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Renewable and Sustainable Energy Reviews 15 (2011) 4470 4482
Contents lists available at SciVerse ScienceDirect
Renewable and Sustainable Energy Reviews
jo ur n al hom ep a ge: www.elsev ier .com/ locate / rser
A review of solar photovoltaic levelized cost of electricity
K. Brankera, M.J.M. Pathaka, J.M. Pearcea,b,
a Department of Mechanical and Materials Engineering, Queens
University, Kingston, Canadab Department of Materials Science &
Engineering and Department of Electrical & Computer
Engineering, Michigan Technological University, Houghton, MI,
USA
a r t i c l
Article history:Received 29 MAccepted 5 JulAvailable onlin
Keywords:PhotovoltaicLevelized costLCOEGrid paritySolar
economi
advantageous source of electricity over expanding geographical
regions. 2011 Elsevier Ltd. All rights reserved.
Contents
1. Introd2. Revie
2.1. 3. LCOE 4. Addre
4.1. 4.2. 4.3. 4.4. 4.5.
5. Nume6. Discu7. Concl
AcknoRefer
Correspon601 M&M Buil
E-mail add
1364-0321/$ doi:10.1016/j.uction . . . . . . . . . . . . . . . .
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. . . . . . . . . . . . . . . . . . . . 4471w of the cost of
electricity and LCOE. . . . . . . . . . . . . . . . . . . . . . . .
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. . . . . . . . . . . . . . . 4471Estimates for solar PV LCOE . . .
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methodology . . . . . . . . . . . . . . . . . . . . . . . . . .
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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . 4472ssing major misconceptions and assumptions in LCOE for
solar PV . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . 4475Discount rate . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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. . . . . . . . . . . . . 4475System costs, nancing and incentives
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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4475System life for solar PV . . . . . . . . . . . . . . . . . . .
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4475Degradation rate and energy output . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . 4476Grid parity . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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rical example in Ontario, Canada. . . . . . . . . . . . . . . .
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. 4478usions . . . . . . . . . . . . . . . . . . . . . . . . . . .
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. . . . . . . . . 4479wledgements . . . . . . . . . . . . . . . . .
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ences . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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ding author at: Department of Materials Science &
Engineering, Department of Electrical & Computer Engineering,
Michigan Technological University,ding, 1400 Townsend Drive,
Houghton, MI 49931-1295, United States. Tel.: +1 906 487 1466.ress:
[email protected] (J.M. Pearce).
see front matter 2011 Elsevier Ltd. All rights
reserved.rser.2011.07.104 e i n f o
arch 2011y 2011e 15 September 2011
cs
a b s t r a c t
As the solar photovoltaic (PV) matures, the economic feasibility
of PV projects is increasingly being eval-uated using the levelized
cost of electricity (LCOE) generation in order to be compared to
other electricitygeneration technologies. Unfortunately, there is
lack of clarity of reporting assumptions, justications anddegree of
completeness in LCOE calculations, which produces widely varying
and contradictory results.This paper reviews the methodology of
properly calculating the LCOE for solar PV, correcting the
mis-conceptions made in the assumptions found throughout the
literature. Then a template is provided forbetter reporting of LCOE
results for PV needed to inuence policy mandates or make invest
decisions.A numerical example is provided with variable ranges to
test sensitivity, allowing for conclusions to bedrawn on the most
important variables. Grid parity is considered when the LCOE of
solar PV is comparablewith grid electrical prices of conventional
technologies and is the industry target for
cost-effectiveness.Given the state of the art in the technology and
favourable nancing terms it is clear that PV has alreadyobtained
grid parity in specic locations and as installed costs continue to
decline, grid electricity pricescontinue to escalate, and industry
experience increases, PV will become an increasingly
economically
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K. Branker et al. / Renewable and Sustainable Energy Reviews 15
(2011) 4470 4482 4471
1. Introduction
It is technically feasible for renewable energy
technologies(RETs) to replace the present fossil fuel electricity
infrastructure[1,2]; however, economic barriers remain the primary
impedimentto a renewable-powered society. Solar photovoltaic (PV)
technol-ogy, which converts sunlight directly into electricity, is
one of thefastest growing RETs in the world [3,4]. PV is considered
a clean,sustainable, renewable energy conversion technology that
can helpmeet the energy demands of the worlds growing population,
whilereducing the adverse anthropogenic impacts of fossil fuel use
[57].From 2000 to 2010, global solar PV deployment has
increasedfrom 0.26 G 1
than 40% [3reduced maincentives f
Despite tainable forsupply contion is cons[1721] giving while
Plifetime genrable with grid [13,15average fortricity pricevalidity
depused to calcity. In additof retail prfeasibility ovarious
me(LCOE) genity generatitechnologienately, the is a lack ofing
understwhich prodconcept of ship betwewhich
depe[11,13,17,1assumptionestimated feliminatingcustomer ch[39].
Reporin not only misguide pocase for exatechnologythe long terof
solar PV hachieving g
1 Units used1 MW = 1000 kWp, Watts pethe
manufactukilowatt-hourthe system). AThe capacity fover a period
o100% of the tim
exist for LCOE, this paper reviews the methodology of
calculatingthe LCOE for solar PV, correcting the misconceptions
made in theassumptions and provides a template for better reporting
neededto inuence the correct policy mandates. A simple numerical
exam-ple is proviconclusions
2. Review
A clear feasibility omining eneelectricity p
by tres [city aariece th
or tits fo
grid sal elet of
LCOnchmrent
mad con
priclude
diffe) takeaid fake a. Rathis, wed awn ifognivity tl yeaer poas
poand oks atrue (electhly tood
shoume f
theave
of e LCOeraleratexity,51]. cessaeld
use the nd dissionies (nW to 16.1 GW [8] with an annual growth
rate of more,911], due to both technological innovations that
havenufacturing costs by 100 times and various governmentor
consumers and producers [3,4,1115].increased incentives and the
demand for more sus-ms of energy, PV has still not become a major
energytributor [3,16]. The tipping point for solar PV adop-idered
to be when the technology achieves grid parityen that
conventional-powered electricity prices are ris-V installed prices
are falling. Grid parity refers to theeration cost of the
electricity from PV being compa-the electricity prices for
conventional sources on the,1720,2224] often graphically given as
the industry
solar PV electricity generation against the average elec- for a
given country. While this is a useful benchmark, itsends on the
completeness and accuracy of the methodulate the lifetime
generation cost of solar PV electric-ion, claims of grid parity at
manufacturing cost insteadice have contributed to confusion [15].
