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Low cost and high efficiency of single phase photovoltaic systembased on microcontroller

Lotfi Khemissi a,⇑, Brahim Khiari a, Ridha Andoulsi a, Adnane Cherif b

a Research Center of Energy (CRTEn), Borj Cedria Science and Technology Park, Hammam Lif 2050, Tunisiab Faculty of Sciences of Tunis, Tunis El Manar University, 2092 Tunis, Tunisia

Received 18 June 2010; received in revised form 3 December 2011; accepted 21 December 2011Available online 2 February 2012

Communicated by: Associate Editor Arturo Morales Acevedo

Abstract

This paper presents a theoretical and practical study of a single phase photovoltaic conversion system. It consists of a step down con-verter to charge a battery with the maximum power available from photovoltaic generator (PVG) and a single phase voltage source inver-ter (VSI) to produce a stable AC voltage (220 V/50 Hz) with lower total harmonic distortion (THD). A new perturb and observealgorithm is designed and implemented in a cheaper microcontroller PIC 16F876 where the duty cycle perturbation and the samplingperiod are selected to insure the stability of the PV system around the maximum power. The control strategy adopted for the inverteris the Selective Harmonic Eliminated Pulse Width Modulation (SHE PWM). The pulses are calculated and transferred on the PIC16F876 memory. With this technique, inverter losses are decreased and the output voltage is easily filtered with a simple low pass filterproducing a perfectly sine wave form voltage. The battery is sized to supply loads in non-sunny times.

With optimization of its various components, the conventional single phase PV system has a low cost, high efficiency but also goodpower quality which represents a good opportunity to use it in many stand alone photovoltaic applications such as houses lighting. Anexperimental system has been made to demonstrate the efficiency of the photovoltaic system and to validate simulations done by Matlab– Simulink environment. 2011 Elsevier Ltd. All rights reserved.

Keywords: Photovoltaic generator; Buck converter; Maximum Power Point Tracking (MPPT); Single phase inverter; Selective Harmonic Pulse WidthModulation; Filter

1. Introduction

Due to rising costs of conventional energy and their lim-

ited resources, photovoltaic energy becomes a promisingenergy with advantages such as the absence of any pollu-tion and the availability with more or less large quantitiesanywhere in the world. Currently, there is a big interestin solar energy applications especially in regions withfavorable climatic conditions. Among these applications

we mention water pumping and lighting especially in iso-lated sites.

The aim of this paper is to develop a photovoltaic appli-

cation that provides a stable AC voltage (220 V/50 Hz)from non-linear photovoltaic generator (PVG) with highefficiency and low cost.

Firstly, the photovoltaic generator recharges a batterythrough a buck converter controlled by a microcontroller16F876 to track the maximum power from the PVG witha new perturb and observe algorithm, then a single-phasevoltage source inverter (VSI) converts the battery voltage(24 V) to a stable AC voltage (220 V/50 Hz) after associa-tion with a simple low pass filter and a step-up transformer.The inverter pulses are calculated to eliminate 5th–9th order

0038-092X/$ - see front matter 2011 Elsevier Ltd. All rights reserved.

doi:10.1016/j.solener.2011.12.019

⇑ Corresponding author. Address: Research Center of Energy, BorjCedria Science and Technology Park, BP 95, Hammam Lif 2050, Tunisia.Tel.: +216 79 325 811/215, +966 540312400; fax: +216 79 325 934/825.

E-mail address: [email protected] (L. Khemissi).

www.elsevier.com/locate/solener

Available online at www.sciencedirect.com

Solar Energy 86 (2012) 1129–1141

http://dx.doi.org/10.1016/j.solener.2011.12.019

mailto:[email protected]



mailto:[email protected]


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harmonics and then saved in the PIC 16F876 memory. TheAC photovoltaic system as designed can be a best solutionfor domestic applications since their components are wellsized to decrease losses and thus decreasing the overall priceof the system.

In (Akkaya and Kulaksiz, 2004), authors have developeda high efficiency AC photovoltaic system but they have useda solar tracker based on a stepper motor to increase the effi-ciency of the system, however this solution increases theoverall price comparing with the uses of maximum powerpoint tracking (MPPT) algorithms to match the maximumpower of the PVG independently of the climatic conditions.

In literature, several algorithms are developed to extractthe maximum power point (MPP) from the PVG such asthe incremental conductance (INC), Perturb and Observe

(PO) and Fuzzy Logic (FL) programs differ in the stability

of the operating point around the optimal point. (Lalouniet al., 2009) proposes a method based on a fuzzy controllerto extract the MPP and significantly decreases the oscilla-tion around the operating point however this methodrequires an advanced control platform. The INC and thePO are the two most used algorithms in practice, the firstis more adapted to abrupt climatic changes, but it requiresa longer calculation time.

