Performance Evaluation of a Micro Off-Grid Solar Energy … · 1.05 1.26 1.47 1.68 1.89 2.10 W Hour of Day F :PVpoweroutput,.kWall-PV(optimum). 0 20406080 100 0 4 8 12 16 Frequency

Research ArticlePerformance Evaluation of a Micro Off-Grid SolarEnergy Generator for Islandic Agricultural Farm OperationsUsing HOMER

EdwardM Querikiol 1 and Evelyn B Taboada2

1Engineering Graduate Program and Department of Electrical and Electronics Engineering School of EngineeringUniversity of San Carlos Talamban Cebu City 6000 Philippines2BioProcess Engineering and Research Center and Department of Chemical Engineering School of EngineeringUniversity of San Carlos Talamban Cebu City 6000 Philippines

Correspondence should be addressed to Edward M Querikiol emquerikiolusceduph

Received 26 March 2018 Revised 29 October 2018 Accepted 13 November 2018 Published 2 December 2018

Academic Editor Jayanta Mondol

Copyright copy 2018 Edward M Querikiol and Evelyn B Taboada This is an open access article distributed under the CreativeCommons Attribution License which permits unrestricted use distribution and reproduction in any medium provided theoriginal work is properly cited

A study was conducted to evaluate the performance of a 15 kW micro off-grid solar power generator in a 2-hectare area of a 23-hectare agricultural farm located in Camotes Island Cebu Philippines (10∘3941015840 N 124∘2091015840 E)The area requires at least 3000 litersof water every day to irrigate its plantation of passion fruit and dragon fruit however there is no water source within the immediatevicinity that can support such requirement A 12 horsepower water pump was installed to provide the required irrigation A 15kW solar photovoltaic (PV) system consisting of 6 units of 250-watts solar PV panel with corresponding 6 units of 200 ampere-hour deep cycle batteries managed by a 3-kW industrial grade inverter provided the power for the water pump and supplied forthe electricity demand of the farm The actual energy usage of the farm was measured from the built-in monitoring of the chargecontroller and the installed system was analyzed to determine its efficiency in meeting the actual load demand The HOMERoptimization tool was used to determine the optimal configuration for the micro off-grid system based on the actual load demandSimulation results showed that the optimum configuration that could supply the actual load is a 263 kW all-PV system with 8kWh batteries Sensitivity analysis was done to consider (1) possible increase in electrical load when the current plantation expandseither in progression or outright to its full-scale size of 23 hectares and (2) variations in fuel cost This study can be considered agood model in assessing renewable energy needs of farms in the country which can be operationalized for agricultural purposes

1 Introduction

11 The Agricultural Sector and Its Challenges Agricultureplays a pivotal role in various key issues we face todayConsidered as one of the main sources of income overa third of the worldwide population engage in farmingfor livelihood [1] Agriculture is seen to facilitate povertyreduction in developing countries where investments in thesector have seen an increase [2] to foster the global agendaon food security and improved nutrition [3] and to cultivateeconomic growth and development [4 5] In the Philippines32 of the population is currently employed in the farmingsector making it one of the primary livelihoods of thecountry [6] The sector is critical in the countryrsquos economic

development by providing food rawmaterials products andsurplus labor [7]

However the agricultural sector faces several challengesThe volatility of prices of farm produce sustainability ofagricultural practices vulnerability of the sector to climatechange and the competition on land use are just some ofthe problems encountered Agricultural water and irrigationmanagement is one of its notable issues Water scarcityand other environmental stresses prove to be a challengefor agriculture in Jining China [8] whereas the optimalallocation of water for irrigation in the drier regions of Ghanawas pointed out as a concern [9] The divergence of waterusage in wetlands and agricultural farms in various regions

HindawiJournal of Renewable EnergyVolume 2018 Article ID 2828173 9 pageshttpsdoiorg10115520182828173

2 Journal of Renewable Energy

in China was also revealed as a challenge in a study by Zou etal [10]

In the Philippines agriculture is dominant in the ruralareas [7] where access to water is a challenge In a 2004report only 44 of the total irrigable area in the countryis irrigated primarily due to insufficient water hindering thecountry frommeeting the increasing demand for agriculturalproducts [11] These rural areas also have very limited accessto electricity deterring installation of water pumps to helpwith irrigation The scarcity of water and the limited access toelectricity lead most farmers to resort to other sources to helpthem irrigate their farms In most cases building a small PVsystem to meet the pumping requirements of the land is thesensible solution [12] Effective sizing of the components isalso important to ensure a reliable adequate and economicaldesign [13ndash17]

12 The Role of Renewable Energy in Agriculture Water is anessential resource in agriculture However limited access towater in most farmlands in the Philippines proves to be achallenge to farmers in rural areas where most irrigable landsare located Renewable energy mostly coming from solarphotovoltaic (PV) systems is a solution that could solve suchproblems on limited resources Numerous studies have beenmade where renewable energy is used to help in irrigationproblems in the agricultural setting

In Western Serbia a group of researchers were able todevise amethod of efficiently irrigating a raspberry plantationby testing a properly sized solar array and water pump takinginto account the depth of well characteristic of the cropand climate of the area An accurate sizing of a 579 Wpphotovoltaic (PV) system to a 10-ha raspberry plantationwas established irrigating the orchard efficiently The sizingmethod was applicable only to farms of the same arealatitude and climatic conditions [18] Case studies fromKenya Morocco Chile and India suggested that irrigationaccounts for up to 60 of the production costs in farmsas they consume around 2m3 to 10m3 of water per hectareper day The solution to this problem was to use solar-powered irrigation spurring an intensification of agriculturalproduction in these countries [19] Applications of solar-powered pumping in Turkey were more advanced as theyused sun-tracking photovoltaic panels to draw maximumpower from the sun which fully automated the wateringsystem using a microcontroller solenoid valves and soilmoisture sensors The area being irrigated is 08 hectaresThere was no indication of the actual yield of the PVsystem and the actual amount of water being drawn out perday since this study was primarily aimed at integrating allthe components to function as a stand-alone solar-poweredautomatic irrigation system [20] A battery-coupled solarwater pumping systemwas implemented inMalaysia with theaim of efficiently monitoring the irrigation of strawberry andrubber plantations that need frequent wateringThe highlightof this study was the use of SCADA (supervisory control anddata acquisition) control system to integrate 2 soil moisturesensors 2 water level sensors as inputs and 2 solenoid valvesas outputs The system successfully reduced issues on powerconsumption system interface and maintenance The term

battery-coupled means that when the sunrsquos energy is absent ordiminished there is still a source of power from the batterythereby irrigation is not compromised [21]

