Modeling and Analysis of Photo-Voltaic Solar Panel under ...downloads.hindawi.com/journals/jre/2019/9639480.pdf · ReseachArticle Modeling and Analysis of Photo-Voltaic Solar Panel

Research ArticleModeling and Analysis of Photo-Voltaic SolarPanel under Constant Electric Load

Elias M Salilih 1 and Yilma T Birhane2

1Department of Mechanical Engineering Jigjiga university PO Box 1020 Jigjiga Ethiopia2School of Mechanical amp Industrial Engineering AA Institute of Technology-AAU Ethiopia

Correspondence should be addressed to Elias M Salilih elju99gmailcom

Received 13 December 2018 Revised 16 March 2019 Accepted 7 July 2019 Published 1 August 2019

Academic Editor Abhijeet P Borole

Copyright copy 2019 Elias M Salilih and Yilma T Birhane This is an open access article distributed under the Creative CommonsAttribution License which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

This paper presents modelling electrical performance of a typical PV panelmodule (which is Kyocera 200GT) for constantelectric loads (which are 2Ω 4Ω 6Ω and 8Ω) under weather condition of a tropical region The specific case of the city Jigjiga(935∘N428∘E) located in the Eastern region of Ethiopia is considered Electrical characteristics of the PVmodule are determinedon the basis of detailed numerical algorithm which was designed based on tested numerical technique from reviewed articlesTheoverall evaluation of the hourly variation in the electrical performance of the PV module is done by means of graphical techniquewhich determines the operating point of the PV module on voltage vs current plane for each load and the performance of the PVpanel is compared for each load The 4Ω electric load resulted in highest daily energy output of the PV panel on a daily basis for 11days of the month of January (out of 12 considered days) but in the last day it resulted in a poorer performance with respect to theother two electrical loads (ie 6Ω and 8Ω electric loads)

1 Introduction

Renewable energy systems have a significant advantage onthe ecology economy and political matters of the world [1]It is estimated that renewable energy sources could accountfor three fifths of the worldrsquos electricity market share and twofifths of the market for fuels by the middle of the 21st centuryMoreover shifting to a renewable energy economy will resultin significant environmental and other advantages which arenot quantified in economic terms

It is predicted that by 2050 carbon dioxide (CO2) emis-sions of the world will be reduced to 75 of their 1985 levelswhich will as a result of efficient use of energy and wideadoption of renewable energy usage [2]

Solar renewable energy systems are more environmen-tally friendly than conventional energy sources over elec-tricity generation The advantages of using solar energysystems fall into two main categories ecology and socio-economic issues From an ecological aspect the use of solarenergy technologies has various positive impacts that includereduction of greenhouse gas emissions (like CO2 NOx) and

of toxic gas emissions (SO2 particulates) prevention of soilpollution reduction of transmission cost and improvementin the quality of water resources [3ndash8]The advantages of solartechnologies comprise energy independency employmentopportunity creation [4 5] acceleration of electrification ofrural communities in isolated areas and diversification andsecurity (stability) of energy supply [4 5 9]

Photovoltaic systems sometimes called solar cells havefound widespread application because they are simple arecompact and have high power-to-weight ratio [10] PV cellbehaves more like a current source than a voltage sourceWhich means while the current output of the PV cellincreases with an increase in solar insolation the voltageoutput will remain constant irrespective to a variation in solarinsolation [11] and this information is valuable in sizing PVpanel for specific application

The output characteristic of PV cell depends mainly onthe solar insolation Variations in solar irradiance and celloperating temperature will nonlinearly affect the current-voltage as well as power-voltage characteristics of a PVmodule [12] In addition to the two parameters (ie solar

HindawiJournal of Renewable EnergyVolume 2019 Article ID 9639480 10 pageshttpsdoiorg10115520199639480

2 Journal of Renewable Energy

COUNTRY LOCATION MAPETHIOPIA

N

E

S

W

Figure 1 Location map of Ethiopia Source Ministry of Agriculture 2000

irradiance and cell operating temperature) the performanceof a PV module depends on its operating point on I-Vplane Forcing a PVmodule to operate near Maximum powerpoint (MPP) results in a higher efficiency Hence in orderto extract maximum power output from a PV module it canbe controlled by maximum power point tracking (MPPT)controller [13] MPPT controllers track maximum possiblepower from the Photovoltaic panel [14] Thus use of MPPTcontroller is one way of optimizing the performance of PVmodule

Several research studies which focus on optimizationof PV systems with the help of MPPT circuit have beenconducted Reshef et al [15] investigated the optimizationof solar array size with the MPPT controller for waterpumping application Singh et al [16] Lujara et al [17] andGhoneim [18] studied the significance of MPPT controlleron optimizing PV water pumping system Veeresh S G etal [19] modeled the optimization of a PV panel with MPPTcontroller whichworkswithmaximum conductancemethodHowever there is a research gap with regard to optimizationof PV panel without MPPT controller The research work inthis paper is intended to fill this gap This paper focuses onoptimization of a PV panel with help of resistance matchingtechnique

In case of directly coupled PV system the electric loadhas an effect on the performance of the PV module Per-haps resistor matching technique is one way of optimizingperformance of a PV module In this research work theeffect of electrical load on efficiency of PV module was

investigated The aim of this research is to contribute tothe optimum use of PV system by resistance or impedancematching technique As it is known some PV system canbe directly coupled to PV panel in those cases once theimpedance of the load (such as an electric motor) is knownthe technique which is demonstrated in this paper can beutilized to select a PV module for a particular load underspecific weather condition In this research a particular PVpanelmodule Kyocera 200GT is simulated under weathercondition of Jigjiga for various electric loads and whichelectric load performed well with the panel is investigated

2 Study Area

The The Federal Democratic Republic of Ethiopia (FDRE)is a noncoastal country in east of Africa surrounded to thenorth by Eritrea to the west by Sudan to the south by Kenyaand to the east by Somalia and Djibouti it lies within thegeographic coordinates from 3∘241015840 North to 14∘531015840 North and32∘421015840 East to 48∘121015840 East (see Figure 1) It covers 1120000square kilometers in nine regional states [20]

The study was carried out under weather condition ofJigjiga area located on 935∘ latitude and 428∘ longitudecoordinate

3 Modeling Characteristics of a PV Device

The objective of this section is to determine the detailedelectrical characteristics of the PV panelmodule from the

