analysis of factors influencing the annual energy production of photovoltaic system

8/13/2019 Analysis of Factors Influencing the Annual Energy Production of Photovoltaic System

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lbuquerqueSacramentoBuffalo

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Cumulative Solar Irradiance

The energy produced by a photovoltaic module 0ver.ayear's period of time is directly related to the availability ofsolar energy, and as a result is site dependent. In Buffalo,NY. there is about 60 and in Sacramento, CA, about 85of the solar energy available in Albuquerque, NM. Thecumulative solar energy incident on a photovoltaic module isin tum strongly dependent on the module's orientationrelative to the sun. To maximize energy production, themodule can be mounted on a Z-axis solar tracker

sothat it

always points directly at the sun. In other applications, itmay be desirable to mount a module in a horizontal orvertical orientation, Generally, it is common practice tomount flat-plate modules on a structure orienting them at atilt-angle from horizontal that is equal to the site latitudeangle. This 'latitude-tilt' orientation provides a good annualcompromise in capturing sunlight without the addedexpense of a solar tracker.

lbuquerqueSacramentoBuffalo

production. Basically, the factor describes how well amodule performs at low irradiance levels. Figure 2 illustrates the V, dependence on irradiance measured fortwo different modules. In the case of the amorphous silicon(a-Si) module shown, the Vmpincreased as the irradiancelevel decreased, thus maintaining an operating voltage atlow irradiance levels higher than at the reference one-suncondition. This behavior can be important. particularly forsites with a high percentage of overcast sky conditions,because it can result in about 10% more annual energyproduction. The a-Si and CdTe#Z modules in Table 1 had anoticeably higher annual energy production, primarilybecause of this V, vs. irradiance effect. Relatively smallertemperature coefficients also contributed about 2 to theapparent energy production advantage for the a-Si module.

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1.00 I 1.01 I 1.00 I 0.99 I 0.99 I 1.01 I 1.02 I 0.97 I 1.11 I 1.00 I 1.M I 0.99 I 1.13 I 0.991.00 I 1.01 I 0.99 I 0.99 I 0.99 I 1.01 1.02 I 0.96 1 1.11 1 0.99 I 1.03 I 0.99 1 1.15 0.981.00 1.00 0.99 I 0.98 I 0.99 1.02 I 0.99 I 0.96 1.09 I 0.98 I 1.01 I 1.00 1.10 0.96

Table 2 shows annual energy available f typical Imultiaystalline silicon (mc-Si) module relative to a latitude-tilt reference case for different module orientations andtracking options. The benefit of solar tracking was found tobe site dependent with the greatest benefit for sites with ahigh percentage of direct beam solar Irradiance, likeAlbuquerque. Module orientation also strongly influencesthe daily and monthly distribution of energy produced.making it possible for designerr to better match photovoltaicenergy production with energy demands that may beseasonally distributed. The seasonal distribution of dc-energy available for different module orientations inAlbuquerque is shown in Figure 1.

Table 2: Influence of module orientation and tracking onannual dc-energy available from a mc-Si module, relative toa latitude-tilt orientation,

Laitude-TillHorizontal

I -AxisTracking0.83

1.23

Maximum-Power-Voltage (Vmp) s. Irradiance

This module-specific factor, or characteristic, is nottypically measured or specified by module manufacturers,but it can have a pronounced influence on annual energy

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Jan Fsb Mar bor May Jm Jul b q Sap Od Nm Dk

Fig.1: Calculated dcenergy available from a 100-W, mc-Simodule by month in different orientations in Albuquerque.

Operating Temperature and Temperature Coefficients

Module performance changes with operatingtemperature, at a rate defined by the module's temperaturecoefficients. Both the electrical current generated by amodule and its voltage are independently influenced byoperating temperature. As temperature increases, voltagetypically decreases and current typically increases, with thelargest relative influence on voltage. As stated previously,the ASTM Standard Reporting Condition sewes as thereference condition for module performance, with celltemperature specified to be 25 C. Therefore, a module'srelative Performance and energy production will decreaseduring operating conditions where the cell temperature is

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above 25 C. The operating temperature is influenced bymodule design (flat-plate, concentrator). mounting technique(open rack, roof mounted). irradiance level, ambienttemperature. wind speed, and to a lesser degree winddirection. Sandia's empirically-based thermal modelcompensates for these influences and relates celltemperature to the environmental parameters given in theNSRDB database (irradiance, ambient temperature, windspeed). In the analysis presented here, the sensitivity ofannual energy production to temperature coefficients wasinvestigated by calculating the ratio of annual energy, withtemperature coefficients applied, divided by annual energy,assuming that module performance had no temperaturedependence.

