a survey of maximum ppt techniques of pv systems

5/24/2018 A Survey of Maximum PPT Techniques of PV Systems

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A Survey of Maximum PPT techniques of PV SystemsAli Nasr Allah Ali

1, Mohamed H. Saied

2, M. Z. Mostafa

3, T. M. Abdel- Moneim

3

1MSc. candidate,

2PhD, GM, Electrical Engineering Dept., Abu Qir Fertilizers & Chemical Industries Co.,

3Full-Prof., Electrical Engineering Dept., Faculty of Engineering, Alexandria University, Alexandria, EGYPT.

[email protected], [email protected]

AbstractThis paper introduces a survey of different

maximum peak power tracking (MPPT) techniques used in the

implementation of photovoltaic power systems. It will discuss

different 30 techniques used in tracking maximum power in

photovoltaic arrays. This paper can be considered as a

completion, updating, and declaration of the good efforts made in

[3], that discussed 19 MPPT techniques in PV systems, while

summarizes additional 11 MPPT methods.

Index Terms - Photovoltaic power generation, Maximum

Power Point Tracking techniques, PV array.

I. INTRODUCTIONTracking of the maximum power point (MPP) of a

photovoltaic (PV) array is usually an essential part of PVsystems. In general, PV generation systems have two major

problems; the conversion efficiency of electric power

generation is low (in general less than 17%, especially under

low irradiation conditions), and the amount of electric power

generated by solar arrays changes continuously with weather

conditions. Moreover, the solar cell (current voltage)characteristic is nonlinear and varies with irradiation and

temperature. There is a unique point on the I-V or (power

voltage) curve of the solar array called MPP, at which theentire PV system (array, converter, etc) operates with

maximum efficiency and produces its maximum output power.

The location of the MPP is not known, but can be located,

either through calculation models, or by search algorithms.Therefore MPPT techniques are needed to maintain the PV

arrays operating point at its MPP [1].

II. PROBLEM OVERVIEWAs the solar radiation varies throughout the day, the power

output also varies. The principle of maximum power trackingcan be explained with the help of Fig. 1, where the line having

slope I/Ro represents a constant load Ro. If this load is

connected directly across PV cell, it will operate a power Pa

differs from the maximum Pb, in spite of the fact that

maximum power is available from the array. Thus, a powerconditioner or DC-DC converter is introduced between the

solar PV module and the load. This converter adapts the load

to the array so that load characteristics are transformed along

locus of maximum points and maximum power is transformedfrom the array. The duty cycle, D, of this converter is changed

till the peak power point is obtained [2].

III. MPPTTECHNIQUESA 30 maximum peak power tracking methods for PV

system will be introduced in the following survey.

Fig. 1. Intersection between the load line and the power voltage and curre voltage curve [2].

1. Hill Climbing/P&O (perturb & observe) methodHill climbing involves a perturbation in the duty ratio

the power converter; P&O involves a perturbation in th

operating voltage of the PV array. In the case of a PV arra

connected to a power converter, perturbing the duty ratio power converter perturbs the PV array current, an

consequently perturbs the PV array voltage; hill climbing anP&O methods are two different ways to perform the samfundamental method.

It can be seen From PV power C/Cscurve; Fig. 2, that th

increment, or decrement of the voltage increases, or decreas

the power when the operating point is on the left of the MPand decreases, or increases the power when being on the rig

of the MPP. The process is repeated periodically until the MP

is reached. The system then oscillates around the MPP. Th

oscillation can be minimized by reducing the perturbation stesize. However, a smaller perturbation size slows down th

MPPT. A solution to this conflicting situation is to have

variable perturbation size that gets smaller towards the MP

A two-stage algorithm is proposed that offers faster tracking the first stage.

Hill climbing and P&O methods can fail under rapid

changing atmospheric conditions as illustrated in Fig.

starting from an operating point A, i.e. P1curve is utilized, atmospheric conditions stay approximately constant,

perturbation V in the PV voltage V will bring the operatin

point to point B and consequently the perturbation will b

reversed due to a decrease in power.


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Fig. 2. Characteristic PV array power curve.

Fig. 3. Divergence of hill cl imbing/P&O from MPP.

However, if the irradiance increases and shifts the power

curve fromP1toP2within one sampling period, the operating

point will move from point A to C. This represents an increase

in power due to the new curve P2, while the perturbation iskept the same. Consequently, the operating point diverges

from the MPP and will keep diverging if the irradiance

steadily increases, numerous number of researches apparel inthe literature recently covering not only these two methods,

but also outlining other MPPT techniques. Fig. 4a shows the

block diagram of the PV system using the hill climbing and

P&O methods, while Fig. 4b shows the algorithm flowchart of

the technique [1], [3]-[39].

2. Incremental ConductanceThe incremental conductance (IncCond) method is based

on the fact that the slope of the PV array power curve at the

MPP is zero, positive on the left, and negative on the right ofthe MPP, Fig. 2. The mathematical relations are shown below;

0 0 1 0 Since

2

So, equation (1) can be written as

Fig. 4a. The block diagrams.

Fig. 4b. The flowchart of P&O control technique.

3

The MPP can thus be tracked by comparing th

instantaneous conductance term (I/V) with the increment

conductance term (I/V)as shown in the flowchart of Fig. Vrefis the reference voltage at which the PV array is forced t

operate. At the MPP, Vrefequals the voltage value at the MP

Vmpp, once the MPP is reached, the operation of the PV array maintained at this point unless a change in I is noted

indicating a change in atmospheric conditions, this MPP

technique is also commonly used and several researcheexplained it in depth details [1], [3], [5]-[12], [40]-[53].

3. Fractional Open-Circuit VoltageThe near linear relationship between Vmppand open circu

voltage of a PV array, under varying irradiance an

temperature levels, has given rise to the fractional Vocmetho

the relationship between the Vmppand Vocis almost linear thus 1 (

Where k1is proportionality constant, since k1is dependent o

the characteristics of the PV array being used, it usually has

be computed beforehand by empirically determining Vmpp an

Voc for the specific PV array at different irradiance antemperature levels. The factor k1 has been reported to b

between 0.71 and 0.78 [3].


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Fig. 5. The IncCond flowchart.

Once k1is known, Vmppcan be computed with Voc measuredperiodically by momentarily shutting down the power

converter. However, this incurs some disadvantages, including

temporary loss of power. To prevent this, it can use pilot cellsfrom which Voc can be obtained. These pilot cells must be

carefully chosen to closely represent the characteristics of the

PV array [3].

Once Vmpphas been approximated, a closed-loop control on

the array power converter can be used to reach this desiredvoltage. Since the relation is only an approximation, the PV

array technically never operates at the MPP [54]-[61].

4. Fractional short-Circuit CurrentFractional short circuit current results from the fact that,

under varying atmospheric conditions, Impp is approximatelylinearly related to theIscof a PV array thus

2 (5)

WhereK2is proportionality constant, just like in the fractional

Voc technique,K2 has to be determined according to the PVarray in use. The constantK2is generally found to be between0.78 and 0.92. Measuring Iscduring operation is problematic.

An additional switch usually has to be added to the power

converter to periodically short the PV array so that Isccan bemeasured using a current sensor. This increases the number of

components and cost.

It is clear that this method and the previous one have majordrawbacks, the power output is not only reduced when finding

Iscbut also because the MPP is never perfectly matched [3],

[62]-[65].

TABLE .FUZZY RULE BASE TABLE

5. Fuzzy Logic ControlFuzzy logic controllers have the advantages of workin

with imprecise inputs, not needing an accurate mathematicmodel, and handling nonlinearity. Fuzzy logic contr

generally consists of three stages: fuzzification, rule ba

lookup table, and defuzzification. During fuzzificatio

numerical input variables are converted into linguistvariables based on a membership function. In this case, fiv

fuzzy levels are used: NB (negative big), NS (negative small

ZE (zero), PS (positive small), and PB (positive big) [3].

The inputs to a MPPT fuzzy logic controller are usually a

errorE and a change in error E. The user has the flexibili

of choosing how to computeE and E. Since dP/dV vanish

at the MPP [3]. By calculate the following

En P n Pn 1Vn Vn 1 6and En E n En 1 7

Once E and E are calculated and converted to th

linguistic variables, the fuzzy logic controller output, which

typically a change in duty ratio D of the power converter, cabe looked up in a rule base table such as Table . Thlinguistic variables assigned to D for the differe

combinations of E and E are based on the power convert

being used and also on the knowledge of the user. Table I based on a boost converter. If, for example, the operating poi

is far to the left of the MPP, that isE is PB, and E is ZE, the

we want to largely increase the duty ratio, that is D should bPB to reach the MPP [3].

