simulation and analysis of perturb and observe mppt...

Advance in Electronic and Electric Engineering. ISSN 2231-1297, Volume 4, Number 2 (2014), pp. 213-224 © Research India Publications http://www.ripublication.com/aeee.htm

Simulation and Analysis of Perturb and Observe MPPT

Algorithm for PV Array Using ĊUK Converter

Tekeshwar Prasad Sahu1, T.V. Dixit2 and Ramesh Kumar3

1M. Tech Scholar in Instrumentation and Control, Bhilai Institute of Technology Durg, C. G., India.

2Associate Professor in Electrical & Electronics Department, Bhilai Institute of Technology Durg, C. G., India.

3Professor in Computer Science Department, Bhilai Institute of Technology Durg, C. G., India.

E-mail: [email protected], [email protected], [email protected]

Abstract

This paper presents the comparative analysis between constant duty cycle and Perturb & Observe (P&O) algorithm for extracting the power from Photovoltaic Array (PVA). Because of nonlinear characteristics of PV cell, the maximum power can be extract under particular voltage condition. Therefore, Maximum Power Point Tracking (MPPT) algorithms are used in PVA to maximize the output power. In this paper the MPPT algorithm is implemented using Ćuk converter. The dynamics of PVA is simulated at different solar irradiance and cell temperature. The P&O MPPT technique is a direct control method enables ease to implement and less complexity. Keywords: Photovoltaic Array (PVA), MPPT, Ćuk Converter.

1. Introduction Among the renewable energy resources, the energy through the solar photovoltaic effect can be considered the most necessary and prerequisite sustainable resource because of the ubiquity, large quantity, and sustainability of solar energy. The output characteristics of PV module depends on the solar irradiance, cell temperature and output voltage of PV module. Since PV module has nonlinear characteristics, it is necessary to model it and simulate for Maximum Power Point Tracking (MPPT) of PV system applications. A PV module generates small power, so the task of a MPPT in a

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PV energy conversion system is to continuously tune the system so that it draws maximum power from the solar array regardless of weather or load conditions (Chermitti et al, 2012). Previously buck, boost and buck-boost converters are used to transfer the power generated by PVA to load (Ankur Bhattacharjee, 2012; Kalirasu and Dash, 2010). In literature it is reported that direct control of Ćuk converter minimizes power loss and avoids the discontinuous conduction. The limitation of PI controller is observed by some of the (Safari and Mekhilef, 2011). The PI controller increase complexity of system. In this work direct control of duty cycle using MPPT technique is explored.

2. Block Diagram of Tracking System The voltage and current generated by PVA are inputs of the MPPT system and the task of the MPPT algorithm is to calculate the reference voltage. The MPPT systems contain two control loops to achieve maximum power. The inner loop contains the MPPT algorithm block and comparator to generate the switching pulses. The external control loop contains the PI controller, which controls the input voltage of the converter. The PI controller works towards minimizing the error between Vref (generated by MPPT block) and the output voltage of DC-DC converter by vary the duty cycle. The MPPT block is used to generate an error signal, which is non zero at most of the operating points except at MPP. Simplicity of operation, ease of design, inexpensive maintenance, and low cost made PI controllers very popular in most linear systems. However, the MPPT technique of standalone PV system is a nonlinear control problem due to the nonlinearity nature of PV module and un-predictable environmental conditions. Hence, PI controller performance is inferior with PVA system (Safari and Mekhilef, 2011).

PV array Ćuk converter load

MPPTsystem

v,i

L Li , vD

Fig. 1: Block Diagram of MPPT Using PI Controller

Fig. 2: Block Diagram of Direct Duty Cycle (δ) Control MPPT

3. Block Diagram of Tracking System 3.1. Photovoltaic System Photovoltaic (PV) cell is a semiconductor device which directly converts the light energy into electrical energy. A PV system consists of a multiple component, including the modules, mechanical connection, electrical interconnections, and mounting for other components. Photovoltaic cells are made of several types of semiconductors

Simulation and Analysis of Perturb and Observe MPPT Algorithm for PV Array 215

using different manufacturing processes (Villalva, et al, 2009). Typically, photovoltaic (PV) cell generates a voltage around 0.5 to 0.8 volts depending upon semiconductor and the built-up technology. The numbers of PV cells are connected in series and parallel to get more amounts of voltage and current known as PV module and if many such modules are connected for any application to get desired amount of current and voltage then it is called as PV array (Ahmad and Singh, 2012).