Most off-grid setups for irrigation systems are one-sourcesystems where photovoltaic energy source is used Howeverthere has to be some alternative to solar power consideringthat weather conditions vary from day to day and powerproduction may not be optimized on a daily basis Thus itbecomes necessary to simulate other forms of energy sourceand add them to the energy mix allowing for farm ownersto decide which is the best package for their farm Tropicalislandic climate in the Philippines is unpredictable comparedto Dunkirk Francersquos oceanic weather and Montana USArsquoscontinental one so there is a need to take weather varia-tions into account [22] HOMER is software that allows forsuch simulation and provides hybrid optimization modelsfor electric renewables It was developed by the NationalRenewable Energy Laboratory (NREL) to optimizemicrogriddesign from village power to island electrification to evenlarge power consumers that connect to the grid It alsoevaluates if staying connected to the grid is economicallyadvantageous than going off-grid [23] HOMER is being usedas a techno-economic optimization tool while comparinggrid-connected stand-alone and diesel-powered homestead[24] Incorporating photovoltaics wind power and biomassinto hybrid systems can also be an option for farms withadditional thermal energy demands for heating and cooking[25] Such optimization tools can simulate overall systemperformance and do economic optimizations with criteriathat include net present cost and the cost of energy [18ndash20] Many off-grid [20ndash26] and on-grid systems [27ndash33]use HOMER as a tool to further scale up the capacity ofa system and with varied energy use A tabulated hybridtechnology analysis using HOMER was created to show thevarious applications the technology adapted and the supplyduration It was found out that the hybrid setup is usedmainlyfor household purposes but not in the agriculture sector [34]HOMER can also play a big part in assessing the feasibility oflarge scale PV on-grid systems [35]

13 The Focus of the Study This paper evaluated the perfor-mance of an installed 15 kW off-grid microgrid solar PVsystem in terms of its ability to meet the irrigation and otheroperational requirements of a 2-hectare plantation located inCamotes Island Cebu Philippines The study aimed to (1)determine the ability of the system tomeet the actual demandof the farm (2) determine the appropriate sizing required forthe actual demand through HOMERPro simulation and (3)perform a sensitivity analysis in HOMERPro varying loadsand fuel cost to assess system robustness

2 Method and Materials

21 Method Figure 1 presents the flow of the case study Anevaluation was conducted on a 15 kW solar PV installationin a 2-hectare farm using the actual energy usage obtainedfrom the built-in monitoring of the charge controller Themeasured load was then used and simulated throughHOME-RPro to determine the optimum configuration that could

Journal of Renewable Energy 3

Evaluationof design

using actual energy usage

Determine optimal

configuration at current use

Sensitivity analysis

varying fuel cost

varying load

profiles

HOMERPro

Figure 1 Research flow

meet the actual load demand Sensitivity analysis was doneto test the robustness of the system when input variableswere varied Cases in islands and remote areas consideredfuel cost component cost energy source and electricity costas uncertain parameters [36] while a study on a stand-alonehybrid energy system in a remote island in China consideredload variations in the sensitivity analysis [37] The sensitivityanalysis for this islandic case study however considered onlythe variations in load and fuel costThe current all-PV systemonly supplies electricity for the 2-hectare plantation and itis necessary to determine the ideal design when the farmwill expand its operations The island is also susceptible tofluctuations in diesel cost due to its location This study didnot consider any other renewable energy resources exceptsolar energy

22 Materials

221 Photovoltaic Power System The photovoltaic powersystem is composed of an inverter solar photovoltaic panelssolar charge controller and battery The components used inthe actual installation were used in the simulation

The off-grid photovoltaic inverter used is a SAKO puresine wave inverter with battery charger and a built-in liquidcrystal display (LCD) for easy monitoring This is an indus-trial grade inverter capable of withstanding fluctuations in thebattery current and has a low-battery protection It functionsboth as an automatic voltage regulator as well as an inverterThe wide input voltage range is suitable for the unpredictableisland weather [38]

The 6 series-connected PV panels are Renesola Virtus IIwith 250 watts maximum output power taken at 1000 Wm2solar irradiance The datasheet by Renvu Solar EquipmentDistribution (Renesola) stated that the efficiency of the panelswill vary from 158 to 160 with irradiance ranging from200Wm2 to 1000Wm2The PVmaterial and workmanshiphas a 10-year guarantee while the linear output power shouldbe constant up to 25 years [39]

The solar charge controller is an Epsolar etracer serieswith a maximum current capacity of 60 amperes It has adata logging capability of up to 450 days The data for batteryvoltage PV voltage battery current energy generated stateof charge battery state charging state ambient and batterytemperature are supported by a timestamp every 20 minutes[40]

A solar-powered street light was also installed to illu-minate the farm during night time (see Figure 2) In thiscontext solar street lighting should be used instead of grid-connected luminaries in cities as they are more sustainable[41 42] This Camotes systemrsquos 48V setup is almost similarto Thailandrsquos off-grid experiment on 4 regions althoughThailandrsquos setup suffers from shading due to trees on the2 regions while the Camotes farm setup is free of growingtrees as the PV panels are on a 10-meter hill [43] Ifcrops are tomatoes the PV panels need to be as close tothe ground as tomatoes needs as much sunshine as well[44]

222 Water Pump The 1-phase AC water pump is a Goulds12 hp convertible jet pump initially a shallow-well pump butfitted with deep-well accessories (see Figure 3) A DC pumpwas not used here like the one used in a small farm in Egypt[45] as a DC pump is dependent on the availability of thesun in order to pump water An existing 3-phase AC waterpump is even more efficient running on solar PV operatingthe maximum power point tracking method [46]TheMPPTmethod can also be used for off-grid lighting system [47]and on typical DC solar home systems on-grid off-grid andhybrid systems as well all governed by the standard DINEN50530 [48]