Journal of Renewable Energy 3

）ＪＰ）Ｉ

I

V

+

minus

Figure 2 Simplified or Ideal equivalent circuit of a PV cell

IＪＰ I＞

I

VRＭ

RＪ

Figure 3 Single-diode model of the theoretical PV cell andequivalent circuit of a practical PV device including the series andparallel resistances

manufacturerrsquos specification on current-voltage plane as wellas on power-voltage plane so that the output of the PV panelcan be predicted under specific electrical loads

31 IDEAL PV Cell Figure 2 showed the equivalent circuitof a theoretical PV cell while Figure 3 shows equivalentcircuit of a practical PV device including the series andparallel resistances And the basic equation from the theoryof semiconductors that mathematically describes the 119868ndash119881characteristic of the ideal PV cell is

119868 = 119868pvcell minus 1198680cell [exp ( 119902119881119886119879) minus 1] (1)

119868119889 = 1198680 [exp ( 119902119881119886119879) minus 1] (2)

where 119868pv is the current generated by the incident light (it isdirectly proportional to the Sun irradiation) 119868119889 is the Shock-ley diode equation 1198680 is the reverse saturation or leakagecurrent of the diode 119902 is the electron charge (160217646 times10minus19 C) is the Boltzmann constant (13806503times 10minus23 JK)119879 (in Kelvin) is the temperature of the 119901ndash119899 junction and 119886 isthe diode ideality constant

32 Modeling the PV Module All PV panel manufacturersprovide basic electrical parameters about their productwhichare the voltage at themaximumpower point (119881119898119901119901) the nom-inal open-circuit voltage (119881119900119888119899) the nominal short-circuitcurrent (119868119904119888119899) the current at maximum power point (119868119898119901119901)temperature coefficient for the short-circuit current (119868)temperature coefficient for the open-circuit voltage (119881) and

the maximum power output (119875maxe) Those parameters aremeasured with reference to standard test conditions (STCs)of solar irradiation and cell temperature The basic electricalparameters are not enough to investigate the performance ofa PV panel Hence it is crucial to find out detailed electricalcharacteristics which model the performance of PV panel

The basic equation (1) of the elementary PV cell does notdetermine the 119868ndash119881 characteristic of a practical PV modulePractical modules aremade of several connected PV cells andthe observation of the characteristics at the terminals of thePV modules requires the inclusion of additional parametersto the basic equation [21]

119868 = 119868pv minus 1198680 [exp(119881 + 119877119904119868119881119905119886 ) minus 1] minus 119881 + 119877119904119868119877119875 (3)

where IPV and 1198680 are the photovoltaic (PV) and saturationcurrents respectively of the modules and 119881119905 = 119873119904119879119902 isthe thermal voltage of the modules with (119873s) number of cellsconnected in series

The diode saturation current 1198680 and its dependence on thetemperature are expressed as [21]

1198680 = 1198680119899 (119879119899119879 )3 exp [119902119864119892119886 ( 1119879119899 minus

1119879)] (4)

where 119864g is the band gap energy of the semiconductor (119864g =112 eV for the polycrystalline Si at 25∘C) 1198680n is the nominalsaturation current and the value of diode ideality constant isusually between 1le a le15 and for silicon-poly material it isaround 13 [22]

1198680119899 = 119868119904119888119899exp (119881119900119888119899119886119881119905119899) minus 1 (5)

with 119881tn being the thermal voltage of 119873s series connectedcells at the nominal temperature 119879n

The light-generated current of the PV cell dependslinearly on the solar irradiation and is also influenced by thetemperature according to the following equation [22]

119868pv = (119868119875V119899 + 119868119879) 119866119866119899 (6)

where 119868119875V119899 (in amperes) is the light-generated current at thenominal condition (usually 25∘C and 1000 Wm2) ΔT =119879 minus 119879n (119879 and 119879n being the actual and nominal temperatures[in Kelvin] respectively) 119866 (watts per square meters) is theirradiation on the device surface and 119866n is the nominalirradiation

The nominal light-generated current 119868119875V119899 can beexpressed with accurate equation of the following [22]

119868119875V119899 = 119877119875 + 119877119878119877119875 119868119904119888119899 (7)

So equation (3) can be expressed with the known valuesgiven by the manufacturerrsquos data sheet (119868119904119888119899 and 119881119900119888119899) theconstants (a q Eg ) and the external influential factors of


radiation and temperature (T G) but the internal influencingparameters (Rs and Rp) are still unknown

Marcelo G et al [21] proposed an interesting method foradjusting Rs and Rp based on the fact that there is only a pairRsRp which ensures Pmaxm = Pmaxe = VmppImpp at the(Vmpp Impp) point of the IndashV curve ie the maximum powercomputed by the IndashV model of equation (3) (Pmaxm) is equalto the maximum experimental power from the datasheet(Pmaxe) at the MPP (where MPP is a maximum power pointwhich means a point where the power output of the solarpanel will be maximum)

The calculated maximum current output of the solarpanel at nominal temperature and solar radiation (at 25∘Cand1000Wm2) could be expressed using (3) as

119868119898119901119901 = 119868pvn minus 1198680119899 [exp(119881119898119901119901 + 119877119904119868119898119901119901119881119905119899119886 ) minus 1]

minus 119881119898119901119901 + 119877119904119868119898119901119901119877119875

(8)

where 119881119898119901119901 is voltage at MPP (maximum power point) andthe thermal voltage of the modules at STC 119868119898119901119901 is current atMPP

Equation (8) is arranged in such a manner to express theshunt resistor with other variables as follows

119877119875= 119881119898119901119901 + 119877119904119868119898119901119901

119868pvn minus 1198680119899 [exp ((119881119898119901119901 + 119877119904119868119898119901119901) 119881119905119899119886) minus 1] minus 119868119898119901119901(9)

From (9) RP is expressed not only in terms parameters such as119868pvn 1198680119899 and 119881119905119899 but also in the nominal maximum powerpoint (ie 119868119898119901119901 and 119881119898119901119901) and the RS hence the resultinggraph due to the pair values (ie RS and RP) will surely passthrough the nominal maximum power points With the helpof the method which was proposed byMarcelo G et al [21] adetail numerical algorithm that can determine the electricalcharacteristic of a PV panel is designed which is shown inFigure 4

4 Operating Temperature andEfficiency of PV Module

According to the equations in Section 3 (see (3) to (7)) solarirradiance intensity (G) and cell operating temperature (T)are the two crucial parameters which nonlinearly affect thecurrent-voltage as well as power-voltage characteristics of aPV module In order to model the electrical characteristicsof the PV module and its power output first it is requiredto determine the cell operating temperature (T) of the PVmodule

