research article optimum availability of standalone...

Research ArticleOptimum Availability of Standalone Photovoltaic PowerSystems for Remote Housing Electrification

Tamer Khatib and Wilfried Elmenreich

Institute of Networked amp Embedded SystemsLakeside Labs University of Klagenfurt PO Box B10a2 9020 Klagenfurt Austria

Correspondence should be addressed to Tamer Khatib tamer khathotmailcom

Received 5 January 2014 Revised 15 April 2014 Accepted 29 April 2014 Published 8 May 2014

Academic Editor Hongxing Yang

Copyright copy 2014 T Khatib and W ElmenreichThis is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in anymedium provided the originalwork is properly cited

The availability of PV systems is discussed to determine the optimum availability at which standalone PV systemsmust be designedOptimization methods and PV systems software such as HOMER and PVMY were used for this purpose Six PV systems withsix availability levels were analyzed in terms of wasted energy cost of energy battery usage and power shortages using realmeteorological data Results show that PV systems with 99 availability are recommended because of their high reliability andfavorably wasted energy

1 Introduction

Considering that PV systems are clean environment-friend-ly and secure energy sources PV system installation hasplayed an important role worldwide However the draw-back of PV systems is their high capital cost compared toconventional energy sources Currently many studies wereconducted that focus on the optimization of standalonePV systems so that the number of PV modules capacityof storage battery and capacity of inverter were optimallyselected Standalone PV systems are widely used in remoteareas without access to electricity grid These systems hadproven their feasibility compared with conversional stan-dalone power systems (eg diesel generators) especially forremote applications because of the difficulty in accessing theremote areas and the cost of transportation However a PVsystem must be designed to meet the desired load demand ata defined level of availability [1]

Many sizing works for PV system can be found inthe literature Based on [1] three major PV-system-sizingprocedures are available namely intuitive numerical (sim-ulation based) and analytical methods in addition to someindividualmethods However most of thesemethods dependon system availability For example in [2] a well-completedoptimization of PV systems in Algeria was implementedby dividing the regions into four zones using sky clearness

indexThe optimization of PV systems was based on differentlevels of system availability and a simulation program whichcalculates the possible sizes of a PV system at a specific systemavailability and load demand Thereafter the optimum PVsystem configuration is selected based on system capital costIn [3] an elegant optimization method for PV system waspresented A PV system mathematical model was developedto optimize its size based on well-defined solar energy dataand load demand The developed model contains modelsfor PV array storage battery and charge regulator Howeverthe optimization considers the combined minimum costwith maximum system availability taking into account theuncertainty in solar energy and the variation in the demandedenergy by the load

The optimization of a PV system was done for three sitesin the UK using the sizing curves derivation in [4] To avoidany load interruption the PV array size was designed basedon the worst monthly average solar energy As for findingthe minimum storage requirement the same method used inplotting the sizing curves of the PV array was used for thebattery The minimum storage requirement was calculatedeach year of the used historical data However PV array sizewas calculated based on the worst monthmethod whichmaycause oversizing in the PV generator especially in monthshaving average solar energy higher than the worst monthThe considered system availability in this study was 100

Hindawi Publishing CorporationInternational Journal of PhotoenergyVolume 2014 Article ID 475080 5 pageshttpdxdoiorg1011552014475080

2 International Journal of Photoenergy

In [5] an optimization of a PV system was presented basedon long term solar radiation series for UK In this study theaverage of the obtained solar radiation series was calculatedand divided in two climatic cycles One of these climaticcycles contains days with average solar radiation equal toor higher than the calculated overall solar radiation averagewhereas other climatic cycles contain days that have averagesolar radiation lower than the calculated overall averagesolar radiation Thereafter the necessary size of the PVgenerator and the storage battery was calculated based on allthe climatic cycles to construct the general-sizing curve atspecific system availability Finally the resultant sizing curvewas fitted to an exponential function to derive amathematicalformula that can be used to calculate PV system size directlyIn [6] a comprehensive sizing of standalone PV systemsfor Malaysia was presented A simulation was performeddepending on the energy flow in a PV system [7] By this sim-ulation the possible sizes of a PVbattery system at differentsystem availabilities for fivemain locationswere obtained andplotted to establish a mathematical correlation between PVarray capacity and system availability and between PV arraycapacity and storage battery capacity After calculating thecoefficients for each region the averages of these coefficientswere calculated to establish amodel for allMalaysia From theexamples of PV system optimization that were given it canbe concluded that the PV systems were designed at differentlevels of availability of 90 to 100