In the PO algorithm The PVG current and voltage aresensed, then PVG power is computed, depending on the signof the difference between PVG output power at k samplingand k + 1 sampling, the duty cycle is changed, then a PI con-troller regulates the output voltage or current to reach itsreference. This method can be improved by using a micro-controller with PWM outputs, in this case the controller is

omitted and the control output variable is the duty cycle.

Nomenclature

PVG photovoltaic generatorVSI voltage source inverterTHD total harmonic distortion

SHE PWM selective harmonic eliminated pulse widthmodulationMPPT maximum power point trackingPO perturb and observe algorithmI ph photocurrent of the photovoltaic generator (A)I s cell reverse saturation current (A)K Boltzman’s constant (1.38 1023 J K1)K T temperature coefficient of the cell (55 e4 K1)T temperature of the cell in Kelvin (K),G irradiation (W/m2)A constant with respect to the temperature

(0.06 A K3)q charge of the electron (1.6

1019 C)

E g band gap (V)B ideality factor of the junctionns number of cells in seriesnp number of cells in parallelRs cell series resistance (X)Rsh cell shunt resistance (X)V array voltage of the array (V)I array array current (A)V oc open circuit voltage of the PVG (V)I sc short circuit current of the PVG (A)V mp voltage at maximum power of the PVG (V)I mp PVG current at maximum power (A)

D(k ) duty cycle of the DC/DC converter at k sam-plingD0 duty cycle initializationI (k ) PVG output current at k samplingV (k ) PVG voltage at k samplingP (k ) PVG power at k samplingDd duty cycle perturbationCCM continuous conduction mode

L inductance of the DC/DC converter (H)C Capacitor of the DC/DC converter (F)Di Lmax maximum peak to peak ripple of the inductor

current (A)DV smax maximum value of the peak-to-peak ripple out-put voltage of the DC–DC converter (V)

f s switching frequency (Hz)C pv input capacitor (F)Dm duty cycle at maximum converter output powerI om DC component of the DC/DC output current at

maximum output power (A)Rpm PV array internal resistance at the maximum

power point (X)Rpv equivalent resistance of the simplified PVG

model (X)D duty cycle cvpv ; cipv; d̂ small variation of PVG voltage, PVG cur-

rent and the duty cycle of the converteri o small variation of the DC/DC converter output

current (A)C f filter capacitor (H)Lf filter inductancegMPPT MPPT efficiencyP actual measured power of the PV generator (W)P max maximum power that the PV generator can pro-

duce under given irradiance and temperature(W)

Rds on resistance of the Mosfet (X)

P Mosfet,loss Mosfet losses (W)tr rise time (s)tf fall time (s)Qgate reverse recovery charge (C)V d forward voltage drop of the diode (V)Rcu inductor resistance (X)P core inductor core losses (W)

1130 L. Khemissi et al. / Solar Energy 86 (2012) 1129–1141

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(Koutroulis et al., 2001) used the PO algorithm on thecheaper microcontroller for battery charging applicationinstead of Hua et al. (1998) where a DSP platform was usedto develop the converter; the PV output power is increasedby 15%. In (Alberto et al., 2009) a new battery chargingbased on microcontroller is developed, the output power is

increased by 25% and the MPPT efficiency reached 95%.However this method used an analog control to reach theoptimal current reference which affects the rapidity of thesystem to track the MPP in the case of sudden climatic vari-ations. In (Salas et al., 2005) authors presented a batterycharging application with a microcontroller, only the PVGcurrent was sensed thus decreasing the overall price, the effi-ciency was increased by 18.5% but the duty cycle perturba-tion needs to be quantified depending on the dynamic of the system to improve efficiency and to ensure a system sta-bility. (Feimia et al., 2005) presented an optimizationmethod of PO in terms of variation of duty cycle and sam-pling period and thus ensured a good MPP tracking even a

sudden change of irradiation occurred (50 W/m2). In TarikDuru, 2006 a maximum power tracking based onI mpp = f (P max) function was implemented. This approachneeds predetermined experimental values of P max and I mpp

of the PVG for different irradiances. With this method theimplemented circuit must be changed once the PVG modulesconfiguration changes, the oscillations around the maximumpower point are considerable.

In this paper a new PO algorithm is used. The duty cycleperturbation and the sampling period of PVG voltage andcurrent are selected depending on the system stability whilea new test on the output power forces the system to operate

near the MPP if a sudden irradiation occur (100 W/m2

/s)thus decreasing losses and improve efficiency of the system.The use of the microcontroller to control the DC–DC con-verter presents a technical and an economic solution suit-able for photovoltaic users to overcome the high cost of PV panels. Indeed, the microcontroller brings the flexibilityto change the real-time maximum power control algorithmwithout further changes in hardware and switches the con-verter through its PWM outputs. The experimental systemis described in Section 2. The DC–DC converter is oper-ated unless the battery is full charged.