Standard heat transfer mechanics must be consideredto calculate the energy balance on the cell module leadingto the prediction of cell temperature At steady-state condi-tions only convection and radiation mechanisms are usuallyconsidered since they are prevalent on the conductionmechanism thatmerely transports heat toward the surfaces of

the mounting frame (especially in the case of rack-mountingfree-standing arrays) A survey of the explicit and implicitcorrelations proposed in literature linking cell temperaturewith standard weather variables and material and system-dependent properties [23]

A large number of empirical correlations exist in anumber of literatures whose application appears to be thebest and simplest Hence an equation has been chosen thatis explicit depends on easily measurable parameters and haswide applicability For variations in ambient temperature andirradiance the cell temperature (in ∘C) can be estimated quiteaccurately with the linear approximation [24]

119879 = 119879119886 + 119866119866119873119874119862119879 (119879119873119874119862119879 minus 119879119886119873119874119862119879) (10)

where 119879 is the cell operating temperature of the PV modulewhich determines the performance of the PV panel alongwith solar radiation intensity 119866 and 119879119873119874119862119879 is nominaloperating cell temperature which is a reference temperaturefor particular PVmodule to calculate cell operating tempera-ture (119879) and it is given by the manufacturerrsquos specificationThe nominal cell temperature (119879119873119874119862119879) is defined as thetemperature of the cell at the conditions of the nominalterrestrial environment (NTE) [24] Solar irradiance 119866119873119874119862119879=800Wm2 ambient temperature119879119886119873119874119862119879 = 20∘C and averagewind speed 1 ms Hence equation (10) can be expressed asfollows

119879 = 119879119886 + 1198668001198821198982 (119879119873119874119862119879 minus 20∘) (11)

The solar module power conversion efficiency can be given as

120578 = 119875119900119906119905119866 times 119860119898 = 119868 times 119881119866 times 119860119898 (12)

where 119868 and 119881 are current and voltage output of the PVmodule corresponding to solar intensity 119866 and cell temper-ature 119879 and 119860119898 is solar panel module area (the dimensionof KC200GT solar module can be found on manufacturerrsquosspec)

5 Methodology

A methodology implemented in this paper is a graphicaltechnique which is used to find an operating point of a PVpanel

When a resistive load is connected to a PV module theoperating point of the module (which is current and voltageoutput) is decided by intersection of the IndashV characteristicscurve of the PVmodule (which is modeled in Section 3) andthe IndashV characteristics of the load curve (which is determinedfrom the famous simple electrical correlation ie V=IR)According to the electrical correlation (ie V=IR) the slopeof the load curve (which is straight line) is expressed as 1Ron I-V plane The operating point will depend on the value ofR (see Figure 5 for visual understanding) [12]

Figure 5 depicts that for smaller resistive load as radiationintensity increases the operating point will move continu-ously towards the maximum power point (MPP) of each


Start

Input data of the manufacturerrsquosspecifications

(０ＧＲ６Ｉ＝Ｈ）Ｍ＝Ｈ＋）＋６）ＧＪＪＭ)Input constants

qkaEＡ

Input STD conditions(25∘C 1000Wm2)

Initialize (２Ｍ =0) for iterationCalculate ）ＩＨ from eq(5)

according to eq(7) ）ＪＰＨ=）Ｍ＝Ｈ for ２Ｍ=0Calculate a value for ２Ｊ with eq(9)

By taking ２Ｍ２Ｊ and ６ＧＪＪ as input to eq(3) calculate ）ＧＪＪＧ

multiply the calculated ）ＧＪＪＧ with ６ＧＪＪ to get ０ＧＲＧ

Calculate Error=０ＧＲＧ-０ＧＲ

ENDYES

Errorlt001

No

Make a 0001 increment to２Ｍ

Calculate ）ＪＰＨ with eq(7) by taking incremented ２Ｍ and２Ｊ as input

Calculate a new value for ２Ｊ with eq(9)From a vectormatrix for voltage (V) from 0 to ６Ｉ＝Ｈ

By taking ２Ｍ２Ｊ and vector V as input to eq(3) calculateVectormatrix I for current

Perform array multiplication to V and I to get arraymatrixfor power P

Select maximum value from vector P (P(max))Calculate Error=０(ＧＲ)-０ＧＲ

Figure 4 Algorithm of computer program used to model a PV panel

curve as it is pointed by points A B and C hence theefficiency will improve continuously In the contrary forhigher resistive load the operating point will not movecontinuously towards the MPP rather first it moves towardsthe MPP and then it moves away from theMPP as pointed bypoints D E and F Hence the efficiency of the PV panel willfirst improve then it drops as radiation intensity continuouslyincreases

6 Results and Discussion

Here in this paper we are modeling a particular PV module(which is Kyocera 200 GT) under constant electric loadand weather condition of Jigjiga Hence annual temperatureand global radiation (ie pyranometer) data from Ethiopian

National Metrology Agency is provided which is measured in15 minutesrsquo difference

61 Output Result of the Computer Program for Selected PVModule A PV module is chosen as reference example formodeling because it is well-suited to traditional applicationsof photovoltaics which is KC200GT

The proposed model was tested using manufacturer datasheets Figures 6 and 7 show different simulations for aKyocera family solar module using the information providedby the manufacturer KYOCERA for the products KC200GT

The I-V curves (which are shown in Figure 6) depict thesimulation results for current versus voltage characteristics ofthe photovoltaic modules with the operating cell temperatureof 25∘C and the effective irradiance level changing (ie


9

8

7

6

5

4

3

2

1

0

curr

ent (

Am

p)

0 5 10 15 20 25 30voltage (Volt)

Figure 5 Effect of resistive load on cell operating point

0 5 10 15 20 25 30

VminusI characteristics at 25 degrees Cent

voltage (Volt)

1000 Wm2

800 Wm2

600 Wm2

200 Wm2

400 Wm2

0

1

2

3

4

5

6

7

8

9

curr

ent (

Am

p)

Figure 6 IndashV model curves of the KC200GT solar module atdifferent irradiations 25∘C

200Wm2 400Wm2 600Wm2 800Wm2 and 1000Wm2)The figure showed the increase in short-circuit current ofthe PV panel with increase in radiation intensity Similarlythe P-V curves (of Figure 7) show power versus voltagecharacteristics at different effective irradiance level and 25∘Ccell temperature It showed the increase in maximum poweroutput of the PV panel with increase in radiation intensity Itcan be validated that I-V curve on Figure 6 and P-V curve ofFigure 7 are very similar to the I-V and P-V curve plotted byMarcelo G et al [21]

