A Comparative Analysis Of Mppt Schemes For Pv Systems Operating Under Non Uniform Irradiance And Partial Shaded Conditions

A Comparative Analysis of MPPT Schemes for PV Systems

Operating Under Non Uniform Irradiance and Partial

Shaded Conditions

J. Maya 1 , R. Geethamani2

1 _{PG scholar,} 2_{Assistant Professor}

1 _{[email protected],} 2_{[email protected]}

Electrical and Electronics, Sri Krishna College of Engineering and Technology Coimbatore, Tamilnadu-641008

Abstract

The performance of PV system under non uniform irradiance and partial shading condition is analyzed with help of conventional perturb and observe method and improved Incremental Resistance algorithm. The outputs are generated using MATLAB/SIMLUNK. Partial Shading of modules is given importance in this work. The Perturb and observe method is evaluated along with fuzzy controller and the output of the system is compared with Incremental Resistance method. The system with fuzzy logic controller was found to be more efficient and attains stability much faster than any other controller. But the power output of system with INR method was found to be more stable and with boosted value. The comparison of the two MPPT schemes is done in this paper and the performance of the schemes is analyzed.

Key words – PV system, MPPT, partial shading, Perturb and Observe method, Fuzzy controller,Incremental resistance method.

1. Introduction

Energy crisis is the world’s major concern in the present scenario.Renewable energy sources have led its helping hand to the human society as a promise for future development. The simple conversion step in PV system has made its way to electricity generation easier. The advancement in power electronics engineering helped in improvement of applications depending on PVsystem. If all theincoming solar irradiance can be efficiently utilized, the whole population can be powered up for years to come with ideal systems. The efficiency of the system was improved from 8% to 44% with help of many Maximum power point tracking schemes. The analysis of PV system is categorized on structure of semi-conductor, converter topology, MPPT algorithms, and loads structure and so on. Thus the PV system is a field of elaborate study.

As years pass by the performance of PV panel may not meet the guarantee period of about 20-25 years offered as in data sheet.Since they are exposed to dust,

atmosphere and other pollutions, the panels may show only poor performance. Also there are chances of having any plant near the panels that offers shade as it grow in to tree as years pass by. Thus the area of MPPT algorithm is being expanded, considering not just the incoming solar irradiance, but also the system and load.

Typically the Perturb and observe method were mostly employed, but the oscillation obtained at the MPP reduced its efficiency [1]. Similarly incremental conductance method is one of the recognized algorithms. For system withthenon-linear characteristics, incremental conductance method was initially used [6].With variation on load characteristics

the usual methods become insufficient. Controllers for tuning the MPP without oscillations were included. Then the parameter of observation was changed to improve the dynamics of control to obtain incremental resistance method [7].

2. PV sys

In general source. Th upon the so

Fi

The major irradiance. temperatur equation.

Where, a r

Boltzmann To improv of temper formulated The suffi parameters Where

Ipvn is the n data she kIandvoltag

Analysis i irradiance study mor bring an an schemes, to

stem model

l the solar ce he characteristi

olar irradiance

ig. 1.Electrical Equ

r equations of s The characteri re co-efficient

represents the d n constant (1.38

ve the performa rature a modi d [5]. G denot x n represen s.

∆

∆

∆

nominal PV cu et. Thecurre ge temperature

is made on P and partially re effective. T nalysis on syste o verify the co

ling

ell isconsidere cs of solar cel

and temperatu

uivalent circuit of

solar cell invo isticequations i

termsand diod

1

diode factor of 8x10-23_).

ance of solar ce ified Io curre tes the solar i nts the nom

(2)

urrent value ob ent temperatu e coefficient kV

PV system fo shaded situati This paper ma em with and w

rrectness.

ed as a curre l mainly depen ure.

