introduction to solar energy and mppt

8/9/2019 introduction to solar energy and mppt

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Project ProgressReport-I

ByG.S.S. CHAITANYA

M.Tech (APS) , 13021D3421

U !er the estee"e! G#$!% ce o& '. Sr$ '#"%r M.Tech,

Ass$st% t Pro&ess r*PARTM*NT + * *CTRICA * *CTR+NICS *NGIN**RING

UNI/*RSITY C+ *G* + *NGIN**RING,(AUT+N+M+US),

0NTU', 'A'INA A

MAXIMUM POWER POINT TRACKING OF A PV ARRAYUSING EVOLUTIONARY PROGRAMMING


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PROGRESS REPORT:

Module I Literature Survey

o Solar energy, photovoltaic cell and itsmodeling.

o Design of boost converter and itsanalysis.o Various maximum po er pointtrac!ing techni"ues.o Implementation of maximum po er

point trac!ing using evolutionary programming techni"ues.

o #omparison of evolutionary

techni"ues ith conventional methods.

In progress

Module$II %nalysis & modelling

of pv module.o Analysis of mathematicalequations of pv module.o Mathematical modeling andsimulation of pv module usingsingle diode model.o I-V,P-V characteristics of a p-v Module under di erentirradiation and temperatureconditions.

#ompleted.


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Module III

Design of boostconverter and

interfacing ith p$v panel.

'oost converter analysis andmathematical modelling.o Interfacing of boost converter

ith p$v module.o I$V, ($V characteristics of a

(Vmodule under partially shadedand varying temperature andirradiation conditions.

#ompleted

Module $IVM(() using

proposedevolutionary

programmingtechni"ues.

o *evie of existing algorithms forM(().

o Methodology for proposedtechni"ue.

o #oding of proposed techni"ue inmatlab.

$$$$$$$$$$$

Module V *esults anddiscussions o #omparison of proposed and

conventional M(() techni"uesusing statistical analysis.

$$$$$$$$$$$$$$$$


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C+NT*NTS1 A2str%ct

I tro!#ct$o

+2ject$3e

P/ P% e4 "o!e44$ g

Boost co 3erter

Co 3e t$o %4 "etho!s &or MPPT.Propose! Ge et$c %4gor$th"

2%se! "etho! .


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A-STRACT:

+o a days , demand for rene able energy sources is rapidly gro ing due to

continuous increase in global fuel prices and the concern over the level of green house

emissions.

%mong the sources available for rene able energy , solar photovoltaic is one of the most

promising source.

peration of a (V cell

% p$v system is an arrangement of components designed to convert the solar irradiance

into usable electric po er for variety of purposes.

ne critical issue of any p$v system is the effectiveness of its Maximum (o er (oint

)rac!ing since it is the most economical ay to improve the overall efficiency of the pv

system.


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M(( varies ith solar irradiance levels, ambient temperature and solar cell temperature.

M(() trac! and maintains the p$v arrays operating voltage at M(( to extract maximum

po er from the p$v array.

)o achieve this , various conventional M(() techni"ues have been proposed and used .

Several methods are being implemented idely, among them the most popular algorithms

are petrub and observe , incremental conductance and hill climbing.

Despite their effectiveness, most of these algorithms are operating very satisfactorily

under uniform irradiance conditions in hich only single pea! po er is detected. If

multiple pea!s exists as in partial shading conditions, conventional algorithms become

impractical and cannot distinguish bet een global and local M((.

)o address this problem soft computing based genetic algorithm have been proposed forM(().


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INTRODUCTION:

% ma-or test in using a (V source is to underta!e its nonlinear output characteristics,

hich vary ith solar irradiation and atmospheric temperature. )he characteristics get

more complex if the hole array does not receive uniform insolation, as in partially

shaded cloudy/ conditions, resulting in many pea!s.

)he presence of many pea!s reduces the efficiency. )herefore the maximum po er

point trac!ing M(()/ as invented to extract the maximum po er from each (V system.