The economicf an energy generation project can be evaluated
usingtrics [15,2528], but the levelized cost of electricityeration
is most often used when comparing electric-on technologies or
considering grid parity for emergings such as PV
[9,11,13,15,17,19,22,24,2832]. Unfortu-LCOE method is deceptively
straightforward and there
clarity of reporting assumptions, justications show-anding of
the assumptions and degree of completeness,uces widely varying
results [3,10,15,25,30,3238]. Thegrid parity for solar PV
represents a complex relation-en local prices of electricity and
solar PV system pricends on size and supplier, and geographical
attributes9,21]. Different levels of cost inclusion and sweepings
across different technologies result in different costsor even the
same location. In addition, the trend of
avoidable costs for consumers and folding them intoarges can
mask real costs of conventional technologies
ting the wrong LCOE values for technologies can
resultsub-optimal decisions for a specic project, but can alsolicy
initiatives at the local and global scale. In the solarmple, it is
still a common misconception that solar PV
has a short life and is therefore extremely expensive inm
[20,21,40,41]. Yet, depending on the location, the costas already
dropped below that of conventional sourcesrid parity
[3,18,2022,42,43]. Since varying estimates
in solar PV industry: W, Watt (measure of power); 1 kW = 1000
W,W; 1 GW = 1000 MW, used in capacity rating of energy
technologies.ak (measure of nominal or rated power of solar PV
system as perrer); kWh, kilowatt-hour (measure of electrical
energy); kWh/kW/yr,s per kilowatt per year (annual energy produced
per rated power of
solar insolation value with these units accounts for capacity
factor.actor (CF) is the ratio of actual power output to nameplate
capacityf time since power systems do not generate at maximum
efciency,e.
eratedmeasuelectripliers vTo redua xedaccounto the the nthe
cos
Theas a beof diffetion ismethomate anot incfor theiff (FITto be
psarily thurdleanalysproducbe dra
Recsensitiseveraconsidrately Carlo) that lowhile index a
monunders[31]. Itthe sanancetems hqualityby theare genity
gencompl[18,19not nein the agentstion ofplant acommsubsidded with
variable ranges to test sensitivity, allowing for to be drawn on
the most important variables.
of the cost of electricity and LCOE
understanding of the relative cost-effectiveness andf different
energy technologies is paramount in deter-rgy management policies
for any nation. The actualrices depend on the marginal cost of
electricity gen-
he given power plant and market-based or regulatory26,44,45].
Various power plants can compete to supplyt different bids, such
that the electricity price from sup-s depending on the accepted bid
and technology [26,46].is volatility, calculations are used by
retailers to assumeered system that is predictable for consumers
and thatr any volatility in the supplied electricity price,
upgradesystem and other administrative duties [26,39,44].
Thusctricity price paid by consumers will be different from
generation [19,47].E methodology is an abstraction from reality
and is usedarking or ranking tool to assess the
cost-effectiveness
energy generation technologies [19,27,32]. The abstrac-de to
remove biases between the technologies. Thesiders the lifetime
generated energy and costs to esti-e per unit energy generated. The
method usually does
risks and different actual nancing methods availablerent
technologies [26,32,48]. For example, a feed in tar-s away the
price risk for RETs by guaranteeing the priceor energy generated by
the source, but does not neces-way the nancing risk for the
technology, which is still aer all technologies should be given the
same economic
ith the only difference being the actual costs, energynd
lifetime [27]. Conceptual parallels with reality can
the scenarios closest to reality are chosen.zing that LCOE is a
benchmarking tool, there is higho the assumptions made, especially
when extrapolatedrs into the future [27,30,32,41,49,50]. Thus, if
used tolicy initiatives, assumptions should be made as accu-ssible,
with respective sensitivity analysis (e.g. Montejustications [30].
Ordinarily, LCOE is a static measuret a snapshot in deriving the
price per generated energy,markets prices are dynamic. The
SolarBuzz solar pricetricity, system and module prices) attempts to
reportdynamic LCOE, although the assumptions should be
and it represents an average for specic circumstancesld be
stressed that the type of nancing is usually keptor all
technologies, even though real markets wouldm differently. In
addition, economic and nancial sys-a large impact on the price of
electricity, although thelectricity rarely changes, which is often
not reectedE. Finally, the technological assumptions often usedized
for the given equipment setup. Costs and electric-ed can vary based
on location, capacity for generation,, efciency, operation, plant
lifetime and other factorsThe efciencies and lifetime are taken as
given, but dorily reect the actual specications and performance
. The usual criticisms of the misuse of the LCOE is thatoutdated
data, do not consider the real plant utiliza-technology, do not
capture the correct lifetime of theo not account for the full costs
of the plant, such as de-ing, carbon and other environmental costs,
insuranceuclear) and fuel subsidies (fossil) [32,52,53].
-
4472 K. Branker et al. / Renewable and Sustainable Energy
Reviews 15 (2011) 4470 4482
Improvements to the LCOE for solar PV can be made oncerealistic
assumptions and justications are given, real nancingvariability is
considered, and consideration is made for techno-logical and
geographical variability. Understanding the true costs,energy
production and system specications would improve thecapabilities of
LCOE software like the Solar Advisor Model (SAM).2
2.1. Estima
In generhigh comp[3,4,10,11,1these studidropped drOne of the
California Elumps solarinclude a raforward looinvestor-owconsistent
limitations.strated thatsources in plants. Anoreport, whiall
technolothin-lm anof incentive
The Onta(through a as the pricgenerator ttion, operaover the
plsion costs [6report by Gimethod incthat the meysis. It shoupart
of the ignores biowith differe
Table 1 America sinspecicatioordered froshowing thwith 30 yeathe
LCOE renot fully coreporting ofor the relatfrom elsewbeing reprethe
assump
3. LCOE m
In this pa correct mwhere few
2 https://ww
considering energy management strategies [37,63]. Calculating
theLCOE requires considering the cost of the energy generating
systemand the energy generated over its lifetime to provide a cost
in $/kWh(or $/MWh or cents/kWh) [27,30,32,34,49]. Many have noted
thatLCOE methothat it is cuaccount for
s expomport e
sumted s27,32tion f the
outpt or .