The main objective of the present paper is to studythe effect of system availability on system size and costto recommend an optimum availability level at which PVsystems must be designed

2 Standalone PV System Availability

Each standalone PV system like any other power systemshas a specific level of availability This reliability level affectssystem performance production feasibility and investment[8ndash14] According to the Sandia National Laboratory in [15]the availability of a standalone PV system can be defined asthe percentage of time at which a power system is capable ofmeeting the load requirementsThe number of hours that thesystem is available divided by 8 760 h gives the annual systemavailability A systemwith 95 availability is expected tomeetthe load requirement of 8 322 h during an average year for theentire useful life of the system An annual availability of 99means that the system can operate the load for 8 672 h of the8 760 h [15] In [16] the PV systemavailability is defined as thepercentage of time at which a PV system is capable ofmeetingthe load requirements

The availability of a PV system can be described bystatistical values In [17] the availability of PV systems isdefined as a statistical value called loss of load probability(LLP) which is given by

LLP =sum

8760

119894=1EnergyDeficit

119894

sum

8760

119895=1LoadDemand

119895

(1)

The numerator in (1) is the sum of the energy demandedwhich the PV system cannot cover in a yearrsquos time On

the other hand the denominator is the sum of the energydemanded in a yearrsquos time After calculating the LLP theavailability (119860) of the PV system can be expressed as

119860 = (1 minus LLP) lowast 100 (2)

Some researchers used another statistical value to describethe availability of a PV system namely loss of power supplyprobability (LOSP) In [18 19] LOSP is described as aprobability function

119891119888= SOC (119905) le SOCmin for 997888rarr 119905 le 119879 (3)

where 119891119888is the probability that the state of charge at any

accumulative time 119905 within the time period 119879 will be equalto or less than the minimum permissible level (SOCmin)

According to this formula the availability of a PV systemcan be calculated as

119860 = (1 minus 119891119888) lowast 100 (4)

However increasing PV system availability increases the sizeof the system and consequently the capital cost of the systemIn [20] the effect of the availability of PV system on PVarray cost is deeply studied According to [20] the systemsize and cost increased rapidly while trying to obtain the lastfew percentages of availabilityThe relation between PV arraycost (size) and system availability was almost liner until 80at which it became logarithmic thereafter In addition theSandia National Laboratory in [15] illustrated the relationbetween the peak sunshine hours of the system and theneeded storage capacity for the system at two levels of systemavailability According to [15] the storage needed from a PVsystem that has 99 availability is higher than that from aPV system with 95 availability Moreover the differencebetween the needed storage capacities becomes much higheras the number of peak sunshine hours becomes lower than 4

Based on that increasing availability of the PV systemincreased the size of the PV array and the needed storagecapacity On these bases knowing the optimum availabilityat which the PV system must be designed is important In[15] two levels of availability are recommended 95 and99 However these authors stated that the 95 availabilityis more recommended Meanwhile in [20] it is suggestedthat the nature of the load of the PV system determinesits availability For example telecommunication repeaterstations will be considered as a critical load Thus 99availability is demanded whereas other noncritical loads canbe designed based on 95 availability In [2] the availabilityof PV systems in the range of 90 to 100 is recommendedMeanwhile in [3] the availability of PV systems in the rangeof 92 to 999 is recommended In [4] it is recommendedthat PV systems must be designed at 100 availability Inaddition in [5] it is suggested that PV system availabilitymust be higher than 95 and that an LLP value of zero cannotbe assigned In [6] the PV system availability in the rangeof 95 to 99 is recommended whereas a 98 availabilityof PV system is recommended in [7] Finally the HOMERsoftware which is a widely used PV system optimization tooldesigns standalone PV systems at 100 availability

International Journal of Photoenergy 3

Table 1 Designed PV systems specification

119860 119862119860(kWp) 119862

119861(Ah12V) 119864PV (kWh) LOLH 119864

119863(kWh) CoE ($kWh) SOC80

100 43 1316 6882 0 4645 06 788199 25 324 4000 199 1789 027 274898 23 270 3681 386 1491 025 259597 22 260 3521 661 1368 024 250296 21 250 3361 736 1217 023 241695 2 240 3201 972 1090 022 2341