The DC–AC stage is based on the SHE PWM method.With this technique, the power Mosfet’s are less switchedwhich decreasing the switching losses. This VSI invertercan be extended to grid connected application as describedin Maris et al. (2007) since the phase shift between invertervoltage and grid is fulfill by switching pulses and the realpower flow becomes fully controlled.

2. Description of the photovoltaic conversion system

2.1. Presentation of the photovoltaic generator

A photovoltaic cell consists of semiconductor materialsthat convert sunlight directly into electricity. Its equivalent

circuit is presented in Fig. 1.

The electrical model of the photovoltaic cell includes aseries resistance (Rs) and a shunt resistor Rsh. These resis-tors have some effects on the I – V characteristics of the cell.The series resistance is the internal resistance of the cell, itdepends on the resistance of the semiconductor. The shuntresistance is due to leakage at the junction. The I–V char-acteristics of a PV cell are governed by the followingequations:

I ¼ I ph I D I sh ð1Þ

I ¼ I ph I s exp qðV cell þ Rs I Þ

BKT

1 V cell þ Rs I

Rsh

ð2Þ

Where I ph is the light current I s is the reverse saturation cur-rent of the diode, K the Boltzmann constant (1.38 1023 J/K), q the charge of an electron (1.6 1019 C), B

the ideality factor of the junction, and T is the temperaturein Kelvin. The light current I ph depends on temperature andirradiation while the reverse saturation current of the diodedepends only on the temperature.

I ph

¼

G

1000 ½ I sc

þ K T

ðT

298

Þ ð3

Þ I s ¼ AT3 exp qE g

BKT

ð4Þ

where G , I sc, K T, E g, A, represent respectively the irradia-tion, the short-circuit current of the PV cell, the tempera-ture coefficient, the band gap and constant with respectto temperature (Rosell and Ibanez, 2006).

The PV modules are the basic components of all PV sys-tem; they can be connected in series to increase their oper-ating voltage and in parallel to increase their current. Thisset is called photovoltaic generator (PVG). The equivalent

circuit of a PV module (Fig. 2) is deduced from that of Fig. 1. The current–voltage equation of a PV module iswritten as:

Iph

Rsh

I shID

VD

RsI

Vcell

Fig. 1. Equivalent circuit of a photovoltaic cell.

(ns /np)Rs

npIph

npI

nsVcell

ID

(ns-1)VD

(np-1)ID npIsh

(ns /np)RshVD

Fig. 2. Equivalent circuit of a PV module.

L. Khemissi et al. / Solar Energy 86 (2012) 1129–1141 1131

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I array ¼ np I ph

np I s exp q

nsBKTðV array þ I array Rs

ns

np

1

V arraynp

nsþ Rs I array

Rsh

ð5Þ

where ns is the number of cells in series and np is the num-ber of cells in parallel.

2.2. Study of the buck converter

The AC photovoltaic system under study consists of aphotovoltaic generator with a maximum power of 277 Wat 1000 W/m2 and 25 C, a buck converter is used to chargethe battery with the maximum power of the PVG and toprevent it against overcharge.

The choice of step down converter is justified becausethe battery voltage (24 V) is less than the PVG voltage at

maximum power 57 V. In other cases, when the load is apure resistor (RL), the DC/DC converter topology mustbe selected depending on the sign of RL – RPM where RPM

represents the internal PVG resistance at maximum power(Enrique et al., 2007).

The voltage source inverter which assuring the interfacebetween the DC bus and the AC bus is controlled by SHEPWM. The inverter is then associated to a low pass filter toremove higher harmonics and a step-up transformer to feed

loads. The simulation of the system of Fig. 3 was done byMatlab–Simulink.

The goal of the MPPT control method is to extract themaximum power from the photovoltaic generator underany climatic condition. To explain this fact, we comparetwo PV battery charging application, the first system is a

well design PV system without MPPT algorithm and thesecond system is equipped with MPPT tracking algorithm(Fig. 5). Assuming that the two systems have the samepower at 25 C (point A1), when the temperature movesto 40 C, the first system operates at point B1 while the sec-ond system operates at point B2 and finally when the tem-perature reaches 50 C, the first system operates at point C1

while the second is at point C2, the extracted power fromthe PVG by the second system is greater by 4% and 17%respectively (Figs. 6 and 7).

In this paper a new perturb and observe (PO) algorithmis used (Fig. 8). The sampling period and the duty cyclevariation (Dd ) are selected to decrease the number and

the amplitude of oscillations around the maximum powerpoint (MPP).

In order to perform this algorithm in face of sudden cli-matic variations (100 W/m2/s) a new test is used after eachduty cycle variation. Based on Fig. 4, a sudden variation of irradiation makes PO less precise because the DP =P B P A is computed on two different level of irradiationand the operating point moves far from MPP (fig. 4b). If DP is greater than a proper threshold, this means that asudden variation of irradiation occurred, in this case, andbased on the assumption that the operating voltage at max-imum power points is independent of irradiation, the DC/

DC converter is reinitialized with the duty cycle D0 = V mp/V battery which moves the system to operate near the MPPthus decreasing power losses.

