Hello.
Thank you for joining us for this section
of the tutorial, Methods and Demonstration
of LCOE and IRR Calculations, which will be
ran by myself, Mike Woodhouse and Kelsey Horowitz.
A review of the topics that our team worked
on: In the upper left you can see an overview
of the component manufacturing costs analysis
that Brittany and Kelsey went over earlier;
systems capital costs analysis that Vignesh
just went over in the previous section.
And today we’ll be diving into some examples
and technical details of project proforma
analysis and that’s what we’ll be diving
into in this section.
So zooming in on that graphic and discussing
the metrics that we’ll be shooting for,
they include LCOE, which you most likely have
heard of.
Another one, internal rate of return, which
has some advantages that we’ll discuss later.
And then a newer metric for us, the levelized
cost of solar plus storage, which is also
a proforma analysis involving cashflows.
And on the bottom you can see a graphical
representation of the cashflows that could
represent what occurs during a life of a PV
project beginning with the cost shown on the
far left, the upfront capital cost for the
installation.
So that’s the time from scoping the project
to getting it built and commissioned and finally
generating power.
The would be T = 0 in terms of kilowatt hour
generation.
Then another benefit shown on the top in addition
to the kilowatt hours shown is any incentives
that can be monetized like tax credits are
relevant in the US for Year 1.
Also depreciation incentives using a tax shelter
there can have benefits for PV systems.
And then also benefits are Feed In Tariff
or PPA revenues.
We’ll talk more in detail about that later.
And residual value on the far right, that
enters into the question of what is a PV system
and storage system worth at the end of its
lifetime?
For example, do the components have any recycling
value or are they a hazardous waste issue?
Or also residual value could also possibly
consider the kilowatt hours that could be
generated past the analysis period depending
upon how you define that term.
Another cost to track over the lifetime, the
lifecycle, in addition to the upfront capital
costs are O&M expenses and that includes preventative
and routine O&M.
Routine O&M could probably be something like
module cleaning if you have a set cleaning
schedule.
Preventative O&M could be vegetation management,
things like that, and asset management so
that’s managerial tasks for maintaining
the payments to insurance companies and whatever
have you.
[Laughs]
Then there can also be corrective O&M issues:
battery inverter repairs.
Unplanned weather events can also cause corrective
O&M responses so things – not all cashflows
in a PV project are known ahead of time.
You try and budget them and predict them as
best as possible, but corrective O&M is another
item that can enter into the picture at some
point.
So let’s first talk about the capital costs
for PV systems.
That was covered by Vignesh and I’ll just
summarize it again here.
These are representing module pricing and
total system pricing more for the US market,
not rest of world, so the pricing could look
higher relative to rest of world.
And then the breakdown of system costs that
we derive for Q1 2020 coming in around 95
US cents per watt.
So that’s the capital cost that we’ll
be using in the model example that I’m going
to go through.
And I should’ve clarified that that system
is for cost model results for a one-access
tracking utility scale system.
The next item is O&M and O&M includes the
preventative planned and unplanned items shown
here, and there can be more that can happen.
But here’s a list of them at any rate, and
we won’t necessarily dive too much into
the details of O&M for the purpose of this
briefer tutorial.
So now we have an overview of some of the
pieces that go into the project proforma.
And next let’s talk about how one calculates
LCOE and IRR for PV projects.
And what we’re going to step through is
how to do this within NREL’s system advisor
model, which is within NREL’s Strategic
Energy Analysis Center which our team is also
within.
So our team does work with the SAM team quite
a bit, actually.
And when you do LCOE modeling within SAM,
there are two modes that you can select, and
it really changes how the cashflow model works
within SAM.
The first mode is calculate the internal rate
of return mode.
This is within the SAM software.
This is where you click the button for specified
PPA price.
This is the mode for when the PPA rates are
set as input, so if you have a given PPA rate
schedule, which could be very relevant to
an actual project going in, and if you want
to incorporate changes like merchant rates
at some point in the proforma anything where
there’s the PPA rates are changing.