0 2 0.4 0.6 0.8 1 4.2I d l U I O (sun')

Fig. V and Pw versus irradiance behavior measuredfor tw different modules, a-Si and mc-Si.

Table 3 shows the results for the modules for threedifferent sites. The temperature coefficients for P for thethree modules shown were approximately -0.5 WC for m eSi, -0.25 WC for a-Si, and -0.4 % for the Si concentrator.The effect of operating temperature on annual energyproduction was found to be dependent on both moduletechnology and site environmental conditions. However, themagntude of the effect on annual energy production may besmaller than commonly assumed.

Table 3 Influence of module temperature coefficient onannual dcenergy available for different sites.

0.97 0.91Buffalo 0.99 1 oo 0.96

Variation in Solar Spectrum

Quantifying the influence of the houdy variation in thesolar spectrum on module energy production requires anacademically complex procedure. Fortunately, as long asthe AM4.5 spectrum standardized by ASTM [ l l ] s used asthe reference for module power specification. the annualenergy production from a module is relatively insensitiie tosolar spectral variation. The variations in moduleperformance that occur during each day and over theseasons effectively average out on an annual basis. Table

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4 illustrates the sensitivity of annual energy production tosolar spectrum in terms of the ratio of calculated annualenergy, with solar spectral influence included, divided byannual energy, assuming the module performance was notinfluenced by variations in the solar spectrum. The a-Simodule considered had the strongest sensitivity, but theimpact on annual energy production was still less than 3%.The direct beam irradiance to which a concentrator moduleresponds has relatively less variation in spectral distributionthan does the global irradiance to which flat-plate modulesrespond. Therefore, the annual energy from the Siconcentrator module showed little sensitivity to solar

Table 4: Influence of variation in solar spectrum on annualdcenergy available or different sites.

SpeCtNm.

mcSi a-Si ConcentratorAlbupueque 0.993 10.9921 0.996Sacramento 1.002 10.9761 1.001Buffalo 1.004 10.9731 1.001

Even though the average annual impact on energy maybe small, it is still important to understand the daily andseasonat influence that the varying solar spectrum has onmodule performance. Figure 3 illustrates the influence ofvariation in solar spectrum on the normalized short-circuit-current (Ir) over the day in Albuquerque, as the sun'selevation angle increases to n w n and then decreases. Fora sea-level site such as Sacramento, the curves shownwould translate to the right by about 10 deg. The behaviorillustrated in Figure 3 for a mc-Si and an aSi module isdependent on the spectral response characteristics of thecells in the module. It is important for those conducting fieldmeasurements or monitoring array power data tounderstand this spectral influence. Measurements will be inerror, relative to the ASTM standard reporting condition, bythe factor shown, depending on the time-ofday thatmeasurements are made.

1 1 ,

0 I O 2 0 Y ) . O Y I " e n

Sun EleW -m Amla (de

Fig. 3 Influence of a varying solar spectrum on module 1as sunk elevation angle (air mass) varies over the day in

Albuquerque, NM.This spectral influence also has a seasonal effect on

the energy produced by photovoltaic modules because inthe summer the sun spends more time at high elevationangles (lowair mass) than in the winter (high air mass). Toillustrate this seasonal effect, daily average energy

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produced by month was calculated with the influence ofsolar spectrum considered, and these values were dividedby energy produced, assuming no solar spectraldependence. Figure 4 shows the resulting ratios for a mc-Simodule and an a-Si module, both oriented at latitude-tilt inAlbuquerque. Note that the spectral influence produces aseasonal variation in both technologies with the magnitudeof the influence being noticeably larger for the a-Si module.This seasonal (summer versus winter) behavior for a-Si

modules has been observed in long-term monitoring of a-Sisystems, and is further augmented by a seasonalannealing.phenomenon that is still the subject of technicaldebate today [12].