LCOE
(1 +
nginer y
, theentd, op
or sown iancinniti
it mnnects ackives w
=
hat wan ar
in a lied
with by msolaW/y
the nr thef kW
majt of
depng coves mlar Pimathe m,67], st cotes for solar PV LCOE
al, estimates for LCOE for solar PV tend to be fairlyared to
alternatives based on common
assumptions4,15,18,19,25,3234,36,37,41,49,5462]. Note thates are
all highly time dependent as the cost of PV hasamatically in the
last several years [9,11,18,19,49].most clear recent LCOE reports
was completed by thenergy Commission in 2010 [14]. Although the
report
PV technologies with a life of only 20 years, its meritsnge of
cost estimates, projections for variables allowingking values, a
range of project types (Merchant; IOU,ned utilities; POU, publicly
owned utilities) and aset of assumptions with detailed justications
and
It should be noted that this report has already demon- solar PV
can be less expensive than traditional energyCalifornia when
considering peak power natural gasther recent reliable report is
Lazards LCOE consultingch lists all the key assumptions made in the
analysis ofgies (PV is split into the two dominant technologies,d
crystalline silicon), considering price ranges, effects and effect
of carbon emission costs [58].rio Power Authority (OPA) in Canada
considered LCOEmethod called levelized unit electricity cost or
LUEC)e (escalating with ination) that would be paid to ahat equals
the present value direct costs (construc-tion and decommissioning)
for the energy generatedants lifetime and included connection and
transmis-3]. Apart from having no estimates made for solar PV,
abson et al. [53] outlined several deciencies in the LUECluding not
fully capturing current and future costs sothod cannot be
considered an all-inclusive cost anal-ld also be pointed out that
the OPA LUEC analysis asIntegrated Power System Plan like many
other LCOEsphysical, social and economic externalities associatednt
supply mix options [53].summarizes several solar PV LCOE results in
Northce 2004 for variables including technology, year, plantns,
lifetime, loan and incentives, and location roughlym best to worst
in terms of reporting and methodology,at solar PV gets a 2025 year
lifespan in most studiesrs considered for projections. As can be
seen in Table 1,sults vary by more than a factor of four and many
dover assumptions. From the survey, it is clear that betterf LCOE
assumptions and justication is required evenively few variables
chosen. Some studies quote a valuehere without restating the major
assumptions or casesented [3,4,33,36,37]. This paper attempts to
improvetions used and the clarity of the LCOE methodology.
ethodology
aper, the LCOE of solar PV is reviewed and claried andethodology
is demonstrated for a case study in Canada,LCOE calculations have
been done for solar PV when
w.nrel.gov/analysis/sam/.
LCOE imore cand Sh
Thegenerafrom [calculaning oenergytial cosfrom 1
Tt=0
(
Rearravalue p
LCOE =
Finallyinvestmnancecosts fas shofor ntial deprices,and
coprojecincent
LCOE =
Note tis just eratedmultipenergyminedsolar inkWh/kplyingper
yeaunits o
Thethe cosis veryfacturiinitiatitial sothe esthave t[11,38tion
codology is very sensitive to the input assumptions, suchstomary to
perform a sensitivity analysis [30,32,65] to
any uncertainty. The general calculation method forressed by
Eqs. (1)(3) [18,27,30,32,34,35,49,66] whilelicated expressions can
be pursued in Darling et al. [30]t al. [27]. Table 2 summarizes the
nomenclature.
of the present value of LCOE multiplied by the energyhould be
equal to the present valued net costs (adapted,49]) in Eq. (1). It
should be noted that the summationstarts from t = 0 to include the
project cost at the begin-rst year that is not discounted and there
is no systemut to be degraded. Other methods can include the
ini-
down payment outside the summation, with t starting
t
r)t Et)
=T
t=0
Ct
(1 + r)t(1)
g, the LCOE can be found explicitly assuming a constantear in
Eq. (2).Tt=0Ct/(1 + r)
t
Tt=0Et/(1 + r)
t(2)
net costs will include cash outows like the initial (via equity
or debt nancing), interest payments if debteration and maintenance
costs (note: there are no fuel
lar PV) and cash inow such as government incentivesn Eq. (3). As
such, the net cost term can be modiedg, taxation and incentives as
an extension of the ini-on [30,65]. If LCOE is to be used to
compare to gridust include all costs required (including
transmissiontion fees if applicable) and must be dynamic with
futurenowledged in the sensitivity analysis. In this paper, noill
be considered.
Tt=0(It + Ot + Mt + Ft)/(1 + r)
t
Tt=0Et/(1 + r)
t
Tt=0(It + Ot + Mt + Ft)/(1 + r)
t
Tt=0St(1 d)
t/(1 + r)t(3)
hile it appears as if the energy is being discounted, itithmetic
result of rearranging Eq. (1). The energy gen-given year (Et) is
the rated energy output per year (St)by the degradation factor (1
d) which decreases the
time. The rated energy output per year can be deter-ultiplying
the system size/capacity in kW by the local
tion that takes capacity factor into account in the units:ear1.
Traditionally, this value is determined by multi-umber of days in
the year by average number of hours
solar PV system operates by system size to get the nalh/year.or
generation cost for solar PV is the upfront cost andnancing the
initial investment, which means the LCOE
endent on the nancing methods available and manu-st reductions.
Thus it has been argued that policy andust focus on this hurdle to
make distributed residen-
V affordable [8,9,15,19,28,49,55,56]. When surveyinges as seen
in Table 1, residential PV systems tend toore expensive LCOE due to
lacking economies of scaledespite amortization facilities and lack
of interconnec-mpared to utility scale PV [19]. The majority of
this paper
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K.
Branker et
al. /
Renew
able and
Sustainable Energy
Review
s 15 (2011) 4470 4482
4473
Table 1Summary of LCOE estimated from various sources in North
America.
EstimatedLCOE ($/kWh)
Technology Year Plant specications Life Financing and incentives
Location and solar resource Ref.
0.280.46 Solar PV (includingtracking 0.5%/year degr.)
2008 Residential ($7.5/W, CF 1433%) 30 No subsidies (30 year
mortgage,100% nanced, 6% IR, 6% DR, 35%TR)
Various cities in USA(10002500 kWh/m2/year)
[11]
0.200.32 Solar PV (includingtracking 0.5%/year degr.)
2008 Residential ($7.5/W, CF 1433%) 30 With subsidies covering
30% initialcost (30 year mortgage, 100%nanced, 6% IR, 6% DR, 35%
TR)
Various cities in USA (10002500kWh/m2/year)
[11]
0.150.80 Solar PV single axis 2009 25 MW (CF 27%, $4.55/Wp) 20
With and without tax benets, andother incentives (merchant,
IOU,POU)
CA, USA [California EnergyCommission]
[14]
0.150.20 Solar PV-crystalline 2009 10 MW (CF 2027%, $5/Wp) 20
Lower price includes incentives USA [58]0.120.18 Solar PV-thin lm
2009 10 MW (CF 2023%, $4/Wp) 20 Lower price includes incentives USA
[58]
0.16 (year 1) Solar PV 2010 Large scale ($3.00/W, CF 21%) 20/100
20 year, 6% IR, no incentives or tax USA Southwest [49]
0.3160.696 Solar PV January 2011 2 kW ($7.51/W) 20 5% cost of
capital (tax andincentives excluded)
Global [used 5.5 sun-hours and 2.5sun-hours as high and low
sites]
[64]
0.1690.372 Solar PV January 2011 500 kW ($3.98/W) 20 5% cost of
capital (tax andincentives excluded)
Global [used 5.5 sun-hours and 2.5sun-hours as high and low
sites]
[64]
0.3190.702 Solar PV December2010
2 kW ($7.61/W) 20 5% cost of capital (tax andincentives
excluded)
Global [used 5.5 sun-hours and 2.5sun-hours as high and low
sites]
[31]
0.1710.376 Solar PV December2010
500 kW ($4.07/W) 20 5% cost of capital (tax andincentives
excluded)
Global [used 5.5 sun-hours and 2.5sun-hours as high and low
sites]
[31]