Figure 8 show simulation results for I-V curve of thephotovoltaic module KC200GT under different temperaturesof operation (ie 25∘C 50∘C and 75∘C) with the irradiationlevel at 1000Wm2 The figure depicts insignificant rise inshort-circuit current while a significant drop in open-circuitvoltage of the PV panel with increase in cell temperatureFigure 9 shows the adverse effect of temperature to themaximum power supplied by the photovoltaic module undera constant irradiance level of 1000Wm2

0 5 10 15 20 25 30

PminusV characteristics at 25 degrees Cent

voltage (Volt)

1000Wm2

800Wm2

600Wm2

400Wm2

200Wm2

020406080

100120140160180200

pow

er (W

att)

Figure 7 PndashV model curves of the KC200GT solar module atdifferent irradiations 25∘C

0 5 10 15 20 25 30

voltage (Volt)25 degreesminuscent50 degreesminuscent75 degreesminuscent

0

1

2

3

4

5

6

7

8

9

curr

ent (

Am

p)

Figure 8 IndashV model curves of the KC200GT solar module atdifferent temperature 1000Wm2

0 5 10 15 20 25 300

20406080

100120140160180200

voltage (Volt)

Pow

er (W

att)

25 degreesminuscent50 degreesminuscent75 dgreesminuscent

Figure 9 PndashV model curves of the KC200GT solar module atdifferent temperature 1000Wm2


0

200

400

600

800

1000

1200Total radiation on the tilted panel

radi

atio

n in

Wm

2

Aprminus1stJanminus1st

Julminus1stOctminus1st

6 8 10 12 14 16 18 204Time (hours)

Figure 10 Hourly variation of global radiation on optimally tiltedpanel

62 Hourly Variation of Global Radiation on a Tilted PanelFlat plate photovoltaic systems (like KC200GT) do not usefocusing devices so all three componentsmdashbeam diffuseand reflectedmdashcan contribute to energy collected hence wehave to use the global radiation in the analysis of moduletemperature as well as power generation [25]

Total radiation intensity (ie global radiation) is mea-sured with pyranometer which measures radiation intensityon horizontal surface However facing a collector toward theequator (for our case Jigjiga is at the Northern Hemispherethis means facing it south) and tilting it up at an angleequal to the local latitude is a good rule-of-thumb for annualperformance [25] hence it will be convincing to tilt oursystem to its optimum angle (ie at an angle equal to thelocal latitude) and to perform the analysis based on the tiltingangle Figure 10 shows hourly variation of global or totalradiation on the optimally tilted panel

63 Hourly Variation of PV Module Operating TemperatureEquation (11) can model operating temperature of a PVmodule fromNOCT and environmental variables (ie ambi-ent temperature and radiation intensity) Figure 11 showsvariation in operating temperature of the PV module for thethe considered days (ie January 1st April 1st July 1st andOctober 1st)

64 Hourly Variation of Electric Performance of the PVModule This paper is concerned with modelling of a typicalPV module (ie Kyocera 200GT) at constant electric loadand under a weather condition of Jigjiga Figures 12 13 14and 15 depict hourly variation in voltage current poweroutput and conversion efficiency of the PV module for thefirst dates of selected months under 2Ω electric load

For the 2Ω electric load as radiation increases all theelectrical characteristics (ie voltage current and poweroutput as well as efficiency) will increase continuously anddecrease when radiation intensity decreases Because asradiation increases the operating point jumps from smaller I-V curve to higher I-V Also as it is mentioned in Section 5 for

0

10

20

30

40

50

60

70hourly cell temperature variation

Janminus1stAprminus1st


6 8 10 12 14 16 18 204Time (Hours)

Tem

pera

ture

(∘C)

Figure 11 Hourly variation of PV module operating temperature



6 8 10 12 14 16 18 204time in 24 hour format

02468

10121416

volta

ge o

utpu

t in

Volt

18

Figure 12 Hourly variation of voltage output of Kyocera 200GT PVmodule for 2Ω resistance

smaller electric loads the operating point will continuouslymove towards maximum power point hence the efficiencywill improve continuously (refer to Figure 5)

65 Effect of Electric Load on Performance of the PV PanelFigures 16 and 17 depict variation in electric performance ofKC 200GT PVmodule for different electric load (ie 2Ω 4Ω6Ω and 8Ω electric resistance) and under weather conditionof January 1st

According to Figure 16 the 4Ω electric load caused adesirable efficiency It resulted in a higher operating efficiencyof the PV module for duration of the time at which the solarradiation intensity is the highest This claim can be furtherinspected with Figure 17 (which shows hourly variation inpower output of the PV module for different electric load)As it is depicted with the figure the 4Ω electric load resultedin the highest power output from 10AM to 3PM time intervalthan other electric loads the reason behind the scenario isthat the PV panel operates relatively nearer to its maximumpower point in the time interval when it is connected to the




0123456789

curr

ent o

utpu

t in

amp


Figure 13 Hourly variation of current output of Kyocera 200GT PVmodule for 2Ω resistance




0

50

100

150

Pow

er in

Wat

t

Figure 14 Hourly variation of power output of Kyocera 200GT PVmodule for 2Ω resistance

4Ω Then the 6Ω electric load has a better power output inthe time interval next to the 4Ω electric load

In addition Figure 16 shows a u shape efficiency curve for6Ω and 8Ω electric load for the time interval where radiationintensity is highest This result asserts the concept stated inSection 5 that for higher resistive load the efficiency of thePV panel drops as the operating point moves beyond themaximum power point

To judge the better performance of the PVmodule on thebasis of electric load the power output does not give us a clearpicture If an electric load gave as a better power output atsome time interval it does not mean that it performed betterthrough all the time Hence to have a clear picture we have tocompare the energy output of the PVmodule for each electricload The following formula can help in the analysis of thedaily energy output of the PV module It calculates the areasunder the curves of Figure 17

119864119900119906119905119901119906119905 =2345sum000

119875119900119906119905 times Δ119905 (13)



0123456789

10

effici

ency

(100

)


Figure 15 Hourly variation of efficiency of Kyocera 200GT PVmodule for 2Ω resistance

2minus ohm4minus ohm

6minus ohm8minusohm

0

2

4

6

8

10

12

14

effici

ency

(100

)


