# Global MPPT Scheme for Photovoltaic String Inverters Based on Restricted Voltage Window Search Algorithm -, Dr. Mutlu BOZTEPE - 2014.pdf

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  • 8/10/2019 # Global MPPT Scheme for Photovoltaic String Inverters Based on Restricted Voltage Window Search Algorithm -,

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    Assoc. Prof. Dr. Mutlu BOZTEPE

    Ege University, Department of Electrical and

    Electronics Engineering

    Global MPPT Scheme for Photovoltaic String

    Inverters Based on Restricted Voltage

    Window Search Algorithm

    3rdRenewable Energy Systems Winter School

    21-25 January 2014http://www.reswinterschool03.com

    Outline

    Introduction to solar cells

    Electrical characteristics of Photovoltaic (PV) modules

    Effect of non-uniform operating conditions on PV

    module electrical characteristics.

    Global MPPT tracking methods

    Restricted Voltage Window method

    Conclusion

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 2

    Operation of solar cells

    P-N junction inside the solar cell induces a built -in

    electric field (E).

    The photon which has higher energy

    than bandgap of material (1.12eV

    for Si) can generate electron-hole

    pair in the diffusion region.

    The generated carriers (electrons

    and holes) are separated into opposite sides of junction

    by electric field, and became majority carriers.

    Carriers are collected by metallic grid and finally the

    current flows through the load

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 3

    P

    N+

    -E

    + -+ -

    Electrical equivalent circuit

    4

    +

    -VPV

    IPV

    Light generatedCurrent IL

    ID

    ParallelresistanceRP

    RSSeries resistance

    IRp

    P

    SPVPVnkTRIVq

    SLRDLPVR

    RIVeIIIIII

    SPVPV

    P

    1

    q: Electron chargen: Diode ideality factor

    K: Boltzmann constantIs: Diode saturation currentT: Cell temperature (K)

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014

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    Current-voltage characteristics

    VPV

    ISCISC

    IPV

    VOCOpen circuitvoltage

    ShortCircuit

    current

    Slope Rp

    5

    P

    SPVPVnkT

    RIVq

    SLPVR

    RIVeIII

    SPVPV

    1

    Slope Rs

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014

    The effect of irradiation and cell temperature

    As solar radiation increases, ISC

    increases proportionally and

    VOC decreases logarithmically.

    As cell temperature increases,

    ISCincreases very little, but VOCdecreases linearly (~-1.52

    mV/C)

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 6

    Parallel connection of solar cells

    Only equivalent cells can be connected in parallel!

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 77

    Series connection of solar cells

    Only equivalent cells can be connected in series!

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 8

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    Solar photovoltaic modules

    A number of solar cells are usually connected in series

    to compose of a solar PV module.

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 9

    Typical 80W crystal Si PV module

    At STC conditions (1000 W/m2, 25C, AM1.5)

    36 cells (125x125 mm2)

    Pm=80 W @ Vm=18V, Im=4,5A

    Voc=22V (0,6Vx36=21,6V)

    Isc=4,9A (3Ax1252/1002=4,69A)

    Max. installation voltage 600V

    8 kg/module

    0,65 m2/module

    958x680x30 mm

    90% power output warranty for 10 yrs.

    80% power output warranty for 20-25 yrs.

    103rd Renewable Energy Systems Winter School, 21-25 Jan. 2014

    PV module examples

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 11

    140Wp72 cells (125x125mm2)

    17.2 kg, 1.32m2

    300Wp72 cells (156x156mm2)

    30.5 kg, 1.94m2

    410Wp96 cells (156x156mm2)

    34 kg, 2.58m2

    PV module current-voltage characteristics

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 12

    0 0.2 0.4 0.6 0.80

    0.5

    1

    1.5

    2

    2.5

    3

    3.5

    4

    4.5

    5

    Voltage [V]

    Current[A]