0.15 Solar PV (1%/yeardegr.)
2011 4.5 kW residential ($5/W, 10 yearinverter life)
35 Not considered (SAM used) Phoenix, USA [19]
0.10 Solar PV (1%/yeardegr.)
2011 150 kW commercial ($4/W, 15 yearinverter life)
35 Not considered (SAM used) Phoenix, USA [19]
0.12 Solar PV (1%/yeardegr.)
2011 12 MW single axis at tilt ($3.9/W,15 year inverter
life)
35 Not considered (SAM used) Phoenix, USA [19]
0.12 Solar PV (1%/yeardegr.)
2011 12 MW two-axis conc. ($4.3/W, 15year inverter life)
35 Not considered (SAM used) Phoenix, USA [19]
0.32 Solar PV (1%/yeardegr.)
2005 4 kW (residential) ($8.47/W) 30 SAM (low values if
unnanced)effects of incentives, nancing andtax considered
Phoenix, USA [55]
0.18 Solar PV (1%/yeardegr.)
2005 150 kW (commercial) ($6.29/W) 30 SAM (low values if
unnanced) Phoenix, USA [55]
0.150.22 Solar PV (1%/yeardegr.)
2005 10 MW (utility scale) ($5.55/W) 30 SAM (low values if
unnanced) Phoenix, USA [55]
0.30 Solar PV (no degr.) 2007 Residential ($8.5/Wp) 30 Home
equity loan/mortgage, 90%debt, 6% IR, 28% TR, 30 year loanwith
government incentives
USA (average maps with statevalues given) (SAM used)
[56]
0.062 Solar PV 2006 3.51 MW, Utility Scale Pv xed atplate
($5.40/Wp, CF 19.5%)
30 No nancing cost due to pay-as-goequity (IOU), includes tax
credits
Springerville, Tucson, AZ, USA(1707 kWh/kW/year)
[59]
0.166 Solar PV 2003 5 MW ($4.16/W, CF 24%) 40 5% DR, no nancing
USA [26]0.269 Solar PV 2003 5 MW ($4.16/W, CF 24%) 40 10% DR, no
nancing USA [26]
0.248 Solar PV 2010 Roof top PV (projected) 25 Weighted average
cost of capital(6.4%)
AZ, USA (1700 kWh/kWp) [18]
0.294 Solar PV 2008 Roof top PV ($5.2/W) 25 Weighted average
cost of capital(6.4%)
AZ, USA (1700 kWh/kWp) [18]
-
4474K.
Branker et
al. /
Renew
able and
Sustainable Energy
Review
s 15 (2011) 4470 4482
Table 1 (Continued)
EstimatedLCOE ($/kWh)
Technology Year Plant specications Life Financing and incentives
Location and solar resource Ref.
0.40 Solar PV (1%/yeardegr.)
2009 Commerical ($6.7/W, CF 18%) 30 7% DR, no incentives
(nancingunclear)
USA [38,10]
0.4020.613 Solar PV (1%/yeardegr.)
2009 Rooftop ($7.20/Wp, CF 17%) 25 5%10% DR, no
incentives(nancing unclear)
AZ, USA [10]
0.3090.499 Solar PV (1%/yeardegr.)
2009 80 MW ($6.7/Wp, CF 19%) 30 5%10% DR, no incentives(nancing
unclear)
AZ, USA [10]
0.5610.860 Solar PV (1%/yeardegr.)
2009 Rooftop ($7.20/Wp, CF 12%) 25 5%10% DR, no
incentives(nancing unclear)
NJ, USA [10]
0.198 Concentrated solarPV (CSP)
2007 65 MW ($3.7/W, CF 22%) 30 7% DR, no subsidies (higher
O&Mthan roof top) (nancing unclear)
NV, USA [10]
0.170.249 Concentrated solarPV (CSP)
2009 80 MW ($4.4/W, CF 29%) 30 5%10% DR, no incentives(nancing
unclear)
USA [10]
0.1220.192 Concentrated solarPV (CSP)
2009 500 MW ($3.9/W, CF 23%) 30 5%10% DR, no incentives(nancing
unclear)
USA [10]
0.250.40 Solar PV(12%/year degr.)
2003 Utility Scale PV or residential($6.209.50/W)
20 With and without subsidies, taxes,etc. (nancing
uncertain)
CA, USA (2000:kWh/m2/year) [61] otherprojectionsmade
0.49 Solar PV 2010 1 kW (CF 20%, $8.73/Wp) 25 Residential
amortization USA [15]
0.1380.206 Solar PV thin-lm 2009 Large scale 20 MW (CF
1827%,$3.74.0/W)
20? With and without incentives,nancing?
CA, USA [25]
0.1350.219 Solar PV crystallinesingle axis tracking
2009 Large scale 20 MW (CF 2328%,$7.047.15/W)
20? With and without incentives,nancing?
CA, USA*done for different project zones
[25]
0.456 Solar PV (xed atplate)
2008 20 MW ($7.98/W, CF 26%) 30? Weighted cost of captial after
tax5.9%, 15 year accelerated Depr?