Figure 16 Hourly variation of efficiency of Kyocera 200GT PVmodule for different electric load under weather condition ofJanuary 1st

where 119864119900119906119905119901119906119905 is daily energy output of the PV panel under anelectric load 119875119900119906119905 is calculated power output and Δ119905 is timeinterval at which calculations are performed

Figure 18 depicts daily energy output of the PVmodule forthe first 12 days of the month of January under 2Ω 4Ω 6Ωand 8Ω electric loads According to the figure the 4Ω electricload resulted in the highest energy output among all otherelectric loads for the first 10 days of the month In January11th it had the same amount of energy output as that of the6Ω electric load but in January 12th it is over taken by both6Ω and 8Ω electric load The 2Ω electric load had the lowestenergy output than all other electric loads for all mentioneddays of the monthThe 2Ω electric load had the lowest energyoutput than all other electric load for all mentioned days ofthe month

From this result it can be concluded that all environ-mental condition will not favor a single electric load all thetime but we can compare the annual performance of thePV module to judge which electric load will optimize theoperation of the PV panel


2minusohm4minusohm

6minusohm8minusohm

020406080

100120140160180

Pow

er in

Wat

t


Figure 17 Hourly variation in power output of Kyocera 200GTPV module for different electric load under weather condition ofJanuary 1st

1 2 3 4 5 6 7 8 9 10 11 12

0405060708091

11

Ener

gy (K

WH

)

The first 12 days of January

2minusohm4minusohm

6minusohm8minusohm

Figure 18 Variation in daily energy output of Kyocera 200GT PVmodule for the first 12 days of January under different electric load

7 Conclusion and Recommendations

Most of previous research papers on solar PV system areconcerned only with modelling the electrical characteristicsof the PV system using a single-diode electrical modeland investigated the effect of environmental parameterswhich are radiation intensity and cell temperature on theperformance of PV systems In case of directly coupled PVsystem the electric load has also an effect on the performanceof the PV system Perhaps resistor matching technique is oneway of optimizing performance of a PV system In this studybeside the environmental parameters the effect of electricalloads on the performance of the PV system is investigated onreal environmental parameter

Based on tasted iterative technique (which is recom-mended by previous research papers) the modelling of aPV panel is performed The hourly variation in electricalperformance of a typical PV panel is simulated under realweather conditions The performance of the PV panel iscompared at different electrical loads The 4Ω electric loadresulted in the best operating performance of the PV panel ona daily basis for 11 days of the month of January (out of 12 days

on which measurements are taken for the month) but in thelast day it resulted in the poorer performance with respect tothe other two electrical loads (ie 6Ω and 8Ω electric loads)Hence it is concluded that every weather condition does notfavor a single load all the time

Data Availability

The Meteorological data used to support the findings of thisstudy are included within the supplementary informationfile(s)

Conflicts of Interest

The authors declare that they have no conflict of interestregarding to the publication of this paper

Acknowledgments

The authors would like to thank Jigjiga University for sup-porting this research

Supplementary Materials

Description of Supplementary Material A supplementarymaterial attached in this research is an Excel file for annualsolar radiation and temperature data provided by EthiopianNational Meteorology agency which is used in the research(Supplementary Materials)

References

[1] A A W Sayigh Renewable Energy Global Progress andExamples in Renewable Energy Wren 2001

[2] T B Johansson H Kelly A K N Reddy and R H WilliamsldquoRenewable fuels and electricity for a growing world economydefining and achieving the potentialrdquo Energy Studies Reviewvol 4 no 3 1993

[3] A Abu-Zour and S Riffat ldquoEnvironmental and economicimpact of a new type of solar louvre thermal collectorrdquo Inter-national Journal of Low-Carbon Technologies vol 1 no 3 pp217ndash227 2006

[4] W Charters ldquoDeveloping markets for renewable energy tech-nologiesrdquo Journal of Renewable Energy vol 22 no 1-3 pp 217ndash222 2001

[5] K Jagoda R Lonseth A Lonseth and T Jackman ldquoDevelop-ment and commercialization of renewable energy technologiesin Canada An innovation system perspectiverdquo Journal ofRenewable Energy vol 36 no 4 pp 1266ndash1271 2011

[6] J M Cansino M D P Pablo-Romero R Roman and RYniguez ldquoTax incentives to promote green electricity anoverview of EU-27 countriesrdquo Energy Policy vol 38 no 10 pp6000ndash6008 2010

[7] R E H Sims H-H Rogner and K Gregory ldquoCarbon emissionand mitigation cost comparisons between fossil fuel nuclearand renewable energy resources for electricity generationrdquoEnergy Policy vol 31 no 13 pp 1315ndash1326 2003

[8] T J Dijkman and R M J Benders ldquoComparison of renewablefuels based on their land use using energy densitiesrdquo Renewableamp Sustainable Energy Reviews vol 14 no 9 pp X3148ndash31552010


[9] P D Lund ldquoEffects of energy policies on industry expansion inrenewable energyrdquo Journal of Renewable Energy vol 34 no 1pp 53ndash64 2009

[10] M A Eltawil and D V K Samuel ldquoVapor compressioncooling system powered by solar PV array for potato storagerdquoAgricultural Engineering International e CIGR E-JournalManuscript vol IX 2007

[11] E F Mba J L Chukwuneke C H Achebe and P C OkolieldquoModeling and simulation of a photovoltaic powered vaporcompression refrigeration systemrdquo Journal of Information Engi-neering and Applications vol 2 no 10 2012

[12] Z Salameh Renewable Energy System Design Elsevier Aca-demic Press 1st edition 2014

[13] S S Chandel M Nagaraju Naik and R Chandel ldquoReviewof solar photovoltaic water pumping system technology forirrigation and community drinking water suppliesrdquo Renewableamp Sustainable Energy Reviews vol 49 article no 4338 pp 1084ndash1099 2015

[14] G Li Y Jin M Akram and X Chen ldquoResearch and currentstatus of the solar photovoltaic water pumping system ndash Areviewrdquo Renewable amp Sustainable Energy Reviews vol 79 pp440ndash458 2017

[15] B Reshef H Suehrcke and J Appelbaum ldquoAnalysis of aphotovoltaic water pumping systemrdquo in Proceedings of the 8thConvention on Electrical And Electronics Engineers in Israel pp7-8 1995

[16] B Singh C P Swamy and B Singh ldquoAnalysis and developmentof a low-cost permanent magnet brushless DC motor drive forPV-array fed water pumping systemrdquo Solar Energy Materials ampSolar Cells vol 51 no 1 pp 55ndash67 1998