It’s easiest actually to do this in IRR
mode.
So in that you get to change the PPA rates
over the time period for the proforma.
And then the IRR by definition is a discount
rate for which the net present value of cash
inflows so for a PV project that would – utility
scale PV project, that would most likely include
PPA revenues and monetized tax benefits.
And it’s when the present value of cash
inflows equals the net present value of cash
outflows, so that would be the installation
cost and the O&M expenses.
So it’s the … what that means is that
a higher IRR corresponds to essentially more
PPA revenues or greater tax benefits and lower
installation costs and lower O&M expenses.
The other mode that you can calculate within
SAM is LCOE, and in that case that’s where
you specify the IRR target.
That is saying that the rate of return still
holding that identity where the net present
value of cash inflows equals net present value
of cash outflows.
So it’s when that IRR is fixed and you are
trying to calculate the PPA rate basically
to achieve that IRR.
And there are two different modes but they
have their advantages, disadvantages.
I actually – it’s not used as commonly.
I actually see a lot of advantages in doing
IRR mode primarily because of the flexibility
it has with inputting various PPA rates over
the life of the project and it’s just more
clear to understand the PPA revenue side.
So when you run the calculations solar resource,
obviously, it affects the result.
That’s intuitive.
The production of more kilowatt hours, if
you think about the simplified LCOE calculation,
dollars per kilowatt or just, yeah, simplified
LCOE dollars per kilowatt hour.
More kilowatt hours increases the denominator
so that lowers the LCOE.
In terms of cashflows you can also think of
more kilowatt hours generating more PPA revenues,
but we’ll talk more about that later and
how that can improve IRR if you’re thinking
about it that way.
But anyway, we all know that lower LCOE is
in sunnier locations and some of the lowest
PPA rates that one will find are typically
in the sunniest locations of the world.
Now I’m going to step you through an example
of how one could do a conceivable technology
evaluation using LCOE IRR methods, and it’s
one where we want to examine the impacts of
different module warranties on PV project
economics.
So what do I mean by that?
Let’s look at these curves.
The top curve represents zero degradation
profiles so that would mean that the first
year energy yield that you get from the project
does not change over time.
There’s no degradation.
That is a hypothetical, completely theoretical.
I don't know that that’s ever been observed
in principle.
So in practice there’s – in silicon there’s
a lot of times a Year 1 D Rate given on the
module warranty datasheets and really these
datasheets, perhaps marketing materials as
much as anything, but looking at some module
datasheets, we found one for an n-Type module.
And the N-type module had the lowest Year
1 D Rate given of just two percent that we
could find.
And then for mono PERC modules, for example,
there typically seems to be a higher D rate.
Some can be as low as two percent, but what
we’re using in this example is what I’ve
called a conservative monoperk warranty degradation
profile.
So this is, again, taken from a module datasheet
and I’m calling it “conservative” because
it gives a high D Rate in Year 1 of three
percent and then a pretty high degradation
rate, relatively high degradation rate of
.7 percent per year for 25 years.
That compares to the anti-module of .3 percent
per year.
So the conservative warranty profile is higher
– relatively high Year 1 D Rate and then
a relatively high degradation rate.
One can find aggressive, you might call them,
mono PERC warranty degradation profiles where
there’s 2, 2.5 percent in Year 1 and then
I’ve seen some as low as .4 percent per
year as the degradation rate.
So there are different warranty profiles offered
by different modules and this is not to say
that n-Type is better than p-Type.
Let’s be clear we’re just looking at some
warranty profiles given the module datasheets.
And we want to translate that to impacts of
PV project economics.
You can see this within SAM by going to the
tab.
It’s within the SAM model called “lifetime
and degradation”.
It’s when you’re inputting the various
input parameters within SAM.
And then you’ll see pop up “annual DC
degradation rate”.
You can use a fixed value so that would be
applying one degradation rate across all years
or in this example we’re showing a higher
D Rate in Year 1 because module warranties
most recently, as far as I can tell, give
a different Year 1 D rate and then a higher
Year 1 D rate than the later degradation rate.
