2 as D(n). With reference
to the I-V and power curve, the fuzzy meta rule for MPPT can be stated as “If the last change in
the duty ratio D(n) has caused the power to rise , keep moving the duty ratio D(n) in the same
direction otherwise , if it has caused the power to drop, then move in the opposite direction”
Rule (i) : if E(n) is A; and ∆E(n) is B; then ∆D(n) is C
Where A, B, and C represent fuzzy sets including positive big (PB), positive small (PS), zero (ZE),
negative big (NB), and negative small (NS). Figure 5 shows the membership functions of the
input variables E(n) and ∆E(n) and the output variable D(n).
E(n)\ ∆E(n) NB NS ZE PS PB
NB PB PB PS PB PB
NS PB PS PS PS PB
ZE NS NS ZE PS PS
PS NB NS NS NS NB
PB NB NB NS NB NB
Figure 6: Fuzzy rule table for ∆D(n)
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Results
Figure 7: I-V and I-P curves under 1000 w/m2
at 25 degree centigrade
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Figure 8 Power supplied for no MPPT
Figure 9 Power Supplied for fuzzy logic controller
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Figure 10 Power Supplied for Fractional Open Circuit case
Controller Type Power Delivered Watts State Of Charge
No MPPT 140 74.89%
Fractional Open Circuit
Current
173.0114 87.51%
Fuzzy Logic Based 173.5729 87.44%
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Conclusion
As it can be observed that there is an improvement of 23% from the case of no mppt to
that of fractional open circuit voltage and fuzzy logic based controller. Fuzzy logic offers only a
marginal improvement in power delivered to the battery. However the state of charge reached
by both the cases is similar. Though fuzzy logic may offer benefits in the long run, there is a
tradeoff between the processing time and cost.
References
[1]http://www.altestore.com/store/Solar-Panels/150-Watts-Up-SolarPanels/Evergreen-
ES-A-200-FA3-200W-12V-Solar-Panel-Black/p7348/
[2] B. M Hasaneen, Adel A. Elbaset , ”Design And Simulation of DC/DC Boost Converter” The
Twelfth International Middle East Power System Conference, MEPCON'2008, South Valley University,
Faculty of Eng., Aswan, Egypt, Vol. I, March 13-15, 2008
[3] N. Khaehintung , P. Sirisuk “Implementation of Maximum Power Point Tracking Using
Fuzzy Logic Controller for Solar-Powered Light-Flasher Applications”