solar cell

olve the effect involve both th de characteristi

(1)

f 1.2 and k is th

ell in wide rang ent equation irradiance valu minal values

(3)

btained from th ure coefficie V is included. or non unifor ion to make th ake an effort without controll ent nd of he ics he ge is ue. of he ent rm he to ler The sec is m in s

3.

e general study ction 3. In secti

made. The incr section 5, follo

Simple sche

e simulation oosing certain C200GT is take

. Equations 1,2 n uniform irr oviding varying rticular time aracteristics we

Table

Par

Fig. 2. (a) I-V

e Figure 2 sho rying irradiance o varies linear adiance the per th non uniform anging.

milarly figure 3 ndition on PV rticular time pe

y on PV witho ion 4 the valida

remental resist owed by the res

eme without

of PV is m n parameter c

en for the anal 2 and 3 is used radiance cond g irradiance fo intervals a ere plotted.

e 1: Specifications

rameter V

Impp 7

Vmpp 2

Pmax 2

Isc 8

Voc

kV -0.1

kI 0.0

Ns

Characteristics at

ows the relatio e. Its seen that rly. But as tem rformance of th m irradiance the

3 shows the e V system wit eriod it generat

ISSN 2

(1) out controller is

ation of fuzzy tance method sults.

t controller

made in MAT criterions. A P

lysis at STC w d for the simul dition is simu or all three mo and the per

s of PV panel

Values 7.61 A 26.3 V 200 W 8.21 A 32.9 1230 V/K 0032 A/K 54 non-uniform irrad

on between cu with irradianc mperature incre he system redu e power curve

effect of partia thout controll tes more than

2348 – 7968

)

s made in controller is briefed

TLAB by PV array with A. M

lation.The ulated by odules for rformance diance urrent and ce, current eases with uces. Thus keeps on al shading ler. At a

which mak point.

Fig. 2.

Fig. 3

With the c to implem controller power outp

kes it difficult

(b) P-V Character

3. (a) I-V characte

characteristics ent a system f is required to put.

t to find the

ristics at non-unifo

eristics curve at Par

curve obtained for supplying

ensure the con

optimum pow

orm irradiance

rtial shading

d it is clear th a load, a prop nstant maximu

wer

hat per um

Fig.

3.

is c wit

The pro cho irra

3.1

The to m spe inv of v

The from

3.2

Ma yea

3. (b) P-V charac

P&O with F

The conv considered as t th DC-DC conv

Fig.3

e controller is t oper tuning of t osen by consid adiance.

1 DC- DC Bo

e system is reg maximize the ecifications ca volving the duty

value 30KHz.

e Capacitor a m equations 5

∆

∆

Tab

Pa

C L Cf Lf Ro

2 MPPT cont

any algorithms ars, for maximu

teristics curve at P

Fuzzy Cont

ventional pertu the MPPT con verter.

. The Basic block

the major part the output. The ering many fac

oost converter

gulated with a D obtained outpu an be obtaine

y cycle Dand t

and inductor v and 6.

ble 2: Converter Sp

arameter

filter filter o

troller

s have been d um power poin

Partial shading

roller

urb and observ ntroller for a P

diagram of the sy

of concern tha e system param ctors as temper

r

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(4

valuesare calc

(5

(6

pecifications

Values

500μF 5mH 470μF 3mH 300ῼ

developed in t nt tracking app

ve method PV system

stem.

at helps in meters are rature and

converter converter equations frequency

4)

culated as

5)

6)

Hill climb simplest on for better a The P&O the oscilla tuning con

Fig

3.3 Fuzzy

The fuzzy the maxim established for FLC ar The memb clarity of member sh NS (negat and PB (p with help o

E / dE N

NB Z

NS Z

ZE P

PS N

PB N

The major

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has shown a v ation shown w ntrollers are req

g 4. Flowchart for

y logic contro

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re an error sign ber ship funct

the output a hip functions a tive small), ZE positive big). T of the function

Table 3: Fu

NB NS

ZE ZE

ZE ZE

PS ZE

NS NS

NB NB

equations con

the early dev xpansion in th eased.