The PV array used in this paper has the characteristicsshown in Table 1 in standard conditions (G = 1000 W/m2

and T = 25 C).The DC–DC converter is chosen to operate in continu-

ous conduction mode (CCM), the inductance is selected tolimit the ripple output current below 10% of its mean value,

PV Generator

Pic

16F876IPV

VPV

DCPV

C Battery

R1

R2

R4

+-

R3

R4

R3

Rseries

Vbat

R5

R6

L

Fig. 3. MPPT control of the buck converter.

0 10 20 30 40 50 60 70 80 900

1

2

3

4

5

6

7

8

Voltage (V)

C u r r e n t ( A )

E=1000 W/m2;T=25 CE=800 W/m2;T=25 CE=600 W/m2;T=25 C

0 10 20 30 40 50 60 70 80 900

50

100

150

200

250

300

Voltage (V)

P o w e r ( W )

E=1000 W/m2; T=25 CE=800 W/m2; T=25 CE=600 W/m2; T=25 C

(a) (b)

A

BC

D

Fig. 4. Effect of irradiation on the: (a) PVG current–voltage characteristics. (b) PVG power–voltage characteristics.


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and the output capacitor is selected to limit the output volt-age variation at 1%.

The inductor and the capacitor can be evaluated as:

L ¼ V pv

4 f s DiLmax

¼ V mp

4 f s DiLmax

¼ 57

4 10; 000 1:317 ¼ 1:08 mH

C ¼ V pv

32 L f 2s DV smax

¼ V mp

32 L f 2s DV smax

¼ 57

32 1:2 103 10; 0002 0:28¼ 53 lF

The selected values are: L = 1.2 mH and C = 60 lF.

Where V pv is the PVG output voltage, V mp the PVGoutput voltage at maximum power; Di Lmax the maximumpeak-to-peak ripple of the inductor current; f s the switchingfrequency and DV smax is the maximum value of the peak-to-peak ripple output voltage of the DC–DC converter.

Taking into account that the ripple of the PV outputcurrent must be less than 2% of its mean value, the inputcapacitor is calculated as given in Koutroulis et al. (2001).

C pv Pð1 DmÞ I om Dm

0:02 I pm Rpm f s ; C pv ¼ 250 lF:

where Dm is the duty cycle at maximum converter outputpower, I om the DC component of the DC/DC converteroutput current at maximum output power, I pm the con-verter input current at maximum output power of PVGand Rpm is the PV array internal resistance at the maximumpower point.

The disadvantage of the PO algorithm is its oscillationaround the maximum power point (MPP). In this paper alinearization around the MPP leads to a good selectionof the sampling period T . The choice of T is a compromisebetween the number of oscillation around the maximumpower, stability of the system and the rapidity of the algo-rithm. To do this the PVG can be modeled by a voltagesource V pv in series with Rpv as mentioned in Koutroulis

et al. (2001) and Villalva and Filho, 2008.A small variation around the MPP leads to write the two

transfer functions from which the sampling period isselected. These functions are the duty-to-control transferfunction (G vd) and duty-to-current transfer function (G id).

G vd ¼ cvpv bd ¼ Rpvð I om Ls þ V mp DmÞ

LC pv Rpv s2 þ Ls þ Rpv D2m

¼ Rpv

cipv bd ð6Þ

G id ¼ bio bd ¼ V mpð1 þ RpvC pv sÞ þ Rpv Dm I om

LC pv Rpv s2 þ Ls þ Rpv D2m

ð7Þ

Where

cvpv ,

cipv ,

bd and

bio represent a small variation of GPV

voltage, current, duty cycle and the DC/DC converter out-put current around the MPP respectively.

G id has an opposite sign of G vd since an increasing of PVG voltage is accompanied by a decreasing of PVG cur-rent (Villalva and Filho, 2008).

The two transfer functions describe the behavior of asecond order system (Fig. 9) with a damper of:

n ¼ 1

2 Rpv Dm

ffiffiffiffiffiffiffiffi L

C PV

r > 0

where L P V pv

4 f sDiLmaxand C pv P

ð1 DmÞ I om Dm

0:02 I pm Rpm f sFig. 9 shows the step response of (6) and (7) for a four

values of n. The smallest time response of the second order

0 10 20 30 40 50 60 70 80 900

50

100

150

200

250

300

Voltage (V)

P o

w e r ( W )

E=1000 W/m2; T=25 CE=1000 W/m2; T=40 CE=1000 W/m2; T=55 C

A1

B1

C1

B2

C2Excess of

power

Fig. 5. Effect of temperature on the PVG output power.