0

100

200

300

400

500

600

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Pow

er

Hour

Figure 1 Simulated load demand

On these bases the availability of PV systems is mostlyrecommended in the range of 95 to 100 However anexact availability level is not yet determined even by thepresent study A more specific availability level must bedefined among the availability levels that are in the range of95 to 100 In the next section a brief analysis of a PVsystem designed at six availability levels is performed to tryto find the optimum availability at which PV systemsmust bedesigned

3 Searching for the Optimum PVSystem Availability

In this section a brief analysis of a PV system designed atsix availability levels (95 96 97 98 99 and 100)is performed to find the best system availability at whichPV systems must be designed Figure 1 shows the used loaddemand The total load demand was 6135 kWhday with amaximum power of 052 kW The average load power was0255 kW and the load factor was 49

In this section the method proposed by [6] was usedto design the PV system at different availability levels Inaddition the tool presented in [21] was used to simulatethese systems using hourly solar radiation and ambienttemperature records for Kuala Lumpur City Malaysia Theproposed method and the HOMER software were used todesign the PV system at 100 availability Then the methodsproposed in [6 21] were used to design and analyze thedesigned PV systems

According to HOMER a PV system with a 4 kWp PVarray and 1500Ah12V storage battery is needed to meet

the desired load demand at zero loss of load probability(100 availability) On the other hand for the method in[6] a PV system with 43 kWp and 1316Ah12V storagebattery is needed to meet the desired load demand Thedifference between the result given by HOMER and that bythe proposed method is attributed to two reasons the natureof the meteorological variable used and the specificationassumption of the device As for the former themethod in [6]used real hourly meteorological data whereas HOMER usedmonthly averages and converted it into hourly data usingembedded models As for the latter many differences existin the defined specifications for the modeled devices such asconversion efficiency of the PV module charging efficiencyof the battery and other factors

Table 1 shows the specifications and statistics of six PVsystems designed at six availability levels The table showsthe availability level (119860) PV array capacity (119862

119860) storage

battery capacity (119862119861) energy generated by the PV array in a

yearrsquos time (119864PV) number of loss load hours (LOLH) dampedenergy (119864

119863) cost of energy generated by the PV system

(CoE) and number of hours in the year that the SOC of thebattery was higher than 80 (SOC

80) As for LOLH thesimulation counted each hour within which an energy deficitoccurs despite the fact that some of the hourly demands canbe partially covered

From the table the system with 100 availability con-sisted of a 43 kWp PV array and a 1316Ah12V storage unitThe system generated 6882 kWh per year whereas 4645 kWhwas damped whichmeans that 675 of the energy generatedwas wasted The cost of energy generated by such a system is06USDkWh In addition the battery SOC was higher than80 in about 899 of a yearrsquos time which indicates that thebattery was not the kind used during a yearrsquos time

As for the system with 99 availability a 25 kWp PVarray and a 324Ah12V storage battery are the recommendedenergy source sizes In a yearrsquos time 4000 kWhwas generatedwhereas 45 of this energy was damped The cost of theenergy generated by the system is 027USDkWhThebatterySOC in 31 of a yearrsquos time was higher than 80 whichmeans that the battery was well used compared with theprevious case The number of hours at which the systemcannot meet the load demand was 199 which translates to22 of a yearrsquos time

As for the remaining system options the performancesof these systems were close to each other whereas the neededPV array and battery capacity were in the range of 23 kWpto 2 kWp and 270Ah12V to 240Ah12V The generated


0

10

20

30

40

50

60

70

80

90

100

()

System availability ()95 96 97 98 99 100

Wasted energyLOLH

SOC80

Figure 2 PV systems comparison

energy was in the range of 3201 kWhyear to 3681 kWhyearwhereas the percentage damped energy was in the rangeof 34 to 40 On the other hand the cost of the energygenerated by these systemswas in the range of 022USDkWhto 025USDkWh whereas the percentage of the days withinwhich the battery SOC was higher than 80 was in the rangeof 28 to 30 The LOLH values of these systems were inthe range of 44 to 111 which are high values especiallycompared with the previous systems

