Proceedings of 2013 2nd International Conference on Advances in Electrical Engineering (ICAEE 2013) 19-21 December, 2013, Dhaka, Bangladesh
Modelling of PV Module with Incremental Conductance MPPT Controlled Buck-Boost Converter
Hasan Mahamudul1*, Monirul Islam2, Ahmad Shameem3 , Juel Rana4 and Dr. Henk Metselaar5 1, 2, 3,5
Faculty of Engineering University of Malaya Kula Lumpur, Malaysia. 4 Department of Electrical and Electronic Engineering 4 Eastern University, Dhaka, Bangladesh. *
[email protected],
[email protected] 1, 2, 3, 5
sunlight, shadow etc. basically, the generation of energy from the PV system varies with its environmental and operational conditions.
Abstract-This paper represents a novel simulation approach of photovoltaic module with incremental conductance MPPT controlled buck-boost converter in simulink platform. Mathematical equations associated with the simulation process have been described with best clarity. Obtained results have been investigated to analyse the performance of the system using a SOLKAR 36 W PV module. This technique can also be used for the simulation of any specific PV module and converter with least changing in parameters.
For this reason extensive research is going on this field and different techniques have been adopted .Among them application of maximum power point tracking algorithm is a very recent and most popular technique for PV system .A number of MPPT algorithm has been established yet, among them (P&O), Incremental Conductance, Fuzzy Neural network are most familiar . But for this work direct control incremental conductance algorithm has been used. Selection of appropriate converter is also very important for an efficient PV system. There are a few topologies can be used with PV system for load connectivity, among them buck-boost converter has been selected here due to its available use in standalone and grid connected PV system and simultaneous step up and step down capability .
Index Terms— PV module, MPPT, Buck-boost, Incremental conductance, Simulink.
I.
INTRODUCTION
To overcome the challenge of energy for the world needs from the last few decades a lot of research is going on renewable energy among them solar energy is the pioneer, at present a lot of research is going on this area. sun is the constant unique source of energy as long as the world live, the sun will continue to give its energy to the earth. Unfortunately, a very little amount from the huge energy which sun gives to earth can be utilized. The amount of energy comes from the sun is nearly 12.2 trillion watt-hours per square mile per hour and really it’s difficult to believe that the world’s rate of energy consumption is only 0.1% of this gigantic amount. On the other hand, due to the depletion of the energy source like coal, oil and natural gas with the rapid growth of population and dramatic industrialization a long term solution of energy crisis has become inevitable. That’s why most of the research at this moment is going on how more energy can be captured from the sun. [1-5]
The sequential work flow of this paper is as follows- In section II. Complete working procedure of the system has been described. In section III.A The necessary equivalent circuit model has been demonstrated and described. All the mathematical equations related to PV system have been included in this portion. In section III.B simulink implementation of the PV system has been given .In section IV.A. and IV.B. Simulation of incremental conductance MPPT algorithm and buck-boost converter have been described respectively . In part V. The simulation results obtained from each parts of this model has been attached sequentially to investigate. Section VI. Includes a short discussion of the included results. Lastly In section VII. A precise conclusion has been added to finalize the work.
Photovoltaic system is the most fundamental technique to utilize solar energy and this system is formed by photovoltaic cell which is actually a photoactive semiconductor material, it converts sunlight directly it into electricity when light strikes the photovoltaic cell . The most important factors which make it more popular is, this conversion of energy is free from any kind of pollution and carbon-di-oxide (C02) emission .Herewith, it does not need that much maintenance and operation cost is low.[6-8] The efficiency of PV system depends on the given parameters like temperature, solar radiation; variation in 978-1-4799-2465-3/13/$31.00 ©2013 IEEE
II.COMPLETE SYTSTEM OVERVIEW The basic energy conversion work flow for a complete PV system can be described as follows- The radiation energy from the sun first absorbed by the PV Panel, Then this absorbed heat energy will be converted to electrical energy by photoconductive semiconductor materials, after that this energy will be supplied to the load through the buck-boost converter and the converter will be controlled by a MPPT controller. Necessary programming for the PV module and MPPT algorithm have been imposed in Simulink. 197
The working principle of the whole system can be shown by figure.1
Figure .1: Schematic arrangement of the complete system
III.A. MODELLING OF PV CELL AND MATHEMATICAL EQUATIONS A PV cell can simply be modelled using the following equivalent circuit [2], [8], as shown in figure 2.
A series of PV cells which are connected together is so called a string and a module is made of cell strings. The equivalent circuit of PV module can be illustrated in figure 3. [8]
Figure.2 Electrical equivalent circuit of PV Cell Figure.3. Electrical equivalent circuit of PV module
Here, Rs is the series resistance and Rsh represents the shunt resistance. Due to the higher value of Rsh with respect to Rs, the shunt resistance is neglected for the simplification of the modelling [5].