In the defuzzification stage, the fuzzy logic controll

output is converted from a linguistic variable to a numeric

variable still using a membership function. This provides a

analog signal that will control the power converter to the MP

MPPT fuzzy logic controllers have been shown to perforwell under varying atmospheric conditions. However, the

effectiveness depends a lot on the knowledge of the user ocontrol engineer in choosing the right error computation an

coming up with the rule base table [3] and [66]-[76].


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Fig. 6. Example of neural network.

6. Neural NetworkNeural networks commonly have three layers: input,

hidden, and output layers as shown in Fig. 6. The number of

nodes in each layer varies and is user-dependent. The input

variables can be PV array parameters like Voc and Isc,atmospheric data like irradiance and temperature, or any

combination of these. The output is usually one or several

reference signal(s) like a duty cycle signal used to drive thepower converter to operate at, or close to, the MPP [3], how

close the operating point gets to the MPP depends on the

algorithms used by the hidden layer and how well the neural

network has been trained. The links between the nodes are all

weighted [3].The link between nodes i and j is labeled as having a

weight of wij in Fig. 6. To accurately identify the MPP, the

wijs have to be carefully determined through a training

process, whereby the PV array is tested over months or yearsand the patterns between the input(s) and output(s) of the

neural network are recorded. Since most PV arrays havedifferent characteristics, a neural network has to be

specifically trained for the PV array with which it will be used.

The characteristics of a PV array also change with time,

implying that the neural network has to be periodically trained

to guarantee accurate MPPT [3] and [77]-[81].

7. Ripple Correlation ControlWhen a PV array is connected to a power converter, the

switching action of the power converter imposes voltage and

current ripple on the PV array. As a consequence, the PV array

power is also subject to ripple. Ripple correlation control(RCC) makes use of ripple to perform MPPT. RCC correlates

the time derivative of the time-varying PV array power with

the time derivative of the time-varying PV array current orvoltage to drive the power gradient to zero, thus reaching the

MPP. If the voltage or the current is increasing and the power

is increasing, then the operating point is below (to the left of)the MPP (V VmpporI > Impp).

When the power converter is a boost converter, increasing

the duty ratio increases the inductor current, which is the same

as the PV array current, but decreases the PV array voltage.Therefore, the duty ratio control input is:

3 8

Fig. 7. The RCC block diagram.

3 9Where k3 is a positive constant. Controlling the duty ratio

this fashion assures that the MPP will be continuously tracke

making RCC a true MPP tracker. The derivatives can also b

approximated by high-pass filters with cutoff frequency highthan the ripple frequency. A different and easy way

obtaining the current derivative is to sense the inductvoltage, which is proportional to the current derivative. Thnon idealities in the inductor (core loss, resistance) have

small effect since the time constant of the inductor is muc

larger than the switching period in a practical converter, Fig.

shows the RCC method block diagram [3], [5], and [82]-[87]

8. Current SweepThe current sweep method uses a sweep waveform for th

PV array current such that the IV characteristic of the P

array is obtained and updated at fixed time intervals. The Vmcan then be computed from the characteristic curve at the samintervals. The function chosen for the sweep waveform

directly proportional to its derivative as in [3];

4 10Where k4 is proportionality constant. The PV array power

thus given by 11At the MPP

0 12

So, from (10) and (12)

4

0 13

The differential equation in (10) has the following solution

14C is chosen to be equal to the maximum PV array curre

Imax and k4 to be negative, resulting in a decreasin

exponential function with time constant = k4. It leads to:


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Fig. 8. Topology of DC-link capacitor droop control.

15The current in (15) can be easily obtained by using some

current discharging through a capacitor. Since the derivative of(15) is nonzero, (13) can be divided throughout by df(t)/dt and,

withf(t) = i(t), (13) can be simplified to [3]; 4

0 16

Once Vmppis computed after the current sweep, (16) can be

used to double check whether the MPP has been reached. In

[88], the current sweep method is implemented through analogcomputation. The current sweep takes about 50 ms, implying

some loss of available power. It is pointed out that this MPPT

technique is only feasible if the power consumption of thetracking unit is lower than the increase in power that it can

bring to the entire PV system.

9. DC-Link Capacitor Droop ControlDC-link capacitor droop control is MPPT technique that is

specifically designed to work with a PV system that is

connected in cascade with an AC system line as shown in Fig.8 [3].

The duty ratio D, of an ideal boost converter is given by

1 17Where V is the voltage across the PV array and Vlink is the

voltage across the DC link. If Vlinkis kept constant, increasing

the current going to the inverter increases the power coming

out of the boost converter, and consequently increases the

power coming out from the PV array. While the current isincreasing, the voltage Vlinkcan be kept constant as long as the

power required by the inverter does not exceed the maximum

power available from the PV array. If that is not the case, Vlinkstarts drooping. Right before that point, the current controlcommand Ipeak of the inverter is at its maximum and the PV

array operates at the MPP. The AC system line current is fed

back to prevent Vlink from drooping and D is optimized tobringIpeakto its maximum [89]-[90].

10.Load Current or Load Voltage MaximizationThe purpose of MPPT techniques is to maximize the power

coming out of a PV array. When the PV array is connected toa power converter, maximizing the PV array power also

Fig. 9. Different load types; 1) voltage source, 2) resistive, 3) resistive and

voltage source, 4) and current source.

maximizes the output power at the load of the converte

Conversely, maximizing the output power of the convert

should maximize the PV array power, assuming a lossleconverter.

It is pointed out that most loads can be of voltage sourc

current-source, resistive, or a combination of these typ

shown in Fig. 9. From this figure, it is clear that for a voltagsource type load, the load current ioutshould be maximized

reach the maximum output power PM. For a current-sourc

type load, the load voltage voutshould be maximized. For thother load types, either ioutor voutcan be used. This is also tru

for nonlinear load types, as long as they do not exhib

negative impedance characteristics [3].

Therefore, for almost all loads of interest, it is adequate

maximize either the load current or the load voltage maximize the load power. Consequently, only one sensor

needed. In most PV systems, a battery is used as the main loa

or as a backup, and a positive feedback is used to control th

power converter such that the load current is maximized an

the PV array operates close to the MPP. Operation exactly the MPP is almost never achieved because this MPPT metho

is based on the assumption that the power converter is lossle[8] and [91]-[95].

11. dP/dV or dP/dI Feedback ControlThanks to the digital signal processors and microcontro

ers being able to handle complex computations, an obviou

way of performing MPPT algorisms is to compute the slop

dP/dV, or dP/dI, of the PV power curve and feed it back to thpower converter with some control to drive it to zero.

The way the slope is computed and its sign is stored for th

past few cycles. Based on these signs, the duty ratio of thpower converter is either incremented or decremented to reac

the MPP. A dynamic step size is used to improve the transie

response of the system [96]-[100].

12. methodThe other method, based on tracking, has the advantag

of both fast and accurate tracking. The analysis of the I-

characteristics of a PV array, leads to an intermediate variab, isgiven by:


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Fig. 10. The method flowchart.

ln ln 18Where Io is reverse saturation current and c is the diodeconstant (c (q/ kTNs)) with q, , k, T and Nsdenoting the

electronic charge, ideality factor, Boltzmann constant,

temperature in Kelvin and the number of series connected

cells, respectively. Thus, depends on all of these parameters.

It is observed that the value of remains within a narrowband as the array operating point approaches the MPP.

Therefore by tracking , the operating point can be quicklydriven to close proximity of the MPP using large iterative

steps [5]. Subsequently, small steps (i.e. conventional MPPTtechniques) can be employed to achieve the exact MPP. In

other words, the method approximates the MPP, while

conventional MPPT technique is used to track the exact MPP.The flow chart for the method algorithm is shown in Fig. 10

[5], [101], and [102].

13. System Oscillation MethodThis is a novel technique for efficiently extracting the

maximum output power from a solar panel under varying

meteorological conditions. The methodology is based onconnecting a pulse-width-modulated (PWM) DC/DC SEPIC

or Cuk converter between a solar panel and a load, or battery

bus. The converter operates in discontinuous capacitor voltage

mode whilst its input current is continuous.

By modulating a small-signal sinusoidal perturbation intothe duty cycle of the main switch and comparing the

maximum variation in the input voltage and voltage stress of

the main switch, the maximum power point (MPP) of thepanel can be located, as in Fig. 11.

Fig. 11. Block diagram of the system oscillation MPP tracking method.

Fig. 12. Equivalent circuit of a solar panel connecting to a converter.