Figure 2 shows a comparison among these systemsin terms of wasted energy (damped energy-to-generatedenergy) battery usage (SOC

80 to the number of hours in ayearrsquos time) and LOLH percentage (LOLH to the number ofhours in a yearrsquos time) The figure shows that systems withavailability in the range of 99 to 95 had almost similarbattery usages Hence systems with 98 to 99 availabilityare recommended in this regard As for LOLH systems withavailability values in the range of 98 to 100 are recommendedFinally systems with availability values in the range of 97to 98 are recommended in terms of wasted energy On thebasis of these results systems with availability values of 98and 99 are most recommended

Referring to the CoE in Table 1 it is noted that byusing the system with 99 availability the supplier lost298 kWhper year in damped energy compared with thesystem with 98 availability Moreover the generation ofenergy costs the supplier 002USD per kWhmore comparedwith the system with 98 availability On the other hand theLOLH value increased by 187 h in the system with 98 avail-ability compared with the systemwith 99 availabilityThusdespite the fact that the system with 98 availability wascheaper in terms of unit cost and damped energy it is less reli-able compared with the system with 99 availability Uponthis basis PV systemswith 99availability are recommendeddue to their high reliability and favorable running costs

4 Conclusion

Optimum PV system availability was studied and presentedin this paper Six PV systems with different reliability levelswere studied using solar energy and ambient temperaturerecords for Kuala Lumpur City Malaysia The performanceanalysis was in terms of wasted energy cost of energy batteryusage and power shortages using real meteorological dataThe results show that PV systems with 99 availability arerecommended due to their high reliability and favorablywasted energy

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

Thiswork is supported by Lakeside Labs Klagenfurt Austriaand funded by the European Regional Development Fund(ERDF) and the Carinthian Economic Promotion Fund(KWF) under Grant KWF 20214|23743|35470 (ProjectMON-ERGY) and 20214|22935|34445 (Project Smart Microgrid)The authors would like to thank Lizzie Dawes for proofread-ing the paper

References

[1] T Khatib A Mohamed and K A Sopian ldquoA review of photo-voltaic systems size optimization techniquesrdquo Renewable andSustainable Reviews vol 22 pp 454ndash465 2012

[2] A H Arab B A Driss R Amimeur and E Lorenzo ldquoPhoto-voltaic systems sizing for Algeriardquo Solar Energy vol 54 no 2pp 99ndash104 1995

[3] G B Shrestha and L Goel ldquoA study on optimal sizing of stand-alone photovoltaic stationsrdquo IEEE Transactions on Energy Con-version vol 13 no 4 pp 373ndash378 1998

[4] A Fragaki and T Markvart ldquoStand-alone PV system designresults using a new sizing approachrdquo Renewable Energy vol 33no 1 pp 162ndash167 2008

[5] T Markvart A Fragaki and J N Ross ldquoPV system sizing usingobserved time series of solar radiationrdquo Solar Energy vol 80no 1 pp 46ndash50 2006

[6] T Khatib A Mohamed K Sopian and M Mahmoud ldquoA newapproach for optimal sizing of standalone photovoltaic sys-temsrdquo International Journal of Photoenergy vol 2012 Article ID391213 7 pages 2012

[7] P Arun R Banerjee and S Bandyopadhyay ldquoOptimum siz-ing of photovoltaic battery systems incorporating uncertaintythrough design space approachrdquo Solar Energy vol 83 no 7 pp1013ndash1025 2009

[8] P Zhang W Li S Li Y Wang and W Xiao ldquoReliabilityassessment of photovoltaic power systems review of currentstatus and future perspectivesrdquo Applied Energy vol 104 pp822ndash833 2013

[9] R Fucci L Lancellotti and C Privato ldquoA procedure for assess-ing the reliability of short circuited concentration photovoltaicsystems in outdoor degradation conditionsrdquo MicroelectronicsReliability vol 54 no 1 pp 182ndash187 2014


[10] G Zini C Mangeant and J Merten ldquoReliability of large-scalegrid-connected photovoltaic systemsrdquo Renewable Energy vol36 no 9 pp 2334ndash2340 2011

[11] R M Moharil and P S Kulkarni ldquoReliability analysis of solarphotovoltaic system using hourly mean solar radiation datardquoSolar Energy vol 84 no 4 pp 691ndash702 2010