USA [41]
0.200.80 Solar PV 2007 Rooftop PV (25 kW) 20? No subsidies
Worldwide range for25001000 kWh/m2 solarinsolation -quoted from
range ofreports
[33]
0.200.50 Solar PV 2009 Rooftop (25 kW) ? No subsidies/incentives
World average quoted fromrange of reports
[3]
0.150.40 Solar PV 2008 Different applications (?) ? Variable
including taxes for USA (?) Different locations, USA (?) see [58]
[4]
0.19 Solar PV 2007 Large scale 20 Independent power
producernancing (no incentives)
Pacic north west, USA [60]
0.220.24 Solar PV 2007 Small scale 20 Independent power
producernancing (no incentives)
Pacic north west, USA [60]
0.255 Solar PV (solar cell) 2008 5 MW ($5.782/W, CF 21%) ? No
incentives, nancing for IPP USA [57]
0.200.50 Solar PV 2006 Varies at consumer level 20? No
incentives Canada [36]
0.20, 0.31 Solar PV 2004 2003 prices ? DR 10% and 15% (Sandia
Model,GenSim)
Chicago, USA [62]
0.3370.526 Solar PV-crystalline
2008 (2005price)
5 MW ($6.31%7.81/W, CF 1525%) 20 ? ? [34]
0.392 Solar PV 2008 5 MW ($7/W, CF 20%) ? ? Minera Escondida
Limitada coppermine (off-grid) South America
[34]
0.25 Solar PV 2010 2006 prices, includes storage ? ? USA
[54]
0.150.78 Solar PV 2003 ? ? ? Canada, taken from US studies
andconverted to Canadian $
[37]
degr., degradation rate; CF, capacity factor; DR, discount rate;
IR, interest rate; TR, tax rate; Depr, depreciation; IPP,
independant power producer; IOU, investor-owned utilities; POU,
publicly owned utilities; W, Wp assumed asmeaning the rated system
power (units displayed as referred in the sources); SAM, Solar
Advisor Model (NREL).
-
K. Branker et al. / Renewable and Sustainable Energy Reviews 15
(2011) 4470 4482 4475
Table 2LCOE calculation nomenclature.
Nomenclature
T Life of the project [years]t Year tCt Net cost of project for
t [$]Et Energy produced for t [$]It Initial investment/cost of the
system including construction,
installation, etc. [$]Mt Maintenance costs for t [$]Ot Operation
costs for t [$]FtrStd
will considepapers like
4. AddressLCOE for so
The maichoice of daverage systhe lifetime
4.1. Discou
Firstly, ttainty and tof discountvaries by
ciFurthermortechnologieThe choicenologies whsector favoubut these
msocial endetructure ansocial discosocial benecount rate (3.54.5%
[6inal discoun[30].
4.2. System
In genercosts assocadministranancing ccosts associin all
powemental andapart from cdent on the
3 Negative include carbonFor example, lutants from c[124].
dwelling. For example, in general, a thin-lm system is less
costlyper unit power than a crystalline silicon system [68].
Inverters havevariable prices, types and lives and the type of
racking and installa-tion needed depends on the house. Nonetheless,
most LCOE studiesreport an avtechnologyneeds to beand how
cogeneral, the[67], but st
pracng wes an
are rovidffer
costsdrastarizeor reUniteendixatiing cnt innanct paying tolar e
cann be iatioge, aup tolar Plar Pnergircumevel
loanand Sthe a
conctee pymehe LCesenethoreasing tthe ethoratesInterest
expenditures for t [$]Discount rate for t [%]Yearly rated energy
output for t [kWh/year]Degradation rate [%]
r costs in the context of residential systems while other[30]
cover utility scale.
ing major misconceptions and assumptions inlar PV
n assumptions made in the LCOE calculation are theiscount rate,
average system price, nancing method,tem lifetime and degradation
of energy generation over.
nt rate
he choice of discount rate comes with ample uncer-his is dealt
with using sensitivity analysis. The concept
rate puts a value on time preference on money, whichrcumstance,
location, and the time period considered.e, some investors vary
their discount rate betweens to reect their perception of its
nancial risks [26].
of discount rate can largely affect the energy tech-ich are
relatively more competitive [49]. The privaters higher discount
rates to maximize short-term prot,ay be too high to capture the
benets of long-term
avours undertaken in the public sector, such as infras-d energy
projects [49]. Governments often estimate aunt rate for rating
public projects that have long-termt. For example, in Ontario,
Canada, the real social dis-SDR) range used is 28%, with an
individuals SDR being3]. Finally, there is a distinction between
real and nom-t rate where ination is included in the nominal
rate
costs, nancing and incentives
al, for the solar PV system costs, there are the projectiated
with actual system, its design and installation;tive costs such as
insurance and interconnection;osts associated with the nancing
method and public
to bestdeclinifacilitirantiesmay pmay sulation not as summcosts
fin the
Deptrys taFinancernmeDebt interesspreadif the sincomtem
cadeprecmortgaloans (of a soogy, soother ein all csome dFIT.
TheSingh while wrongguaranated paallow tthe prloan mual
incextendWhile loan mlation ated with taxes. However, what is not
often consideredr generation technologies are the economic,
environ-
health cost of negative externalities.3 The system price,apacity
and manufacturing variability, is highly depen-
type of solar PV system and location and type of the
externalities for conventional electrical generation
technologies dioxide emissions, thermal and air pollution and
habitat disruption.
there are costs due to health problems associated with the air
pol-oal-red generation [122,123] and for global climate
destabilization
certain nashould be nessarily whconstructs mandate.
4.3. System
The nabe the man[75,76]. Hoels is well erage for solar PV, not
distinguishing between different types and balance of system (BOS)
costs. If averaging
made for simplication, then the assumptions mademmon they are
should be reported (such as in [67]). In
BOS and labour costs represent 50% of the system costrategies
are being developed to halve these comparedtice [69]. Solar
manufacturing prices have been rapidlyith economies of scale
through turn-key manufacturingd industrial symbiosis [68,70,71].
Inverter life and war-being extended to 10 years [11,72] and
micro-inverterse an economical choice for residential systems,
whichfrom partial shading challenges [73,74]. Finally, instal-
will decrease with technological experience, althoughically
[15]. Recent estimated installed system costs ared in Table 3. It
should be noted that average installedsidential systems are lower
in Germany and Japan thand States [67].ng on an individuals credit
history and the coun-on system, different nancing methods can be
used.an come in the form of loans, a second mortgage, gov-centives,
third party nancing and equity nancing.ing (loans or mortgages) is
usually preferable sincements are non-taxable in some systems and
it allows
he cost of the system over a longer period. Furthermore,PV
system is recognized by a feed-in-tariff program, the
be recognized as business activities for which the sys-used
against taxes via the capital cost allowance in assetn [67].
Finally, although many are adverse to a secondmortization allows
for a longer loan term than usual
40 years). This is important given the long working lifeV system
(greater than 20 years). As a proven technol-V should be able to
obtain similar nancing methods asy technologies, although this is
not necessarily the casestances as was recently shown in the
difculties for
opers to nd nancing for projects under the Ontario
method effect on LCOE was recently considered byingh [28]. They
indicated that the LCOE value is static,ctual cost of electricity
increases, which results in thelusions for grid parity. Further,
the loan period is for theeriod and not the working life of the PV
system. A gradu-nt instead of an equated payment loan was suggested
toOE of the solar PV to escalate like grid electricity. Thus,
t day LCOE would be lower than with the traditionald, increasing
as the standard of living of the individ-ed. The new loan method
was suggested since simplyhe loan term did not reduce the LCOE
signicantly [28].analysis was not done for a specic system, the
newd was done for different terms, interest rates and esca-,
illustrating that grid parity could occur today underncial
circumstances with the new method. Finally, itoted that what is
mathematically feasible in not nec-at is socially feasible based on
the current economicof society and such an approach would require a
policy
life for solar PV
nceable life for a solar PV system is usually considered
toufacturers guarantee period which is often 2025 yearswever,
research has shown that the life of solar PV pan-beyond 25 years;
even for the older technologies, and
-
4476 K. Branker et al. / Renewable and Sustainable Energy
Reviews 15 (2011) 4470 4482
Table 3Summary of recent solar PV installed system costs.