3.2. Mathematical Model of PV Module The current–voltage relationship of mathematical model is represented in equation (Tsai et al, 2008).

S PS

S P SP PH P S

SH

IRV N Vq IRN N N

I N I N I exp 1kTA R

(1)

The PV module photocurrent which depends on the solar irradiation & cell’s operating temperature, which is described as:

sc i refph

[I K (T T )]I 1000

(2) On the other hand, the cell’s saturation current varies with the cell temperature,

which is described as:

3 Grefc

S RSref

1 1qE T TTI I expT kA

(3)

Reverse saturation current can be described as:

exp 1

SCRS

OC

S

IIqV

N kAT

(4)

3.3. Different Parameter Used in Standalone PV Module The Solkar 36W PV modules are taken as the reference PV module for simulation and electrical characteristics are: NP= 36, NS = 1,Tref = 25oC, A = 1.6, q=1.6*10^-19, k=1.380658e-23 ,ISC = 2.55 A,VOC = 21.24, Eg = 1.1 (Pandiarajan and Ranganath, 2011).

3.4. Simulation Result of PV Module The simulation results of i-v curve and p-v curve of PV model for different solar irradiation and constant temperature (T=250C) are shown in Fig.3.

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Fig. 3: i-v Curve and p-v Curve for Different Solar Irradiance.

From the above current & power curve for different solar irradiation and constant

temperature, it can be observe that current & power of the PV module increases with increasing the solar irradiation.

The simulation results of i-v curve and p-v curve of PV model for constant solar irradiation (β = 800 W/m2) and different temperature are shown in Fig.4. From the above it can be observe that voltage and power of the PV module decreases with increasing the cell temperature.


Fig. 4: i-v Curve and p-v Curve for Different Cell Temperature.

4. Modeling of DC-DC ĆUK Converter PVA generated voltage is fed to the converter and Ćuk converter output connected to the load. By varying the duty cycle the voltage gain of both Buck–Boost and Ćuk converters can be set higher or lesser than unity. Although the buck–boost configuration is cheaper than the Ćuk but it has some limitations such as high peak and discontinuous input current, poor transient response and efficiency. The Ćuk converter has low switching losses and the highest efficiency among non-isolated DC-DC converters. It can also provide a better output-current characteristic due to the inductor on the output stage (Safari and Mekhilef, 2011; Durán 2011).The practical circuit of Ćuk converter using diode and MOSFET are shown in Fig.5 (Rashid, Third Edistion; Erickson and Maksimovic; Second Edition).

2v

2C

1C1L 2L1i 2i

gV

1v

RG1 D1

Fig. 5: Ćuk Converter Using Diode and MOSFET Switch.

Fig. 6: Simulation Circuit Diagram of Ćuk Converter.

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The inductor voltages and capacitor current equations during ON and OFF state are as shown in (6).The conversion ratio (M) is the relation between input and output voltage of Ćuk converter. This conversion ratio is the function of Duty cycle as shown below:

on2

g off

TVM ( )V 1 T

(5)

The connection port in Fig.6 of Ćuk converter is connected to PVA. The simulation circuit diagram of PVA fed Ćuk converter and duty cycle generator unit is shown in Fig.7.

L1 g g 1

L2 1 2 2

C1 2 1

2C2 2

Where = -1

v V (V V ) 0

v (V V ) (V ) 0i i i 0

Vi i 0

R

(6)

5. Modeling and Simulation of PVCC 5.1. MATLAB/SIMULINK Model of PVCC for Duty Cycle (δ = 0.6) The boosted voltage by converter is fed to load with negative polarity & constant duty cycle. A PWM pulse generated by duty cycle generator is applied to IGBT/Diode. Simulation model of PV array with Ćuk converter is shown in Fig.7. The PV module consists two blocks such as generator unit and photovoltaic cell.