Fig. 13. Circuit diagram of a SEPIC converter.

The nominal duty cycle of the main switch in the convertis adjusted to a value, so that the input resistance of th

converter is equal to the equivalent output resistance of th

solar panel at the MPP. This approach ensures maximu

power transfer under all conditions without usinmicroprocessors for calculation [103].

The MPP is tracked by operating the interfacing pow

converter in such a manner that the ratio of the peak dynam

resistance (reflected across the PV terminals) to twice th

internal resistance (rg) of the array as in Fig. 12 which equalspre-determined constant (ko). At MPP, ko is equal

(Vpv=Vpv), where Vpv is the peak ripple of the PV arravoltage [5], Fig. 13 shows the converter circuit details.

14. Constant Voltage TrackerFig. 14 shows the control-circuit configuration of th

constant voltage tracker. This is a new constant voltage track

uses the physical fact that the temperature characteristic of thp-n junction diode is very similar to that of the solar array.


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Fig. 14. Control-circuit configuration of the constant voltage tracker.

A solar-cell surface-temperature change by the

environment is detected in the forward voltage drop of the p-njunction diode installed at the backside surface of the solar

array, which is used as a reference voltage of the constant

tracker [104].

The input voltage dVr of the pulse width modulator isrepresented as follows:

2 2 1 19Where Vs is the output voltage of the solar array, Vref is the

reference voltage of Vs, Vdis the forward voltage drop of the

p-n junction diodes, and K1 and K2 are the gains of theamplifiers Amp1 and Amp2 respectively [104].

15.Look-up Table MethodIn this case, the measured values of the PV generator's

voltage and current are compared with those stored in the

controlling system, which correspond to the operation at the

maximum point, under predetermined climatologicallyconditions. In one of the methodsIpvis defined as a function of

Ppv * IMPP= f(Pmax) [8]. In this method, a PI type controller

adjusts the duty cycle of the DC-DC converter. The zero erroris reached when the current and power of the Photovoltaic

generator are equal to the pre-determined values of IMPP andPmax. Any change of the insolation or load, results in adisturbance of the tuned system, and the PI controller again

brings the system to its optimum operating point.

These algorithms have the disadvantage that a large

capacity of memory is required for storage of the data.

Moreover, the implementation must be adjusted for a panel PVspecific. In addition, it is difficult to record and store all

possible system conditions. But it has also some advantages. It

is simple and the system is able to perform fast tracking, as all

the data regarding maximum point are available [8], [105]-[107].

16. On-Line MPP Search AlgorithmIn this algorithm, the main task is to determine the value of

reference maximum power, and then, the current power iscompared with it. This difference is called maximum power

error. In order to have the PV array be operated at its MPP the

maximum power error should be zero or near to zero [8].The operating power is the PV array output power to the

load, and is given as; the multiplication of PV array output

voltage by the current. Here, first reference maximum power

(RMP) is to be required. Since RMP is changed with variation

in temperature and solar irradiation level, it is not a constant

Fig. 15. Flow chart of the on line search algorithm.

reference and has a non-linear uncertainty that makes th

tracking of PV array reference maximum power is difficult. T

get the RMP, to find the maximum power error, the flow cha

shown in Fig. 15 [8], [108].If the reference MPP is changed due to change temperatu

or solar irradiation level, the algorithm adjusts the arra

voltage and finds the new MPP. This algorithm will not b

able to determine the PV array MPP if the load power current is much smaller than the PV array MPP power an

current. In this case, additional loads should be connected t

increase the PV array current so that the PV array can boperated at the MPP. It is preferred that we can charge th

battery as an additional load [108].

17.Array Reconfiguration MethodIn this method the PV arrays are arranged in differe

series and parallel combinations such that the resulting MPPmeet a specific load requirement. This method is tim

consuming and tracking of the MPP in real time is not obviou[109]. According to the technique suggested to optimize th

operation of photovoltaic system; it assumed that the sol

array is going to be divided into two modules. The first on

represents the basic module, and the second will be divide

into sub modules. Three ways of arranging these modul

together can be achieved [3], [109], the parallel, series, anparallel-series arrangements, Figs. 16a, 16b, and 16

respectively.


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Fig. 16a. The parallel arrangement.

Fig. 16b. The series arrangement.

Fig. 16c. The parallel - series arrangement

18.Linear Current Control MethodIn this method, a MPPT circuit is proposed which not only

can track the maximum power of the array instantaneously but

also can be implemented easily. The main idea is based on the

graphical interpretation of the solution of two algebraic

equations as the intersecting point of two curves on the phase

plane [110].

First, the traditional I-V characteristic of a solar array isgiven by:

exp 1 20Where

Is: generated current under a given insulation

Io: the reverse saturation current

Rs: the intrinsic resistance of the solar array

Fig. 17a. The maximum output power curve at the intersecting point.

Fig. 17b. The maximum power point is located at the intersecting point.

K: the Boltzmans constant

T: absolute temperatureq:charge of an electron

A: an ideality factor for a p-n junction

Thus, for the proposed MPPT controller, the first curve

represented by f (P, I) = 0 on the (power current) plane a

follows:, ln

0 21

Second, at the maximum output power point, one has th

following necessary condition 0 22

It follows from equations (20) and (22) that one has thfollowing second maximum output power constraint equation

, ln 0 23

It is interesting to see that for a practical solar arra

equation (23)can be approximated by a linear line to simpli

the hardware implementation, as shown in Figs. 17a and 17[3], [110].


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19.IMPPand VMPPComputation MethodIMPP and VMPP are computed from equations involving

temperature and irradiance levels, which are not usually easy

to measure. OnceIMPPor VMPPis obtained, feedback control is

used to force the PV array to operate at the MPP [3]. The PV

current I and the terminal voltage V, at the insulation Q and

the module temperature T, are described as follows;

1 24 1

Ns 25Where,Iand Vare the output current and the terminal voltage

of a PV module at the standard test conditions (STC). STC are

defined as follows; the standard solar insulation (Qo) is l

kW/m2, the standard module temperature (Ts) is 25 C, and the

solar spectrum is at the air mass (AM) 1.5, respectively.

Moreover, Isc is the short circuit current at STC, is the

temperature coefficient of Isc, is the temperature coefficient

of the open circuit voltage of the module, Rs is a seriesresistance of the module, andKis the curve correction factor,

respectively.

The output power P of the PV array is calculated by

(26)

The currentIMPPand the voltage VMPP, which maximize the

output power, are calculated by differentiating P with respect

toI[111].

2

2 27

20. State-based MPPT MethodThe PV system is represented by a state space model, and a

nonlinear time varying dynamic feedback controller is used to

track the MPP. Simulations confirm that this technique isrobust and insensitive to changes in system parameters and

that MPPT is achieved even with changing atmospheric

conditions, and in the presence of multiple local maximacaused by partially shaded PV array or damaged cells.

However, no experimental verification is given [3], [112].

21. One-cycle control (OCC) MethodThis control scheme is based on the output current-

adjusting feature of OCC. The output current of the inverter

can be adjusted according to the voltage of the photovoltaic

(PV) array so as to extract the maximum power from it Fig.

18.

Fig. 18. Inverter power stage interfacing the photovoltaic cells to the gri

intersecting point.

Fig. 19. The best fixed voltage algorithm flowchart.

Simple low-cost one-stage inverter, with MPPT accuracy

proposed. The proposed topology has two function

automatically adjusting the output power according to sunlig

level, and outputting a sinusoidal current to the grid. It has thfollowing features [3], [113].

1)Constant switching frequency.2)Low output current harmonics and high power factor, i.

PF = 1.

3)Simple main circuit with one stage power conversion.4)A simple controller that only needs some line

components, i.e., no DSP's or multipliers are necessary.5)Maximum power point tracking accuracy.6)Low cost and high efficiency.

22. The Best Fixed Voltage (BFV) AlgorithmStatistical data is collected about irradiance an

temperature levels over a period of one year and the BF

representative of the MPP is found. The control sets either th

operating point of the PV array to the BFV, or the outpu

voltage to the nominal load voltage. The advantages of thalgorithm are simplicity and ease of implementatio

However, it has limitations in efficiency and depends on

good mathematical statistical research to find the BFV

extract more power from the PV array. But the operation therefore never exactly at the MPP and different data has to b

collected for different geographical regions, Fig. 19 [3], [7

and [114].

23.Linear Reoriented Coordinates Method (LRCM)This method solves the PV array characteristic equatio

iteratively for the MPP, where the equation is manipulated

find an approximate symbolic for the MPP. It requires the


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Fig. 20. The PV Inverter System for uti lity applications.