0 1 2 3 4 5 6 7 8 9 10100

105

110

115

120

125

130

Time (s) 1 0 0 * ( P o

w e r w i t h M P P T / P o w e r w i t h o u t M P P T )

Fig. 7. Excess of power ¼ PVGwith MPPT algorithm

PVGwithout MPPT algorithm.

0 1 2 3 4 5 6 7 80

50

100

150

200

250

300

Time (s)

P o w e r ( W )

PV system with MPPT

well design PV system without MPPT

Fig. 6. PVG output power with and without MPPT.


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system is reached when n = 0.7. With the precalculated val-ues of L and C in the manuscript (n = 0.62), the timeresponse is 10 ms and it is close to time response withn = 0.7 but contrary there is an over size of the inductancewhen n = 0.7. We have conclude that the precalculatedL = 1.2 mH and C pv = 250 lF are the most appropriate

values in our design.

Fig. 10a–c shows PVG current, voltage and power fortwo values of sampling period (1 ms and 50 ms). It is obvi-ous that for T = 1 ms (blue line) the system presents moreoscillation around the maximum power than for T = 50 ms(red line) because the system (PV, DC–DC, battery)does not reach his steady state before the second pertur-bation of duty cycle occur. We conclude that a goodselection of the sampling period is a compromise betweenstability of the PV system and rapidity of the MPP trackingalgorithm.

Tacking into account the delay caused by the microcon-troller to compute the PVG power, it is suitable to chooseT twice the time during it the system reaches his steadystate. By using this method, we avoid power losses due to

the oscillation around the MPP.

Fig. 8. Flowchart of the MPP tracking algorithm.

Table 1Parameters of the PVG.

Characteristics of the photovoltaic generator (1000 W/m2

; T = 25 C)Open-voltage circuit (V oc) 77 VShort-circuit current (I sc) 5.6 AVoltage at maximum power (V mp) 57 VCurrent at maximum power (I mp) 4.85 AMaximum power (W ) 277 W


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The parameters of the proposed MPPT algorithm areselected depending on the stability of the system to

decrease the number of oscillations around the MPP(T = 50 ms) and to limit the amplitude variation of thepower around the MPP (duty cycle perturbation = 1%)

the algorithm is also optimized against a sudden variationof irradiation as mentioned in the flowchart of Fig. 8. InFig. 12, we compare the performances of three perturband observe algorithms for the irradiation profile of Fig. 11: the first algorithm is a classical PO algorithm,the second algorithm is an optimized PO without taking

account the sudden climatic variations and the last one isthe proposed algorithm which is optimized in terms of sam-pling period, duty cycle and also against a sudden irradia-tion variations (100 W/m2/s). It is clear that the MPP iswell tracking with the proposed algorithm.

2.3. Study of the voltage source inverter

The structure used of the voltage source inverter (VSI) isthe full bridge consisting of four Mosfet’s IRFP250N(Fig. 13). This topology is chosen with consideration thatit is capable to deliver a high current at low voltage ( Ismailet al., 2006). The unipolar Selective Harmonic Pulse widthModulation is adopted where switching angles are calcu-lated to eliminate from 5th to 9th order harmonics for dif-ferent modulation index ratio. The output voltage is

0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045 0.05-0.5

0

0.5

1

1.5

2

Time (s)

G v d , G i p v d z=0.7

z=1

z=0.626

z=0.313

Fig. 9. Step response of the G Vd and G id.

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40

10

20

30

40

50

60

70

80

90

100

Time (s)

P V G

V o l t a g e ( V )

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4-6

-4

-2

0

2

4

6

Time (s)

P V G C u r r e n t ( A )

(a)

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4-600

-500

-400

-300

-200

-100

0

100

200

300

Time (s)

P V G P o w e r ( W

)

(c)

(b)

Fig. 10. (a) PVG voltage; (b) PVG current; (c) PVG power for two sampling period values; T = 1 ms (blue line) and T = 50 ms (red line). (For

interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)


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composed of a low number of switching comparing withtraditional PWM output voltage. An LC filter is requiredto reduce its harmonic content and to produce a pure sinu-soidal output voltage.

Because of odd quarter-wave symmetry (Fig. 15), the dccomponent and the even harmonics are equal to zero.

V outðt Þ ¼P1

n¼1vn sinðnxt Þ where V n ¼ 4V dc

np

P N

k ¼1ð1Þk þ1

cosðnakÞ for odd n.Where N is the number of the switching angles per quar-

ter and ak is the switching angles which must satisfy:0 < a

1 <

<a

N < p/2 and n is the harmonic order.