The well required 3 lengths of 20-foot 2-inch pipes toreach the water table Operating at a working pressure of 30psi it can pump out 600 liters per hourThe aim here is just toregard the ACwater pump as an ordinary electrical appliancethat can be turned on and off anytime


(a) (b)

Figure 2 Solar street lamps for (a) farm lighting and (b) the 6-panel PV installation

Figure 3 Water pump at work in Camotes farm Cebu Philippines

223 Weather Data In the HOMER Pro Microgrid analysistool the meteorological data were taken from a solar windand temperature database (NASA Surface Meteorology andSolar Energy database) and were made available in thesimulation page The coordinates of the Camotes installation(10∘3941015840 N 124∘2091015840 E) served as input to the said tool toconsider exact location as solar irradiation can vary from onecity to another [49]

224 Simulation Simulation and sensitivity analysis weredone using the HOMERPro software The software is thelatest bundled pack with advanced storage multiyear andMATLAB link option An optimizer returns for the optimumnet present cost and cost of energy The load profile from thefarmhousewas inputted as a single electrical load averaging at535 kWhday throughout the year Though water pumping iscommonly referred to as a deferrable load in the actual farmoperation it was considered as just an electrical appliance thatcan be turned on and off whenever water was needed either

for irrigation or for household consumption The solar panelused the figures from the installed PV panels with 04∘Cas temperature effects on power The nominal operating celltemperature was 45∘C and its efficiency at standard testconditions is 154 In the economic analysis diesel fuel pricewas set at US$09liter Nominal discount rate was set at of4 8 and 16The expected inflation rate was 3 and theproject lifetime was set at 25 years Annual capacity shortagewas set at 5

23 Research Environment The off-grid PV system wasinstalled in a dragon fruit and passion fruit farm located inCamotes Island Cebu Philippines Although the total farmarea is approximately 23 hectares the initial cultivated landis around 1 hectare for each fruit Passion fruit stems areguided up to a trellis with supports that are equidistant toeach other while dragon fruits are from the cactus family andare separately planted and supported by a concrete post (seeFigure 4)

3 Results and Discussion

31 Load Profile of the Farm Electricity consumption of the2-hectare farm was mainly attributed to irrigation light-ing and household appliances like mobile phone chargerstelevision and radio The actual energy usage of the farmwas obtained from the built-in monitoring of the chargecontroller The actual system generated a total of 433357kWh on its first 81 days of operation or an average of 535kWhday Figure 5 shows the daily energy produced over theobservation period

Of the total production for the 81 days 1987 kWh chargedthe battery while simultaneously powering an electrical loadof 234657 kWh An average of 2453 kWhday was consumedto charge the battery bank Figure 6 shows the daily energygenerated to charge the battery as seen by the solar chargecontroller


Figure 4 Passion fruit (left) and dragon fruit (right) plantations in Camotes Cebu

02468

270

920

1517

01

2016

210

120

1625

01

2016

290

120

1602

02

2016

060

220

1611

02

2016

150

220

1619

02

2016

2016

-02-

hellip27

02

2016

020

320

1606

03

2016

260

520

1630

05

2016

030

620

1603

06

2016

040

620

1608

06

2016

kWh

Energy Generated (kWh) as seen by the solar charge controller

Figure 5 Daily energy generated (81-day observation)

01234

270

920

1517

01

2016

210

120

1625

01

2016

290

120

1602

02

2016

060

220

1611

02

2016

150

220

1619

02

2016

2016

-02-

hellip27

02

2016

020

320

1606

03

2016

260

520

1630

05

2016

030

620

1603

06

2016

040

620

1608

06

2016

kWh


Figure 6 Daily energy generated to charge the battery (81-dayobservation)

32 Evaluation of Installed 15kW Solar PV Microgrid The15kWp PV system was used to power (1) the water pumpusing a 12 horsepower convertible jet pump for irrigation(2) the installed solar street light and (3) various householdenergy requirements of the farm The system capital costfor the existing system was roughly US$2885 Although thesystem was running to meet irrigation and other operationalrequirements of the farm simulation shows that the systemis not at optimum configuration Table 1 shows the feasibleconfigurations per HOMERPro simulation for the currentload demand of the farm

The optimum configuration with the lowest net presentcost at US$ 8405 and lowest cost of energy (COE) at US$0202 is an all-PV 263 kW with 8 kWh battery installationThis configuration produces 3869 kWhyear with excess

electricity at 402 and unmet electrical load of 361Figure 7 shows the PV power output of the system

Autonomy of the optimum system is 215 hours Thebatteryrsquos nominal capacity is 801 kWh with usable nominalcapacity of 480 kWh Figure 8 shows the state of charge ofthe battery

The optimal system is compared economically withoperating only a 11 kW diesel generator set which has thelowest initial capital cost among the feasible configurationsThe results showed that the optimal system has a return ofinvestment of 389 internal rate of return of 448 anddiscounted payback of 218 years

33 Sensitivity Analysis Sensitivity analysis was done on theoptimum design varying the load and the diesel fuel costThe load considered did not include the energy generationfor battery charging and was projected to increase with theincrease of land area to farm Load variations were computedat increases of 20 40 60 80 and 100 of land area(see Figure 9)

The initial diesel fuel cost was US$ 09liter Variations indiesel fuel cost were computed considering price fluctuationsof diesel in the Philippines for a one-year period from Octo-ber 25 2017 to October 16 2018 [50] The median (096)maximum (1662)minimum (-598) and average (086)percentages were applied to vary the costs Figure 10 showsthe percentages of oil price fluctuations for the periodconsidered

The analysis was run at 4 8 and 16 discount ratesFigure 11 shows the results of the analysis when discount rateis set at 4 As both load demand and diesel cost increaseall-PV installation will still be optimal

The same is true when discount rate is set at 8 where anall-PV installation would still be optimal at varied loads anddiesel cost Figure 12 shows the result of the analysis

However when the nominal discount rate is set at 16optimum configuration when the farm expands to its fulloperational size of 23 hectares given that diesel price is lowis a combination of diesel generator and solar PV All-PVwould still be optimal at 20 40 60 and 80 increasein land area at different values for diesel cost and for full-sizeoperations at higher diesel costs Figure 13 shows the result