% dc0dc converter step up0 step do n/ serves the purpose of transferring maximum

po er from the solar (V module to the load. It acts as an interface bet een the load and

the module.

.


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Bloc diagram of the proposed model


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O-.ECTIVE:

)o overcome the dra bac!s of conventional methods li!e (erturb & bserve method,

soft computing techni"ue based on 1enetic algorithm is developed.

)he proposed 1enetic algorithm based approach eliminates this problem of partial shading

and the performance of the 1enetic algorithm method is evaluated and compared ith the

conventional (& method .


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MODELLING OF PV SYSTEM:

% solar cell is the building bloc! of a solar panel. % photovoltaic module is formed

by connecting many solar cells in series and parallel. #onsidering only a single solarcell, it can be modeled by utili2ing a current source, a diode and t o resistors. )his

model is !no n as a single diode model of solar cell as sho n in figure .

S$ g4e !$o!e "o!e4 o& %so4%r ce44

)he output current from the (V cell can be found using the e"uation3


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4here

I ph3 Light$generated current or photocurrent %/5

Id3 Diode current %/5

Io3 saturation current %/5

* sh 3 is the shunt resistance. 6/

!3 is 'olt2man constant 7 8.9:;< = 8;$>9 ?0@

"3 is Alectron charge 7 8.B = 8;$8C #


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SOLAR PANEL C/ARACTERSTICS:

P V I V C "+"&'!+(*'(&* o*o "+ "5! u5d!+ &o5*'"5'

(++"d("'(o5 "5d '!# !+"'u+!o+ 6 "5! * &o55!&'!d (5

*!+(!*7


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Matla! model for " pv panels connected in series


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igher is the solar irradiation, higher ould be the solar input to the solar cell and

hence po er magnitude ould increase for the same voltage value. 4ith increase in the

solar irradiation the open circuit voltage increases. )his is due to the fact that, hen more

sunlight incidents on to the solar cell, the electrons are supplied ith higher excitation

energy, thereby increasing the electron mobility and thus more po er is generated.

n the contrary the temperature increase around the solar cell has a negative

impact on the po er generation capability. Increase in temperature is accompanied by a

decrease in the open circuit voltage value. Increase in temperature causes increase in the

band gap of the material and thus more energy is re"uired to cross this barrier. )hus the

efficiency of the solar cell is reduced.


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' S) # +VA*)A* DASI1+3

-oo*' &o5)!+'!+


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PERTUR- O-SERVE MET/OD:

PV C "+"&'!+(*'(&* F o8 & "+' o P O


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RESULTS ANALYSIS:

P/ Mo!#4e "o!e4$ gres#4ts

I$V and ($V characteristics for different temperature levels at constant irradiation.


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*$ $*$ &$


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#. $sram and P. %. &hapman, '&omparison of Photovoltaic ArrayMa(imum Po)er Point #rac ing #echniques,' Energy Conversion,IEEE Transactions on, vol. 22, pp. 439-449, 2007.

*$+$*$ &$

/0

1. 2ohm and M. $. *opp, '&omparative study of ma(imum po)erpoint trac ing algorithms,' Progress in photovoltaics: esearch an!

"pplications, vol. ##, pp. 47-$2, 2007.

30

4. alam, 5. Ahmed, and B. . Merugu, '#he application of softcomputing methods for MPP# of PV system6 A technological andstatus revie),' "pplie! Energy, vol. #07, pp. #3%-#4&, 7'' 20#3.

70

M. A8a!, '9ptimal po)er point trac ing for stand-alone PV systemusing particle s)arm optimi8ation,' in In!(strial Electronics )I*IE+,20#0 IEEE International *y posi( on, 20#0, pp. 9$9-973.

:0

1. B. +ogel, 'Applying evolutionary programming to selected travelingsalesman pro!lems,' Cy ernetics an! syste s, vol. 24, pp. 27-3$,#993

"0


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#2A ;

introduction to solar energy and mppt

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