The non-linear system of SHE PWM waveform can bewritten as follows:

cosða1Þ cosða2Þ þ cosða3Þ cosða4Þ þ cosða5Þ ¼ p

4 M

cosð3a1Þ cosð3a2Þ þ cosð3a3Þ cosð3a4Þ þ cosð3a5Þ

¼ 3p4V dc

h3


¼ 5p

4V dc

h5


¼ 7p

4V dc

h7


¼ 9p

4V dc

h9

where M ¼ h1

V dcis the modulation index which controls the

amplitude of the fundamental component h1. To eliminatethe harmonics 3, 5, 7 and 9 we put h3 = h5 = h7 = h9 = 0

To solve the switching angles, the Newton–Raphsonmethod is applied. Fig. 14 gives these angles versus modu-lation index.

Fig. 16 shows the frequency spectrum of the output volt-age. The harmonics from 3th to 9th are removed. The outputvoltage of the VSI shown in the fig. 15 has a THD = 15.5%.A simple LC filter reduces the other harmonics and the fil-tered output voltage has a THD = 1.02%. Fig. 17 shows

the output voltage of the PV system.To compute the low pass filter parameters and based on

Fig. 18, we can write:

V sn

V en

¼ 1

j1 Lf C f n2x2j ¼ 1

1 nxx0

2

where

x0 ¼ 1 ffiffiffiffiffiffiffiffiffiffi Lf C f

p and n is the harmonic order

0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8500

600

700

800

900

1000

1100

Time (s)

I r r a d i a t i o n ( W / m 2 )

Fig. 11. Irradiation variation.

0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8100

120

140

160

180

200

220

240

260

280

Time (s)

P V G p o w e r ( W )

Classical PO Algorithm

Optimised PO Algorithm

Proposed PO Algorithm

Fig. 12. Maximum power point tracking with three MPPT algorithms.

Fig. 13. Structure of the voltage source inverter.

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 110

20

30

40

50

60

70

80

90

Modulation Index (M)

F i r i n g a n g l e s ( a l p h a 1 . . . . a l p h a 5 )

Fig. 14. Switching angles versus modulation index for the SHE PWM

inverter.


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The resonance frequency of the LC filter is written asF 0 = pF where F is the fundamental frequency (50 Hz)and p is non-integer to avoid harmonic amplification. If,for example, the 11th harmonic is decreased at 1/10 of its

amplitude:

V s11

V e11

¼ 1

1 11xx0

2

¼ 1

10; F 0

F ¼

ffiffiffiffiffi11

p ¼ 3:31 ¼ p Lf C f

¼ 1

3:312 100000¼ 9:24 107

The selected values in this case are: C f = 450 lF andLf = 2 mH. For the same value of the filter inductance, toattenuate the 11th harmonic about 1/20 of its amplitude,a larger capacitor is used (900 lF) (Fig. 16b). The filtered

VSI output voltage is shown in Fig. 15.

3. Efficiency of the PV system

3.1. MPPT efficiency

The MPPT efficiency can be evaluated as (Hohm andRopp, 2003):

gMPPT ¼R t

0 P actualðt Þdt R t 0 P maxðt Þdt

where P actual(t) is the measured power of the PV generatorand P max(t) is the maximum power that the PV generatorcan produce under given irradiance and temperature.

MPPT efficiency

0.9

0.92

0.94

0.96

0.98

1

1.02

1.04

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Time (s)

E

f f i c i e n c y

Série1

Fig. 19. Efficiency of the proposed MPPT algorithm.

Fig. 16. Frequency spectrum of the VSI output voltage. (a) Before LC filter. (b) After LC filter.

0.04 0.045 0.05 0.055 0.06 0.065 0.07 0.075 0.08-30

-20

-10

0

10

20

30

Time (s)

V o l t a g e ( V )

Fig. 15. Output voltage of the VSI with SHE PWM.

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4-400

-300

-200

-100

0

100

200

300

400

Time (s)

O u

t p u t V o l t a g e

Fig. 17. Output voltage.

Lf IsnIen

Cf

tt

V VIcn

VsnVen

Fig. 18. Low pass filter for higher harmonics reduction.


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Fig. 19 presents practical results of the PVG outputpower during a period of 20 s when irradiation is 900 W/m2 and the temperature is 41 C. From Fig. 22 the maximumpower is 250 W. The PVG power is averaged by one second.The average MPPT efficiency during this time is 97.3%.

3.2. DC–DC converter efficiency

The efficiency of the DC–DC converter is estimated as:g ¼ P in P loss

P in; where P in is the input power and P loss is the

power losses. We sort them as the resistance power losses,passive element power losses and device power losses (LinLuo and Hong, 2007).