So if you want to input those customized inputs,
you need to go within SAM and edit the degradation
schedule.
Some tricks that I have found to do this include
if you’re doing it in Excel, if you’re
trying to program these numbers like 3, 3.68,
4.25 you can see going down, maybe you’ve
got a column with data in Excel.
Sometimes it does not paste exactly in the
SAM I found and I have to go through the Notes
app on a Mac.
For you PC users, I don't know what to tell
you.
[Laughs] Hopefully, you don’t have these
glitches but there are some tricks to swap
that from Excel to SAM.
Hopefully, you figure them out.
I wish you luck.
After you’ve input the degradation profiles
into SAM, you can calculate the project PPA
revenues over the life of the project.
And I’ll show you in the next slide what
this looks like more within an actual SAM
model.
But for now these are just results that you
could create on a spreadsheet.
You take the dollars per kilowatt hour or
dollars per megawatt hour more typically in
utility scale, PPA rate x the energy yield
x the system size and that’s how you calculate
PP revenues in dollars.
Just look at the units and you’ll see the
things cross out and give you the units of
dollars.
So, again, that’s variable PPA rates affect
PPA revenues at different years and then energy
yield.
Higher energy yield is going to create more
project revenues and then, obviously, bigger
systems would also in pure dollar terms generate
more revenues.
So in this example that I’ve shown, we’ve
taken the warranty profiles and multiplied
those three factors over the different years.
And to remind you degradation profiles are
applied against the first year energy yield.
So as the energy yield declines, the project
PPA revenues decline.
And so with those different warranty profiles
within SAM, you would calculate these different
revenue trajectories and you can see a difference
in lost revenues due to the different warranty
profiles.
Just to show you where this appears within
SAM is what I’m … after calculating project
revenues, the next step, the next line in
the SAM cashflow model and a lot of other
PV project proforma models is project earnings
before interest, taxes, depreciation and amortization
or EBITDA.
EBITDA = PPA revenues – O&M expenses.
So this is where your O&M factors come in
is at the EBITDA stage.
And what we’ve shown here, this example
of some $6.00 per kilowatt per year O&M expense.
That’s the Year 1 O&M expense, and to that
we’ve added a 2.5 percent real escalator.
So that is done after talking to some O&M
service providers.
A lot of them shared that it was their convention
to express O&M costs with an escalator, typically
understood in that on the order of two maybe
to five percent per year.
Presumably it includes maybe increased O&M
expenses due to time.
It’s just like budgeting for an extra O&M
budget.
Some people might hold O&M flat, in which
case the lines shown in this figure would
not be curved.
They would be completely flat across the top.
But if you look at this, even the zero degradation
profile is curving down because of the escalator
that we have included in O&M.
Without an escalator, the zero degradation
profile would be completely horizontal.
Now looking at the other degradation profiles,
the warranty degradation profile for the n-Type
versus the p-Type, again, the n-Type was projected
to generate more PPA revenues than the p-Type
conservative profile.
And so that does also translate to more EBITDA
for the n-Type and so the p-Type would have
some lost earnings due to the different warranty
profiles.
Again, this is just an example system based
upon warranty profiles, not saying at all
that n-Type is better than p-Type just looking
at warranty profiles.
So now you can see these results also in SAM.
It’s below revenues, as I mentioned, and
EBITDA, again, shows up as its own line item
and it’s PPA revenues – O&M expenses.
Now, to be honest, if you are doing technology
evaluation, I don’t see any problem with
stopping at EBIDTA because there you’ve
caught all of the technology factors essentially
including the degradation characteristics
and also the O&M aspects, so the technical
aspects of the PV project and storage project
could possibly end at EBITDA.
However, if you want to account for the interest,
taxes, depreciation, amortization so a lot
of the tax side, the financing side, then
you carry it some steps further, and then
you can get to LCOE and IRR.