[17] N K Lujara J D van Wyk and P N Materu ldquoLoss modelsof photovoltaic water pumping systemsrdquo in Proceedings of the5th IEEE AFRICON Conference (Electrotechnical Services forAfrica) vol 2 pp 965ndash970 IEEE 1999

[18] A A Ghoneim ldquoDesign optimization of photovoltaic poweredwater pumping systemsrdquo Energy Conversion and Managementvol 47 no 11-12 pp 1449ndash1463 2006

[19] V S Gonal and G S Sheshadri ldquoSolar energy optimizationusing MPPT controller by maximum conductance methodrdquo inProceedings of the 7th IEEEPower India International Conference(PIICON) IEEE India 2016

[20] A Mengistu Agricultural Profile of Ethiopia from FAOhttpwwwfaoorgagagpdocpastureforagehtm

[21] V Singla and V K Garg ldquoModeling of solar photovoltaicmodule amp effect of insolation variation using MATLABSIMU-LINKrdquo International Journal of Advanced Engineering Technol-ogy 2013

[22] M G Villalva J R Gazoli and E R Filho ldquoComprehensiveapproach to modeling and simulation of photovoltaic arraysrdquoIEEE Transactions on Power Electronics vol 24 no 5 2009

[23] R Araneo U Grasselli and S Celozzi ldquoAssessment of a prac-tical model to estimate the cell temperature of a photovoltaicmodulerdquo International Journal of Energy and EnvironmentalEngineering 2014

[24] A Luqu and S Hegedus ldquoHandbook of Photovoltaic Scienceand Engineerinrdquo in Sussex PO19 8SQ pp 296-297 John Wileyamp Sons Ltd West Sussex UK 2003

[25] G M Masters Electric Renewable and Efficient Power SystemJohn Wiley amp Sons 1st edition 2004

Hindawiwwwhindawicom Volume 2018

Nuclear InstallationsScience and Technology of

TribologyAdvances in


International Journal of

AerospaceEngineeringHindawiwwwhindawicom Volume 2018

OpticsInternational Journal of


Antennas andPropagation



Power ElectronicsHindawiwwwhindawicom Volume 2018

Advances in

CombustionJournal of


Journal of


Renewable Energy

Acoustics and VibrationAdvances in


EnergyJournal of


Hindawiwwwhindawicom

Journal ofEngineeringVolume 2018


International Journal ofInternational Journal ofPhotoenergy


Solar EnergyJournal of


Shock and Vibration


Advances in Condensed Matter Physics


RotatingMachinery



High Energy PhysicsAdvances in


Active and Passive Electronic Components

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

Submit your manuscripts atwwwhindawicom


COUNTRY LOCATION MAPETHIOPIA

N

E

S

W

Figure 1 Location map of Ethiopia Source Ministry of Agriculture 2000

irradiance and cell operating temperature) the performanceof a PV module depends on its operating point on I-Vplane Forcing a PVmodule to operate near Maximum powerpoint (MPP) results in a higher efficiency Hence in orderto extract maximum power output from a PV module it canbe controlled by maximum power point tracking (MPPT)controller [13] MPPT controllers track maximum possiblepower from the Photovoltaic panel [14] Thus use of MPPTcontroller is one way of optimizing the performance of PVmodule

Several research studies which focus on optimizationof PV systems with the help of MPPT circuit have beenconducted Reshef et al [15] investigated the optimizationof solar array size with the MPPT controller for waterpumping application Singh et al [16] Lujara et al [17] andGhoneim [18] studied the significance of MPPT controlleron optimizing PV water pumping system Veeresh S G etal [19] modeled the optimization of a PV panel with MPPTcontroller whichworkswithmaximum conductancemethodHowever there is a research gap with regard to optimizationof PV panel without MPPT controller The research work inthis paper is intended to fill this gap This paper focuses onoptimization of a PV panel with help of resistance matchingtechnique

In case of directly coupled PV system the electric loadhas an effect on the performance of the PV module Per-haps resistor matching technique is one way of optimizingperformance of a PV module In this research work theeffect of electrical load on efficiency of PV module was

investigated The aim of this research is to contribute tothe optimum use of PV system by resistance or impedancematching technique As it is known some PV system canbe directly coupled to PV panel in those cases once theimpedance of the load (such as an electric motor) is knownthe technique which is demonstrated in this paper can beutilized to select a PV module for a particular load underspecific weather condition In this research a particular PVpanelmodule Kyocera 200GT is simulated under weathercondition of Jigjiga for various electric loads and whichelectric load performed well with the panel is investigated

2 Study Area

The The Federal Democratic Republic of Ethiopia (FDRE)is a noncoastal country in east of Africa surrounded to thenorth by Eritrea to the west by Sudan to the south by Kenyaand to the east by Somalia and Djibouti it lies within thegeographic coordinates from 3∘241015840 North to 14∘531015840 North and32∘421015840 East to 48∘121015840 East (see Figure 1) It covers 1120000square kilometers in nine regional states [20]

The study was carried out under weather condition ofJigjiga area located on 935∘ latitude and 428∘ longitudecoordinate

3 Modeling Characteristics of a PV Device

The objective of this section is to determine the detailedelectrical characteristics of the PV panelmodule from the


）ＪＰ）Ｉ

I

V

+

minus


IＪＰ I＞

I

VRＭ

RＪ





119868119889 = 1198680 [exp ( 119902119881119886119879) minus 1] (2)








1198680 = 1198680119899 (119879119899119879 )3 exp [119902119864119892119886 ( 1119879119899 minus

1119879)] (4)


1198680119899 = 119868119904119888119899exp (119881119900119888119899119886119881119905119899) minus 1 (5)



119868pv = (119868119875V119899 + 119868119879) 119866119866119899 (6)



119868119875V119899 = 119877119875 + 119877119878119877119875 119868119904119888119899 (7)







minus 119881119898119901119901 + 119877119904119868119898119901119901119877119875

(8)



119877119875= 119881119898119901119901 + 119877119904119868119898119901119901








119879 = 119879119886 + 119866119866119873119874119862119879 (119879119873119874119862119879 minus 119879119886119873119874119862119879) (10)


119879 = 119879119886 + 1198668001198821198982 (119879119873119874119862119879 minus 20∘) (11)




5 Methodology





Start



qkaEＡ







ENDYES

Errorlt001

No
















9

8

7

6

5

4

3

2

1

0

curr

ent (

Am

p)