Table 1 Feasible configurations at 535 kWhday load demand

PV Generator Battery Converter COE NPC Initial Capital263kW 8kWh 0810kW US$ 0202 US$ 8405 US$ 3255259kW 110kW 7kWh 0849kW US$ 0225 US$ 9696 US$ 3238

110kW 5kWh 0798kW US$ 0556 US$ 23999 US$ 1080525kW 110kW US$ 0679 US$ 29320 US$ 3921

110kW US$ 0806 US$ 34793 US$ 14078

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0

6

12

18

24PV Output

000021042063084105126147168189210

kWH

our o

f Day

Figure 7 PV power output 263kW all-PV (optimum)

0 20 40 60 80 1000

4

8

12

16Frequency Histogram

State of Charge ()

Freq

uenc

y (

)

(a)


20406080

100

SOC

()

Monthly Statisticsmaxdaily highmeandaily lowmin

(b)


6

12

18

24Battery Bank State of Charge

3044587286100

Hou

r of D

ay

(c)

Figure 8 State of charge of battery 263 kW all-PV (optimum)

05

101520253035

5 ha 10 ha 14 ha 18 ha 23 ha

kWh

Figure 9 Projected load variations at increments in land area

4 Conclusions

A 15kW solar PV was installed in a 2-hectare farm inCamotes to power its 12 horsepower water pump forirrigation and to supply electricity for its operations and

minus01minus005

0005

01015

02

Oct

25

201

7N

ov 8

201

7D

ec 1

3 2

017

Jan

3 2

018

Jan

17 2

018

Jan

31 2

018

Feb

14 2

018

Feb

27 2

018

Mar

14

201

8M

ar 2

8 2

018

Apr 1

8 2

018

May

2 2

018

May

18

201

8Ju

ne 1

3 2

018

June

22

201

8Ju

ly 3

201

8Ju

y 25

201

8Au

g 8

201

8Au

g 22

201

8Se

p 5

201

8Se

p 19

201

8O

ct 3

201

8O

ct 1

6 2

018

Figure 10 Oil price fluctuation (October 25 2017 to October 162018)

other household requirements The measured energy usageper the built-in monitoring of the solar charge controlleraveraged 535 kWhday HOMERPro was used to determine


10 15 20 25 30085

090

095

100

105Optimal System Type

Electric Load 1 (kWhd)

System TypesPVBatteryFixed

Interest Rate = 1

Die

sel P

rice

($L

)

Figure 11 Sensitivity analysis at 4 nominal discount rate

10 15 20 25 30085

090

095

100

105 Optimal System Type



Interest Rate = 48

Die

sel P

rice

($L

)


10 15 20 25 30085

090

095

100



System TypesPVBatteryPVGenBatteryFixed

Interest Rate = 126

Die

sel P

rice

($L

)



the optimal configuration that would satisfy the actual energyusage of the farm Simulation results showed that the optimalconfiguration is a 263kW PV and 8kWh battery installationwith COE of US$0202 and net present cost of US$8405Sensitivity analysis varying the load demand and diesel fuelprices indicated that at 4 and 8 discount rate an all-PVsystem would remain optimal while at 16 discount rate ahybrid system of PV and diesel generator would be optimalat higher diesel costs while an all-PV system would remainoptimal at lower diesel costsThe results of the study providedfor a goodmodel that can be used in evaluating the renewableenergy needs of farms in the country

5 Recommendations

The case study considered only solar energy as the renewableenergy resource Adding other sources of renewable energy todetermine optimal configurations and to test the sensitivity ofthe optimal system is recommended for future studies Theload demand profile of the farm was averaged to simplifycalculations Classification of loads and determining howthese loads differ on a daily basis are recommended forfurther studies Irrigation and the management of waterresource on the farm could also be considered

Data Availability

Research data will be provided upon request

Conflicts of Interest

The authors declare that they have no conflicts of interest

Acknowledgments

This research was made possible through the support of theGreen Enviro-Management Systems Inc (GEMS) the Uni-versity of San Carlos and the DOST-Engineering Researchand Development for Technology (ERDT) for the researchand scholarship grant

References

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[2] D Cervantes-Godoy and J Dewbre ldquoEconomic Importance ofAgriculture for Poverty ReductionrdquoOECDProgramme on FoodAgriculture and Fisheries Paper vol 27 no 23 2010

[3] A D Jones and G Ejeta ldquoA new global agenda for nutritionand health The importance of agriculture and food systemsrdquoBulletin of theWorld HealthOrganization vol 94 no 3 pp 228-229 2016

[4] D Byerlee A de Janvry and E Sadoulet ldquoAgriculture forDevelopment Toward a New Paradigmrdquo Annual Review ofResource Economics vol 1 no 1 pp 15ndash31 2009

[5] L Christiaensen L Demery and J Kuhl ldquoThe (evolving) roleof agriculture in poverty reduction-An empirical perspectiverdquo

Journal of Development Economics vol 96 no 2 pp 239ndash2542011

[6] Philippine Statistics Authority Philippine Agriculture In Fig-ures 2016

[7] C F Habito andRM Briones ldquoPhilippine Agriculture over theYearsrdquo in Policies to Strengthen Productivity in the Philippines p38 2005

[8] Y Xie D Xia L Ji and G Huang ldquoAn inexact stochastic-fuzzyoptimization model for agricultural water allocation and landresources utilization management under considering effectiverainfallrdquo Ecological Indicators vol 92 pp 301ndash311 2018

[9] D Acheampong B B Balana F Nimoh and R C AbaidooldquoAsssesing the effectiveness and impact of agricultural watermanagement interventions the case of small reservoirs innorthern GhanardquoAgricultural Water Management vol 209 pp163ndash170 2018

[10] Y Zou X Duan Z Xue et al ldquoWater use conflict between wet-land and agriculturerdquo Journal of Environmental Managementvol 224 pp 140ndash146 2018

[11] P F Barba ldquoThe Challengesrdquo in Water Resources Managementin the Philippines 2004

[12] P Persad N Sangster E Cumberbatch and A RamkhalawanldquoInvestigating the Feasibility of Solar Powered Irrigation forFood Crop Production A Caroni Caserdquo J Assoc Prof EngTrinidad Tobago vol 40 no 2 pp 61ndash65 2011

