Conference Ppt 2

7/25/2019 Conference Ppt 2

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Low Complexity Neural Network for Maximum

Power Point Tracking of Photovoltaic System in

Rapidly Changing eather Conditions

Presented !y"#

Prachitara Satapathy

Dept. of Electrical Engg.


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Outline

Introduction

Proposed PV system

PV array modeling & characteristics

Proposed techniques

Computationally efficient FL!! "CEFL!!#

$rigonometric FL!! "$FL!!#

%esult analysis

Conclusion and future or'%eferences


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IntroductionPV systems are most preferred (ecause)

*perate at +PP to ma,imi-e the efficiency of system.

+PP$

technique used to get the ma,imum possi(le poer from solar

panels.

+a,imum poer point trac'er "+PP$# trac's the +PP &

connected (eteen the PV array and (oost conerter.

Proides clean green energy

Less operating & maintenance cost

Smart distri(uted generationMPP

MPP


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Proposed PV system

Solar $rradiance

TemperatureVPV

%mpp

or %ref

&oost

converter

Control

unitMPPT

controller

'NN(

P%array

Fig.1Block diagram of PV system+PP$ controller generates the reference oltage ith input as irradiance and

temperature.

Control unit to generate duty cycle for the (oost conerter.

)uty

cycle


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P% array modeling * characteristics

/asic (uilding (loc' of PV arrays is solar cell. P0! 1unction that conerts light energy into electricity directly.

$ ph

P

%P%

$)

#

+

Rsh

$sh

RS $P%

R,

-ig. /. Single diode model to model single solar cell


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pplying 2irchhoff3s la to the node 4P3 e get

Dshphp I0I0I5I

"6#

Contd7.

$he mathematical model of PV array is represented (y the

equation)

( )

+

+=

sh

Spvpvps

s

spvpv

rspphppv

RRIVNN

N

RIV

kTA

qININI 6e,p

"8#9


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Parameters %alues

Maximum Power (Pmpp) 40W

Vola!e a maximum power (Vmpp) 6:.;V

Current at ma,imum poer "Impp# "#$A

Shor %ir%ui %urre& (Is%) "#$A

'pe&%ir%ui vola!e (Vo%) "#*V

Temperaure %oe++i%ie& o+ shor%ir%ui (ki)

0#00,

-ell reverse sauraio& %urre& (Irr) #".0,A

Num/er o+ series %ells (Ns) $

a!le.0 1ey specifications of ELDORA-40 module '0k2m/3 /45C(

Contd7.


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5 45 0555

45

055

Vpv (Volt)

Ipv(Am

p)

I-V characteristics of PV array

MPP

MPP

MPP

0555 2m/

655 2m/

455 2m/

5 45 0555

4555

05555

Vpv (Volt)

Pp

v(W

att)

P-V characteristics of PV array

MPP

MPP

MPP

0555 2m/

455 2m/

655 2m/

a!

"!

-ig.6. 'a( $#% characteristics and '!( P#% characteristics of P% array

Contd7.


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Proposed $echniques

Functional Lin' rtificial !eural !etor' "FL!!# is used

to trac' +PP.

/ecause it is


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Computational efficient FL!! "CEFL!!#

$rigonometric FL!! "$FL!!#

Contd7.

-ig.7. the structure of neural network for MPPT

$o lo comple,ity FL!!s are discussed here.


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Computationally 8fficient -L9NN 'C8-L9NN(

Single layer netor'

ll the inputs of the input pattern pass through FE/ to produce

the e,panded input pattern

$he structure of CEFL!! is shon in Fig.=.

-ig.4. 9rchitecture of Computationally 8fficient -L9NN


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The output of FEB is described by theequation:

Contd7.

#tanh">

6>6

? ==

==

+=&1pi

1i

s

1

s

1i

s

i

s

i 2Aa345

875P"P58# and 156> 87n"n58#

"@#

Ahere> p 5 num(er of output of FE/>

n 5 num(er of input to FE/ for one output>

a 5 input (ias eight matri,>

s 5 current num(er of sample>S 5 total num(er of samples or patterns

nd 5 input eight matri,.


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Ahere>

=

=

#B".........>#>"C

>#B".........>#>"C

MWkWW

M2k22

sss

Tsss

fter the e,pansion the output is calculated (y

= =M

k

sss k2kW66

#9"#"D

s2sWs6

5input matri, for 4sth3 sample>

5output eight matri, for 4sth3 sample>

5predicted output for 4sth3 sample>M 5 total num(er of input to

the summation (loc' after e,pansion.

";#

"=#

Contd7.


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Trigonometric -L9NN 'T-L9NN(

Single layer neural netor'

$rigonometric functions are used in the FE/

Each ,iin input pattern is e,panded using trigonometric functions

ith order 4p3 as )

sin" ,i#> cos" ,i#> sin "8 ,i#> cos"8 ,i#>7sin"p ,i#>

cos"p ,i#9.


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Contd7.

$he structure of the $FL!! is shon in Fig.G.

-ig.:. 9rchitecture of Trigonometric -L9NN


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$he trigonometric e,pansion after the FE/ is gien (elo)

the output is calculated (y)

Contd7.

( )

( )

====

==

===

#cos"#>sin"

>>

#>cos"#>sin"

>>>6

@H@

8

@:@

8G8=

8

8;86

ssss

sss

ssss

ssss

2pi22pi2

22eemperaur2

2pi22pi2

22irra7ia&%e22

"G#

=

=M

k

sssk2kW6

6

#9"#" ":#'56> 87.+"+5H#

=

=

#B".........>#>"C

>#B".........>#>"C

MWkWW

M2k22

sss

Tsss

Ahere>

"#


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daptation *f Aeights nd Performance

Ealuation

$he error for each sample is e,pressed as)

$he cost function is )

$he cost function minimi-ed (y gradient descent algorithm (y

training the eights.