0 5 10 15 20 25 30voltage (Volt)


0 5 10 15 20 25 30


voltage (Volt)

1000 Wm2

800 Wm2

600 Wm2

200 Wm2

400 Wm2

0

1

2

3

4

5

6

7

8

9

curr

ent (

Am

p)




0 5 10 15 20 25 30


voltage (Volt)

1000Wm2

800Wm2

600Wm2

400Wm2

200Wm2

020406080

100120140160180200

pow

er (W

att)


0 5 10 15 20 25 30


0

1

2

3

4

5

6

7

8

9

curr

ent (

Am

p)


0 5 10 15 20 25 300

20406080

100120140160180200

voltage (Volt)

Pow

er (W

att)




0

200

400

600

800

1000


radi

atio

n in

Wm

2



6 8 10 12 14 16 18 204Time (hours)







0

10

20

30

40

50

60




6 8 10 12 14 16 18 204Time (Hours)

Tem

pera

ture

(∘C)





02468

10121416

volta

ge o

utpu

t in

Volt

18








0123456789

curr

ent o

utpu

t in

amp






0

50

100

150

Pow

er in

Wat

t





119864119900119906119905119901119906119905 =2345sum000

119875119900119906119905 times Δ119905 (13)



0123456789

10

effici

ency

(100

)




6minus ohm8minusohm

0

2

4

6

8

10

12

14

effici

ency

(100

)







2minusohm4minusohm

6minusohm8minusohm

020406080

100120140160180

Pow

er in

Wat

t



1 2 3 4 5 6 7 8 9 10 11 12

0405060708091

11

Ener

gy (K

WH

)


2minusohm4minusohm

6minusohm8minusohm






Data Availability




Acknowledgments




References







































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018



）ＪＰ）Ｉ

I

V

+

minus


IＪＰ I＞

I

VRＭ

RＪ





119868119889 = 1198680 [exp ( 119902119881119886119879) minus 1] (2)








1198680 = 1198680119899 (119879119899119879 )3 exp [119902119864119892119886 ( 1119879119899 minus

1119879)] (4)


1198680119899 = 119868119904119888119899exp (119881119900119888119899119886119881119905119899) minus 1 (5)



119868pv = (119868119875V119899 + 119868119879) 119866119866119899 (6)



119868119875V119899 = 119877119875 + 119877119878119877119875 119868119904119888119899 (7)







minus 119881119898119901119901 + 119877119904119868119898119901119901119877119875

(8)



119877119875= 119881119898119901119901 + 119877119904119868119898119901119901








119879 = 119879119886 + 119866119866119873119874119862119879 (119879119873119874119862119879 minus 119879119886119873119874119862119879) (10)


119879 = 119879119886 + 1198668001198821198982 (119879119873119874119862119879 minus 20∘) (11)




5 Methodology





Start



qkaEＡ







ENDYES

Errorlt001

No
















9

8

7

6

5

4

3

2

1

0

curr

ent (

Am

p)

0 5 10 15 20 25 30voltage (Volt)


0 5 10 15 20 25 30


voltage (Volt)

1000 Wm2

800 Wm2

600 Wm2

200 Wm2

400 Wm2

0

1

2

3

4

5

6

7

8

9

curr

ent (

Am

p)




0 5 10 15 20 25 30


voltage (Volt)

1000Wm2

800Wm2

600Wm2

400Wm2

200Wm2

020406080

100120140160180200

pow

er (W

att)


0 5 10 15 20 25 30


0

1

2

3

4

5

6

7

8

9

curr

ent (

Am

p)


0 5 10 15 20 25 300

20406080

100120140160180200

voltage (Volt)

Pow

er (W

att)




0

200

400

600

800

1000


radi

atio

n in

Wm

2



6 8 10 12 14 16 18 204Time (hours)







0

10

20

30

40

50

60




6 8 10 12 14 16 18 204Time (Hours)

Tem

pera

ture

(∘C)





02468

10121416

volta

ge o

utpu

t in

Volt

18








0123456789

curr

ent o

utpu

t in

amp






0

50

100

150

Pow

er in

Wat

t





119864119900119906119905119901119906119905 =2345sum000

119875119900119906119905 times Δ119905 (13)



0123456789

10

effici

ency

(100

)




6minus ohm8minusohm

0

2

4

6

8

10

12

14

effici

ency

(100

)







2minusohm4minusohm

6minusohm8minusohm

020406080

100120140160180

Pow

er in

Wat

t



1 2 3 4 5 6 7 8 9 10 11 12

0405060708091

11

Ener

gy (K

WH

)


2minusohm4minusohm

6minusohm8minusohm






Data Availability




Acknowledgments




References







































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018







minus 119881119898119901119901 + 119877119904119868119898119901119901119877119875

(8)



119877119875= 119881119898119901119901 + 119877119904119868119898119901119901








119879 = 119879119886 + 119866119866119873119874119862119879 (119879119873119874119862119879 minus 119879119886119873119874119862119879) (10)


119879 = 119879119886 + 1198668001198821198982 (119879119873119874119862119879 minus 20∘) (11)




5 Methodology





Start



qkaEＡ







ENDYES

Errorlt001

No
















9

8

7

6

5

4

3

2

1

0

curr

ent (

Am

p)

0 5 10 15 20 25 30voltage (Volt)


0 5 10 15 20 25 30


voltage (Volt)

1000 Wm2

800 Wm2

600 Wm2

200 Wm2

400 Wm2

0

1

2

3

4

5

6

7

8

9

curr

ent (

Am

p)




0 5 10 15 20 25 30


voltage (Volt)

1000Wm2

800Wm2

600Wm2

400Wm2

200Wm2

020406080

100120140160180200

pow

er (W

att)


0 5 10 15 20 25 30


0

1

2

3

4

5

6

7

8

9

curr

ent (

Am

p)


0 5 10 15 20 25 300

20406080

100120140160180200

voltage (Volt)

Pow

er (W

att)




0

200

400

600

800

1000


radi

atio

n in

Wm

2



6 8 10 12 14 16 18 204Time (hours)







0

10

20

30

40

50

60




6 8 10 12 14 16 18 204Time (Hours)

Tem

pera

ture

(∘C)





02468

10121416

volta

ge o

utpu

t in

Volt

18








0123456789

curr

ent o

utpu

t in

amp






0

50

100

150

Pow

er in

Wat

t





119864119900119906119905119901119906119905 =2345sum000

119875119900119906119905 times Δ119905 (13)