[13] E N Abdullah AlShemmary L M Kadhom and W J Al-Fahham ldquoInformation technology and stand-alone solar sys-tems in tertiary institutionsrdquo in Proceedings of the TerraGreen2013 International Conference on Advancements in RenewableEnergy and Clean Environment pp 369ndash379 Lebanon Febru-ary 2013

[14] F Cuadros F Lopez-Rodrıguez A Marcos and J Coello ldquoAprocedure to size solar-powered irrigation (photoirrigation)schemesrdquo Solar Energy vol 76 no 4 pp 465ndash473 2004

[15] T Sujatha G B Devidas T Sankarappa and S M Hanagodi-math ldquoDielectric and AC conductivity studies in alkali dopedvanadophosphate glassesrdquo International Journal of EngineeringScience vol 2 no 7 pp 302ndash309 2013

[16] Y-O N Udoakah E E Nta I E Okon and U E AkpabioldquoDesign of a 1 kva PV system for electrical laboratory in facultyof engineering University of Uyo Nigeriardquo in Proceedings of the4th IEEE Global Humanitarian Technology Conference GHTC2014 pp 1ndash5 USA October 2014

[17] V C Sontake and V R Kalamkar ldquoSolar photovoltaic waterpumping system - A comprehensive reviewrdquo Renewable ampSustainable Energy Reviews vol 59 pp 1038ndash1067 2016

[18] B Gajic Z Tomic and Z Sredojevic ldquoa Simple MethodEstimates and Economic Indicatorsrdquo Agricultural economicsvol 38 no 60 pp 223ndash236 2013

[19] J Sass ldquoRelevance of Solar-Driven Irrigationrdquo Systems forAgricultural Development with Reference to Small-Scale FarmingCommunities p 23 2015

[20] M Dursun and S Ozden ldquoApplication of Solar PoweredAutomatic Water Pumping in Turkeyrdquo International Journal ofComputer and Electrical Engineering pp 161ndash164 2012

[21] A I Abdelkerim M M Eusuf M J Salami A Aibinu and MA Eusuf ldquoDevelopment of Solar Powered Irrigation SystemrdquoIOP Conference Series Materials Science and Engineering vol53 p 012005 2013

[22] P-L Poirion An Algorithm to Improve the Renewable EnergyProduction Alternative Renewable Energy


[23] R Kempener O LavagneD dOrtigue J Skeer S Vinci andDGielen ldquoRenewable Energy Systems Status andMethodologicalIssuesrdquo 2015

[24] M P McHenry ldquoA technical economic and greenhouse gasemission analysis of a homestead-scale grid-connected andstand-alone photovoltaic and diesel systems against electricitynetwork extensionrdquo Journal of Renewable Energy vol 38 no 1pp 126ndash135 2012

[25] M Frisk ldquoSimulation and Optimization of a Hybrid RenewableEnergy System for application on a Cuban farmrdquo Simulationand Optimization of a Hybrid Renewable Energy System forapplication on a Cuban farm 2017

[26] V A Ani and B Abubakar ldquoFeasibility analysis and simulationof integrated renewable energy system for power generation ahypothetical study of rural health clinicrdquo Journal of Energy vol2015 Article ID 802036 7 pages 2015

[27] A K Pradhan S K Kar and M K Mohanty ldquoOff-GridRenewable Hybrid Power Generation System for a PublicHealth Centre in Rural Villagerdquo Int J Renew Energy Res vol6 no 1 2016

[28] A H Al-Hamdani A F Dawood K N Abdullah and SM Mousaui ldquoOptimal sizing of photovoltaic systems usingHOMER for Baghdadrdquo International Journal of Computationand Applied Sciences vol 1 no 2 pp 1ndash6 2016

[29] T Givler and P Lilienthal ldquoUsing HOMER Software NRELrsquosMicropower Optimization Model to Explore the Role of Gen-sets in Small Solar Power Systems Case Study Sri Lankardquo TechRep NRELTP-710-36774 2005

[30] P Gilman and P Lilienthal ldquoMicropower SystemModelingwithHomerrdquo in in Integration of Alternative Sources of Energy F AFarret and and M G Simoes Eds pp 379ndash418 John WileySons Inc 2006

[31] K E Okedu and R Uhunmwangho ldquoOptimization of renew-able energy efficiency using HOMERrdquo International Journal ofRenewable Energy Research vol 4 no 2 pp 421ndash427 2014

[32] S Treado ldquoThe effect of electric load profiles on the perfor-mance of off-grid residential hybrid renewable energy systemsrdquoEnergies vol 8 no 10 pp 11120ndash11138 2015

[33] R SahuM Digbijoy M Tanushree and P Nishant ldquoDesigningand Study Standalone Hybrid Energy System For TechnicalInstitutesrdquo Tech Rep 2016

[34] R Sen and S C Bhattacharyya ldquoOff-grid electricity generationwith renewable energy technologies inIndia An application ofHOMERrdquo Journal of Renewable Energy vol 62 pp 388ndash3982014

[35] M S Adaramola ldquoViability of grid-connected solar PV energysystem in Jos Nigeriardquo International Journal of Electrical Poweramp Energy Systems vol 61 pp 64ndash69 2014

[36] S Bahramara M P Moghaddam and M R HaghifamldquoOptimal planning of hybrid renewable energy systems usingHOMER A reviewrdquo Renewable amp Sustainable Energy Reviewsvol 62 pp 609ndash620 2016

[37] T Ma H Yang and L Lu ldquoA feasibility study of a stand-alonehybrid solarndashwindndashbattery system for a remote islandrdquo AppliedEnergy vol 121 pp 149ndash158 2014

[38] Shenzhen Kingsako Electronics Co Ltd ldquoSako Pure Sine WaveInverter SKN-M Series specs 05-5000VArdquo 2018

[39] Renvu Solar Equipment Distribution Renesola Virtus II Mod-ule

[40] Beijing Epsolar Technology Company eTracer series NetworkMaximum Power Point Tracking Solar Charge Controller

[41] TheResearch Center on Renewable Energies (CENER) ldquoImple-mentation of micro-grids with high penetration of renewableenergiesrdquoOPTIMAGRID SOE2P2E322 pp 1ndash125 2012