    Single cell 36 cells

    0 5 10 15 20 250

    0.5

    1

    1.5

    2

    2.5

    3

    3.5

    4

    4.5

    5

    Voltage [V]

    Current[A]

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    PV module current-voltage characteristics

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 13

    Power-voltage characteristics

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 14

    VM

    IM

    VOC

    ISC

    MaximumPower point(MPP)

    Maximum Power Point Tracking (MPPT)

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 15

    Constant resistance as load

    Battery

    as load

    MPP tracking

    1000 W/m2

    750 W/m2

    500 W/m2

    250 W/m2

    k gc [W]

    Radiation

    (W/m2) Constant

    R

    Battery

    MPP

    tracking

    1000 79,3

    (%99)

    68,0

    (%85)

    80,0

    (%100)

    750 48,0(%81,2)

    50,5(%85,4)

    59,1(%100)

    500 21,3

    (%56)

    33,3

    (%87,6)

    38,0

    (%100)

    250 5,3(%30)

    16,3(%92)

    17,7(%100)

    MPPT realization

    By using control input;

    Converter (or inverter) input impedance can be controlled

    Or PV voltage (or current) can be controlled

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 16

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    MPPT Methods

    Fractional open-circuit voltage: (V=k1*Voc, k1=0.750.8)

    Fractional short-circuit current: (I=k2*Isc, k2=0.780.92)

    Incremental conductance:

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 17

    IVP .dV

    dIVI

    dV

    dP

    0dV

    dP

    MPPatdV

    dP0

    0dV

    dP

    P-V curve

    Perturbation & Observation algorithm:

    MPPT Methods

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 18

    Vstep

    Other MPPT Methods

    Fuzzy logic control

    Neural network

    Ripple correlation control

    Current sweep, etc

    Most widely used ones;

    Perturbation&Observation (P&O)

    Incremental conductance

    Both method are designed to track only single power

    peak, and exhibits local maximum tracking behaviour

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 19

    Non-uniform operating conditions

    Irradiation differences

    Partial shading, dissimilar inclination&orientation

    Temperature differences

    Non-unifom heat flow, cooling differences

    Parameter differences

    Aging, production tolerances

    The power-voltage and current voltage curves of a PV

    module are affected by these non-uniform operating

    conditions drastically!

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 20

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    Shading problem

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 21

    Energy losses due to partial shading

    German 1000 roofs programme were affected by

    shading causing 10% energy loss[Renew. Energy, 33(9), 20482056, 2008]

    The power loss due to the improper MPPT may be as

    high as 70% according to the real measurements [IEEE T.Ind. Electron., 55(7), 25692580, 2008]

    Thus, in recent years,

    numerous studies worldwide

    have been performed to

    mitigate the power loss

    due to partial shading

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 22

    IEEE T.En.Conv. 22(2),2007,439-449

    The effect of shading on series solar cells

    Shaded cell has lower Isccurrent than other cells.

    If Ipv>Isc_shadedthen the cell voltage can reverse, and it

    behaves as a load!!!

    If reverse voltage exceeds breakdown limit of the cell,

    dissipated power increases significantly.

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 23

    I

    A

    B

    +

    -VA

    +

    -

    VB

    +

    -

    VG

    A

    B

    -VB VA

    Operating

    current

    Ipv

    Vpv

    Hot spot effect

    Dissipated power raises the cell temperature, and

    creates hot spot effect.

    If Tc>Tmax, the module can be damaged permanently!!!

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 24

    Heat dissipated in ashaded cell caused themodule to crack.

    http://pveducation.org/pvcdrom/modules/hot-spot-heating

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    How bypass diode affects the I-V curve?

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    Shaded unshaded.

    Without bypass

    diode

    How bypass diode affects the P-V curve?

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 30

    Shaded unshaded.

    Without bypass diode

    Shading problem

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 31

    Prog. Photovolt Res. Appl., 16,529536, 2008.