Jm F.b Mar rpr Yay Jun Jul *us S.p NW D.c

Fig. 4: Seasonal (monthly) influence of the valying solafspectrum on energy available from a mc-Si module andfrom an a-Si module in Albuquerque

Influence of Solar Anglesf-Incidence

The final factor influencing the dcenergy available frommodules is the effect of optical losses that vary with theanglHf-incidence (AOI) of sunlight striking the module.The effect relates primarily to the direct beam component ofsolar irradiance because the modules response to diffuse

solar irradiance is largely independent of module orientation.For flat-plate modules, the optical loss is associated with thereflectance loss f he glass front surface. Thereflectance of the glass surface increases significantly forAOI greater than about 60 degrees. The net result is lesssunlight reaching the cells inside the module and reducedenergy production for large angles-of-incidence. Like theinfluence of solar spectral variation, the influence of thisoptical loss on annual energy production is relatively small,but can have a significant seasonal (monthly) effectdepending on the orientation of the module. Table 5summarizes the AOI influence on annual energy productionfor a mc-Si module in four orientations at three differentsites. There is no AOI related energy loss for a modulemounted on a hw-axis solar tracker (AOI=O degrees). Thelargest effect on annual energy was small, about 4 . for a

vertically oriented module, and for the typical case of amodule oriented at latitude-tiit the annual loss was onlyabout 1 . Figure 5 illustrates the measured influence ofAOI on module performance for a variety of commercialmodules. The seasonal (monthly) affect on energyproduction is illustrated in Figure 6 for a mc-Si modulemounted horizontally or vertically in Albuquerque.

Particularly for building-integrated PV systems, the influenceof AOI on the monthly energy production needs to beconsidered during system design.

Table 5: Influence of AOI optical losses on annual dcenergyavailable for different module orientations.

Buffalo

1 . 7 , , ,

o to a0 J 40 5 ) m m m sa

w - w ( wFig. 5:response of module Isc versus A01 for variety of modules.

Measured influence of optical loss on relative

Jan FsD ar *pr May Jun Jul hw Sap Oct NOv WC

Fig. 6 Seasonal (monthly) influence of solar angle-of-incidence on energy produced by a m cSi module with glassfront surface.

ac-ENERGY PROVIDED BY PV SYSTEMS

Sandias long-term goal is to understand all factors thatinfluence photovoltaic system performance and reliability.Developing a fundamental understanding of the factorsinfluencing the dcenergy available from individualphotovoltaic modules is a significant step toward that goal.However, the module-level factors previously discussed in

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this report need to be put in perspective relative to system-level factors that can ovewhelm them.

System-level factors may introduce energy losses dueto module mismatch in the array, array soiling, wiring andterminal resistance, array performance degradation with age[13], and incompatibility of system components. In addition,grid-connected systems may have energy losses associatedwith inverter efficiency versus load and temperature, inverter

tare loss, maximum-power-point-tracking (MPPT) efficiency,isolation transformer efficiency, etc. Stand-alone systemshave additional dc-energy losses and system designconstraints associated with charge-controlier efficiency(util iiation of dc-energy available from the array), batterycapacity, battery charge and discharge efficiency, anddesign (sizing) tradeoffs in seiecting a suitable ratio betweendcenergy available from the array and the anticipated a oenergy requirement In poorly designed systems,combinations of these factors can quickly result in theinability of the system to power the intended load,constituting a 'system failure.'

Although the results are somewhat'site and moduletechnology dependent, Table 6 is an attempt to categotizedifferent factors that can influence system acenergyproduction, along with the range of thei r potential impact. InTable 6, the influence of inverters and charge controllers arelumped into the factor called 'power conversion. dc to ac.Several factors in the table have been previously discussed.Energy storage and array utilization associated with stand-alone photovoltaic systems are discussed in another paperat this conference [6]. In addition, module performancedegradation mechanisms and rates are discussedelsewhere 1131. Field testing experience m has provided anestimate for the range of influence of module mismatch onarray performance, for relatively new systems. However,this range is likely to be larger after several years of systemoperation as the module mismatch is likely to increase inmagnitude. The issue of selecting power conditioninghardware (inverter) that is compatible with the photovoltaicarrays operating characteristics has been a design issue forsystem integrators for many years [5]. Sandia's arrayperformance modeling capabilities are now being used toassist system integrators in better matching array designswith inverter requirements.

