Implementation of Fuzzy Logic Based MPPT Controller for Solar

Photo Voltaic Application

Gaganambha

1 a

, Varsha V

1 b

, Shamala N

1 c

and Arjun Joshi

1 d

Department of Electrical and Electronics Engineering, Vidya Vikas Institute of Engineering and Technology, Mysuru

Keywords: Solar Photovoltaic Array (SPV), MPPT, Zeta Converter, Brushless DC Motor (BLDC).

Abstract: In this work, a straightforward water pumping system that is driven by a BLDC motor and fed by a solar

photovoltaic array is proposed. Because of its smaller size, quieter operation, and increased dependability,

BLDC motors are used. A solar photovoltaic array serves as the source of energy for the motor. The maximum

power is extracted and the zeta converter switch is regulated by means of maximum power point tracking or

MPPT. A solar array's voltage is increased via a zeta converter. VSI switching pulse is generated by the

electronic commutation of the BLDC motor. In this instance, an incremental conductance approach is utilized

in conjunction with a fuzzy-based MPPT controller, and the outcomes are compared. MATLAB / SIMULINK

software is used to simulate the proposed system and examine its simulation results.

1 INTRODUCTION

Today the rate of consumption of energy is increasing

more rapidly due to increase in population,

communication network, industries, transportation,

etc. Development and success of any country is

mainly depends on uninterrupted power supply.

However, the availability of conventional fossil fuels

(such as oil, natural gas, coal, gasoline, and diesel) is

declining, leading to an energy dearth. Using energy

from renewable sources to supplement fossil fuel

consumption is one alternative (Sujata S Naik et al.,

2019).

There are numerous varieties of sources of

sustainable energy, such as solar, wind, hydro, and

tidal energy. Among all these sources of renewable

energy, solar energy is unique in that as it produces

power that is free of cost, non-toxic, and always

clean. Additionally, the price of SPV panels is

declining nowadays, which draws more attention to

the use of solar photovoltaic applications (Kumar R

et al., 2014). Both residential and commercial

applications based on renewable energy employ this

technology. Water pumping is the most efficient and

affordable use of all application-based SPV systems

https://orcid.org/0009-0005-6161-4393

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https://orcid.org/0009-0008-5919-6219

for generating electricity from solar photovoltaic

arrays (Chandani Sharma et al., 2014).

Typically, in general run of the things simple,

affordable, and effective motors are employed for

water pumping applications. Direct current motors

and induction motors are primarily utilized for

pumping load applications due to their easy

availability and outstanding performance under all

load conditions, However, when these motors are

utilized for solar photovoltaic applications, they

overheat and require elaborate controls because of

low motor voltage (A. Shahin et al., 2010, H Kukde,

2017). Consequently, in low voltage situations,

dependable and efficient motors are needed to

overcome these issues; brushless DC motors are

utilized in these applications.

The term "brushless direct current motor" (BLDC)

refers to a motor without any brushes (R. Saxena et

al, 2008) Due to the lack of brushes and a

commutator, brushless DC motors have several

advantages: longer life, reduced inertia from minimal

friction, increased efficiency, increased

dependability, and a high maximum speed

(AbolfazlHalvaeiet., 2005, T. Esram et al., 2007)

150

Gaganambha, ., V., V., N., S. and Joshi, A.

Implementation of Fuzzy Logic Based MPPT Controller for Solar Photo Voltaic Application.

DOI: 10.5220/0012531400003808

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Intelligent and Sustainable Power and Energy Systems (ISPES 2023), pages 150-154

ISBN: 978-989-758-689-7

Be advised that papers in a technically unsuitable

form will be returned for retyping. After returned the

manuscript must be appropriately modified.

2 METHODOLOGY

Fig 1: Block representation of the proposed system.

2.1 Maximum Power Point Tracking

The voltage at which a solar module generates the

most electricity is known as its maximum power

point. The main goal of MPPT is to determine the

highest power that a photovoltaic panel can generate

under various environmental conditions, such as

temperature, sun irradiation, and solar cell

temperature (M. Lokanadham et al., 2012)

2.2 Incremental Conductance MPPT

(Inc MPPT)

The basic tenet of the incremental conductance

method is that the power curve of a solar array has a

zero slope at the highest power point (Nandini. D et

al., 2017). In order to measure the output voltage and

current of the solar array, this method employs

voltage and current sensors. Using this technique, the

PV array's voltage is adjusted based on the voltage at

the source of the most power. This is dependent on

the photovoltaic module's incremental and

instantaneous conductance (T. Esram.et al., 2007). A

comparison is made between the array conductance

(I/V) and the incremental conductance (dI/dV). When

(I/V) = (dI/dV), there is a maximum output yield; at

the maximum power point, dP/dV = 0 (Nandini. D et

al., 2017, M. Lokanadham et al., 2012).

dP/dV = VdI/dV+I(V) (1)

dI/dV= -I(V)/V (2)

Fig 2: Inc MPPT flow chart.

2.3 Fuzzy Logic MPPT

A novel technique for regulating MPPT to determine

peak power is fuzzy logic. To implement fuzzy logic

control, three fundamental modules are needed:

fuzzification, deffuzification, and inference engine

(T. Esram et al., 2007).