$he learning rate "J# is ta'en in the range of "?.60?.8#.

67e = "H#

#"8

6 8ke4= "6?#


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Differential Error)

%oot +ean Square Error "%+SE#5

+ean (solute Percentage Error "+PE#

5

67e = "66#

Contd7.

SK#e" 8

[ ] 6??S9K#KdLe"LD

"68#

"6@#


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R8S;LT 9N9LN

Menerated in the +$L/KSC%IP$ enironment

$he reference oltage "Vmpp# for randomly ta'en irradiance and

temperature for the discussed PV system

Irradiance is aried in the range of "6??06???# AKm8in a step of 8= AKm8.

$he temperature is aried in the range of "8=0:=#?

C in a step of 8?

C.

?N data for training> ne,t 6? N data for testing and last 6?N is for

alidation from the H?? samples


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Case" 0 'C8-L9NN(

Contd7.

-ig.?. Target and Predicted using C8-L9NN

?/5 ?75 ?:5 ?@5 @555

5.4

0

target & predicted of testing

No. of samples

magnitude(p

.u)

target

predicted


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Case" / 'T-L9NN(

Contd7.

-ig.@. Target and Predicted using T-L9NN

?/5 ?75 ?:5 ?@5 @55

5

5.4

0

target & predicted of testing

No. of samples

m

agntue

p.u

target

predicted


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Case" 6 Comparison of different errors !etween C8-L9NN and

TR-L9NN

Contd7.

-ig.A. error comparison !etween C8-L9NN and T-L9NN

5 /5 75 :5 @5#5.54

55.54

5.0

error during testing

No. of samplesmagnitude(p.u

)

C8-L9NN

T-L9NN


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TR-L9NN

Contd7.

-ig.05. RMS8 comparison !etween C8-L9NN and T-L9NN

5 /5 75 :5 @55

/

7

:x 05

#6!"# $uring testing

No. of samples

magnitude(p.u

)

C8-L9NN

T-L9NN


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TR-L9NN

Contd7.

-ig.00. M9P8 comparison !etween C8-L9NN and T-L9NN

5 /5 75 :5 @5

5

5.0

5./!AP# $uring testing

No. of samplem

agnitude

(p.u

)

C8-L9NN

T-L9NN


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$ype of

netor'

!etor'

structure

!o. ofiteration

intraining

E,ecution time

"ms#

error

!o. ofAeights

to (eupdated

CEFL!!

80G06 :8? @?.;more

68

$%FL!!

80H06 :8? 8:.8 less H

C>MP9R$S>N &8T88N C8-L9NN 9N) T-L9NN

);R$N= TB8

TR9$N$N= PR>C8SS

Contd7.

C>NCL;S$>N 9N) -;T;R8 >R1


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C>NCL;S$>N 9N) -;T;R8 >R1

Compared to CEFL!!> $FL!! is)Very good technique to predict the output.

+ore efficient

Less erroneous

Less computational comple,ity.+ore accurate

$he future or's are)

I# Implementation of control unit to find the duty cycle for the

(oost conerter

II#


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%EFE%E!CES

S. Premrudeepreechacharn> and !. Patanapirom. OSolar0array modelling

and ma,imum poer point trac'ing using neural netor's.O> Poer $ech

Conference Proceedings> 8??@ IEEE /ologna. Vol. 8. IEEE> 8??@.

De-so Sera> $amas 2ere'es> %emus $eodorescu and Frede /laa(1erg.

OImproed +PP$ algorithms for rapidly changing enironmental

conditions.O Poer Electronics and +otion Control Conference> 8??G.EPE0PE+C 8??G. 68th International> pp. 6G6;06G6H. IEEE> 8??G.

Fangrui Liu> ong 2ang> u Qhang and Shan,u Duan >OComparison of

P&* and hill clim(ing +PP$ methods for grid0connected PV conerter.O>

Industrial Electronics and pplications> 8??. ICIE 8??. @rd IEEE

Conference on. IEEE> 8??. Qhou Ruesong>Song Daichun>+a ou1ie> Cheng Deshu. O$he simulation

and design for +PP$ of PV system /ased on Incremental Conductance

+ethod.O information engineering "ICIE#> ASE international conference

on 8?6?. Vol. 8> IEEE> 8?6?.


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$rishan Esram and Patric' L. Chapman> OComparison of photooltaic array

ma,imum poer point trac'ing techniques.O IEEE transactions on energy

conersion ec 88> no. 8 "8??:#) ;@H.

+ummadi Veerachary> $omono(u Sen1yu and 2atsumi e-ato> O!eural0netor'0(ased ma,imum0poer0point trac'ing of coupled0inductor

interleaed0(oost0conerter0supplied PV system using fu--y controller.O

Industrial Electronics> IEEE $ransactions on =?> no. ; "8??@#) :;H0:=.

$sai0Fu Au> Chien0 and u02ai Chen. O fu--y0logic0

controlled single0stage conerter for PV0poered lighting systemapplications.O Industrial Electronics> IEEE $ransactions on ;:> no. 8 "8???#)

8:08HG.

Ci0Siang $u> and i0Tie Su. ODeelopment of generali-ed

photooltaic model using +$L/KSI+LI!2.O In Proceedings of the

orld congress on Engineering and computer science> ol. 8??> pp. 60G.8??.

2. $.


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Conference Ppt 2