[12] J K Kaldellis P Koronakis and K Kavadias ldquoEnergy balanceanalysis of a stand-alone photovoltaic system including variablesystem reliability impactrdquo Renewable Energy vol 29 no 7 pp1161ndash1180 2004

[13] V Sharma and S S Chandel ldquoPerformance and degradationanalysis for long term reliability of solar photovoltaic systems areviewrdquo Renewable and Sustainable Energy Reviews vol 27 pp753ndash767 2013

[14] M Lee D Soto and V Modi ldquoCost versus reliability sizingstrategy for isolated photovoltaic micro-grids in the developingworldrdquo Renewable Energy vol 69 pp 16ndash24 2014

[15] Sandia International Laboratory Standalone Photovoltaic PowerSystems Sandia International Laboratory Albuquerque NMUSA 1995

[16] T Ball andV Risser ldquoStand-alone terrestrial photovoltaic powersystemsrdquo in Proceedings of the 20th IEEE Photovoltaic SpecialistsConference Tutorial Notes Las Vegas Nev USA 1988

[17] P Tsalides and A Thanailakis ldquoLoss-of-load probability andrelated parameters in optimum computer-aided design ofstand-alone photovoltaic systemsrdquo Solar Cells vol 18 no 2 pp115ndash127 1986

[18] EOfry andA Braunstein ldquoThe loss of power supply probabilityas a technique for designing standalone solar electrical (Pho-tovoltaic) systemsrdquo IEEE Transactions on Power Apparatus andSystems vol 102 no 5 pp 1171ndash1175 1983

[19] I Abouzahr and R Ramakumar ldquoLoss of power supply prob-ability of stand-alone photovoltaic systems a closed formsolution approachrdquo IEEE Transactions on Energy Conversionvol 6 no 1 pp 1ndash11 1991

[20] S R Wenham M A Green and M E Watt Applied Photo-voltaics Earthscan London UK 2007

[21] T Khatib A Mohamed and K Sopian ldquoA software tool foroptimal sizing of PV systems in Malaysiardquo Modelling andSimulation in Engineering vol 2012 Article ID 969248 16 pages2012

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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International Journal ofPhotoenergy


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Advances in

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Bioinorganic Chemistry and ApplicationsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

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In [5] an optimization of a PV system was presented basedon long term solar radiation series for UK In this study theaverage of the obtained solar radiation series was calculatedand divided in two climatic cycles One of these climaticcycles contains days with average solar radiation equal toor higher than the calculated overall solar radiation averagewhereas other climatic cycles contain days that have averagesolar radiation lower than the calculated overall averagesolar radiation Thereafter the necessary size of the PVgenerator and the storage battery was calculated based on allthe climatic cycles to construct the general-sizing curve atspecific system availability Finally the resultant sizing curvewas fitted to an exponential function to derive amathematicalformula that can be used to calculate PV system size directlyIn [6] a comprehensive sizing of standalone PV systemsfor Malaysia was presented A simulation was performeddepending on the energy flow in a PV system [7] By this sim-ulation the possible sizes of a PVbattery system at differentsystem availabilities for fivemain locationswere obtained andplotted to establish a mathematical correlation between PVarray capacity and system availability and between PV arraycapacity and storage battery capacity After calculating thecoefficients for each region the averages of these coefficientswere calculated to establish amodel for allMalaysia From theexamples of PV system optimization that were given it canbe concluded that the PV systems were designed at differentlevels of availability of 90 to 100

The main objective of the present paper is to studythe effect of system availability on system size and costto recommend an optimum availability level at which PVsystems must be designed

2 Standalone PV System Availability

Each standalone PV system like any other power systemshas a specific level of availability This reliability level affectssystem performance production feasibility and investment[8ndash14] According to the Sandia National Laboratory in [15]the availability of a standalone PV system can be defined asthe percentage of time at which a power system is capable ofmeeting the load requirementsThe number of hours that thesystem is available divided by 8 760 h gives the annual systemavailability A systemwith 95 availability is expected tomeetthe load requirement of 8 322 h during an average year for theentire useful life of the system An annual availability of 99means that the system can operate the load for 8 672 h of the8 760 h [15] In [16] the PV systemavailability is defined as thepercentage of time at which a PV system is capable ofmeetingthe load requirements