Fig. 7: MATLAB/SIMULINK Model of PVCC for δ =0.6

5.2 Simulation Result of MATLAB/SIMULINK Model of PVCC for Duty Cycle δ= 0.6 Voltage generated by PV module is applied at the input of Ćuk converter for constant duty cycle δ=0.6. The simulation results of the output power of the PV module (input power of the Ćuk converter) and the output power of the Ćuk converter for different solar irradiance after simulation are shown in Fig.8.


Fig. 8: Output Power Curve of the PV Module and Ćuk Converter for

Constant δ = 0.6 and Different β.


Constant δ = 0.6 and Different T

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The results of the output power of the PV module (input power of the Ćuk converter) and the output power of the Ćuk converter after simulation for different temperature and constant solar irradiance (β=1000W/m2) are shown in Fig.9.

6. Maximum Power Point Algorithm To improve the efficiency of the solar panel MPPT is used. According to maximum power point theorem, output power of any circuit can be maximize by adjusting source impedance equal to the load impedance, so the MPPT algorithm is equivalent to the problem of impedance matching. In present work, the Ćuk Converter is used as impedance matching device between input and output by changing the duty cycle of the converter circuit. A major advantage of Ćuk converter is that high or low voltage obtained from the available voltage according to the application. Output voltage of the converter is depend on the duty cycle, so MPPT is used to calculate the duty cycle for obtain the maximum output voltage because if output voltage increases than power also increases. In this paper Perturb and Observe (P&O) and constant duty cycle techniques are used, because these require less hardware complexity and low-cost implementations (Esram and Chapman, 2007; Zainudin and Mekhilef, 2010).

6.1. Perturb & Observe MPPT Algorithm

Start

Calculate v(k) and i(k)

P(k) P(k 1)

P(k) v(k)* i(k)

v(k) v(k 1) v(k) v(k 1)

1

k k 1

G to start

Y NN

Y

Y

N

1 1 1

Fig. 10: Flow Chart of P&O MPPT.

It is the simplest method of MPPT to implement. In this method only voltage is

sensed, so it is easy to implement. In this method power output of system is checked by varying the supplied voltage. If on increasing the voltage, power is also increases then further ‘δ’ is increased otherwise start decreasing the ‘δ'. Similarly, while decreasing voltage if power increases the duty cycle is decreased. These steps continue


till maximum power point is reached. The corresponding voltage at which MPP is reached is known as reference point (Vref). The entire process P&O algorithm is shown in Fig.10.

6.2. MATLAB/SIMULINK Model of PVCC Using P&O MPPT Algorithm The MATLAB/SIMULINK model of PV model with Ćuk converter using P&O algorithm is shown in Fig.11.

Fig. 11: MATLAB/SIMULINK Model of PVCC Using P & O Algorithm.

6.3. Simulation Result of PVCC Using Perturb & Observe (P&O) MPPT Algorithm A PVA fed Ćuk converter’s duty cycle is generated through P&O algorithm in embedded system function block. The simulation results of output power of the PVA (input power to Ćuk converter) and Ćuk converter for different solar irradiance and constant temperature (T=300C) are shown in Fig.12.

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Different β and P&O MPPT. From the various simulation results for different solar irradiance and constant cell

temperature it is clear that output power of the PV module and Ćuk converter increases with increasing solar irradiance.

The results of the output power of the PV module (input power of the Ćuk converter) and the output power of the Ćuk converter after simulation for different temperature and constant solar irradiance (β=1000W/m2) are shown in Fig.13.


Different T and P & O MPPT.


From the various simulation results for constant solar irradiance and different cell temperature it is clear that output power of the PV module and Ćuk converter decreases with increasing temperature.

The output of PV system for P&O and constant duty cycle algorithms under constant temperature and different solar irradiance as well as different temperature and constant solar irradiance are shown in Table-1 and Table-2.

