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International Journal of Advanced Scientific and Technical Research Issue 3 volume 6, Nov.-Dec. 2013

Available online on http://www.rspublication.com/ijst/index.html ISSN 2249-9954

R S. Publication (http://rspublication.com), [email protected]. Page 337

DESIGN AND SIMULATION OF MPPT ALGORITHM

OF PHOTOVOLTAIC SYSTEM USING INTELLIGENT

CONTROLLER

S. Shamshul Haq1, B. Wilson Shyam sunder

2 , G. Mohammad Zameer

3

1Department of EEE, SJCET, Kurnool, A.P, INDIA.

2Department of EEE, GPCET, Kurnool, A.P,INDIA.

3Department of EEE, VIFCET, Hyderabad, A.P, INDIA.

ABSTRACT

This paper presents an intelligent control technique for maximum power point tracking (MPPT)

of a photovoltaic system under different irradiation and cell temperature conditions. PV system

operates with maximum power output at a particular operating point know as maximum power

point. Maximum power point varies, based on the irradiation & cell temperature, so an

appropriate control technique must be used to track (MPP) & operate the system at that point. In

this paper a PI controller and fuzzy logic controller (FLC) are used as MPPT controllers, applied

to a DC-DC boost converter. The simulation results show that fuzzy logic controller possesses a

much better behavior than a PI controller.

Keywords: Maximum Power Point Tracking, Fuzzy Logic Controller, Photovoltaic system.

INTRODUCTION

Renewable energy sources have become a important contributor to the total energy consumed in

the world. New energy sources are continuously enhanced due to the critical situation of the fuels

such as oil, gas & others. The demand for solar energy has increased by 20% to 25% over past

20 years [1].Between 2004 &2009, grid connected PV systems capacity reached 21GW and is

increasing at a annual average rate of 60 % [2]. To increase the benefits from the PV systems, a

lot of research activities are going around the world in an attempt to improve efficiency,

reliability & to reduce the cost.

PV cells with no pollutant emission, converts sunlight directly to electric power. The conversion

efficiency of electric power generation of a PV system is very low(9-17%) especially during low

irradiation conditions and the power generated changes continuously with weather conditions

The PV generators can be grid connected (operating distributed generation systems) or can

operate in stand-alone (autonomous) systems. Solar photovoltaic is a phenomenon where the

solar irradiation is converted directly into electricity through solar cell [3].




MODELOF PHOTOVOLTAIC CELL MODEL

In simulation mathematical equations describing the system characteristics are formulated &

translated into computer codes. Single diode circuit model is most commonly used to analyses

the energy generation in a photovoltaic cell that represent the electrical behavior of the pn-

junction.

An ideal module consists of a single diode connected in parallel with a light generated current

source.

Figure.1 Equivalent Circuit of PV cell

Where Iph represents cell photo current Rs & Rsh indicate the intrinsic shunt & series resistances

of the cell. PV cells are inter-connected to form larger unit called as PV modules & these

modules are inter connected in parallel/series to form PV arrays. Photovoltaic penal is modeled

using the mathematical equations (1) – (4) [8] - [9]

The equation for module photo – current is given as

Iph = [Iscr + Ki (T- 298)] * α/1000 (1)

Reverse saturation current (Irs ) is given as

Irs = Iscr/[exp(qVoc/NsKAT)-1] (2)

As the temperature varies module saturation current (Io) varies ,It is given

Io=Irs[T/Tr]3exp[q*Ego/BK{1/Tr-1/T}] (3)

Output current of PV module is given as

IL=Np*Iph – Np*Io[exp{q*(Vpv + IpvRs) / NsAKT}-1] (4)

The proposed model consists of No. cells connected in parallel(Np) =1 , No. of cells connected

in series( Ns) = 36

Where VL ,IL, Tr, T ,Iph, Io, Iscr are output voltage, output current of pv module, reference

temperature ,operating temperature, light generated current, module saturation current, module

short circuit current.




Table 1: Electrical Characteristics Data of Solkar 36 KW PV Module

Rated Power 37.8W

Current at Maximum Point (Impp) 2.25A

Voltage at Maximum Point (Vmpp) 16.56V

Short Circuit Current ( Vsc) 2.55

Open Circuit Voltage ( Voc) 21.24

No.of cells in parallel (Np) 1

No. of cells in series (Ns) 36

The above electrical specifications are under conditions of irradiance of 1 KW/m2, spectrum of

1.5 air mass & cell temperature of 25o C. The P-V & I-V characteristics of PV array for different

irradiation are obtained as show below in Fig(2) & Fig(3)

Figure 2 Output P-V characteristics Figure 3.Output I-V characteristics

The simulink model of PV module is modeled using equations (1)- (4)

DC – DC BOOST CONVERTER

It is a power electronic device & it has a capability of providing an voltage which is higher than

the input voltage [10].The circuit diagram of a boost converter is shown in fig (4)

Fig (4).Boost Converter

In boost converter value of L is calculated such that the peak current of inductor at maximum

input power does not exceed the power switch current rating.

L ≥Vm(1-D)D/fs ǀ ΔIǀ ( 5)




Where fs is switching frequency, D is the duty cycle at maximum input power of the converter ,

ΔI is the ripple of inductor current, Vm and Im the maximum output voltage and current at

maximum output power.

Capacitor value at the input is calculated as

Ci ≥ ImD2/[0.02(1-D)Vinfs] ( 6 )

Where Vin is the input voltage of photovoltaic input voltage at maximum power point.

Output capacitor value is calculated as

Co ≥ DIout / rfsVout ( 7)

Where r is the output ripple factor.