LCOE and IRR are presumably after tax calculations
and so that factors into the next steps, and
it is beyond the scope of this tutorial to
go into all the different tax benefits and
how to monetize them even within SAM.
Different workshop altogether.
But just to summarize, if you did want to
go into SAM and input some representative
tax assumptions – and I’ll discuss the
US here – it’s understanding that a relevant
depreciation schedule is five-year MACRS.
That’s typical and in 2020 it’s possible
to qualify for a 26 percent investment tax
credit in the United States.
Next year it’ll be 22 percent for utility
scale and then in 2022 it is 10 percent.
So in the results of that shown here do this
over a 30-year analysis period assumed a $0.95
per watt capital cost that was given in the
earlier slide and from Vignesh.
We talked about the O&M expense and the energy
yield of 2.350.
It’s our understanding that’s close to
the mean.
I believe that was from an LBL study.
So when you do that and you can do this totally
– these results shown are actually SAM results.
Using a $30.00 per megawatt hour fixed PPA
rate, we calculated an improvement in IRR
of .93 percent or 93 basis points and a lowering
in LCOE by $1.2 dollars per megawatt hour
when the IRR is held constant at six percent.
Now if the technology generates more PPA revenues
over the lifetime of the project in principle
one could pay more upfront for the technology.
It has a higher net present value.
All of those PPA revenues in the future and
higher EBIDTA in the future can be translated
back to in the present value after taxes.
And what I’ve shown here is just an example
breakeven analysis for this example shown
here, and we calculate that the value of the
different warranty profiles works out to be
on the order of five to six cents per watt
which is quite remarkable if we consider rest
of world module pricing nowadays, not US pricing
but rest of world is probably, as far as we
hear, 20 or 25 cents per watt.
So this is the value of the module based upon
the warranty profile could be on the order
of 25 percent or so of the total module selling
price.
So this is an interesting topic we feel going
forward diving into the total value of the
module being more than just the initial price.
I just wanted to – it is with some hesitation
that I included this last slide, but I wanted
to show an equation roughly for LCOE and sometimes
I think as a community we like to look at
this because we’re trying to simplify it
and put it all on a PowerPoint or maybe something
that will fit within a paper.
Really LCOE and IRR calculations most likely
involved spreadsheets and proforma cashflow
analysis, but sometimes we try and come up
with an equation.
It’s an exercise in folly if you ask me.
[Laughs]
But nonetheless, here is one and the advantage
of it is you can highlight some technical
opportunities like in installation cost, lower
installation cost, lower LCOE, reducing the
numerator.
And installation costs can be reduced by improving
efficiency, lower component costs and then
also you get a lower installation cost for
fixed tilt versus tracking, for example, the
system architecture.
But when you do LCOE, you have to consider
energy yield and so maybe there again if it
improves energy yield and PPA revenues, it
can be worth more paying more upfront initially.
The other important part of LCOE is monetizing
any tax credits and so an item within this
equation is depreciation.
That’s a significant tax benefit – can
be and another one within the United States
anyway is the investment tax credit.
But if you are not in the US and doing LCOE
calculations, I would encourage you to also
research what tax incentives can be monetized
and would be relevant for your proforma analysis
because it can significantly impact the results.
The other – the denominator, the capacity
factor term basically, energy yield.
That is the kilowatt hours generated.
So more kilowatt hours increases the denominator,
lowers LCOE and that, of course, is the function
of the system location, the orientation, its
tilt angle, whether it’s tracking or not.
Bifaciality is another hot topic now for increasing
energy yield.
Temperature coefficient plays that’s where
that comes in and low light level efficiency
if that’s relevant at all so climate effects
also affect the capacity factor term, and
that’s why greater solar resource equals
lower LCOE.
The other one, recycling and repowering, we
didn’t talk about that.
But the recycling or repowering ideas could
also factor into residual value.
And also the residual value of remaining kilowatt
hours if the project was ended should be considered.
Another factor that’s kind of a liability
driven in LCOE calculations since the discount
rate is fixed is the PV module and system
reliability.