    Shading problem

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 32

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    Central inverter

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 33

    Prog. Photovolt Res. Appl., 16,529536, 2008.

    Extracted power: 3230 Watt or 2971 Watt?

    String inverter

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 34

    Prog. Photovolt Res. Appl., 16,529536, 2008.

    Extracted power: 1568+2046=3614 Watt?or 529+2046=2575 Watt?

    Micro-inverter

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 35

    Global MPPT methods

    Hardware based

    Dynamic reconfiguration, Distributed MPPT concept, Module

    integrated DC/DC converter, constant input power converter

    etc.

    Software based (Can be realized only by software

    modifications)

    Complex methods: Fibonacci search algorithms, ANN or Fuzzy

    controllers, Bayesian fusion technics, differential evolution,sequential extremum seeking, ant colony optimization, etc.

    Less complex: Two stages MPPT methods, global peak search

    algorithm, DIRECT search algorithm, etc..

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 36

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    1

    Global MPPT methods

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 37

    Global MPPT methods

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 38

    Global MPPT methods

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 39

    Global MPPT methods

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 40

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    Choice of the Global Voltage Step VGSTEP

    The choice of VGSTEP directly affects both the scanning time

    and the algorithm accuracy. However the optimum value

    should be around the voltage difference between two adjacent

    local power peaks.

    MATLAB Simulink

    simulations for 1000

    random irradiance values

    between 1001000W/m2.

    Voltage difference between

    two adjacent local power

    peak larger than 0.5VocP ,

    but mostly around of

    0.8VocP

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 45

    Choice of the Global Voltage Step VGSTEP

    0.5VocPand 1.0Vocreach

    global maximums B and D.

    On the contrary, 1.5VocPmisses point B and evolves

    towards B.

    1.0Voccan miss a peak if

    adjacent peaks have nearly

    equal power.

    So, VGSTEP is selected

    between 0.5VocPand

    1.0Vocby balancing

    tradeoff tracking eff. and

    convergence speed

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 46

    Power operating triangle (POT) and

    Voltage Window (VW)

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 47

    Minimum andmaximum valuefor VW are point

    A and Brespectively

    The global

    power peak mustbe in the rangeof VW, in otherwords between Aand B.

    Narrowing the upper limit of the VW

    Narrowing the VW

    reduce the

    searching steps and

    therefore decrease

    the convergence

    time

    2000 random

    irradiation values

    0.9 Voc is selected

    as upper limit for

    VW

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 48

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    POT update

    The proposed algorithm uses datasheet values of both ISC and

    VOC to define the first triangle POTSTC.

    POTSTCis not closely cover

    P-V curve

    After measuring current

    at Vmin, the algoritm finds

    point A.

    And then new triangle POT1

    is defined which is closely

    covers P-V curve

    VW=[Vmin Vmax]

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 49

    VWS algorithm flowchart

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 50

    Sudden shading detection method

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 51

    Shading is detected if k: sensitivityparameter

    Slope2 isalways higherthan slope1

    Algorithm operation

    Lets assume

    operating point

    is Q.

    1,2,3,4 and 5

    are checked.

    a,b,c and d

    are omitted

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 52

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    Algorithm evaluation (Uniformnon-uniform)

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 53

    Algorithm evaluation (During non-uniform)

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 54

    Algorithm evaluation (uniformnon-uniform)

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 55

    Power,voltage andcurrent plotswith respectto time

    Algorithm evaluation (non-uniformuniform)

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 56

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    Algorithm evaluation (during uniform)

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 57

    Algorithm evaluation (during uniform)

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    Power,voltage andcurrent plotswith respectto time

    Experimental setup

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 59

    P-V curves programmed in the SAS.

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 60

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    Proposed VWS Agarwal

    algorithm algorithm

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 61

    Comparison

    3rd Renewable Energy Systems Winter School, 21-25 Jan. 2014 62

    633rd Renewable Energy Systems Winter School, 21-25 Jan. 2014