The availability of a PV system can be described bystatistical values In [17] the availability of PV systems isdefined as a statistical value called loss of load probability(LLP) which is given by

LLP =sum

8760

119894=1EnergyDeficit

119894

sum

8760

119895=1LoadDemand

119895

(1)

The numerator in (1) is the sum of the energy demandedwhich the PV system cannot cover in a yearrsquos time On

the other hand the denominator is the sum of the energydemanded in a yearrsquos time After calculating the LLP theavailability (119860) of the PV system can be expressed as

119860 = (1 minus LLP) lowast 100 (2)

Some researchers used another statistical value to describethe availability of a PV system namely loss of power supplyprobability (LOSP) In [18 19] LOSP is described as aprobability function

119891119888= SOC (119905) le SOCmin for 997888rarr 119905 le 119879 (3)

where 119891119888is the probability that the state of charge at any

accumulative time 119905 within the time period 119879 will be equalto or less than the minimum permissible level (SOCmin)

According to this formula the availability of a PV systemcan be calculated as

119860 = (1 minus 119891119888) lowast 100 (4)

However increasing PV system availability increases the sizeof the system and consequently the capital cost of the systemIn [20] the effect of the availability of PV system on PVarray cost is deeply studied According to [20] the systemsize and cost increased rapidly while trying to obtain the lastfew percentages of availabilityThe relation between PV arraycost (size) and system availability was almost liner until 80at which it became logarithmic thereafter In addition theSandia National Laboratory in [15] illustrated the relationbetween the peak sunshine hours of the system and theneeded storage capacity for the system at two levels of systemavailability According to [15] the storage needed from a PVsystem that has 99 availability is higher than that from aPV system with 95 availability Moreover the differencebetween the needed storage capacities becomes much higheras the number of peak sunshine hours becomes lower than 4

Based on that increasing availability of the PV systemincreased the size of the PV array and the needed storagecapacity On these bases knowing the optimum availabilityat which the PV system must be designed is important In[15] two levels of availability are recommended 95 and99 However these authors stated that the 95 availabilityis more recommended Meanwhile in [20] it is suggestedthat the nature of the load of the PV system determinesits availability For example telecommunication repeaterstations will be considered as a critical load Thus 99availability is demanded whereas other noncritical loads canbe designed based on 95 availability In [2] the availabilityof PV systems in the range of 90 to 100 is recommendedMeanwhile in [3] the availability of PV systems in the rangeof 92 to 999 is recommended In [4] it is recommendedthat PV systems must be designed at 100 availability Inaddition in [5] it is suggested that PV system availabilitymust be higher than 95 and that an LLP value of zero cannotbe assigned In [6] the PV system availability in the rangeof 95 to 99 is recommended whereas a 98 availabilityof PV system is recommended in [7] Finally the HOMERsoftware which is a widely used PV system optimization tooldesigns standalone PV systems at 100 availability



119860 119862119860(kWp) 119862

119861(Ah12V) 119864PV (kWh) LOLH 119864


100 43 1316 6882 0 4645 06 788199 25 324 4000 199 1789 027 274898 23 270 3681 386 1491 025 259597 22 260 3521 661 1368 024 250296 21 250 3361 736 1217 023 241695 2 240 3201 972 1090 022 2341

0

100

200

300

400

500

600

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Pow

er

Hour









119860) storage










0

10

20

30

40

50

60

70

80

90

100

()


Wasted energyLOLH

SOC80






4 Conclusion




Acknowledgments


References
































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of



119860 119862119860(kWp) 119862

119861(Ah12V) 119864PV (kWh) LOLH 119864


100 43 1316 6882 0 4645 06 788199 25 324 4000 199 1789 027 274898 23 270 3681 386 1491 025 259597 22 260 3521 661 1368 024 250296 21 250 3361 736 1217 023 241695 2 240 3201 972 1090 022 2341

0

100

200

300

400

500

600

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Pow

er

Hour









119860) storage










0

10

20

30

40

50

60

70

80

90

100

()


Wasted energyLOLH

SOC80






4 Conclusion




Acknowledgments


References
































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of


0

10

20

30

40

50

60

70

80

90

100

()


Wasted energyLOLH

SOC80






4 Conclusion




Acknowledgments


References
































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of























Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of

research article optimum availability of standalone...

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