Presumably more reliable systems also have
benefits in lower discount rates.
They lower O&M expenses and, yeah, numerous
benefits.
And that is the end of my section, thank you.
And next I will hand it to Kelsey.
All right, now I’ll walk you through two
NREL tools that you can use for calculating
levelized cost of energy or LCOE.
The first is NREL’s System Advisory Model
or SAM.
There’s a link to SAM’s website here.
It has a lot of different features, including
very sophisticated financial models, many
different options for modifying the specifics
of module and system technologies and design
and for PV the ability to pair with storage
and look at how that could impact your project
economics.
This can and has been used in detailed site
planning and analysis, and we also use SAM
on our team for creating the benchmark LCOE
numbers that come out in our annual reports.
But some researchers find that SAM has a learning
curve and can be a bit of black box and difficult
to accurately and quickly understand potential
impacts of different R&D directions without
potentially introducing some confounding factors
if you don’t really know what you’re doing.
So because of that, we introduced NREL’s
Simplified Online PV LCOE Calculator that
also has a link to it here, and this is a
much more simplified tool.
It’s just online and it’s specifically
targeted at PV researchers who want to quickly
explore the potential impacts of different
high level R&D directions.
This is also PV specific whereas SAM allows
you to calculate LCOE for a myriad of different
energy technologies.
It’s not as accurate or as fully featured
as SAM so I wouldn’t use this for detailed
project planning.
On the other hand, it does include some things
that SAM doesn’t like a breakdown of the
cost components within a PV module.
One caveat to this is that it was last updated
in mid-2018, which I’ll talk about a little
bit more when I demo the tool.
And we are planning an update for the calendar
year so, hopefully, that’ll be updated and
in the meantime this can still give you a
rough sense of potential value of different
R&D directions.
So now I’m going to go through and actually
demo each of these tools for you.
I’m going to walk you through the comparative
PV LCOE calculator.
It has the web address in the slide deck as
well, but it’s just NL.gov/PV/LCOEcalculator.
And, again, this tool’s really meant to
be a simple way for researchers to quickly
compare incumbent technologies to different
proposed technologies or R&D directions to
give some sense of their potential value if
you don’t have bandwidth or expertise to
really fully dive into SAM and make sure that
you’re getting a reasonable result with
it.
So this is a somewhat simplified model and
this is what it looks like.
You can see there’s this intersection here
and then the blue box called Baseline and
then a green box called Proposed.
So this blue box Baseline is basically meant
to represent an incumbent technology that
you would want to compare against.
And if you click this preset button here,
you can see that there’s a few different
baseline preset options to select from.
So you can choose mono-Si, multi-Si or CdTe,
which are the technologies with the largest
market shares today.
You can also select a package type so glass-polymer
or glass-glass and a system type currently
fixed tilt, utility scale, single-axis tracked,
utility scale and roof-mounted, residential
scale are supported.
So we don’t have commercial mounted onto
commercial rooftop in here at this time.
And then you pick a location.
You can see there’s one location per state,
so the state is used to calculate the installed
system costs for that state.
And then the location corresponds to the length
at which we are taking irradiance data to
calculate the LCOE for the specific model.
Okay so say I want to look at a multi-Si,
glass-polymer backsheet single axis tracked
utility scale in Kansas City, Missouri.
I click Use This Preset.
It’ll automatically slide these bars and
adjust the values so that they match that
preselected technology.
And then if you want to do this, you can copy
the proposed technology from the baseline.
So this may be, for example, if you only have
data about how one section of the cell or
the system changes with your idea so, for
example, you know that you have this new front
layer that you’ve created that you think
adds 60 cents per meter2 for the front layer,
but you don’t really have data on the cell
cost, backlayer cost, all of these different
components of O&M in _____ systems, for example.
And so you just want to use the presets that
are equal to what the incumbent or the baseline
scenario because you think that those will
stay the same.