[42] A Gonzalez J-R Riba and A Rius ldquoOptimal sizing of ahybrid grid-connected photovoltaic-wind-biomass power sys-temrdquo Sustainability vol 7 no 9 pp 12787ndash12806 2015

[43] T Jinayim NMungkung andN Kasayapanand ldquoPerformanceanalysis of off-grid solar photovoltaic electrification systemsfor sustainable ICTs development Field study in 4 regions ofThailandrdquo in Proceedings of the 6th International Conference onApplied Energy ICAE 2014 pp 1925ndash1928 Taiwan June 2014

[44] M A Hossain ldquoLife cycle cost and feasibility of solar pumpsfor sustainable irrigation in Bangladeshrdquo in Proceedings of thein International Workshop on Solar-Powered Irrigation Systems(SPIS) in developing countries no May p 26 2015

[45] NM KhattabMA Badr E T El ShenawyH H Sharawy andM S Shalaby ldquoFeasibility of Hybrid Renewable Energy WaterPumping System for a Small Farm in Egyptrdquo Int J Appl EngRes vol 11 no 11 pp 7406ndash7414 2016

[46] V S Korpale D H Kokate and S P Deshmukh ldquoPerformanceAssessment of Solar Agricultural Water Pumping Systemrdquo inProceedings of the 5th International Conference on Advances inEnergy Research ICAER 2015 pp 518ndash524 India December2015

[47] Z Y He and H Chen ldquoIntegrated solar controller for solarpowered off-grid lighting systemrdquo in Proceedings of the 1stInternational Conference on Smart Grid and Clean EnergyTechnologies ICSGCE 2011 pp 570ndash577 China September 2011

[48] M Muller R Brundlinger O Arz W Miller J Schulz andG Lauss ldquoPV-off-grid hybrid systems and MPPT charge con-trollers a state of the art analysesrdquo in Proceedings of the 2013ISES Solar World Congress SWC 2013 pp 1421ndash1430 MexicoNovember 2013

[49] G Liu ldquoSustainable feasibility of solar photovoltaic poweredstreet lighting systemsrdquo International Journal of Electrical Poweramp Energy Systems vol 56 pp 168ndash174 2014

[50] Department of Energy Oil Monitor 2017 httpswwwdoegovphoil-monitor

Hindawiwwwhindawicom Volume 2018

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Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

Submit your manuscripts atwwwhindawicom


in China was also revealed as a challenge in a study by Zou etal [10]

In the Philippines agriculture is dominant in the ruralareas [7] where access to water is a challenge In a 2004report only 44 of the total irrigable area in the countryis irrigated primarily due to insufficient water hindering thecountry frommeeting the increasing demand for agriculturalproducts [11] These rural areas also have very limited accessto electricity deterring installation of water pumps to helpwith irrigation The scarcity of water and the limited access toelectricity lead most farmers to resort to other sources to helpthem irrigate their farms In most cases building a small PVsystem to meet the pumping requirements of the land is thesensible solution [12] Effective sizing of the components isalso important to ensure a reliable adequate and economicaldesign [13ndash17]

12 The Role of Renewable Energy in Agriculture Water is anessential resource in agriculture However limited access towater in most farmlands in the Philippines proves to be achallenge to farmers in rural areas where most irrigable landsare located Renewable energy mostly coming from solarphotovoltaic (PV) systems is a solution that could solve suchproblems on limited resources Numerous studies have beenmade where renewable energy is used to help in irrigationproblems in the agricultural setting

In Western Serbia a group of researchers were able todevise amethod of efficiently irrigating a raspberry plantationby testing a properly sized solar array and water pump takinginto account the depth of well characteristic of the cropand climate of the area An accurate sizing of a 579 Wpphotovoltaic (PV) system to a 10-ha raspberry plantationwas established irrigating the orchard efficiently The sizingmethod was applicable only to farms of the same arealatitude and climatic conditions [18] Case studies fromKenya Morocco Chile and India suggested that irrigationaccounts for up to 60 of the production costs in farmsas they consume around 2m3 to 10m3 of water per hectareper day The solution to this problem was to use solar-powered irrigation spurring an intensification of agriculturalproduction in these countries [19] Applications of solar-powered pumping in Turkey were more advanced as theyused sun-tracking photovoltaic panels to draw maximumpower from the sun which fully automated the wateringsystem using a microcontroller solenoid valves and soilmoisture sensors The area being irrigated is 08 hectaresThere was no indication of the actual yield of the PVsystem and the actual amount of water being drawn out perday since this study was primarily aimed at integrating allthe components to function as a stand-alone solar-poweredautomatic irrigation system [20] A battery-coupled solarwater pumping systemwas implemented inMalaysia with theaim of efficiently monitoring the irrigation of strawberry andrubber plantations that need frequent wateringThe highlightof this study was the use of SCADA (supervisory control anddata acquisition) control system to integrate 2 soil moisturesensors 2 water level sensors as inputs and 2 solenoid valvesas outputs The system successfully reduced issues on powerconsumption system interface and maintenance The term

battery-coupled means that when the sunrsquos energy is absent ordiminished there is still a source of power from the batterythereby irrigation is not compromised [21]

Most off-grid setups for irrigation systems are one-sourcesystems where photovoltaic energy source is used Howeverthere has to be some alternative to solar power consideringthat weather conditions vary from day to day and powerproduction may not be optimized on a daily basis Thus itbecomes necessary to simulate other forms of energy sourceand add them to the energy mix allowing for farm ownersto decide which is the best package for their farm Tropicalislandic climate in the Philippines is unpredictable comparedto Dunkirk Francersquos oceanic weather and Montana USArsquoscontinental one so there is a need to take weather varia-tions into account [22] HOMER is software that allows forsuch simulation and provides hybrid optimization modelsfor electric renewables It was developed by the NationalRenewable Energy Laboratory (NREL) to optimizemicrogriddesign from village power to island electrification to evenlarge power consumers that connect to the grid It alsoevaluates if staying connected to the grid is economicallyadvantageous than going off-grid [23] HOMER is being usedas a techno-economic optimization tool while comparinggrid-connected stand-alone and diesel-powered homestead[24] Incorporating photovoltaics wind power and biomassinto hybrid systems can also be an option for farms withadditional thermal energy demands for heating and cooking[25] Such optimization tools can simulate overall systemperformance and do economic optimizations with criteriathat include net present cost and the cost of energy [18ndash20] Many off-grid [20ndash26] and on-grid systems [27ndash33]use HOMER as a tool to further scale up the capacity ofa system and with varied energy use A tabulated hybridtechnology analysis using HOMER was created to show thevarious applications the technology adapted and the supplyduration It was found out that the hybrid setup is usedmainlyfor household purposes but not in the agriculture sector [34]HOMER can also play a big part in assessing the feasibility oflarge scale PV on-grid systems [35]