Fuzzification is the systematic approach of

changing a computational input variable into a

linguistic one. Fuzzy controllers use duty cycle as its

output, which is employed to control DC-DC

converters. The input variables are error and change

in error. To produce a fuzzy output, the inference

engine applies the rule to a fuzzy input. NB (negative

big), NS (negative small), ZE (zero), PS (positive

small), and PB (positive big) are the five fuzzy levels

that are employed. Language variable attributed to

change in duty cycle for various combinations of E

and CE. Fuzzy rules' main objective is to change the

duty cycle in order to move the operational stance to

the maximum power point. During defuzzification,

the fuzzy logic controller's output is changed from a

linguistic variable to a numerical variable value using

the membership function(T. Esram et al., 2007).

Fig 3: Configuration of Fuzzy Logic Controller.

Implementation of Fuzzy Logic Based MPPT Controller for Solar Photo Voltaic Application

151

2.4 Zeta Converter

Fig 4: Circuit diagram of Zeta Converter.

The zeta converter is a fourth order DC-DC converter

made up of a switch, a diode, two inductors, and two

capacitors. This converter has ability to transform an

input voltage into an output voltage that is not

inverted. It has aptness to work in both step-up and

step-down modes(Sujata S Naik et al., 2019, Nandini.

D et al., 2017).

Vout = Vin * (D/ (1-D)) (3)

2.5 Implementation

The electrical power required by the motor-pump is

generated by a solar array. The motor receives this

power from zeta converter and VSI. The MPPT

controller receives data from the solar photovoltaic

array and utilizes it to modify the zeta converter's duty

cycle to maximize power. A switching pulse

produced will switch an IGBT of the converter by the

pulse generator via maximum power point controller.

Here, the duty cycle of the zeta converter can be

altered to function in either step-up (boost) or step-

down (buck) mode. The converter used in this work

is operating in boost mode, which boosts the output

value from the SPV array. So that regulated output at

the converter can be obtained. The DC output power

of the converter is converted into AC power by the

voltage source inverter and then sent to BLDC motor.

By operating the VSI in 120-degree conduction

mode, commutation losses can be minimized. The

switching pulse for VSI is provided by hall signals of

a BLDC motor.

2.6 Photovoltaic Array

The photovoltaic Array is modelled by using one

diode model. Series resistance Rs used to build solar

cells is coupled in series with a parallel combination

of current sources made up of diodes and shunt

resistance Rsh.

Fig 5: Proposed System's Matlab Model.

Fig 6: Equivalent photovoltaic cell circuit.

Diode Current (Id) = [e (

V/NS+I*RS/NS)/VT*C

-1] IS NP (4)

Shunt Current(Ish)=(V+I*Rs)/Rp (5)

Terminal Voltage=k*Top/q (6)

Phase current (Iph)=[(TopTref)k+Isc]Irr (7)

(Is)=Irs(Top/Tref)(q*1.12/k*N)(1/Top1/Tref) (8)

Load current (I)=Iph*NpIsh (9)

Fig 7: Simulink model of SPV panel.

2.7 Simulink Model BLDC Motor

Simulink model of BLDC motor built with Matlab

program is displayed in Fig 12. The three-phase

winding BLDC motor receives power from a VSI,

with each phase offset by a 120-degree angle.

ISPES 2023 - International Conference on Intelligent and Sustainable Power and Energy Systems

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Fig 8: BLDC motor Simulink model.

3 RESULT AND DISCUSSION

At 1000W/m2 solar irradiation, conduction of a solar

photovoltaic array supplied BLDC motor employing

a zeta converter is examined. And maximum power

can be tracked by using MPPT controller. The curve

of the array voltage with respect to time is shown in

Fig. 9. As seen in graph, the array voltage begins at a

low beginning value and gradually rises as motor

speed increases. Once the motor speed reaches a

constant value, the array voltage then stays constant.

Fig 9: PV panel Output voltage.

Fig 10: PV panel Output power.

3.1 Incremental Conductance MPPT

Fig 11: Converter Output voltage using Inc MPPT.

Fig 12: Motor Speed using Inc MPPT.

Fig 13: Emf_abc using Inc MPPT.

Fig 14: Motor torque.

3.2 Fuzzy MPPT

Fig 15: Output voltage of converter using Fuzzy MPPT.

Fig 16: Speed of BLDC motor using Fuzzy MPPT.

Implementation of Fuzzy Logic Based MPPT Controller for Solar Photo Voltaic Application

153

Fig 17: Motor torque.

4 CONCLUSION

A straightforward solar photovoltaic array with a

BLDC motor based on a Zeta converter has been

proposed to power a water pumping system. In order

to power the motor, a photovoltaic array, a circuit

made up of one diode-equivalent solar cells is used as

the input source. This array has numerous advantages,

such as being free, clean, and non-polluting.

Fuzzy based MPPT controller is used to run the

converter switch and extract the maximum power

from the solar panel; the results are compared with

the incremental conductance approach. It can be

noticed that Fuzzy based MPPT gives better results,

and time taken to achieve speed response is fast. Here

Zeta converter is used because of its various

advantages such as circuit is simple, fast response,

wide range of power tracking. And for boosting the

photovoltaic array output voltage zeta converter is

used.

The absence of brushes in brushless motors results

in improved performance characteristics, eliminating

the drawbacks of standard brushed DC motors.

Electronic commutation is used in Brushless DC

motors to execute commutation, and the motor's

speed is controlled without the use of an additional

control circuit. The proposed system is created using

MATLAB / SIMULINK software. To validate the

suggested system, output waveforms of PV panel, the

zeta converter, and the Brushless DC motor are

shown.

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