The maximum Mosfet’s (IRFP250N) losses are calcu-lated as:

P MOSFET;loss ¼ P Conduction;loss þ P Switching;loss

¼ I 2om RDS Dm þ V mp I om ðt r þ t f Þ f sþ QGate V mp f s

¼ 4:35 W:

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 850.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

C u r r e n t ( A )

Voltage (V)

397.5 W/m2; T=32.58 C

552.27 W/m2; T=36.76 C

656.32 W/m2; T=37.85 C

E=768.15 W/m2; T=40.27 C

E=907.97 W/m2; T=41.7 C

E=962.5 W/m2; T=41.88 C

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85

0

50

100

150

200

250

300

P o w e r ( W

)

Voltage (V)

E=397.5 W/m2 ; T=32.58 C

E=552.27 W/m2 ; T=36.76 CE=656.332 W/m2 ; T=37.85 CE=768.15 W/m2; T=40.27 CE=907.97 W/m2 ; T=41.7 C

E=962.5 W/m2 ; T=41.88 C

(a) (b)

Fig. 22. (a) Experimental current–voltage curves of the PVG. (b) Experimental power–voltage curves of the PVG.

0 0.05 0.1 0.15 0.2 0.25 0.3-10

0

10

20

30

40

50

60

70

80

90

Time (s)

P o w e r ( W )

DC input power

Inverter output power

Load power

Fig. 20. DC and PV inverter output power for 70 W power load.

T >

1) Ref B: 5 Volt 50 us

Fig. 23. Control signal of the buck converter.

0 0.05 0.1 0.15 0.2 0.25 0.30.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

1

Time (s)

E f f i c i e n c y

Inverter Efficiency

DC/AC stage efficiency

Fig. 21. Inverter and DC–AC stage efficiency.


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P switching = 0.023 W are very low regarding to conductionlosses. When switching losses exceeds some limits a non-dissipative turn-on turn-off snubber is used which improves

the converter efficiency due to additional energy transferredto the load as detailed in LSanots et al. (2006).

The Shottcky diode power losses are estimated as:

P diode;loss ¼ V d I om ð1 DmÞ ¼ 4:64 W :

The inductor losses are:

P Inductor;loss ¼ I 2om Rcu þ P Core ¼ 0:7837 W:

g ¼ P in P loss

P in¼ 277 ð4:35 þ 4:64 þ 0:7837Þ

277 ¼ 96:46%

3.3. DC–AC stage efficiency

The efficiency of the SHE PWM inverter and the DC–

AC stage is done by simulation using Matlab–Simulinkenvironment. For a load power of 70 W the efficiency of the inverter is 96% while the efficiency of the DC–AC con-version stage (inverter + filter + transformer) is 86%. Thesignificant losses in DC–AC conversion stage are locatedon the single phase transformer (Figs. 20 and 21).

3.4. Efficiency of the whole system

The overall efficiency of charging and discharging of alead–acid battery is about 90% (Messenger and Ventre,2004).

The efficiency of the whole system is then:

gSystem ¼ gMPPTgDCDCgBatterygDCAC

¼ 0:973 0:965 0:9 0:86 ¼ 72:67%:

4. Experimental results

A series of measurements with the photovoltaic genera-tor, available in our site, are used to plot the experimental

Fig. 24. Output voltage and current of the PVG.

T

T

>

3 >

2) Ref A: 5 Volt 5 ms3) Ref B: 5 Volt 5 ms

(a) (b)

T

>

>

1) Ref A: 5 Volt 10 us2) Ref B: 5 Volt 10 us

(c)

T

>

>

1) Ref A: 5 Volt 5 ms

2) Ref B: 5 Volt 5 ms

Fig. 25. Control signals of the VSI: (a) switches state of leg 1; (b) switches state of leg 2; (c) dead time for VSI protection.


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I–V and P–V characteristics as shown in Fig. 22a and b.From these curves the optimal PVG voltage is 57 V andthe maximum power is 277 W.

A Microcontroller PIC 16F876 controls the duty cycleof the DC/DC converter. It generates a 10 kHz PWM sig-nal with its internal PWM circuit (Fig. 23). The PWM duty

cycle is controlled by the PIC program, described later, tooptimize the power output from the photovoltaic genera-tor. The buck converter forces PVG to operate around itsMPP as illustrated in Fig. 24.

The input power from the PVG is calculated by measur-ing the voltage and current with the PIC’s A/D inputs. ThePVG voltage is sensed through a resistor divider and thePVG current is measured by a current sense resistor(1.5 mX) and a difference amplifier. The battery voltage issensed with another resistor divider and it is used to informabout the state of charge of the battery. The microcontrol-ler stops charging the battery when its voltage exceeds 28 Vto prevent its overcharge. The battery is sized to supply a

load of 70 W during a period of 8 h per day for three con-secutive cloudy days with a capacity of 200 Ah.

The VSI power topology consists of four N channelMosfet’s (IRFP250N) with low on-resistance (0.075 X)which decreases resistive losses in the VSI. The control cir-cuit of the VSI is based on a PIC 16F876 microcontroller inwhich pulses are programmed to eliminate from 3th to 9thorder harmonics for different modulation index ratio. Theinverter stops feeding the load if the battery voltage becamebelow 21 V (M = 0.8). An isolation circuit is used to isolatepulses for protection and safety between a safe and apotentially hazardous environment. An IR2110 driver is

used to control a pair of MOSFET’s connected in the sameleg using the bootstrap technique.