very good perfo when reaching

quired.

perturb and obser

oller

er is implemen nt as it does n l model. The p nal and change tions and rule and its stabilit are used [3] NB

E (zero), PS ( The inference plot and 17 ru

uzzy inference table

ZE PS

PB PB

PS PS

ZE ZE

NS ZE

NB ZE

cerned is

veloped and th he field, the nee

ormance, but f the MPP, bett

rve method

nted here to tun not require a we parameters use e in error signa s determine th ty. Mainly fiv B (negative big (positive smal

table is forme ules.

e

PB

PB PS NS ZE ZE

he ed

for ter

ne ell ed al. he ve g), ll), ed

Wh sys

4. I

Al

The stan to Inc par for

The hig cha sca

Sin con wit

here, Ppv and I stem.

Incrementa

gorithm

e algorithms s ndard test cond

change the b cremental cond rtial shaded an fixed scaling f

Fig 5. Flowc

e scaling fact ghly varying ir anged in to di aling factor pro

nce duty cycl ntroller to the c th the scaling f

1

Ipv are power

al Resistanc

so far impleme ditions. Varyin behavior of p ductance metho nalysis. But it

factor[11].

chart ofIncrementa

tor also neede rradiance natu iscrete domain operty.

e is the requ converter, the e factor to obtain

ISSN 2

and current o

e MPPT

ented were eff ng nature of clim parameterinvol

od wasmodifie was implemen

al Resistance meth

ed to be chan ure.[12] The si

n to achieve a

(

(

uired output error signal is m n new duty cycl

2348 – 7968

(7)

(8)

of the PV

ficient for mate tend ved. The ed for the

nted only

hod.

nged, for ignals are a varying

(9)

10)

The maxim to these thr

It is clear parameter. linearizatio chosen in t

5. Simul

The Syste powered by array is sim The system fuzzy cont the adaptiv non uniform . Fig.6. Power Th variation in standard te noted that not sustain algorithms tracking ca The Fuzzy MPP with fuzzy contr after a sm 1000w/m2 seconds lat

The powe irradiance partial sha

mum power po ree conditions.

1 1 ; 1

r that the sc With the chan on is also var this paper.

lation and R

em considers y a PV array o mulated with h m is incorporate

troller, and the ve incremental

m irradiance an

Output for partial

he power o n the incoming est condition is the power outp n for longer pe s and controlle

an be understoo

y controller is u P&O methodI roller, the outp mall disturban for 2 seconds, ter a 800w/m2

er output is r applied. The p ading mode is

oint is tracked

| | ;

| | ;

aling factor i nge in scaling ried. Afixed s

Results

a nominal r f KC200GTmo help of MATLA edwith the P& en a compariso l resistance alg nd partial shad

shading without c

utput obtaine g solar irradian

s shown in .Fig put is highly n eriod. Thus th ers for maximu

od

used to reduce t It is seen that f put is stabilized nce. A varyin

and reduced t till 5 second w

reduced with peak power is a

analyzed by a

by checking o

0 0

0

is an importa factor the pow scaling factor

residential loa odel. A3 modu AB/SIMULINK &O algorithm an

on is made wi gorithm for bo ded condition

controller.

ed during an ce other than th gure 6. It can b non linear and d he importance

um power poi

the oscillation from Fig. 7 wi d within secon ng irradiance to 500w/m2 _for were given.

respect to th about 550W. Th applying varyin on ant wer is ad ule K. nd ith oth ny he be do of int at ith ds of r 4 he he ng irra thre diff Fig. 500w No par pow com the def poi It ma tran avo The con abo dur Sha per also the out of t 9. natu adianceof1000w ee modules res ferent peak.