Fig. 21. P-V and I-V Curves with LRCM.

measurement of Voc andIscand other constants representing the

PV array characteristic curve, to find the solution themaximum error in using LRCM to approximate the MPP was

found to be 0.3%, but this was based only on simulation

results [3]. Fig. 20 shows the PV power system used in this

method, the main idea for the LRCM is to find the I-V curve

knee point, Fig. 21. The I-V curve knee point is the optimalcurrent (Iopt) and the optimal voltage (Vopt) that producesPmax

[115]. Using the I-V curve, a linear current equation can be

determined from the initial and final values. The slope of the I-

V curve at the knee point is approximated by the slope of thelinear current equation [3], [115].

24. Slide Control MethodThe buck-boost converter is used to achieve the MPPT.

The switching function, uof the converter is based on the fact

that dP/dV> 0 on the left of the MPP, and dP/dV< 0 on the

right; u is expressed as 0 0 1 0Where u= 0 means that the switch is open and u = 1 means

that the switch close and S is given by

29 This control is implemented using a microcontroller thatsenses the PV array voltage and current. Simulation andexperimental results showed that operation converges to the

MPP in several tens of milliseconds [3], [116].

25. Temperature MethodsThe open-circuit voltage Voc of the solar cell, that varies

with the cell temperature as reported in Fig. 22 (whereas the

short-circuit current is directly proportional to the irradiance

Fig. 22. P-V under temperature variation.

TABLE . PARAMETERS OF THE OPTIMAL VOLTAGE EQUATION

level and relatively steady over cell temperature changes), ca

be described through the following equation [10]

30Where VocSTC= 21.8 V is the open-circuit voltage und

Standard Test Conditions (STC), (dVov/dT) = -0.08 V/K is th

temperature gradient, T is the cell temperature (K), and Tstcthe cell temperature under STC. On the other hand, th

optimal voltage is described through the following equatio[10]. 31Table shows each of the parameters of the optim

voltage equation (31) in relation to the irradiance levels. The

are two different temperature methods available in both

which require at least the same measurements of thtemperature T and of the PV array voltage Vpv for a

regulator [117]; as shown below:

a. The Temperature Gradient (TG) Algorithm:It uses the temperature T to determine the open-circu

voltage Voc from equation (30). The optimum operatinvoltage Vopis then determined as in the frictional open circu

voltage technique, avoiding power losses due to the open

circuit operations [10].

b. The Temperature Parametric (TP) Method:It determines the operating voltage Vop instantaneously b

equation (31), therefore it requires also the measurement

solar irradiance S [10].

(28)


11/17

26. Three Point Weight Comparison MethodIt is a three-point weight comparison method that avoids

the oscillation problem of the perturbation and observation

algorithm which is often employed to track the maximum

power point. Furthermore, a low cost control unit is

developed, based on a single chip to adjust the output voltage

of the solar cell array [118].

The P&O algorithm compares only two points, which arethe current operation point and the subsequent perturbation

point, to observe their changes in power and thus decidewhether increase or decrease the solar array voltage. In

comparison the algorithm of the three-point weight

comparison Fig. 23 is run periodically by perturbing the solar

array terminal voltage and comparing the PV output power onthree points of the P-V curve.

The three points are the current operation point A, a point,

B, perturbed from point A, and a point C, with doubly

perturbed in the opposite direction from point B. Fig. 24

depicts nine possible cases. In these cases, for the points A andB, if the Wattage of point B is greater than or equal to that of

point A, the status is assigned a positive weighting. Otherwise,the status is assigned a negative weighting. For the points A

and C, when the Wattage of point C is smaller than that of

point A, the status is assigned a positive weighting.

Otherwise, the status is assigned a negative weighting. Ofthe three measured points, if two are positively weighted, the

duty cycle of the converter should be increased. On the

contrary, when two are negatively weighted, the duty cycle of

the converter should be decreased. In cases with one positive

and one negative weighting, the MPP is reached [118].

27.PV Output Senseless (POS) Control methodThis is another new method in PV MPPT. The main

advantage of this method is that the current flowing into theload is the only one considerable factor. In case of a huge PVgeneration system, it can be operated much more safely than a

conventional system. The load power is proportional to the

source power of a PV array as illustrated in Fig. 25. A loadpower is equal to what multiplied the voltage with the current

of a load terminal. So, if the load current increases when the

load power increases, the load current will be proportional to

the source power that is the output power of the solar cell. So,the POS MPPT can be applied to all PV generation systems

with this simple algorithm [119]. Fig. 26 shows the algorithm

of the proposed control scheme.

The power conversion system is controlled by PWM (Pulse

Width Modulation) control. An increment of the duty ratiocauses an increase in the output current of the power converter

which is the load current flowing into the load [119].

The load current of PV generation system is the onlysignificant component of the control method this makes the

structure of the control circuit is simple, and the

manufacturing cost of the control device is decreased.

Especially in the case of a large PV generation system, thesystem can be operated effectively and much more safely,

because the voltage and current feedback of PV modules are

not needed [119].

Fig. 23. Algorithm for the three-point weight comparison.

Fig. 24. Possible states of the three perturbation points.

Fig. 25. Power characteristics of a PV array and a load.


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Fig. 26. Block diagram of PV output senseless MPPT control method

28.A Biological Swarm Chasing AlgorithmIt is a novel photovoltaic PV MPPT, based on biological

swarm chasing behavior, proposed to increase the MPPT

performance for a module-integrated PV power system. Each

PV module is viewed as a particle; as a result, the maximumpower point is viewed as the moving target. Thus, every PV

module can chase the maximum power point (MPP)

automatically. Theoretically experiments have proved that the

MPPT performance in transient state is obviously improved.

Comparing the proposed Bio-MPPT with a typical P&OMPPT method, the MPPT efficiency is improved about 12.19

% in transient state. Experimental results have shown that the

proposed Bio-MPPT algorithm can adapt well in changingenvironments, is flexible, and robust. A microcontroller is

needed to implement this method [120].

29. Variable Inductor MPPT MethodThis method presents a new topology of MPPT controller

for solar power applications that incorporated a variableinductance versus current characteristic. Power transfer in

solar photovoltaic applications is achieved by impedancematching with a DC-DC converter with MPPT by the

incremental conductance method. Regulation and dynamic

control is achieved by operating with continuous conduction.

It has been shown that under stable operation, the required

output inductor has an inductance versus current characteristic

whereby the inductance falls off with increasing current,

corresponding to increasing incident solar radiation. Thismethod shows how a variable sloped air-gap inductor,

whereby the inductor core progressively saturates withincreasing current, meets this requirement and has the

advantage of reducing the overall size of the inductor by 60%,

and increases the operating range of the overall tracker torecover solar energy at low solar levels [121].

The Inductance versus current (L-i) characteristic of the

variable inductor is shown in Fig. 27. The variable inductor is

based on a sloped air-gap (SAG) and the L-i characteristic of

the inductor is controlled by the shape of the air-gap.

Fig. 27. Characteristics of the Variable Inductor

Fig. 28. Comparison of CCM Conditions in a MPPT DC/DC Converter with

variable inductance.The role of the variable inductor in the stable operation o

the buck converter is explained by reference to Fig. 2

Continuous conduction can only be achieved with inductancvalues above the dashed line in Fig. 28 (the shaded area is o

limits). The lower limit of load current (corresponding to lo

solar insulation) is given by Io1 as long as the inductance greater than L1. Evidently, at higher currents (and high

insulation levels), sayIo2, a smaller inductorL2would suffic

with the added advantage of a reduced volume occupied by th

inductor. Conversely, setting the inductance atL2would lim

the lower load range to values of current (and solar insulatiogreater thanIo2.

The buck converter should work in the continuous curre

mode (CCM) to insure the stable operation of the syste

during changing the duty cycle in MPPT. The role of thvariable inductor in the stable operation of the buck convert

is to keep the operation of the converter in the continuouconduction mode and it can only be achieved with inductanc

values above the dashed line in Fig. 28 (the shaded area is o

limits) [121]. This method gives very good results in the lolevel of solar intensity.

30. Variable Step-Size Incremental Resistance (INR) MethodThe step-size for the incremental conductance MPP

determines how fast the MPP is tracked. Fast tracking can b

achieved with bigger increments, but the system might not ru

exactly at the MPP, instead oscillates around it; thus, there iscomparatively low efficiency. This situation is inverted whe

the MPPT is operating with a smaller increment. So


13/17

satisfying tradeoff between the dynamics and oscillations has

to be made for the fixed step-size MPPT. The variable step-size iteration can solve the tough design problem [122]. Fig.