IMPLEMENTATION OF MPPT CONTROLLERS

( i) PI MPPT CONTROLLER

A proportional integral controller is a generic control loop feedback controller. PI controller

attempts to reduce the error to minimum value by changing the control input. A PI controller can

be easily implemented to track MPP because of simple operation, past success record, ease of

design & use. PI controller based MPPT for PV module is shown in fig (5)

Fig(5).Block diagram of PI Controller based MPPT

PI controller works with the co-operation of proportional & integral action. The mathematical

equation can be given as

P = Kpe + KpKi ∫ edt + P(0) (8)

Where P , Kp , Ki , e are the controller output proportional gain, integral constant , & error input.

P(0) = initial value of controller output.

(ii) FUZZY LOGIC MPPT CONTROLLER

Lotfi Zadeh , the father of fuzzy logic , claimed that many sets surrounding us are defined by a

non –distinct by a non – distinct boundary. He externad two valued logic, defined by pair of




binary { 0 , 1}, to the whole continuous internal [0,1], there by introducing a gradual transition of

false to truth [11]. It provides a general method of expressing linguistic rules based on fuzzy sets

& fuzzy algorithms. The main advantages of fuzzy logic controller is it does not require any

mathematical model of the system. Complex systems deal with complex systems can be

controlled without the knowledge of exact mathematical model of the system.

The fuzzy logic controller consists of three blocks -

1. Fuzzification 2.Inference 3.Defuzzification.

In the proposed fuzzy logic based technique the error(E) & changing of error (CE) are the inputs.

The error value is calculated as

E K = dp

dv=

Pph K −Pph (K−1)

Vph K − Vph (K−1) (9)

𝐶𝐸 𝐾 = 𝐸 𝐾 − 𝐸(𝐾 − 1) (10)

Where Pph(K) is the power of the photovoltaic system. In this proposed work the inputs of the

fuzzy logic are expressed in five linguistic variables ,As shown in figure ( 6a ) & figure ( 6b )

Fig (6a). Input Variable “error” Fig(6b) Input Variable “Change in error”

The control surface which relates the input & output variables of the system are governed with a

set of rules. A rule would be “If x is A Then y is B”, the rule table is as show in Fig (7a).Fig (7b)

shows the surface rule viewer.




(7a) Fuzzy Logic Rule Table Fig(7b) Surface Rule Viewer

The control scheme of Fuzzy controller based MPPT for PV module is represented as shown in

Fig (8)

Fig(8).Block diagram of Fuzzy controller based MPPT for PV module

SIMULATIONS AND RESULTS :

To show clearly the performance of these two controllers, simulation work is carried out. A

MATLAB /SIMULATION based modeling scheme for PV system along with MPPT PI and

Fuzzy controller are proposed. These simulation scheme are suitable for studying the P-V & I-V

characteristics under a non – uniform irradiation & different temperature. The results of fuzzy

logic controller are compared with the PI controller results.




Simulation circuit of PI based MPPT Controller as show in fig (9a) & fig(9b) shows the

simulation of FLC based MPPT for PV systems.

Fig(9a).Simulink model of PI controller Fig(9b) Simulink model of FLC based MPPT

based MPPT

Proposed Simulink model of PV system with MPPT controller is as shown in fig(10)

Fig(10)Simulink model of PV system with MPPT controller

The out power of a PV module with PI Controller based MPPT is shown in fig(11).




Fig (11) .PV Output power with PI Controller based MPPT at 500,800 & 1000 irradiations

Fig(12) PV Output power with fuzzy logic controller based MPPT at 500, 800 ,1000 irradiations

Combined output power of PV module using PI & FLC based MPPT are shown in fig(13)

Fig(13).Output power of PV using PI & FLC based MPPT




CONCLUSION

In this paper maximum power point tracking controllers are designed to extract the highest

possible power from the solar arrays. The proposed controllers FLC & PI controller are

implemented to a Boost DC-DC converter for tracking maximum power point. These two

controllers are tested using the MATLAB/SIMULINK. The results of these two controllers are

compared. From the results comparing both PI controller & FLC shows that FLC is having better

response & steady state output when compared to PI controller.

REFERENCE

[1] Jeyraj Selvaraj, Nasrudin A. Rahim, “Multilevel Inverter For Grid-Connected PV System

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[9]S. Nema, R.K.Nema, and G.Agnihotri, “Matlab / simulink based study of photovoltaic cells /

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[10] J.H.Su, J.J.Chen, and D.S.Wu, “Learning feedback controller design of switching converters

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[11] J. Jantzen, "Tutorial on Fuzzy Logic", Technical University of Denmark: Department of

Automation, Technical report number 98-E 868, 19 Aug 1998, URL: http://www.iau.dtu.dk

http://www.iau.dtu.dk/




S.SHAMSHUL HAQ is the Assistant Professor in the department of EEE, St.Johns

College of Engineering, Yemmiganur. He has completed his M.Tech from JNTU Hyd.

He has 6 years of teaching experience. His area of interests are Power systems,

Renewable Energy sources, Artificial Intelligent, Power Electronic converters.

B.Wilson Shyam Sunder is Assistant Professsor in department of EEE, G.Pullaiah

College of Engineering & Technology, Kurnool. He completed his M.Tech from

JNTU Kakinada. He is having three years of teaching experience. His area of interest

are Power systems, multilevel Inverters, High voltage Engineering.

G. Mohammad zameer is working as Assistant Professor at VIF College of

Engineering & Technology. He completed his M.Tech from SK University Anantapur.

He is having six years of teaching experience. His area of interest is Renewable Engery

Sources, Power Electronics.

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