Examples of the consequence of component selectionon array utiliition and resulting annual ac-energyproduction for two different grid-tied systems are illustratedin Figures 7, 6, and 9. Figure 7 illustrates a scatter plot ofhourly values for the array maximum-power-voltage (Vversus the array maximum power level. Superimposed onthe scatter plot is the 'input voltage window' for the inverterused in the system. For this situation, the inverterrequirements did not match the V characteristics of thearray, or vice versa, and the net result was significantenergy loss due to reduced inverter efficiency.

Figures 8 and 9 illustrate a situation where the samegrid-tied system design was being considered for two siteswith distinctly different environmental conditions. In thiscase, the inverter selected had a wide MPPT voltagewindow (2504


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A m y aximum Power. P (kw)

Fig. 8: Scatter plot of hourly-average V values for a 3.0-kW, array versus array maximum power level for systemlocated in Madison, WI. The cumulative distribution curvefor Dower is also shown.

IB sshotl sm .165. n n w e 2002 ~ O ~ Y I Ns H x 2 w m i wse S a n D l ~ ~ ~ . C A - Y c d u I e f m - ldesnt , Q I B O d m u U I

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h y aximum Power. P (kw)

Fig. 9: Scatter plot of hourly-average V values for a 3.0-kW, array versus array maximum power level for systemlocated. in San Diego, CA.

CONCLUSIONS

It is clear from this work there are many factors that canhave a significant influence on the ac-energy production andreliability of photovoltaic systems. The continued evolutionof system testing and performance modeling procedures willimprove the ability of system integrators to design, install,and monitor the performance of systems. Theseimprovements will lead to photovoltaic systems with highperformance and high reliability at a minimum cost.

ACKNOWLEDGEMENTS

The authors would like to acknowledge valuable discussionswith the following: Bob Hammond (APS), Jim Rand

(AstroPower), John Wohlgemuth (BP Solar), ChuckWhitaker (Endecon). Ron Orozw (Energia Total), DanShugar (Powerlight), Georg Schultz (RUS), Miles Russell(SAPC), Tom Hansen (TEP), and Moneer Azzam (SolarDynamics). [Sandia i s a multi-program laboratory operatedby Sandia Corporation, a Lockheed Martin Company, for the

United Sfafes Department of Energy under Confract DEACW94AL85000.]

REFERENCES

[ ] STM E 1036, 'Testing Electrical Performance of Non-concentrator Photovoltaic Modules and Arrays UsingReference Cells.[2] Anon.. Solar-Electric Power: The US. Photovoltaic

Industry Roadmap, April 2001.[3] T. Townsend, et al., A New Performance index for PVSystem Analysis. 7 WCPEC. 1994, pp. 1036-1039.[4] S. Ransome and J. Wohlgemuth, 'kWh/kWpDependency on PV Technology, Balance of SystemsPerformance, and Marketing Watts, 29Ih E PVSC, 2002,New Orleans.[5] M. C. Russell, Grid-Tied PV System Modeling: How andWhy, l''WCPEC, 1994, pp. 1040-1043.[6] D. King, et al., Experimental Optimization of thePerformance and Reliability of Stand-Alone PhotovoltaicSystems, 2dh E PVSC, 2002, New Orleans.m D. King, et al., Field Experience with a NewPerformance Characterization Procedure for Photovoltaic

[E] C. Whitaker, et al., 'Application and Validation of a NewPV Performance Characterization Method. 2dh EPVSC. 1997, pp. 1253-1256.(91 B. Kroposki, et al.. 'Comparison of Module PerformanceCharacterization Methods, 2dh /E PVSC. 2000, pp.1407-1411.[ I O ] Anon.. 'NSRDB Vo1.2, National Solar Radiation DataBase, 1961-1990. NREL/lP-463-57&1,1995.[ l l ] ASTM E 892, 'Terrestrial Solar Spectral Irradiance atAir Mass 1.5 or a 37 Tilted Surface.[I21 J. Wohlgemuth and S. Ransome. Performance of BPSolar Tandem Junction Amorphous Silicon Modules, 2dnE PVSC. 2002, New Orleans.

[13] M. Quintana, et ai., 'Commonly ObSeNed Degradationin Field-Aged Photovoltaic Modules, 2dh lEEE PVSC,2002, New Orleans.

Arrays, World PVSEC. 1998. pp. 1947-1952.

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analysis of factors influencing the annual energy production of photovoltaic system

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