13 The Focus of the Study This paper evaluated the perfor-mance of an installed 15 kW off-grid microgrid solar PVsystem in terms of its ability to meet the irrigation and otheroperational requirements of a 2-hectare plantation located inCamotes Island Cebu Philippines The study aimed to (1)determine the ability of the system tomeet the actual demandof the farm (2) determine the appropriate sizing required forthe actual demand through HOMERPro simulation and (3)perform a sensitivity analysis in HOMERPro varying loadsand fuel cost to assess system robustness

2 Method and Materials

21 Method Figure 1 presents the flow of the case study Anevaluation was conducted on a 15 kW solar PV installationin a 2-hectare farm using the actual energy usage obtainedfrom the built-in monitoring of the charge controller Themeasured load was then used and simulated throughHOME-RPro to determine the optimum configuration that could


Evaluationof design


Determine optimal



varying fuel cost

varying load

profiles

HOMERPro



22 Materials









(a) (b)












02468

270

920

1517

01

2016

210

120

1625

01

2016

290

120

1602

02

2016

060

220

1611

02

2016

150

220

1619

02

2016

2016

-02-

hellip27

02

2016

020

320

1606

03

2016

260

520

1630

05

2016

030

620

1603

06

2016

040

620

1608

06

2016

kWh



01234

270

920

1517

01

2016

210

120

1625

01

2016

290

120

1602

02

2016

060

220

1611

02

2016

150

220

1619

02

2016

2016

-02-

hellip27

02

2016

020

320

1606

03

2016

260

520

1630

05

2016

030

620

1603

06

2016

040

620

1608

06

2016

kWh

















110kW US$ 0806 US$ 34793 US$ 14078


6

12

18

24PV Output

000021042063084105126147168189210

kWH

our o

f Day


0 20 40 60 80 1000

4

8

12


State of Charge ()

Freq

uenc

y (

)

(a)


20406080

100

SOC

()


(b)


6

12

18


3044587286100

Hou

r of D

ay

(c)


05

101520253035

5 ha 10 ha 14 ha 18 ha 23 ha

kWh


4 Conclusions


minus01minus005

0005

01015

02

Oct

25

201

7N

ov 8

201

7D

ec 1

3 2

017

Jan

3 2

018

Jan

17 2

018

Jan

31 2

018

Feb

14 2

018

Feb

27 2

018

Mar

14

201

8M

ar 2

8 2

018

Apr 1

8 2

018

May

2 2

018

May

18

201

8Ju

ne 1

3 2

018

June

22

201

8Ju

ly 3

201

8Ju

y 25

201

8Au

g 8

201

8Au

g 22

201

8Se

p 5

201

8Se

p 19

201

8O

ct 3

201

8O

ct 1

6 2

018




10 15 20 25 30085

090

095

100




Interest Rate = 1

Die

sel P

rice

($L

)


10 15 20 25 30085

090

095

100




Interest Rate = 48

Die

sel P

rice

($L

)


10 15 20 25 30085

090

095

100




Interest Rate = 126

Die

sel P

rice

($L

)




5 Recommendations


Data Availability




Acknowledgments


References

































































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018



Evaluationof design


Determine optimal



varying fuel cost

varying load

profiles

HOMERPro



22 Materials









(a) (b)












02468

270

920

1517

01

2016

210

120

1625

01

2016

290

120

1602

02

2016

060

220

1611

02

2016

150

220

1619

02

2016

2016

-02-

hellip27

02

2016

020

320

1606

03

2016

260

520

1630

05

2016

030

620

1603

06

2016

040

620

1608

06

2016

kWh



01234

270

920

1517

01

2016

210

120

1625

01

2016

290

120

1602

02

2016

060

220

1611

02

2016

150

220

1619

02

2016

2016

-02-

hellip27

02

2016

020

320

1606

03

2016

260

520

1630

05

2016

030

620

1603

06

2016

040

620

1608

06

2016

kWh

















110kW US$ 0806 US$ 34793 US$ 14078


6

12

18

24PV Output

000021042063084105126147168189210

kWH

our o

f Day


0 20 40 60 80 1000

4

8

12


State of Charge ()

Freq

uenc

y (

)

(a)


20406080

100

SOC

()


(b)


6

12

18


3044587286100

Hou

r of D

ay

(c)


05

101520253035

5 ha 10 ha 14 ha 18 ha 23 ha

kWh


4 Conclusions


minus01minus005

0005

01015

02

Oct

25

201

7N

ov 8

201

7D

ec 1

3 2

017

Jan

3 2

018

Jan

17 2

018

Jan

31 2

018

Feb

14 2

018

Feb

27 2

018

Mar

14

201

8M

ar 2

8 2

018

Apr 1

8 2

018

May

2 2

018

May

18

201

8Ju

ne 1

3 2

018

June

22

201

8Ju

ly 3

201

8Ju

y 25

201

8Au

g 8

201

8Au

g 22

201

8Se

p 5

201

8Se

p 19

201

8O

ct 3

201

8O

ct 1

6 2

018




10 15 20 25 30085

090

095

100




Interest Rate = 1

Die

sel P

rice

($L

)


10 15 20 25 30085

090

095

100




Interest Rate = 48

Die

sel P

rice

($L

)


10 15 20 25 30085

090

095

100




Interest Rate = 126

Die

sel P

rice

($L

)




5 Recommendations


Data Availability




Acknowledgments


References

































































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018



(a) (b)