Solar PV technology Installed cost [$/Wp] Project scale
Crystalline ( UtilityCrystalline (Crystalline (Thin-Film
CdThin-Film a-Crystalline aCrystalline aCrystalline aCrystalline
aCrystalline aCrystalline a
a Estimate bb Average ofc Average of
Table 4Effect of degra
Degradation
0.2% 0.5% 0.6% 0.7% 0.8% 1.0%
current oneyear lifetim[28] expliciworking lifeguarantee pthe
loan terwould still was plottedloan term, awould be susidered
[49which it cothat the opethe asset. Sicosts rise, this
considerelife, the asseexpensive tare due to rcleaning ancosts that
wthe life of mrated since nitely theconsidered able energywhich
thereof degradatthe system(Pmax).
Finally, tfor differen(c-Si) PV mestablishedprovided th20 years
oriimmature tels are belo
.3% f the lbut mtemhe ual prd th
es th gain
grad
ermis onn pron wire ofation
[49] PV ster
[77]es ha
year.Europe)a 5.00 China)a 4.42 Japan)a 5.02 S/CdTea 4.28
Si/-Sia 3.52 nd thin lm (USA)b 7.50 nd thin lm (Germany)c 7.70 nd
thin lm (Japan)c 4.70 nd thin lm (USA)c 5.90 nd thin lm (CA,USA)b
7.30 nd thin lm (CA,USA)b 6.10
ased on module prices [68]. installed systems [67]. installed
systems excluding sales taxes [67].
dation rate and performance requirement on system life.
rate Lifetime to 80%Pmax [years]
Lifetime to 50%Pmax [years]
100 25040 10033 8329 7125 6320 50
s are likely to improve lifetime further [7781]. A 30e or more
is becoming expected [82]. Singh and Singhtly called for scientists
to give an authentic gure on the
of solar PV systems to improve condence for the loaneriod [28].
An important consideration is that even ifm was shorter, the energy
output from the PV panelscontinue at a negligible cost. If the LCOE
for each year
over time, with different equations before and after thedjusting
for the annualized loan cost, the yearly LCOEbstantially less after
the loan term than currently con-]. In general, the working life of
an asset is the life forntinues to perform its tasks effectively.
It is often trueration and maintenance (O&M) costs rise with
the age ofnce annual capital costs tend to decline and annual
O&M
was 17deneevent, the sysises tmaterision, anlifetimedge is
4.4. De
Detdependsulatioand catems adegradrantiessiliconthat
fainitelymodulthe 1%Table 5ere is a minimum average cost per year
at which point itd the economic life of the asset [83,84]. At the
economict is then replaced or refurbished, since it becomes moreo
run the asset thereafter. For solar PV, the O&M costseplacing
inverters (usually every 10 years), occasionald electrical system
repairs [49,85], which are relativeill decrease with time. It
should also be noted thatany conventional power plants is much
longer than
they tend to be refurbished or re-commissioned inde- same could
be true of solar PV plants [49]. Thus, what isthe economic life of
the system depends on the accept-
output, which depends on the degradation rate (rate at is a
reduction in output). Table 4 illustrates the effection rate and
acceptable performance on the lifetime of
in terms of a percentage of maximum power output
he lifetime and reliability of solar PV can be consideredt solar
PV technologies. Crystalline silicon wafer basedodules offer the
best in-eld data being the technology
on the market for the longest time. Skoczek et al. [77]e results
for c-Si PV modules in the eld for more thanginally characterized
between 1982 and1986 (relativelyechnologies). In their ndings, more
than 65.7% of pan-w the 1% per year degradation rate (mean power
loss
In anothnology) andof 0.2%, alththe earlier dFurthermorat least
15 years [78]. actual in-ecluded thatconsidered
It shouldsilicon (a-S[87]. In a-Siof exposurereached [88Si:H PV
are value, ignorcompound gies, the outby conventogy,
becausperformancbeen shownnometers
cUtilityUtilityUtilityUtilityCapacity weighted average
(2009)Residential (25 kW) (2009)Residential (25 kW)
(2009)Residential (25 kW) (2009)Residential 10 kW (2010)>100 kW
(2010)
or 21 years average). For PV technology, it is difcult toifetime
since ordinarily there is no single catastrophicore gradual aging
and degradation. The end of life of
has not been reached once the power output still sat-ser.
Gradual degradation occurs due to chemical andocesses associated
with weathering, oxidation, corro-ermal stresses [78,77]. Current
research would improverough greater quality in production processes
as knowl-ed about failure mechanisms [78,86].
ation rate and energy output
ning the energy output of solar PV over its lifetime assumed
degradation rate of the panels. Module encap-tects against weather
factors, moisture and oxidation
thstand mechanical loads (e.g. wind and hail). PV sys-ten nanced
based on an assumed 0.51.0% per year
rate [65] although 1% per year is used based on war-. This rate
is faster than some historical data given for[77,78,86]. In a study
on c-Si modules, it was founddegradation occurs earlier and then it
stabilizes indef-. In the study, more than 70% of 1923-year-old
c-Sid an annual degradation rate of 0.75%, still less than
assumed [77]. The failure sources are summarized in
er study, c-Si PVs installed in 1982 (much older tech- tested in
2003 had an annual power degradation rateough this rate was faster
in the latter 4 years [78]. Thus,egradation must have been slower
than 0.2% per year.e, accelerated aging tests indicated that the
panels hadyears more of acceptable performance beyond the
21Finally, another study indicated that the degradation ofld c-Si
cells is 0.20.5% per year [86]. It can thus be con-
in general, a degradation rate of 0.20.5% per year is reasonable
given technological advances.
be noted here that there is a special case for amorphous
i:H) PV, which suffers from light-induced degradation
PV cells, performance degrades rapidly in the rst 100 h to 1 sun
illumination until a degraded steady state is90]. The effect has of
yet not been eliminated, but a-
sold with warranties valued at the degraded steady stateing the
above specied initial performance. To furtherthe appropriate
calculations of such thin lm technolo-put of a-Si based solar cells
is generally under-predictedional techniques developed on
c-Si-based PV technol-e of the superior a-Si:H temperature
coefcients ande in diffuse light conditions [9193]. In addition, it
has
that the use of integrating photometers such as pyra-an directly
introduce errors in the prediction of a-Si PV
-
K. Branker et al. / Renewable and Sustainable Energy Reviews 15
(2011) 4470 4482 4477
Table 5Summary of power loss results for 204 modules installed
in 19821986 with 1923 years [77].