7. Power outpu w/m2 _{and 800w/m}

w Fig 8 den rtial shading w wer is maxi mpromise is n

STC. The fuzzification m int.

can also be intained to an nsient up to 0 oided by using

Fig. 8 Power outp

e major advan nverter is the out 1kW. The ring any variati

ading can be rmanent reason o important. W irradiance lev tput then tends

the maximum The movemen ure, thus th

w/m2_{, 800w/m} spectively. The

ut for non-uniform m2 _irradiance

otes the pow with fuzzy con

imized and needed to be m

fuzzy con method could

noted that n optimum o 0.01 seconds.

better design.

put of partially shad controller

ntage of using ability to ach e algorithm is ion in the weat

e more comp n, the analysi When consideri

vel is continuo to settle in litt output, which nt of clouds c he power ge

m2 _{and 500w/} e Each module

m irradiance with

er output obt ntroller. It is more stable made when co ntroller with

find the glob

The Power o of 320W after This transien

ded PV panels wit r

INR along w hieve a booste also able to ther.

plicated if d s on the occu ing fast movin ously varied. T tle lesser point can be seen as can be very ra enerated reduc

/m2_{to the} e generate

1000w/m2_,

ained for seen that , but a onsidering

centroid bal power

output is r a peak nt can be

th Fuzzy

with boost ed power tune well

ISSN 2348 – 7968

irradiance gradually from about 700W. That is power is generated respective to the value of irradiance, unless as fuzzy controller were the power obtained is of the minimum optimum value.

Fig. 9. Power output due non uniform irradiance using INR.

When implementing the incremental resistance method with nominal scaling factor for different irradiance at each module, a stabilized output is obtained. The scaling factor helps in maintaining a very high output power. The controller can be used to tune the power output between various peaks and ultimately finding the global maxima of the system.

Fig. 10. Power output due to partial shaded modules using INR.

From figure 10 it can be noted that the power output reaches a value of 0.5kW during the partially shaded condition of modules after a slow decrease from a transient.Without the controller the power output will be the power output of the single module, with the INR MPPT controller the output is maintained the next highest possible value of the whole system capacity. Here the power variation is linear and with less transients.

5.1 Comparison of Results

The partial shaded condition is considered as the dominant issue in this paper. Hence the comparison is made under the analysis for shading only. The power output obtained under three conditions are observed and noted. The analysis shows that incremental

resistance method show better performance with boosted power value.

Table 4: Comparison of Results

Sl.

No. PV system

Power Output

Non-Uniform Irradiance

Partial shaded Condition

1 _Controller Without _(STC) 600W 200W

2 P&O with _FLC 550W 320W

3 INR Method 710W 450W

Considering the power rating that can be obtained from PV system, Fuzzy controller shows 53% efficiency and system with INR controller provides 75% efficiency along with the boosted output. For a system requiring boosted output value INR method can be chosen, but for system whose priority is stability instead of power output value Fuzzy controller can be considered.

5. Conclusion

The growing energy crisis leads us to focus on renewable energy sources. Photovoltaic system being the more energy efficient is been widely used on many application. Photovoltaicsystem requires less stages of conversion making it much more reliable. Maximum power point tracking algorithms are used to improve system efficiency.From the developed algorithms proper choice of method is necessary to obtain the required outcome.In this paper an effort is made to analyze the effect of varying irradiance along with partial shaded condition with help of perturb and observe method and fuzzy controller . A comparative study is made with incremental resistance method for all parameter variations. With the Implementation of fuzzy controller, output could be stabilized faster but the peak overshoot obtained in the output was further reduced by implementing INRmethod.

For partial shading condition both fuzzy controller and incremental resistance algorithm shows better performance, but the power output can be boosted to very high value without disturbing the design aspect of the system with Incremental Resistance method.

References

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Maya Jreceived under graduation degree in Electrical and Electronics Engineering from Anna University, Chennai, in 2012. She is currently pursuing Post Graduation on Power Electronics and Drives. Her area of interest is towards Power Electronics in Renewable Energy Systems.