02468

270

920

1517

01

2016

210

120

1625

01

2016

290

120

1602

02

2016

060

220

1611

02

2016

150

220

1619

02

2016

2016

-02-

hellip27

02

2016

020

320

1606

03

2016

260

520

1630

05

2016

030

620

1603

06

2016

040

620

1608

06

2016

kWh



01234

270

920

1517

01

2016

210

120

1625

01

2016

290

120

1602

02

2016

060

220

1611

02

2016

150

220

1619

02

2016

2016

-02-

hellip27

02

2016

020

320

1606

03

2016

260

520

1630

05

2016

030

620

1603

06

2016

040

620

1608

06

2016

kWh

















110kW US$ 0806 US$ 34793 US$ 14078


6

12

18

24PV Output

000021042063084105126147168189210

kWH

our o

f Day


0 20 40 60 80 1000

4

8

12


State of Charge ()

Freq

uenc

y (

)

(a)


20406080

100

SOC

()


(b)


6

12

18


3044587286100

Hou

r of D

ay

(c)


05

101520253035

5 ha 10 ha 14 ha 18 ha 23 ha

kWh


4 Conclusions


minus01minus005

0005

01015

02

Oct

25

201

7N

ov 8

201

7D

ec 1

3 2

017

Jan

3 2

018

Jan

17 2

018

Jan

31 2

018

Feb

14 2

018

Feb

27 2

018

Mar

14

201

8M

ar 2

8 2

018

Apr 1

8 2

018

May

2 2

018

May

18

201

8Ju

ne 1

3 2

018

June

22

201

8Ju

ly 3

201

8Ju

y 25

201

8Au

g 8

201

8Au

g 22

201

8Se

p 5

201

8Se

p 19

201

8O

ct 3

201

8O

ct 1

6 2

018




10 15 20 25 30085

090

095

100




Interest Rate = 1

Die

sel P

rice

($L

)


10 15 20 25 30085

090

095

100




Interest Rate = 48

Die

sel P

rice

($L

)


10 15 20 25 30085

090

095

100




Interest Rate = 126

Die

sel P

rice

($L

)




5 Recommendations


Data Availability




Acknowledgments


References

































































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018




02468

270

920

1517

01

2016

210

120

1625

01

2016

290

120

1602

02

2016

060

220

1611

02

2016

150

220

1619

02

2016

2016

-02-

hellip27

02

2016

020

320

1606

03

2016

260

520

1630

05

2016

030

620

1603

06

2016

040

620

1608

06

2016

kWh



01234

270

920

1517

01

2016

210

120

1625

01

2016

290

120

1602

02

2016

060

220

1611

02

2016

150

220

1619

02

2016

2016

-02-

hellip27

02

2016

020

320

1606

03

2016

260

520

1630

05

2016

030

620

1603

06

2016

040

620

1608

06

2016

kWh

















110kW US$ 0806 US$ 34793 US$ 14078


6

12

18

24PV Output

000021042063084105126147168189210

kWH

our o

f Day


0 20 40 60 80 1000

4

8

12


State of Charge ()

Freq

uenc

y (

)

(a)


20406080

100

SOC

()


(b)


6

12

18


3044587286100

Hou

r of D

ay

(c)


05

101520253035

5 ha 10 ha 14 ha 18 ha 23 ha

kWh


4 Conclusions


minus01minus005

0005

01015

02

Oct

25

201

7N

ov 8

201

7D

ec 1

3 2

017

Jan

3 2

018

Jan

17 2

018

Jan

31 2

018

Feb

14 2

018

Feb

27 2

018

Mar

14

201

8M

ar 2

8 2

018

Apr 1

8 2

018

May

2 2

018

May

18

201

8Ju

ne 1

3 2

018

June

22

201

8Ju

ly 3

201

8Ju

y 25

201

8Au

g 8

201

8Au

g 22

201

8Se

p 5

201

8Se

p 19

201

8O

ct 3

201

8O

ct 1

6 2

018




10 15 20 25 30085

090

095

100




Interest Rate = 1

Die

sel P

rice

($L

)


10 15 20 25 30085

090

095

100




Interest Rate = 48

Die

sel P

rice

($L

)


10 15 20 25 30085

090

095

100




Interest Rate = 126

Die

sel P

rice

($L

)




5 Recommendations


Data Availability




Acknowledgments


References

































































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018






110kW US$ 0806 US$ 34793 US$ 14078


6

12

18

24PV Output

000021042063084105126147168189210

kWH

our o

f Day


0 20 40 60 80 1000

4

8

12


State of Charge ()

Freq

uenc

y (

)

(a)


20406080

100

SOC

()


(b)


6

12

18


3044587286100

Hou

r of D

ay

(c)


05

101520253035

5 ha 10 ha 14 ha 18 ha 23 ha

kWh


4 Conclusions


minus01minus005

0005

01015

02

Oct

25

201

7N

ov 8

201

7D

ec 1

3 2

017

Jan

3 2

018

Jan

17 2

018

Jan

31 2

018

Feb

14 2

018

Feb

27 2

018

Mar

14

201

8M

ar 2

8 2

018

Apr 1

8 2

018

May

2 2

018

May

18

201

8Ju

ne 1

3 2

018

June

22

201

8Ju

ly 3

201

8Ju

y 25

201

8Au

g 8

201

8Au

g 22

201

8Se

p 5

201

8Se

p 19

201

8O

ct 3

201

8O

ct 1

6 2

018




10 15 20 25 30085

090

095

100




Interest Rate = 1

Die

sel P

rice

($L

)


10 15 20 25 30085

090

095

100




Interest Rate = 48

Die

sel P

rice

($L

)


10 15 20 25 30085

090

095

100




Interest Rate = 126

Die

sel P

rice

($L

)




5 Recommendations


Data Availability




Acknowledgments


References

































































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018



10 15 20 25 30085

090

095

100




Interest Rate = 1

Die

sel P

rice

($L

)


10 15 20 25 30085

090

095

100




Interest Rate = 48

Die

sel P

rice

($L

)


10 15 20 25 30085

090

095

100




Interest Rate = 126

Die

sel P

rice

($L

)




5 Recommendations


Data Availability




Acknowledgments


References

































































Advances in



Journal of


Renewable Energy



EnergyJournal of









Shock and Vibration




RotatingMachinery








Volume 2018




5 Recommendations


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

Performance Evaluation of a Micro Off-Grid Solar Energy … · 1.05 1.26 1.47 1.68 1.89 2.10 W Hour of Day F :PVpoweroutput,.kWall-PV(optimum). 0 20406080 100 0 4 8 12 16 Frequency