Averagelosses (%)
Std dev (%) Reasons
Power loss inatio
Loss in VOC (terminal)
f subs
Loss in ISC (sdelivered)
le agintercon
Loss in Fill Fto maximu
le agintercondation
system outa-Si:H PV ddepending Si:H coversspectrum wa-Si:H PV
wwider specthave been wson generalPV modulesmodules [9
4.5. Grid pa
As mentfor the costof solar PVsupplied elelectricity iLCOE is
notfor the totathe realisticto back calcto be to atta
Yang [15would suggcost-effecticlaimed. Thwere not amwrongfully
installed coCamstars Aper kWh of applied to trecycling at
5. Numeri
In Cana$0.17/kWh the LCOE fothe simplitions, the LCvariables toa
realistic sare declininthe relativefor the base[11,78,86], uof 1.5%
of tcompanies)the total ins
7,72gh loent Ktor oe ranin th
1Awith
is 1ere d 10
OE dend int fave LCOs $0.7. Noto haours
2, waryinnt raould red [e it irrant
3 sstemfromscouWh/rease
$2.2ptionpeteime, easet eco
4 ill on are prmin17.3 23.5 Comb
open circuit voltage potential across 10.6 18.5 Loss o
hort circuit current maximum current 5.8 20 Moducell in
actor, FF (ratio of maximum actual powerm theoretical power)
9.1 22 Moducell indegra
put, and over the course of a year, the output from anevice can
vary by 1020% due to this spectral effect,on seasonal and
locational effects [94102]. Because a-
only a small fraction of this range, differences in theill have
an amplied effect on the performance of anhen compared to c-Si PV
devices, which cover a muchral range because of its smaller
bandgap. These effectsidely documented [94,95,97103] and is the nal
rea-
ly attributed to the well-documented claims that a-Si:H will
produce more energy per rated power than c-Si PV5].
rity
ioned before, grid parity is considered a tipping point
effectiveness of solar PV, and entails reducing the cost
electricity to be competitive with conventional grid-ectricity.
For parity, the total cost to consumers of PVs compared to retail
grid electricity prices. Although the
the same as retail electrical prices, it is used as a proxyl
price to be paid by consumers, adding in as many of
costs as possible. The LCOE methodology is then usedulate what
the required system and nance costs needin grid parity.] determined
that a realistic examination of grid parityest that solar PV is
much further away from becomingve in distributed (residential)
systems than is normallye main problem Yang identied was (1) many
analystsortizing all of the cost to the end consumers and (2)
considering $1/Wp manufactured cost instead of retailst when
calculating grid parity [15]. However, applyingdvanced Product
Quality model suggests that the costthe solar industry can be
shifted down by 1317% whenhe manufacturing supply chain from design
to system
end of life [23].
cal example in Ontario, Canada
da, electricity prices range from $0.06/kWh toin major cities
[51] so that as a proxy for grid parity,r residential solar would
need to be in this range. Usinged method outlined in Section 3 and
improved assump-
[4,11,6althourepresity faca viablstates
Fig.varies outputrates w4.5% anthe LCterm ais mosest, thLCOE
ilationsyears tof cont
Fig.with vdiscourate wcompabecausPV wa
Fig.the syvaries real di1270 klife inccost ofassumto comof
lifetto decrcurren
Fig.outputoutputto deteOE was calculated for Ontario, Canada
using ranges of test sensitivity as an example. As shown in Table
5,tarting fully installed system price is $5/Wp1 as pricesg and
thin-lm PV would show better performance inly cloudy region of
Ontario [9698]. Other assumptions
example case include: a degradation rate of 0.5%/yearsing 100%
debt nancing, an operating (insurance) cost
he total system cost (average quotes from 3 insurance and a
maintenance (inverter replacement) cost of 9% oftalled system cost
(ranged from 6 to 9% in US for 2009)
installed syand 1270 kWcost of
-
4478 K. Branker et al. / Renewable and Sustainable Energy
Reviews 15 (2011) 4470 4482
Fig. 1. LCOE idiscount ratesdegradation ra
6. Discussi
Table 1 gand inconsito be addregiven, the fon $/kWh for solar PV
system varying interest rates, loan terms and (A, 0%; B, 4.5%; C,
10%) assuming initial installed system cost of $5/Wp,te of
0.5%/year and energy output of 1270 kWh/kW/year.
on
ives an example of the existing varying LCOE estimatesstency of
reporting assumptions. Thus, the rst pointssed is the reporting of
LCOE. With the value or rangellowing assumptions must be provided
and justied:
Fig. 2. LCOE inassuming zeroenergy output
Fig. 3. LCOE fzero interest loutput of 1270
1. Solar PV 0.5%/yea
2. Scale, siz(resident
3. Indicatiographic l
4. Lifetime sarily eq
5. Financiacost of ca
6. Additiontion, carbshould b
A simple yeto calculate $/kWh for solar PV system varying system
costs and discount rates interest loan, 30 year lifetime,
degradation rate of 0.5%/year and
of 1270 kWh/kW/year.
or lifetime of solar PV system versus initial cost of the system
for aoan, discount rate of 4.5%, degradation rate of 0.5%/year and
energy
kWh/kW.
technology and degradation rate (e.g. c-Si or a-Si:H, andr
degradation rate).e and cost of PV project [including cost
breakdown]ial, commercial, utility scale/# kW, # MW, $/Wp).n of
solar resource: capacity factor, solar insolation, geo-ocation, and
shading losses.of project and term of nancing (these are not
neces-ual).l terms: nancing (interest rate, term, equity/debt
ratiopital), discount rate.al terms: ination, incentives, credits,
taxes, deprecia-on credits, etc. (these need not be in the
analysis, but ite stated whether or not these are included).
t correct methodology with clear assumptions was used the LCOE
for solar PV in Ontario, Canada. The results
-
K. Branker et al. / Renewable and Sustainable Energy Reviews 15
(2011) 4470 4482 4479
Fig. 4. LCOE floan, discount
as presentesidering theconstrainininclude Mospecic varcosts and
ecircumstantechnologic
The highdle to adopFigs. 14, locount rate nancing istime of
thePositive disin the near far term. Ifcoal-red pwhich has na
positive dConsumptivfuel costs ththat requirnegligible cment,
capitconcept is l
Fig. 3 decould resulfor residentprovide eitit was as
ifgovernmenallowing goa greater scmeant to renance), whicontracts
gucial instituthistories an
The miscdiscussed hteed and ne
facilities do not acknowledge this extended time, the LCOE
shouldstill consider the working life for the operation and
maintenancecosts and energy production [49]. In the case of
degradation rate,
nctions may be needed in the LCOE calculation to recognizer
som
have modes usally, a
feasstani andpply r pro imolar
be mid past in811orescn, b
beins oldn athey c
neecultntinuable ater ives 1]. Cer c
g BOd adoverationemerm
le. Focity ttabng re
be r, for or energy output versus initial cost of the system for
a zero interest rate of 4.5%, degradation rate of 0.5%/year and 30
year lifetime.
d in Figs. 14 with contours give a useful way of con- LCOE for
various systems and specications withoutg the assumptions. Other
sensitivity techniques wouldnte Carlo Simulations [30].