0123456789

10

effici

ency

(100

)




6minus ohm8minusohm

0

2

4

6

8

10

12

14

effici

ency

(100

)







2minusohm4minusohm

6minusohm8minusohm

020406080

100120140160180

Pow

er in

Wat

t



1 2 3 4 5 6 7 8 9 10 11 12

0405060708091

11

Ener

gy (K

WH

)


2minusohm4minusohm

6minusohm8minusohm






Data Availability




Acknowledgments




References







































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018



Start



qkaEＡ







ENDYES

Errorlt001

No
















9

8

7

6

5

4

3

2

1

0

curr

ent (

Am

p)

0 5 10 15 20 25 30voltage (Volt)


0 5 10 15 20 25 30


voltage (Volt)

1000 Wm2

800 Wm2

600 Wm2

200 Wm2

400 Wm2

0

1

2

3

4

5

6

7

8

9

curr

ent (

Am

p)




0 5 10 15 20 25 30


voltage (Volt)

1000Wm2

800Wm2

600Wm2

400Wm2

200Wm2

020406080

100120140160180200

pow

er (W

att)


0 5 10 15 20 25 30


0

1

2

3

4

5

6

7

8

9

curr

ent (

Am

p)


0 5 10 15 20 25 300

20406080

100120140160180200

voltage (Volt)

Pow

er (W

att)




0

200

400

600

800

1000


radi

atio

n in

Wm

2



6 8 10 12 14 16 18 204Time (hours)







0

10

20

30

40

50

60




6 8 10 12 14 16 18 204Time (Hours)

Tem

pera

ture

(∘C)





02468

10121416

volta

ge o

utpu

t in

Volt

18








0123456789

curr

ent o

utpu

t in

amp






0

50

100

150

Pow

er in

Wat

t





119864119900119906119905119901119906119905 =2345sum000

119875119900119906119905 times Δ119905 (13)



0123456789

10

effici

ency

(100

)




6minus ohm8minusohm

0

2

4

6

8

10

12

14

effici

ency

(100

)







2minusohm4minusohm

6minusohm8minusohm

020406080

100120140160180

Pow

er in

Wat

t



1 2 3 4 5 6 7 8 9 10 11 12

0405060708091

11

Ener

gy (K

WH

)


2minusohm4minusohm

6minusohm8minusohm






Data Availability




Acknowledgments




References







































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018



9

8

7

6

5

4

3

2

1

0

curr

ent (

Am

p)

0 5 10 15 20 25 30voltage (Volt)


0 5 10 15 20 25 30


voltage (Volt)

1000 Wm2

800 Wm2

600 Wm2

200 Wm2

400 Wm2

0

1

2

3

4

5

6

7

8

9

curr

ent (

Am

p)




0 5 10 15 20 25 30


voltage (Volt)

1000Wm2

800Wm2

600Wm2

400Wm2

200Wm2

020406080

100120140160180200

pow

er (W

att)


0 5 10 15 20 25 30


0

1

2

3

4

5

6

7

8

9

curr

ent (

Am

p)


0 5 10 15 20 25 300

20406080

100120140160180200

voltage (Volt)

Pow

er (W

att)




0

200

400

600

800

1000


radi

atio

n in

Wm

2



6 8 10 12 14 16 18 204Time (hours)







0

10

20

30

40

50

60




6 8 10 12 14 16 18 204Time (Hours)

Tem

pera

ture

(∘C)





02468

10121416

volta

ge o

utpu

t in

Volt

18








0123456789

curr

ent o

utpu

t in

amp






0

50

100

150

Pow

er in

Wat

t





119864119900119906119905119901119906119905 =2345sum000

119875119900119906119905 times Δ119905 (13)



0123456789

10

effici

ency

(100

)




6minus ohm8minusohm

0

2

4

6

8

10

12

14

effici

ency

(100

)







2minusohm4minusohm

6minusohm8minusohm

020406080

100120140160180

Pow

er in

Wat

t



1 2 3 4 5 6 7 8 9 10 11 12

0405060708091

11

Ener

gy (K

WH

)


2minusohm4minusohm

6minusohm8minusohm






Data Availability




Acknowledgments




References







































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018



0

200

400

600

800

1000


radi

atio

n in

Wm

2



6 8 10 12 14 16 18 204Time (hours)







0

10

20

30

40

50

60




6 8 10 12 14 16 18 204Time (Hours)

Tem

pera

ture

(∘C)





02468

10121416

volta

ge o

utpu

t in

Volt

18








0123456789

curr

ent o

utpu

t in

amp






0

50

100

150

Pow

er in

Wat

t





119864119900119906119905119901119906119905 =2345sum000

119875119900119906119905 times Δ119905 (13)



0123456789

10

effici

ency

(100

)




6minus ohm8minusohm

0

2

4

6

8

10

12

14

effici

ency

(100

)







2minusohm4minusohm

6minusohm8minusohm

020406080

100120140160180

Pow

er in

Wat

t



1 2 3 4 5 6 7 8 9 10 11 12

0405060708091

11

Ener

gy (K

WH

)


2minusohm4minusohm

6minusohm8minusohm






Data Availability




Acknowledgments




References







































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018





0123456789

curr

ent o

utpu

t in

amp






0

50

100

150

Pow

er in

Wat

t





119864119900119906119905119901119906119905 =2345sum000

119875119900119906119905 times Δ119905 (13)



0123456789

10

effici

ency

(100

)




6minus ohm8minusohm

0

2

4

6

8

10

12

14

effici

ency

(100

)







2minusohm4minusohm

6minusohm8minusohm

020406080

100120140160180

Pow

er in

Wat

t



1 2 3 4 5 6 7 8 9 10 11 12

0405060708091

11

Ener

gy (K

WH

)


2minusohm4minusohm

6minusohm8minusohm






Data Availability




Acknowledgments




References







































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018



2minusohm4minusohm

6minusohm8minusohm

020406080

100120140160180

Pow

er in

Wat

t



1 2 3 4 5 6 7 8 9 10 11 12

0405060708091

11

Ener

gy (K

WH

)


2minusohm4minusohm

6minusohm8minusohm






Data Availability




Acknowledgments




References







































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018
































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018














Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018


Documents

Modeling and Analysis of Photo-Voltaic Solar Panel under ...downloads.hindawi.com/journals/jre/2019/9639480.pdf · ReseachArticle Modeling and Analysis of Photo-Voltaic Solar Panel