Table 1: Output of PV System for constant T = 30 Centigrade.

Algorithm Solar irradiance β

(W/m2) PV Module

Power (Watt) Ċuk Converter Power (Watt)

P & O 900 27.3 25.4 1000 31.3 29.4 1100 34.6 32.7

δ = 0.6 900 23 22 1000 28.8 26.8 1100 33.5 31.5

Table 2: Output of PV System for Constant Solar irradiance β = 1000W/m2

Algorithm Temperature (Centigrade)

PV Module Power (Watt)

Ċuk Converter Power (Watt)

P & O 30 31.3 29.4 40 27.4 25.6 50 24 22.4

δ = 0.6 30 28.8 26.8 40 26.9 25.2 50 24.7 23.1

7. Conclusion In this paper, P&O and constant duty cycle algorithm of MPPT is implemented using Ćuk converter. The model is simulated with MATLAB/SIMULINK. It is shown that PV system output power increases with rise in solar irradiance and fall in cell temperature. Therefore, solar cell performance better in winter season than summer. The P&O gives the optimum duty cycle as compare to Constant duty cycle control, to extract the maximum power from PV system. References

[1] Ali Chermitti, Omar Boukli-Hacene and Samir Mouhadjer (2012) “Design of a Library of Components for Autonomous Photovoltaic System under Matlab/Simulink”, International Journal of Computer Applications (0975 – 8887), Volume 53– No.14.

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[2] Ankur Bhattacharjee (2012) “Design and Comparative Study of Three Photovoltaic Battery Charge Control Algorithms in MATLAB/SIMULINK Environment”, International Journal of Advanced Computer Research (ISSN (print): 2249-7277 ISSN (online): 2277-7970), Volume-2 Number-3 Issue-5.

[3] Athimulam Kalirasu and Subharensu Sekar Dash (2010) “Simulation of Closed Loop Controlled Boost Converter for Solar Installation,” SERBIAN JOURNAL OF ELECTRICAL ENGINEERING, Vol. 7, No. 1.

[4] Azadeh Safari and Saad Mekhilef (2011) “Simulation and Hardware Implementation of Incremental Conductance MPPT with Direct Control Method Using Cuk Converter”, IEEE Transaction on Industrial Electronics, Vol.58, no.4.

[5] E. Durán, M.B. Ferrera, J.M. Andújar, M.S. Mesa (2011) “I-V and P-V Curves Measuring System for PV Modules based on DC-DC Converters and Portable Graphical Environment” IEEE, 978-1-4244.

[6] Hairul Nissah Zainudin and Saad Mekhilef (2010) “Comparison Study of Maximum Power Point Tracker Techniques for PV Systems” 14th International Middle East Power Systems Conference (MEPCON’10), Cairo University, Egypt, Paper ID 278.

[7] Huan-Liang Tsai, Ci-Siang Tu, and Yi-Jie Su (2008) “Development of Generalized Photovoltaic Model Using MATLAB/SIMULINK” WCECS2008.

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[9] Nicola Femia, Giovanni Petrone, Giovanni Spagnuolo and Massimo Vitelli (2005) “Optimization of Perturb and Observe Maximum Power point Tracking Method,” IEEE transaction on power electronics, vol.20, no.4.

[10] Pandiarajan.N and Dr. Ranganath Muthu (2011)“Development of Power Electronic Circuit Oriented Model of Photovoltaic Module”, International Journal of Advanced Engineering Technology, E-ISSN 0976-3945 Vol.II/ Issue IV.

[11] Trishan Esram and Patrick L. chapman (2007) “Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques,” IEEE Transaction on power electronics, vol.22, no.2.

[12] Zameer Ahmad and S.N. Singh (2012) “Extraction of the Internal Parameters of Solar photovoltaic Module by developing Matlab / Simulink Based Model”, International Journal of Applied Engineering Research, ISSN 0973-4562 Vol.7 No.11.

[13] Mohammad H. Rashid., “power electronics converters, applications and design,” third edition, Pearson education.

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