Furthermore, the effect ofiables can easily be seen once the
calculations take allnergy into consideration. For Canada, under
specicces, solar PV LCOE grid parity is a reality once certainal,
pricing and policy hurdles are addressed.
initial upfront cost of solar PV still seems to be a hur-tion,
despite declining cost of systems. As shown inwer interest rates,
longer term loans and higher dis-
are preferred in combination. The preference for debt due to the
ability to spread out the cost over the life-
system, and is highly inuenced by the discount rate.count rates
mean cash inows (benets) are preferredterm, whilst cash outows
(costs) are preferred in the
comparing a consumptive technology like nuclear orlants to a
capital intensive technology like solar PV,o fuel cost that is
susceptible to price uctuation risk,iscount rate biases towards
consumptive technologies.e technologies involve long installation
times and highat would seem preferred over a capital intensive
plant
step futhat fowouldfailurethe rat
Finnot becircumHawaithe suinvertetinue tsome sshoulding grto
inve[15,10pact long rution ofmore aPV, eveual if tenergyis a
difstill corenew
Greincent[23,11customportinreduceFITs.
Gdardizmanaglong-tetainabelectrithe proroundishouldwouldes high
upfront costs in a short installation time, butosts thereafter. In
terms of sustainable energy manage-al intensive technologies should
be preferable, but thisost in the current economic
system.monstrated that a zero interest loan over a long periodt in
the lowest LCOE values. Financing still is an issueial systems and
incentives should be considered thather zero interest loans or
offset interest costs so that
there was no interest. A zero interest loan from thet would work
for distributed PV community programs,vernments to meet their
renewable energy targets onale. The Ontario FIT Program is the
opposite incentiveduce the effect of long-term costs (interest and
mainte-le providing some economic return. Again, although
FITarantee a price for the energy, as seen in Ontario, nan-ions
still consider loans in terms of individuals creditd not the value
of the contract.onception about system lifetime and degradation
wasere. Solar PV lifetimes will often be greater than guaran-w
industry norms will at least be 30 years. If nancing
revenue. Ficleaner andnologies toan income greater
inctainability should asseincome claenergy targsupported athey
could dtions with creation [12
7. Conclus
As the soof PV projecost of elecother electre systems, more
energy is produced in earlier years and a higher weighting with a
positive discount rate. Ases and degradation mechanisms are better
understood,ed in LCOE can be systematically improved.lthough Yang
[15] stated that some system costs wouldible for grid parity, the
fact is that it is under certainces grid parity has already been
reached in places like
California [107] and much can still be done to improvechain to
reduce costs [23,67,70]. Solar module prices,ices, system and
component lives and BOS costs con-prove as research and development
evolves, puttingmanufacturers at grid parity today [23]. In
addition, itentioned that cost effectiveness (or in this case
obtain-rity) is not necessarily a sufcient driver for people
any new technology including residential PV systems4]. An
example is the adoption of energy efcient com-ent light bulbs
(CFLs) that are more economic in theut have a higher upfront cost
giving them the percep-g expensive [110]. In Canada, CFLs are being
adopteder technology (incandescent) are banned. The LCOE of
grid parity may be of little consequence to an individ-annot
reap near term prots (savings) or the required
ds as the next best alternative. Concerning grid parity, it
endeavour considering, fossil fuels and nuclear powere to receive
larger indirect and direct subsidies than
energy technologies [115119].adoption of solar PV will be driven
by governmentand policies and solar PV supply chain
innovationonsumers would prefer innovative products, greaterare,
increased reliability and quality of panels and sup-S, greater
standardization in installation quality andministrative time for
government incentives such asnments can monitor and create the
policy for stan-
to improve quality and provide training and interfacent
education [111]. Government policies need to haveobjectives and
certainty so that incentives are sus-r example, encouraging third
party sale of solar PVo the grid beyond the FIT at a retail price
would increaseility of the system. Furthermore, if public policies
sur-tail, insurance and nancing are aligned, then solar PVecognized
for its added value, like a swimming poola residential dwelling
except that PV would producenally, tax breaks (sale or income) can
be considered for
renewable technologies over fossil fuel based tech- encourage
their adoption. One study indicated thattax benet for purchase of
the technology could haveentive than low interest loan [120]. To
ensure sus-of solar PV adoption through incentives, governmentsss
the impact of incentives on adoption for differentsses and
determine which will be best to meet theirets. Finally, in the same
way that governments havend invested in conventional power
generation projects,o so for PV manufacturing to be able to reap
cost reduc-economies of scale and other social benets like
job1].
ions
lar photovoltaic (PV) matures, the economic feasibilitycts is
increasingly being evaluated using the levelizedtricity (LCOE)
generation in order to be compared toicity generation technologies.
A review of methodology
-
4480 K. Branker et al. / Renewable and Sustainable Energy
Reviews 15 (2011) 4470 4482
and key assumptions of LCOE for solar PV was performed. The
LCOEcalculations and assumptions were claried and a correct
method-ology and reporting was demonstrated for a case study in
Canada.It was found that lack of clarity in assumptions and
justications insome LCOEicy initiativis a need fodistributionset of
assumassumptionA higher inccations is resource. Givenancing teity
in specigrid electricincreases, Pgeous sourc
Acknowled
The authural Scienchelpful disc
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A review of solar photovoltaic levelized cost of electricity1
Introduction2 Review of the cost of electricity and LCOE2.1
Estimates for solar PV LCOE
3 LCOE methodology4 Addressing major misconceptions and
assumptions in LCOE for solar PV4.1 Discount rate4.2 System costs,
financing and incentives4.3 System life for solar PV4.4 Degradation
rate and energy output4.5 Grid parity
5 Numerical example in Ontario, Canada6 Discussion7
ConclusionsAcknowledgementsReferences