The output current of a PV module is defined as [9], [10]
Io=Np*Iph-Np*Irs[exp(KoV/Ns)-1]
The output current of a PV cell can be calculated using [11] Io=Iscr/[exp(qVoc/kT)]-1
(2)
Where
(1)
I0 is the PV array output current V is the array output voltage, Iph is the cell photocurrent that is proportional to solar irradiation. Irs is the cell reverse saturation current that mainly depends on temperature. Ns and Np is respectively the number of series and parallel cells in the PV module
Where: q is the charge of an electron. V oc is open circuit voltage Isc is the short circuit photon generated current. k is Boltzmann’s constant. T is the cell operating temperature in Kelvin (K)
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Ko is a constant [9], calculating from:
The above four are the main equations for the mathematical modelling of photovoltaic module .The main input parameters used for this simulation is T,S ,Ns, Np And Vin which is considered as triangular wave has maximum value of Voc.
Ko=q/kAT Where:
Because by changing only this parameters simulation for any specific module can be simulated .
A is the p-n junction ideality factor its value depends on PV technology [12]
III.B. SIMULINK IMPLEMENTATION OF THE PV MODULE
Table.1. Factor A for different PV technology
Technology Si Mono Si-poly a-Si:H a-Si:H tandem a-Si:H triple CdTe CTS AsGa
A 1.2 13 18 3.3 5 1.5 1.5 1.3
The modelling is based on mathematical equation and the above equations (2), (3), (4) are used here consequently to obtain the PV output current, voltage and power for required conditions For this some special simulink block is used such as [2];
Table.2. Imporatnt Simulink blocks
For PV input voltage
In the above equation (2), cell photocurrent is calculated from: Iph=[Iscr+Ki(T-Tr)*S/1000]
(3)
Where:
For variable temperature and irradiation input
T is cell operating temperature. Tr is the reference temperature. And cell reverse saturation current Irs is calculated from: Irs=Irr*[T/Tr]exp(qEg/kA[1/Tr-1/T])
For including the mathematical equations in the model for Iph, Irs and Ipv
(4)
Where, Irr is the reverse saturation current at Tr. Eg is the band gap energy of the semiconductor used in the cell. •
Complete simulink block diagram of PV system is demonstrated bellow-
Figure.4: External view of PV module in Simulink window
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IV.A. SELECTION OF MPPT ALGORITHM Incremental conductance algorithm works on the power graph of PV module. The main theoretical conception, based on which incremental conductance algorithm works can be shown by the equations;
dI/dV+I/V=E ; At MPP; D optimum dI/dV>-I/V+E ; Left of the MPP; D increase
dI/dV0
No
Decre ase Duty Cycle
No
Yes
Increase Duty Cycle
Decrease Duty Cycle
Yes
Increase Duty Cycle
Update value of “D”
Figure.6: Flow-Chart of Inc based MPPT Algorithm
Figure .5: Basic P-V curve for understanding the location and tracking of MPP
IV.B. SELECTION AND DESIGN OF CONVERTER For PV System modelling selection of appropriate converter is very important .The purpose of use of PV panel, circuit complexity of converter, controller and sensor availability, expertise skill etc. are the main factors which influence the selection of converter .By considering above all parameters for this work buck-boost converter is selected .The main equations of Buck-boost converter-
According to this equation the simulation of the buck boost converter has been carried in Simulink. The specifications of the necessary components selected for this work are listed below: 1)
Inductor =290 µH
2) Input Filter Capacitor=250 µF
d0=1-D, where ,D= duty cycle ILmax-ILmin=V0/L(1-D)T, where T=time period.