The control signals of the VSI are shown in Fig. 25a andb. The switching losses are decreased since the two Mos-fet’s of the leg no. 2 are switched only one time per period.To prevent the simultaneous conduction of two transistorsof the same leg, a dead time of 2 ls is used as shown inFig. 25c.

Figs. 26 and 27 present the VSI output voltage beforeand after an LC filter. The output voltage has a perfectlysine wave form, 50 Hz frequency with low harmonics.The output voltage is fed to step up transformer to amplify

it to a 220 V level. The resulting photovoltaic applicationcan feed domestic appliances and can be extended to beconnected to a single phase supply network.

5. Conclusion

In this work, a single phase photovoltaic system is sim-ulated and tested. The buck converter is used to charge abattery with new maximum power algorithm ensuring alow cost implementation, good efficiency and a stabledynamic behavior.

The VSI is controlled by a Selective Harmonic Elimi-nated PWM method which decrease inverter losses andimprove the efficiency of the overall system. The outputvoltage is easily filtered and a stable 220 V/50 Hz voltageis obtained to feed AC loads. The two converters are digi-tally controlled with a cheaper micro-controller which per-

mits easy program modification of the MPP Trackingalgorithm or inverter switches. This application can beused to cover home appliances in isolated sites and canbe extended to grid connected applications.

References

Akkaya, R., Kulaksiz, A., 2004. A microcontroller-based stand alonephotovoltaic power system for residential appliances. Applied Energy78, 419–431.

Alberto, M.P., Jorge, A., Miguel, J.P., Juan, A.M., 2009. A modularstrategy for isolated photovoltaic systems based on microcontroller.Renewable Energy 34, 1825–1832.

Enrique, J.M., Duran, E., Sidrach-de-cardona, M., Andujar, J.M., 2007.

Theoretical assessment of the maximum power point trackingefficiency of photovoltaic facilities with different converter topologies.Solar Energy 81, 31–38.

Feimia, N., Petrone, G., Spagnuolo, G., Vitelli, M., 2005. Optimization of perturb and observe maximum power point tracking method. IEEETransactions on Power Electronics 20 (4), 963–973.

Hohm, D.P., Ropp, M.E., 2003. Comparative study of maximum powerpoint tracking algorithms. Progress in Photovoltaics Research andApplications, 47–62.

Hua, C., Lin, J., Shen, C., 1998. Implementation of a DSP-controlledphotovoltaic system with peak power tracking. IEEE Transactions onIndustrial Electronics 45 (1), 99–107.

Ismail, B., Taib, S., M. Saad, A.R., Isa, M., Hadzer, C.M.S., 2006.Development of a single phase SPWM microcontroller-based inverter.In: First International Power and Energy Conference PECon 2006, pp.

437–440.

T >


Fig. 26. Output voltage of the VSI.

>


Fig. 27. Output voltage after LC filter association.


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Koutroulis, E., Kalaitzakis, K., Voulgaris, N., 2001. Development of amicrocontroller-based photovoltaic maximum point tracking controlsystem. IEEE Transactions on Power Electronics 16 (1), 46–54.

Lalouni, S., Rekioua, D., Matagne, E., 2009. Fuzzy logic controls stand-alone photovoltaic system with battery storage. Journal of PowerSources 193, 899–907.

Lin Luo, F., Hong, Y., 2007. Small signal analysis of energy factor andmathematical modeling for power DC–DC converters. IEEE Trans-actions on Power Electronics 22 (1), 69–79.

LSanots, J., Autunes, F., Chehab, A., Cruz, C., 2006. A maximum powertracker for PV systems using a high performance boost converter.Solar Energy 80, 772–778.

Maris, T.I., Kourtesi, St., Ekonomou, L., Fotis, G.P., 2007. Modeling of single-phase photovoltaic inverter. Solar Energy Materials & SolarCells 91, 1713–1725.

Messenger, Roger A., Ventre, Jerry, 2004. Photovoltaic Systems Engi-neering, second ed. pp 59–60.

Rosell, J.I., Ibanez, M., 2006. Modeling power output in photovoltaicmodules for outdoor operating conditions. Energy Conversion andManagement 47, 2424–2430.

Salas, V., Olias, A., Barrado, A., 2005. Evaluation of a new maximumpower point tracker (MPPT) applied to the photovoltaic stand-alonesystems. Solar Energy Materials & Solar Cells 87, 807–815.

Tarik Duru, H., 2006. A maximum power tracking algorithm based on

I mpp = f (P max) function for matching passive and active loads to aphotovoltaic generator. Solar Energy 80, 812–822.

Villalva, M.G., Filho, E.R., 2008. Dynamic analysis of the input-controlled buck converter fed by a photovoltaic array. Journal of Automatic and Control 19 (4), 463–474.


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