Okay so let’s keep going with this example
where I have an new front layer that I think
costs 60 cents a meter2 more than in the traditional
cell, and I think that for this I will get
a .4 percent boost in efficiency but then
nothing else about the cell will change.
And so I can just drag these sliders and update
the values.
You can also type these in here if you want
so type in 470, 466 and the slider will adjust
if you don’t want to actually manually move
the slider.
And then if you scroll down here, you can
see the baseline LCOE compared to the proposed
LCOE, really trying to keep as many other
assumptions constant as possible like, for
example, the financial parameter discount
rate.
You could see in this case you get very small
savings in LCOE and this particular location
because of that small boost in efficiency
that you saw, which reduced the tool install
system costs and the module costs.
Module price so one thing to note about this
and to be careful of when doing research and
trying to evaluate the value of that research
is that price point does not always correspond
to costs.
So in this case this is really the potential
cost savings you could get for the balance
of module materials like the front glass and
the backsheet, et cetera, as you have that
higher efficiency, but in reality people may
want to charge a premium for that module.
And so you may or may not actually see this
model cost savings _____ _____ _____ installed
costs, but it can at least give you some sense
of the kind of fundamental value potential
savings in terms of module costs, system costs
and proposed the LC weight of your proposed
idea.
Like I mentioned in the slide, one caveat
to this is the last time this website was
update was March 2018, so it’s using about
two-year-old data for the system installed
cost model.
But system installed cost data actually comes
from NREL from cost models that are published
annually in our benchmark report.
We are hoping to make an update this fiscal
year or by the end of this calendar year.
And then you’ll be able to see that if you
look down in the section with the citation
here.
And those changes will reflect bold changes
to the pricing of the input materials, the
installation process itself and improvements
to how our model captures impacts of efficiency
on system cost.
Okay so that’s this tool.
We’ll walk through SAM.
This is in no way intended to be comprehensive
or help you to be able to actually use SAM
at the end of this conversation.
But I just wanted to give you an overview,
a sense of the look and feel of SAM and how
it’s different from the online PV LCOE tool
that we just walked through.
So this is the welcome page for SAM and using
the latest version, which is from February
29, 2020.
You go up here and start a new project.
You can see that SAM allows you to model a
variety of different energy technologies,
not just PV.
If we look at PV, there’s a detailed PV
model, PV watts which is only PV watts and
then high-concentration PV.
Click on the Detailed PV Model, which is what
we use most frequently, and you can see you
can look at different types of systems, power
purchase agreements or distributive systems
with different ownership models and classes.
If you select the No Financial Model, it just
uses SAM’s performance module so you can
see the energy production for the system,
for example, throughout the year, but it won’t
actually calculate the financial parameters
or metrics associated with the system.
So, as an example, let’s go through one
of these single owner power purchase agreement
systems.
So here on the left you have all the different
tabs where you can specify the parameters
of your system and its finances.
So this location and resource page is just
where you put in the location and resource
that you want to use for the LCOE modeling
and download the weather files here.
The module tab is where you put in the module
specifications, so there’s a few different
options to do this.
There’s two libraries One of them is the
CEC performance model with module database,
and you can see there’s a whole bunch of
different options here for commercially available
panels from different companies that have
the specifications already loaded in here.
The other model with module database is the
SAM PV array performance model.
You can click on help or just Google these
different databases to get more details on
what they are, what they assume and how they're
different.
You can also just input efficiency versus
irradiance here in a simple efficiency model
as well as other characteristics of the panels.
Or you can enter your own specifications within
the CEC performance model here or use the
single diode model.
When we’re doing technoeconomic analysis
for our benchmark reports, we typically use
modules out of the CEC performance module
database associated with the technology that
we’re looking at from a leading company
or a set of leading companies.
And then similarly you can select an inverter
from this database where they have information
about inverters from many different commercial
companies or specify some of your own input
parameters and load things off an inverter
datasheet.
This is the tab where you can put things like
AC and DC sizing, the electrical configuration,
tracking and orientation.
This is something you want to be careful with
if you’re doing these calculations … all
right, here we go, sorry.