29 shows the corresponding PV output power, slope of output

power versus output current and the product of the outputpower and its slope curves.

An improved variable step-size algorithm is proposed for

the INR MPPT method and is devoted to obtain a simple and

effective way to ameliorate both tracking dynamics andtracking accuracy. The primary difference between this

algorithm and others is that the step-size modes of the INR

MPPT can be switched by extreme values/points of a threshold

function, which is the product Cof exponential of a PV arrayoutput powerPnand the absolute value of the PV array power

derivative |dP/dI|as

32Where nis an index. As shown in Fig. 30, the product of thefirst degree exponential (n=1) of the PV array powerPand its

derivative |dP/dI|is applied to control the step-size for the INR

MPPT. The product curve has two extreme values/points (M1and M2) which are corresponding to two current values (I1and

I2) at two sides of MPP. The INR MPPT is in the variable

step-size mode when the PV array output current is between

I1and I2. Otherwise, it is in the fixed step-size mode. Theabove idea is formulized [122] by

0, 0, 0, 0,

(33)

Furthermore, similar to equations (1) (3) this proposedmethod is also based on the fact that the slope of the PV array

power curve is zero at the peak power point (MPP), positive tothe left of the MPP, and negative to the right, as given by

[122]: 0 0 34 0

Since

35 It can be written

36

Fig. 29. Normalized power, slope of power versus current, and the product

power and its slope (C1= P*(dP/dI), C2= P*(-dP/dI).

Fig. 30. Flowchart of the partially variable step-size INR MPPT algorithm

The MPP can thus be tracked by comparing thinstantaneous resistance (V/I) to the incremental resistan

(V/I) as shown in the flowchart in Fig. 30. Iref is th

reference current at which the PV array is forced to operate. Athe MPP, Iref equals to IMPP. Once the MPP is reached, th


14/17

operation of the PV array is maintained at this point unless a

change in V is noted, indicating a change in atmosphericconditions at the MPP. The algorithm decreases or increases

Irefto track the new MPP [122].

IV. DISCUSSIONStarting from 19 MPPT comparison table showed in [3],

table summarizes the major C/Cs of the 30 previous

mentioned MPPT techniques. Both old and updated methodsare investigated carefully to get all required comparison

criterion, the new added techniques are shaded in the tab

below.V. CONCLUSION

There are many different techniques for maximum pow

point tracking of photovoltaic PV systems. It is shown that

least 30 methods have been introduced in the literature, wi

several variations on implementation. This paper should serv

as a convenient reference for future work in PV powgeneration.

TABLE .MAJOR CHARACTERISTICS OF DIFFERENT MPPTTECHNIQUES

MPPT techniquePV array

dependent?

True

MPPT?

Analog

or

digital?

Periodic

tuning?

Convergence

speed

Implementation

complexity

Sensed

parameters

Hill Climbing / P&O No Yes Both No Varies Low Voltage, Current

Incremental Conductance No Yes Digital No Varies Medium Voltage, Current

Fractional Voc Yes No Both Yes Medium Low Voltage

Fractional Isc Yes No Both Yes Medium Medium Current

Fuzzy Logic Control Yes Yes Digital Yes Fast High Varies

Neural Network Yes Yes Digital Yes Fast High Varies

RCC No Yes Analog No Fast Low Voltage, Current

Current Sweep Yes Yes Digital Yes Slow High Voltage, Current

DC Link Capacitor Droop Control No No Both No Medium Low Voltage

Load I or V maximization No No Analog No Fast Low Voltage, Current

dP/dV or dP/dI Feedback Control No Yes Digital No Fast Medium Voltage, Current

Method No Yes Digital No Fast High Voltage, Current

System Oscillation Method No Yes Analog No N/A Low Voltage

Constant Voltage Tracker Yes No Digital Yes Medium Low Voltage

Lookup Table Method Yes Yes Digital Yes Fast Medium

Voltage, Current,

Irradiance,

Temperature

Online MPP Search Algorithm No Yes Digital No Fast High Voltage, Current

Array Reconfiguration Yes No Digital Yes Slow High Voltage, Current

Linear Current Control Yes No Digital Yes Fast Medium Irradiance

IMPP and VMPP Computation Yes Yes Digital Yes N/A MediumIrradiance,

Temperature

State Based MPPT Yes Yes Both Yes Fast High Voltage, Current

OCC MPPT Yes No Both Yes Fast Medium Current

BFV Yes No Both Yes N/A Low None

LRCM Yes No Digital No N/A High Voltage, Current

Slide Control No Yes Digital No Fast Medium Voltage, Current

Temperature method No Yes Digital Yes Medium High

Voltage,

Irradiance,

TemperatureThree Point Weight Comparison No Yes Digital No Varies Low Voltage, Current

POS Control No Yes Digital No N/A Low Current

Biological Swarm Chasing MPPT No Yes Digital No Varies High

Voltage, Current,

Irradiance,

Temperature

Variable Inductor MPPT No Yes Digital No Varies Medium Voltage, Current

INR method No Yes Digital No High Medium Voltage, Current


15/17

REFERENCES

[1] M. Berrera, A. Dolara, R. Faranda, and S. Leva, Experimental test ofseven widely-adopted MPPT algorithm, IEEE Bucharest Power Tech

Conference 2009, pp. 1 - 8.[2] V. Agarwal and A. Vishwakarma, A Comparative Study of PWM

Schemes for Grid Connected PV Cell, Power Electronics and Drive

Systems, 2007. PEDS '07. 7th International Conference, pp. 1769

1775.

[3] T. Esram, and P. L. Chapman, Comparison of Photovoltaic ArrayMaximum Power Point Tracking Techniques, IEEE transactions onenergy conversion, vol. 22, no. 2, june 2007.

[4] F. Liu, Y. Kang, Y.Zhang and S. Duan, Comparison of P&O and HillClimbing MPPT Methods for Grid-Connected PV Converter, Industrial

Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference,pp. 804 - 807.

[5] S. Jain, and V. Agarwal, Comparison of the performance of maximumpower point tracking schemes applied to single-stage grid-connected

photovoltaic systems, IET Electr. Power Appl., 2007, pp. 753 - 762.[6] C. Jaen, C. Moyano, X. Santacruz, J. Pou, and A. Arias, Overview of

maximum power point tracking control techniques used in photovoltaic

systems, Electronics, Circuits and Systems, 2008. ICECS 2008. 15th

IEEE International Conference, pp. 1099 - 1102.

[7] S. Ahmad, N. R. Mittal, A. B. Bhattacharya, M. Singh, Simulation,Output Power Optimization and Comparative Study of Silicon and ThinFilm Solar Cell Modules, Industrial Electronics and Applications

(ICIEA), 2010 the 5th IEEE Conference, pp. 624 629.

[8] H. P. Desai, and H. K. Patel, Maximum Power Point Algorithm in PVGeneration: An Overview, Power Electronics and Drive Systems, 2007.

PEDS '07. 7th International Conference, pp. 624 - 630.[9] D. P. Hohm, M. E. ropp, Comparative study of maximum power point

tracking algorithms using an experimental, programmable, maximum

power point tracking test bed, Photovoltaic Specialists Conference,

2000. Conference Record of the Twenty-Eighth IEEE, pp. 1699 - 1702.[10] R. Faranda, S. Leva and V. Maugeri, MPPT techniques for PV

Systems: energetic and cost comparison, in Proc. IEEE PES General

Meeting, Pittsburgh (PL), USA, 21-25 July, 2008, pp. 1 - 6.

[11] J. Lopez-Seguel, S. I. Seleme, P. Donoso-Garcia, L. F. Morais, P.Cortizo and M. S. Mendes, Comparison of MPPT Approaches inAutonomous Photovoltaic Energy Supply System Using DSP,

Industrial Technology (ICIT), 2010 IEEE International Conference, pp.

1149 - 1154.

[12] C. Hua, and C. Shen, Comparative Study of Peak Power TrackingTechniques for Solar Storage System, Applied Power ElectronicsConference and Exposition, 1998. APEC '98. Conference Proceedings

1998. Thirteenth Annual, pp. 679 - 685 vol.2.

[13] L. L. Buciarelli, B. L. Grossman, E. F. Lyon, and N. E. Rasmussen, Theenergy balance associated with the use of a MPPT in a 100 kW peak

power system, in IEEE Photovoltaic Spec. Conf., 1980, pp. 523527.[14] W. J. A. Teulings, J. C. Marpinard, A. Capel, and D. OSullivan, A new

maximum power point tracking system, in Proc. 24th Annu. IEEE

Power Electron. Spec. Conf., 1993, pp. 833838.