3) Mosfet IRS045
VsdT=-V0(1-d)T
4) Resistive Load=35 Ω,35 W
Therefore ,
5) Output Filter Capacitor=330 µF
Vs/V0=D/1-D
6) Switching Frequency=10 kHz
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V. SIMULATION RESULT
i
Temperature
Voltage meas ure PWM GENERAT OR
330 uf
Np
Output Current display
G
290 uH
Ns
i Diode
250 uf
Vari able irradiations
PV MODULE
S
D S
V+
T
Ns
Current measurement
Current measurement
T
35Ω
Output current ,voltage and power scope
-V No of series Cell
Output voltage display
Np
Input current Output power display Duty cycle
No of parallel cell Input voltage
Duty cycle scope Direct control Incremental conductance Al gorithm
Figure.7: Simulink implementation of the complete system for data analysis
Obtained Characterstics curves of SOLKAR 36 W PV module
Figure.9: P-V curves of the PV module at different radiations
Figure.8: V-I curves of the PV module at different radiations
Output Curves of the simulated Buck-boost converter
Figure.10: Voltage and current curves of the converter at buck condition
Figure.11: Voltage and current curves of the converter at boost condition
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Resultant tracking curve of currnet, voltage and power with respect to variable irradiation
Figure.12:Variable irradiations with respect to time
Figure.13: Power, voltage and current tracking with the change of irradiations
REFERENCES
VI. DISCUSSION
[1] S. Nema, R.K.Nema, and G.Agnihotri, “Matlab / simulink based study of photovoltaic cells / modules / array and their experimental International journal of Energy and Environment Volume 1, Issue 3, 2010 pp.487-500 [2 ] Matlab/Simulink Models For Typical Soft Starting Means For A DC Motor International Journal of Electrical & Computer Sciences IJECS-IJENS Vol: 11 No: 02. [3] I. H. Altas and A.M. Sharaf, “A Photovoltaic Array Simulation Modelfor Matlab-Simulink GUI Environment,” IEEE, Clean Electrical Power,International Conference on Clean Electrical Power (ICCEP '07), June14-16, 2007, Ischia, Italy. [4]S.Chowdhury, S.P.Chowdhury, G.A.Taylor, and Y.H.Song, “Mathematical Modeling and Performance Evaluation of a Stand-Alone Polycrystalline PV Plant with MPPT Facility,” IEEE Power and EnergySociety General Meeting - Conversion and Delivery of Electrical Energy 1in the 21st Century, July 2024, 2008, Pittsburg, USA. [5]M.Veerachary,“Power Tracking for Nonlinear PV Sources with CoupledInductor SEPIC Converter,” IEEE Transactions on Aerospace andElectronic Systems, vol. 41, No. 3, July 2005. [6] N. Pandiarajan and R. Muthu, “Mathematical Modeling of Photovoltaic Module with Simulink,” in Proceedings of the International Conference on Electrical Energy Systems (ICEES
The obtained figures Fig.8 and Fig.9 represents the obtained characteristics curve of the used PV module , Fig.10 and Fig.11 shows the output of the converter for buck and boost condition individually and Finally Fig.12 and Fig.13 present here the tracking curves of the system. And sequentially all these figures coincide with theoretical prediction and company specified value which ensures the validity of the system. VII. CONCLUSIONS This model represents a versatile and simple way of photovoltaic module simulation with a buck-boost converter. The characteristics curves obtain from this model have been matched with the theoretical prediction which ensures the validity of this model. The tracking curves represents dynamic response of MPP searching capability of the model .For further extension and future work like partial shading effect analysis, Solar pumping system, Grid connected PV system , high voltage PV application and smart grid photovoltaic interconnection system can make use of this model as fundamental stage .
’11), Jan 2011. [7] N Pandiarajan and R Muthu, “Development of Power ElectronicCircuit Oriented Model of Photovoltaic Module,”International Journal of Advanced Engineering Technology, vol.2, no. 4th, pp. 118–127, 2011.), Jan 2011. [8] K Kachhiya, M Lokhande and M patel , “Matlab/Simulink Model of Solar Module and MPPT algorithm ,” in Proceedings of theNational Conference on Recent trends in Engineering & technology [9] Safari. A and S. Mekhilef Simulation and Hardware Implementation of Incremental Conductance MPPT with Direct Control Method Using Cuk Converter IEEE Transactions on Industrial Electronics, Vol. 58, Issue 4, 2011, 1154 -1161 [10] G. Petrone, G. Spagnuolo, R. Teodorescu, M. Veerachary, and M. Vitelli,‘‘Reliability issues in photovoltaic power processing systems,’’ IEEE Trans. Ind. Electron., vol. 55, no. 7, pp. 2569---2580, Jul. 2008. [11] C. Hua, J. Lin, and C. Shen, ‘‘Implementation of a DSPcontrolled photovoltaicsystem with peak power tracking,’’ IEEE Trans. Ind. Electron.,vol. 45, no. 1, pp. 99---107, Feb. 1998. [12] Rakesh A.Patel “Design and Implementation of single phase grid connected Photovoltaic Inverter using DSP”,Nirma University of Science and Technology Ahmedabad, May 2008.
ACKNOWLEDGMENT The authors wish to thank all the members of Renewable energy cluster of University of Malaya for their kind co-operation .This work is under an ongoing project of University of Malaya (UM.C/HIR/MOHE/ENG/21-“Phase Change Materials for Energy Storage System).Authors would like to thank the University Research grant authority for their necessary economic supports.
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