When I had selected that other option for
the inverter, it had blown up the DC to AC
ratio to something really unrealistic.
So, anyway, you want to be really careful
when configuring all these parameters so that
you don’t get something crazy that causes
you to get really high or really low LCOE
values.
It doesn’t really having anything to do
with what you would actually see for the economics
of your underlying system with a specific
module technology.
So it takes some time to figure out how to
configure all of these inputs.
You can also input information about shading
and more details on the layout of the array
here.
Losses, losses by type.
You can put in monthly soiling values by pasting
in an array here or manually entering values.
We just added this tab called Grid Interconnection
Limits so, for example, if you can’t output
more than a certain amount onto the grid,
you can enter that here and then it won’t
let you produce PV beyond that limit on the
AC side.
You can also insert an array of curtailment
values throughout the year.
So you can input degradation rate and other
information about the lifetime of the system.
This is the System Cost tab so what SAM really
cares about is the final value here, which
is calculated based on all these different
inputs.
So one of the things that we try to do if
we’re doing a parametric analysis, for example,
where we want to be able to just vary one
cell easily and look at the potential impacts
on LCOE is you can set everything to zero
except the module cost and put the full system
installed cost into this bucket and then just
vary the module cost using this Parametrics
tab down here on the bottom left corner and
see how that affects your LCOE.
SAM does try to do a good job of configuring
their defaults not just for system costs but
for all these different parameters.
So they take input from around the lab and
other places.
And these should be a pretty good representation
of some defaults for the median values that
you might see in a given year.
It’s always good to check those things as
well.
You also input your operations and maintenance
costs here.
It’s where you configure your financial
parameters.
If you have no idea what these should be and
you’re trying to compare between technologies,
it’s helpful to leave these as the default.
There may be some cases where you actually
have reason to believe that a certain technology
would, for example, have a higher or lower
discount rate if it’s risky or an earlier
stage, for example.
And so maybe you want to configure those but
it’s sort of an advanced analysis.
This is where you can input information about
the revenue, so SAM doesn’t just calculate
LCOE.
It actually calculates revenues as well as
present value, payback periods and things
like that.
So you can specify any compensation based
on tie of delivery, incapacity payments, work
curtailment payments if that exists or specify
a target IRR, an internal rate of return or
a PPA price.
I’m going through this super fast just to
give you a sense of what this tool is.
There’s a lot more information and some
resources I’ll provide on the next slide
about how to use SAM, and you can always click
this Help button up in the corner on a given
tab as well.
Incentives, federal, state incentives and
utility incentives.
These are production-based or capacity-based
and depreciation parameters.
Again, if don’t even know what that means,
just leave this alone to stay at the default
value.
So then you come down here and you click Simulate,
and SAM creates all of these different output
tabs.
This is a summary that gives you some of the
key metrics you might be interested in, so
here’s the nominal and real LCOE for the
system, PPA prices, energy yield, capacity
factor, net present value, et cetera, here.
And then they also have some nice summary
charts that automatically output.
You can look for more detailed information
on a specific set of data here by filtering
through these values on the data table.
For example, you can look at losses, create
your own graphs, look at the actual cashflow
in each year.
The system plots some different time series
values, look at profiles for each month of
the year, for example, get some statistics,
create heat maps.
So you can see there’s really a lot of sort
of much more sophisticated capability in terms
of both input configuration and reporting
here, which can be good or bad depending on
what you’re trying to do.
Certainly, if you’re actually trying to
get a very accurate assessment of costs for
a specific project or get a little bit more
into the weeds on some of the input parameters,
this is a tool that will allow you to do that.
I’m not going to go into these again just
because we don’t have that much time.
But you can see here down in the bottom left
there’s also a lot of other cool functions
with SAM, so you can do parametric analysis
really easily here.
You can do some stochastic analyses, P50.
P90 analyses.
And then you can also look at these different
macros that have been created and run these.