[15] Y. Kim, H. Jo, and D. Kim, A new peak power tracker for cost-effective photovoltaic power system, in Proc. 31st Intersociety Energy

Convers. Eng. Conf., 1996, pp. 16731678.

[16] O. Hashimoto, T. Shimizu, and G. Kimura, A novel high performanceutility interactive photovoltaic inverter system, in Conf. Record 2000

IEEE Ind. Applicat. Conf., 2000, pp. 22552260.[17] E. Koutroulis, K. Kalaitzakis, and N. C. Voulgaris, Development of a

microcontroller-based, photovoltaic maximum power point tracking

control system, IEEE Trans. Power Electron., vol. 16, no. 21, pp. 4654, Jan. 2001.

[18] M. Veerachary, T. Senjyu, and K.Uezato, Maximum power pointtracking control of IDB converter supplied PV system, in IEE Proc.Elect. Power Applicat. 2001, pp. 494502.

[19] W. Xiao and W. G. Dunford, A modified adaptive hill climbing MPPTmethod for photovoltaic power systems, in Proc. 35th Annu. IEEE

Power Electron. Spec. Conf., 2004, pp. 19571963.[20] O. Wasynczuk, Dynamic behavior of a class of photovoltaic power

systems, IEEE Trans. Power App. Syst., vol. 102, no. 9, pp. 3031

3037, Sep. 1983.

[21] C. Hua and J. R. Lin, DSP-based controller application in battestorage of photovoltaic system, in Proc. IEEE IECON 22nd Int. Con

Ind. Electron., Contr. Instrum., 1996, pp. 17051710.[22] M. A. Slonim and L. M. Rahovich, Maximum power point regula

for 4 kW solar cell array connected through inverter to the AC grid,

Proc. 31st Intersociety Energy Conver. Eng. Conf., 1996, pp. 166

1672.

[23] A. Al-Amoudi and L. Zhang, Optimal control of a grid-connected Psystem for maximum power point tracking and unity power factor,

Proc. Seventh Int. Conf. Power Electron. Variable Speed Drives, 199

pp. 8085.[24]N. Kasa, T. Iida, and H. Iwamoto, Maximum power point tracking w

capacitor identifier for photovoltaic power system, in Proc. Eighth In

Conf. Power Electron. Variable Speed Drives, 2000, pp. 130135.

[25] L. Zhang, A. Al-Amoudi, and Y. Bai, Real-time maximum power potracking for grid-connected photovoltaic systems, in Proc. Eighth I

Conf. Power Electronics Variable Speed Drives, 2000, pp. 124129.[26] C. C. Hua and J. R. Lin, Fully digital control of distributed photovolta

power systems, in Proc. IEEE Int. Symp. Ind. Electron. 2001, pp. 16

[27] M. L. Chiang, C. C. Hua, and J.-R. Lin, Direct power control fdistributed PV power system, in Proc. Power Convers. Conf., 2002, p

311 315.

[28] K. Chomsuwan, P. Prisuwanna, and V. Monyakul, Photovoltagridconnected inverter using two-switch buck-boost converter, in Con

Record Twenty-Ninth IEEE Photovoltaic Spec. Conf., 2002, pp. 152

1530.

[29]N. Femia, G. Petrone, G. Spagnuolo, and M. Vitel li, Optimizing Ducycle Perturbation of P&O MPPT Technique, 35th Annual IEEE PowElectronics Specialists Conferenre, Aochen, Germay. 2004, pp. 1939

1944 Vol.3.

[30] Y. Jung, G. Yu, J. Choi, and J. Choi, High-frequency DC link invertfor grid-connected photovoltaic system, in Conf. Record Twenty-Nin

IEEE Photovoltaic Spec. Conf., 2002, pp. 14101413.

[31] S. Jain and V.Agarwal, A new algorithm for rapid tracking approximate maximum power point in photovoltaic systems, IEE

Power Electron. Lett., vol. 2, no. 1, pp. 1619, Mar. 2004.

[32] T. Tafticht and K. Agbossou, Development of a MPPT method fphotovoltaic systems, in Canadian Conf. Elect. Comput. Eng., 2004, p

1123 1126.

[33]N. Femia, G. Petrone, G. Spagnuolo, and M. Vitelli, Optimization perturb and observe maximum power point tracking method, IEE

Trans. Power Electron., vol. 20, no. 4, pp. 963973, Jul. 2005.[34] P. J. Wolfs and L. Tang, A single cell maximum power point trackin

converter without a current sensor for high performance vehicle soarrays, in Proc. 36th Annu. IEEE Power Electron. Spec. Conf., 200

pp. 165171.[35]N. S. DSouza, L. A. C. Lopes, and X. Liu, An intelligent maximu

power point tracker using peak current control, in Proc. 36th Ann

IEEE Power Electron. Spec. Conf., 2005, pp. 172177.

[36]N. Kasa, T. Iida, and L. Chen, Flyback inverter controlled by sensorlecurrent MPPT for photovoltaic power system, IEEE Trans. InElectron., vol. 52, no. 4, pp. 11451152, Aug. 2005.

[37] A. Pandey, N. Dasgupta, and A. K. Mukerjee, High-performanalgorithms for drift avoidance and fast tracking in solar MPPT system

IEEE Trans. Energy Convers., vol. 23, no. 2, pp. 681689, Jun. 2008.[38] I. SEFA, and S. Ozdemir, Experimental Study of Interleaved MPP

Converter for PV Systems, IEEE, 2009, pp 456 - 461.

[39] C. Jaen, J. Pou, G. Capella, A. Arias, and M. Lamich, On the use of strackers to improve maximum power point tracking controllers appli

to photovoltaic systems, power quality, Alternative energy a

distributed systems, IEEE 2009, pp. 67 - 72.[40] A. F. Boehringer, Self-adapting dc converter for solar spacecraft pow

supply, IEEE Trans. Aerosp. Electron. Syst., vol. AES-4, no. 1, p

102 111, Jan. 1968.

[41] E. N. Costogue and S. Lindena, Comparison of candidate solar arrmaximum power utilization approaches, in Intersociety Ener

Conversion Eng. Conf., 1976, pp. 14491456.

[42] J. Harada and G. Zhao, Controlled power-interface between solar ceand ac sources, in IEEE Telecommun. Power Conf., 1989, pp. 22.1/

22.1/7.


16/17

[43] K. H. Hussein and I. Mota, Maximum photovoltaic power tracking: Analgorithm for rapidly changing atmospheric conditions, in IEE Proc.

Generation Transmiss. Distrib., 1995, pp. 5964.[44] A. Brambilla, M. Gambarara, A. Garutti, and F. Ronchi, New approach

to photovoltaic arrays maximum power point tracking, in Proc. 30th

Annu. IEEE Power Electron. Spec. Conf., 1999, pp. 632637.

[45] K. Irisawa, T. Saito, I. Takano, and Y. Sawada, Maximum power pointtracking control of photovoltaic generation system under non-uniforminsolation by means of monitoring cells, in Conf. Record Twenty-

Eighth IEEE Photovoltaic Spec. Conf., 2000, pp. 17071710.

[46] T.-Y. Kim, H.-G. Ahn, S. K. Park, and Y.-K. Lee, A novel maximumpower point tracking control for photovoltaic power system underrapidly changing solar radiation, in IEEE Int. Symp. Ind. Electron.

2001, pp. 10111014.

[47] Y. C. Kuo, T. J. Liang, and J. F. Chen, Novel maximum-power pointtracking controller for photovoltaic energy conversion system, IEEE

Trans. Ind. Electron., vol. 48, no. 3, pp. 594601, Jun. 2001.[48] G. J. Yu, Y. S. Jung, J. Y. Choi, I. Choy, J. H. Song, and G. S. Kim, A

novel two-mode MPPT control algorithm based on comparative study of

existing algorithms, in Conf. Record Twenty-Ninth IEEE Photovoltaic

Spec. Conf., 2002, pp. 15311534.

[49] K. Kobayashi, I. Takano, and Y. Sawada, A study on a two stagemaximum power point tracking control of a photovoltaic system under

partially shaded insolation conditions, in IEEE Power Eng. Soc.

Gen.Meet., 2003, pp. 26122617.

[50] W. Wu, N. Pongratananukul, W. Qiu, K. Rustom, T. Kasparis, and I.Batarseh, DSP-based multiple peak power tracking for expandable

power system, in Eighteenth Annu. IEEE Appl. Power Electron. Conf.Expo., 2003, pp. 525530.

[51] J. Sachin and V. Agarwal, An integrated hybrid power supply fordistributed generation applications fed by nonconventional energysources, IEEE Trans. Energy Convers., vol. 23, no. 2, pp. 622631, Jun.

2008.

[52] Y. Yusof, S. H. Sayuti, M. A. Latif and M. Z. che wanik, Modellingand simulation of Maximum power point tracker for photovoltaic

system, National power & Energy conf. (PECon), 2004 Proceedings,Malaysia.

[53]N. Femia, D. Granozio, G. Petrone, G. Spaguuolo and M. Vitelli,Optimized One-Cycle Control in Photovoltaic Grid Connected

Applications, IEEE Trans. Aerosp. Electron. Syst., vol. 2, no 3, July

2006.

[54] D. J. Patterson, Electrical system design for a solar powered vehicle,in Proc. 21st Annu. IEEE Power Electron. Spec. Conf., 1990, pp. 618

622.[55] M. A. S. Masoum, H. Dehbonei, and E. F. Fuchs, Theoretical andexperimental analyses of photovoltaic systems with voltage and current-

based maximum power-point tracking, IEEE Trans. Energy Convers.,

vol. 17, no. 4, pp. 514522, Dec. 2002.

[56] H. J. Noh, D. Y. Lee, and D. S. Hyun, An improved MPPT converterwith current compensation method for small scaled PV-applications, in

Proc. 28th Annu. Conf. Ind. Electron. Soc., 2002, pp. 11131118.[57] K. Kobayashi, H. Matsuo, and Y. Sekine, A novel optimum operating

point tracker of the solar cell power supply system, in Proc. 35th Annu.

IEEE Power Electron. Spec. Conf., 2004, pp. 21472151.

[58] B. Bekker and H. J. Beukes, Finding an optimal PV panel maximumpower point tracking method, in Proc. 7th AFRICON Conf. Africa,

2004, pp. 11251129.

[59] M. A. S. Masoum, S. M. M. Badejani, and E. F. Fuchs, Microprocessorcontrolled new class of optimal battery chargers for photovoltaic

applications, IEEE Trans. Energy Convers., vol. 19, no. 3, pp. 599606,

Sep. 2004.

[60] Y. M. Tung, A. P. Hu, N. K. Nair, Evaluation of Micro ControllerBased Maximum Power Point Tracking Methods Using dSPACE

Platform, Australian University, Power Engineering Conference 2006.[61] D. T. Ojima and W. Komatsu, a MPPT Algorithm Implementation

Using FPGA for an Experimental PV System, 9th Brazilian Power

Electronics Conference, pp. 672-675, 2008.

[62] T. Noguchi, S. Togashi, and R. Nakamoto, Short-current pulse basedadaptive maximum-power-point tracking for photovoltaic power

generation system, in Proc. 2000 IEEE Int. Symp. Ind. Electron., 2000,

pp. 157 162.

[63]N. Mutoh, T. Matuo, K. Okada, and M. Sakai, Prediction-data-basmaximum-power-point-tracking method for photovoltaic pow

generation systems, in Proc. 33rd Annu. IEEE Power Electron. SpConf., 2002, pp. 14891494.

[64] S. Yuvarajan and S. Xu, Photo-voltaic power converter with a simpmaximum-power-point-tracker, in Proc. 2003 Int. Symp. Circuits Sys

2003, pp. III-399III-402.

[65] S. M. Alghuwainem, Matching of a DC motor to a photovoltagenerator using a step up converter with a current locked loop, IEE

1993, pp 192 - 198.

[66] R. M. Hilloowala and A. M. Sharaf, A rule-based fuzzy logic controlfor a PWM inverter in photo-voltaic energy conversion scheme, Proc. IEEE Ind. Appl. Soc. Annu. Meet. 1992, pp. 762769.

[67] C. Y. Won, D. H. Kim, S. C. Kim, W. S. Kim and H.-S. Kim, A nemaximum power point tracker of photovoltaic arrays using fuz

controller, in Proc. 25th Annu. IEEE Power Electron. Spec. Con

1994, pp. 396403.[68] T. Senjyu and K. Uezato, Maximum power point tracker using fuz

control for photovoltaic arrays, in Proc. IEEE Int. Conf. Ind. Techno

1994, pp. 143147.

[69] G. J. Yu, M. W. Jung, J. Song, I. S. Cha, and I. H. Hwang, Maximupower point tracking with temperature compensation of photovoltaic f

air conditioning system with fuzzy controller, in Proc. IEEPhotovoltaic Spec. Conf., 1996, pp. 14291432.

[70] M. G. Simoes, N. N. Franceschetti, and M. Friedhofer, A fuzzy logbased photovoltaic peak power tracking control, in Proc. IEEE I

Symp. Ind. Electron. 1998, pp. 300305.

[71] A. M. A. Mahmoud, H. M. Mashaly, S. A. Kandil, H. El Khashab, aM. N. F. Nashed, Fuzzy logic implementation for photovolta

maximum power tracking, in Proc. 9th IEEE Int. Workshop Rob

Human Interactive Commun., 2000, pp. 155160.[72]N. Patcharaprakiti and S. Premrudeepreechacharn, Maximum pow

point tracking using adaptive fuzzy logic control for grid-connect

photovoltaic system, in IEEE Power Eng. Soc. Winter Meet., 2002, p

372 377.

[73] B. M.Wilamowski and X. Li, Fuzzy system based maximum powpoint tracking for PV system, in Proc. 28th Annu. Conf. IEEE InElectron. Soc., 2002, pp. 32803284.

[74] M. Veerachary, T. Senjyu, and K. Uezato, Neural-network-basmaximum-power-point tracking of coupled-inductor interleaved-boo

converter- supplied PV system using fuzzy controller, IEEE Trans. In

Electron., vol. 50, no. 4, pp. 749758, Aug. 2003.[75]N. Khaehintung, K. Pramotung, B. Tuvirat, and P. Sirisuk, RIS

microcontroller built-in fuzzy logic controller of maximum power potracking for solar-powered light-flasher applications, in Proc. 30

Annu. Conf. IEEE Ind. Electron. Soc., 2004, pp. 26732678.[76] T.L. Kottas, Y. S. Boutalis and A. D. Karlis, New Maximum Pow

Point Tracker for PV Arrays Using Fuzzy Controller in Clo

Cooperation with Fuzzy Cognitive Network, IEEE Trans. Ener

Conv., vol.21, no.3, September, 2006.

[77] T. Hiyama, S. Kouzuma, and T. Imakubo, Identification of optimoperating point of PV modules using neural network for real tim

maximum power tracking control, IEEE Trans. Energy Convers., vo

10, no. 2, pp. 360367, Jun. 1995.

[78] K. Ro and S. Rahman, Two-loop controller for maximiziperformance of a grid-connected photovoltaic-fuel cell hybrid pow

plant, IEEE Trans. Energy Convers., vol. 13, no. 3, pp. 276281, Se

1998.

[79] A. Hussein, K. Hirasawa, J. Hu, and J. Murata, The dynamperformance of photovoltaic supplied dc motor fed from DCD

converter and controlled by neural networks, in Proc. Int. Joint ConNeural Netw., 2002, pp. 607612.

[80] X. Sun, W. Wu, X. Li, and Q. Zhao, A research on photovoltaic enercontrolling system with maximum power point tracking, in Proc. Pow

Convers. Conf., 2002, pp. 822826.[81] L. Zhang, Y. Bai, and A. Al-Amoudi, GA-RBF neural network bas

maximum power point tracking for grid-connected photovolta

systems, in Proc. Int.Conf. Power Electron. Machines and Drives, 200

pp. 1823.

[82] P. Midya, P. T. Krein, R. J. Turnbull, R. Reppa, and J. KimbaDynamic maximum power point tracker for photovoltaic application


17/17

in Proc. 27th Annu. IEEE Power Electron. Spec. Conf., 1996, pp. 1710

1716.

[83] Y. H. Lim and D. C. Hamill, Simple maximum power point tracker forphotovoltaic arrays, Electron. Lett., vol. 36, pp. 997999, May 2000.

[84] L. Stamenic, M. Greig, E. Smiley, and R. Stojanovic, Maximum powerpoint tracking for building integrated photovoltaic ventilation systems,

in Proc. IEEE Photovoltaic Spec. Conf., 2000, pp. 15171520.

[85]N. Kasa, T. Lida and H. iwamoto, Maximum power point trackingwith capacitor identifier for photovoltaic power system, IEEE proc.