You’re also able to create your own scripts
in SAM, and there’s a Python interface so
you can interact with inputs and outputs of
SAM, run SAM through Python, which is pretty
nice so a lot of flexibility there.
You can see this is where you create a new
script and then just very briefly show you
if you look at some of these distributed options.
It looks very similar here.
But some of these things like these financial
parameters, for examples, are different because
of the way that these systems are financed
in the residential market.
And then you can also input things like electricity
rates for a given location, what type of metering
there if it’s net metering or net billing.
You can actually search for rates here for
different utilities so because I’m in Colorado
with Xcel Energy, I can actually find their
rates now.
Show the active ones and say I want to pick
this time of use rate that they have so download
and apply that rate here.
And you can also input the electric load each
month or throughout the year so this is 8760
each hour of the year.
And these things all affect the payback period
and the finances for a distributed system
that’s co-located with the load.
Okay so now I’ll give you a couple tips
for using SAM for PV R&D evaluation.
Again, there are a lot of things that you
should know, not just what I’m showing here
because SAM is complicated and you can easily
convolute different effects if you don’t
know how to use it.
So I really recommend diving more deeply into
their documentation if you’re interested
in using this tool.
I’ve provided the link again here.
You can see they also have a forum and people
will answer questions for you.
If you are interested and you do really have
the time to learn SAM, it is a very cool tool
that you can do a lot of analysis with.
So just two things that I’ve noticed when
using SAM for PV R&D evaluation: One of them
is if you’re trying to look at the effect
of efficiency on LCOE, the only thing you
need to change in SAM is the total installed
system cost under the System Cost tab and
that’s per watt.
SAM does not automatically calculate how efficiency
influences those installed system costs.
So you’re going to have to manually compute
those values or take data from our latest
reports on those topics, which is what I would
recommend, and then put it into that installed
cost cell in SAM that we just looked at.
If you do change the efficiency using that
simple efficiency model in the module tab
that we walked through where you could change
the efficiency of different irradiance levels,
I’ve noticed that you can get some weird
effects where the system design will change
or the layout will change.
And you can see things like the LCOE going
up as efficiency increases if you change nothing
else.
And so you really need to know what you’re
doing and be very careful to avoid those issues.
So I would actually recommend not changing
that if you’re trying to look at efficiency
impact, just leaving that efficiency value
fixed or using a module from a module database
that has other characteristics outside of
efficiency similar to what you would expect
for your technology even with different efficiency
levels.
And that works out because LCOE is actually
normalized both in the numerator and denominator
by efficiency so it’s dollar per rated watt
divided by watt hour per rated watt and the
rated watts depends directly on efficiency.
And so you don’t actually need to change
those if you just update the system installed
cost and leave everything else the same.
You should get the sense of how efficiency
impacts the LCOE.
When you are picking that number to put in
the installed cost box, I would recommend
again using data from our most recent reports
on this that use our bottom-up model.
We’ve done some recent research that shows
if you use a simple efficiency model where
you categorize costs as area-dependent or
power-dependent and then use a simple equation
to calculate cost per watt with efficiency
from that, that that is not really an accurate
representation of the savings that you can
get with the higher efficiency or penalty
for lower efficiency.
And I have a lot more recent data on this
but haven’t quite been published yet I’d
be happy to discuss with you if you have questions.
A second tip for using SAM if you’re trying
to compare across technologies on a technology-only
basis in the long term is to use a standard
set of financial parameters.
And, again, if you have no idea what those
should be, SAM does a pretty good job of configuring
the default, so it’s okay to just leave
those as they are.
But if you are trying to commercialize a new
technology in the near term, just be aware
that there could be some difference in financing
costs as you’re pricing in that initial
risk of any new technology.
So, again, different ways to use this tool
and the online PV LCOE calculator depending
on if you’re doing more long-term research
planning, try to kind of prepare data for
proposals or understand at a high level if
a certain research direction is valuable versus
near-term planning for projects or technology
transfer.
All right so that’s it.
Hopefully, that was a helpful overview of
those two tools.