Electr power appl vol 147 no. 6 november 2000

[86] Casadei D., Grandi G., and Rossi C., Single-phase single-stagephotovoltaic generation system based on a ripple correlation controlmaximum power point tracking, IEEE Trans. Energy Convers., 2006,

21, (2), pp. 562568

[87] Esram T., Kimball J.W., Krein P. T., Chapman P. L., and Midya P.,Dynamic maximum power point tracking of photovoltaic arrays using

ripple correlation control, IEEE Trans. Power Electron., 2006, 21, (5),pp. 12821291.

[88] M. Bodur and M. Ermis, Maximum power point tracking for low powerphotovoltaic solar panels, in Proc. 7th Mediterranean Electrotechnical

Conf., 1994, pp. 758761.

[89] M. Matsui, T. Kitano, D. h. Xu, and Z. q. Yang, A new maximumphotovoltaic power tracking control scheme based on power equilibriumat DC link, in Conf. Record 1999 IEEE Ind. Appl. Conf., 1999, pp.

804809.

[90] T. Kitano, M. Matsui, and D. h. Xu, Power sensor-less MPPT controlscheme utilizing power balance at DC link-system design to ensure

stability and response, in Proc. 27th Annu. Conf. IEEE Ind. Electron.Soc., 2001, pp. 13091314.

[91] C. R. Sullivan and M. J. Powers, A high-efficiency maximum powerpoint tracker for photovoltaic arrays in a solar-powered race vehicle, inProc. 24th Annu. IEEE Power Electron. Spec. Conf., 1993, pp. 574580.

[92] A. S. Kislovski and R. Redl, Maximum-power-tracking using positivefeedback, in Proc. 25th Annu. IEEE Power Electron. Spec. Conf., 1994,

pp. 10651068.

[93] H. valderrama-Blavi, C. Alonso, L. Martinez-Salamero, S Singer, BEstibals and J Maixe-Altes, AC-LFR concept applied to modular

photovoltaic power conversion chains, IEE Proc-Electr. Power Appl.

Vol. 149, No 6 November 2002

[94] J. Arias, F. F. Linera, J. Martin-Ramos, A. M. Pernia, and J.Cambronero, A modular PV regulator based on microcontroller with

maximum power point tracking, in Proc. IEEE Ind. Appl. Conf., 2004,pp. 11781184.

[95]

D. Shmilovitz, On the control of photovoltaic maximum power pointtracker via output parameters, in IEE Proc. Elect. Power Appl., 2005,

pp. 239248.[96] R. Bhide and S. R. Bhat, Modular power conditioning unit for

photovoltaic applications, in Proc. 23rd Annu. IEEE Power Electron.

Spec. Conf., 1992, pp. 708713.

[97] H. Sugimoto and H. Dong, A new scheme for maximum photovoltaicpower tracking control, in Proc. Power Convers. Conf., 1997, pp. 691696.

[98] S. J. Chiang, K. T. Chang, and C. Y. Yen, Residential photovoltaicenergy storage system, IEEE Trans. Ind. Electron., vol. 45, no. 3, pp.

385394, Jun. 1998.[99] J. A. M. Bleijs and A. Gow, Fast maximum power point control of

current-fed DCDC converter for photovoltaic arrays, Electron. Lett.,

vol. 37, pp. 56, Jan. 2001.

[100]C. L. Hou, J. Wu, M. Zhang, J. M. Yang, and J. P. Li, Application ofadaptive algorithm of solar cell battery charger, in Proc. IEEE Int.

Conf. Elect. Utility Deregulation Restruct. Power Technol., 2004, pp.810813.

[101]S. Jain, V. Agarwal, A new algorithm for rapid tracking ofApproximate maximum power point in photovoltaic systems, IEEE

power electronics letters, 16 19, vol 2 no 1 march 2004.[102]S. Jain, V. Agarwal, New current control based MPPT technique for

single stage grid connected PV systems, energy conversion and

management, 2006, pp. 625-644.

[103]Chung H. S. H., Tse K. K., Ron Hui S. Y., Mok C. M., and Ho M. T., Anovel maximum power point tracking technique for solar panels using aSEPIC or Cuk converter, IEEE Trans. Power Electron., 2003, 18, (3),

pp. 717724.

[104]Obayashi K., Matsuo H., and Sekine Y., An excellent operating potracker of the solar-cell power supply system, IEEE Trans. In

Electron., 2006, 53, (2), pp. 495499.[105]T. Hiyama and K Kitabyashi, Neural Network based estimation

maximum power generation, IEEE trans. On energy conversion, v

12, pp 241-247, sept 1997

[106]H. El-Sayed, A. Ibrahim, and Faten F. Houssiny, Microcomputcontrolled buck regulator for maximum power point tracker for

pumping system operates from photovoltaic system, IEEE Internation

Fuzzy Systems Conference Proceedings August 22-25, 1999, Seo

Korea, 406 - 411, vol.1.[107]H. Tarik Duru, A maximum power tracking algorithm based on Impp

f(Pmax) function for matching passive and active loads to a photovolta

generator, solar energy 2005, pp. 812-822.

[108]I. H. Atlas, A. M. Sharaf, A novel on line MPP search algorithm for Parrays,IEEE transaction on Energy conversion vol 11, No 4 Decemb

1996, pp. 748 754.[109]M. A. El-Shibini and H. H. Rakha, Maximum power point tracki

technique, in Proc. Integrating Research, Ind. Educ. Energy Commu

Eng. Electrotechnical Conf., 1989, pp. 2124.

[110]C. T. Pan, J. Y. Chen, C. P. Chu and Y. S. Huang, A fast maximupower point tracker for photovoltaic power systems, in Proc. 25

Annu. Conf. IEEE Ind. Electron. Soc., 1999, pp. 390393.[111]T. Takashima, T. Tanaka, M. Amano, and Y. Ando, Maximum outp

control of photovoltaic (PV) array, in Proc. 35th Intersociety Ener

Convers. Eng. Conf. Exhib., 2000, pp. 380383.

[112]E. V. Solodovnik, S. Liu, and R. A. Dougal, Power controller desifor maximum power tracking in solar installations, IEEE Trans. PowElectron., vol. 19, no. 5, pp. 12951304, Sep. 2004.

[113]Y. Chen and K. M. Smedley, A cost-effective single-stage inverter wmaximum power point tracking, IEEE Trans. Power Electron., vol. 1no. 5, pp. 12891294, Sep. 2004.

[114]P. C. M. de Carvalho, R. S. T. Pontes, D. S. Oliveira, Jr., D. B. Riffel, G. V. de Oliveira, and S. B. Mesquita, Control method of

photovoltaic powered reverse osmosis plant without batteries based

maximum power point tracking, in Proc. IEEE/PES Transmiss. DistrConf. Expo.: Latin America, 2004, pp. 137142.

[115]E. I. rtiz-Rivera and F. Peng, A novel method to estimate the maximupower for a photovoltaic inverter system, in Proc. 35th Annu. IEE

Power Electron. Spec. Conf., 2004, pp. 20652069.

[116]M. Zhang, J. Wu, and H. Zhao, The application of slide technology PV maximum power point tracking system, in Proc. Fifth World ConIntell. Contr. Automat., 2004, pp. 55915594.

[117]M. Park, and I. K. Yu, A Study on Optimal Voltage for MPPObtained by Surface Temperature of Solar Cell, in Proc. IECON, 200

pp. 2040- 2045.[118]Y. T. Hsiao, and C. H. Chen, Maximum Power Tracking f

Photovoltaic Power System, in Proc. Industry Application Conferen

2002, pp. 1035- 1040.

[119]S. Lee, H. Park, G. Kim, H. Seo, M. H. Ali, M. Park, and I. Yu, TExperimental Analysis of the Grid connected PV System Applied bPOS MPPT, International Conference on Electrical Machines a

Systems 2007, Oct., Seoul, Korea, pp. 484 493.

[120]L. Chen, C. Tsai, Y. Lin, and Y. Lai, A Biological Swarm ChasinAlgorithm for Tracking the PV Maximum Power Point, IEEtransaction on energy conversion, Vol.25, No.2, June 2010, pp. 484

493.

[121]L. Zhang, W. G. Hurley, and W. Wolfle, A New Approach to AchieMaximum Power Point Tracking for PV System with a Variab

Inductor, 2010 2nd IEEE International Symposium on Pow

Electronics for Distributed Generation Systems, pp. 948 952.[122]Q. Mei, M. Shan, L. Liu, and J. M. Guerrero, A Novel Improv

Variable Step-Size Incremental Resistance (INR) MPPT Method for P

Systems, 2010 IEEE, pp.242 -2434.

a survey of maximum ppt techniques of pv systems

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