In this section, I will review our procedures
and some suggestions for completing techno-economic
analysis, or TEA, at the PV module level.
So in this section, the focus will be a little
different than TEA for the PV system level,
but that will be covered in a later section.
So briefly, what is techno-economic analysis?
If you break down the name, it refers to the
combined analysis of both technical and economic
factors.
So for example consider the technical and
economic effects of thinning a solar cell.
You have a thinner solar cell, so it's using
less material, which means your material costs
per cell are lower.
However, what are the effects of thinning
on the efficiency of the cell?
If the cell is no longer optically thick,
efficiency will decrease, so your cost per
watt will go up.
TEA accounts for both the effects on the technical
performance and the economic performance of
thinning a solar cell, so it can quantify
the trade-offs and identify an optimum thickness.
So here is an overview of the content I'm
going to cover in this section of the tutorial.
I'm just going to jump right in with scoping.
In order to complete the subsequent steps
in the analysis process, you have to scope
your TEA first.
To scope your cost model, you should identify
the questions you're trying to answer.
Maybe you're interested in identifying the
highest cost categories of your technology
in order to highlight areas for improvement,
or you want to map the anticipated trajectory
of technology progress, or compare the techno-economic
performance of different materials or processes.
You also need to identify the primary audience
of your TEA results.
For example, researchers will often have different
areas of focus than manufacturers.
You should also consider the current stage
of your technology.
What scale is your technology at now, and
what scale are you interested in?
Laboratory unit costs and performance are
typically going to be higher than the costs
and performance of a commercialized product,
so modeling at laboratory scale will appear
more expensive.
If laboratory development of your technology
is still in process, you may want to model
theoretical potential.
However, that will require significant assumptions.
Finally, you should consider the resources
you have at your disposal, such as time and
funding.
This can limit the degree of detail in your
model, or how many iterations or scenarios
you perform.
You may have to prioritize some areas for
high detail, and rely on assumptions for others.
So now I'll review considerations when selecting
reference design scenarios and iterations
and process flows for your cost model.
The first step is to choose one or more reference
designs.
Depending on your scope, you may only need
one.
Some options for selecting a reference design
include performing a survey of products in
the market and defining a design that is generally
reflective of the market; or you can consult
industry members or other experts that can
describe or identify designs that are appropriate
or generally reflective of the market.
You could also conduct a literature review.
However, be aware that some device designs
or aspects of devices in academic literature
are not always reflective of what will be
used if that technology were produced commercially.
If you are planning to publish your TEA results,
it is best to select reference designs that
are not specific to one company.
This helps protect proprietary information,
avoids the appearance of marketing a particular
company, and will give your publication broader
impact.
After selecting reference designs, you can
then define any necessary scenarios for your
techno-economic analysis.
Different scenarios can include modeling production
at different volumes to show economies of
scale, or map a trajectory for the technology.
Modeling different manufacturing locations
will reflect local differences in costs such
as labor and electricity rates.
You could also vary design parameters such
as product size or material compositions,
or process options such as deposition methods
or automation.
Finally, there are other aspects of process
flows that must be selected which vary significantly
at different scales and stages of production,
such as the through-put of production equipment,
uptime, or yields.
Now I'll review the building process and financial
structure of the cost models.
I'm going to walk through a diagram of how
different parameters get filtered through
our cost model.
First I'm showing a list of many different
module and cell technologies that our team
has analyzed.
For each of the technologies listed on the
left, you have to collect the data listed
in red in the center, referred to as cost
of ownership data.
As we've explained earlier in this section,
this data will vary significantly based on
what scenarios you are considering.
Finally, the cost of ownership data is structured
into a cost model using the techniques on
the right, including generally-accepted accounting
principles and international financial reporting
standards.
These standards classify costs into three
main categories.
Variable costs are tied to output, while fixed
costs remain constant regardless of output.
Together, variable and fixed costs comprise
the cost of goods sold, or COGS.
Additional expenses not in COGS include research
and development expenses as well as sales,
general, and administrative expenses, or S,G,
& A. These three categories estimate total
module costs.
It is important to note, however, that the
concept of module costs, or total module costs,
is not the same as the concept of module price,
which we will cover in a couple slides from
now.
So we will show a short video of how to go
from total module costs to a modeled module
price, but first I'm going to go over a few
basic finance terms that you might need to
be familiar with when working with a cost
model or looking at TEA results.
I don't think anything in this tutorial will
be dependent on your understanding of these
terms, but you may see them referenced a few
times.
So the first term is depreciation.
This refers to the category of fixed costs,
such as equipment or buildings, that can be
expensed over multiple years.
The expense schedule, or depreciation schedule,
is set by the IRS for tax purposes.
You may also hear the term cash flow, or cash
flow analysis, which describes the accounting
of revenues and costs over some project lifetime.
So the key point there is that it's over a
specific life; it's a dynamic analysis.
The discount rate represents the time value
of money and is used in a cash flow analysis
to discount future revenues and costs compared
to the current value of money.
So if you're not familiar with the concept
of a discount rate, you can think of it as
a similar concept to inflation, where the
same denomination of money was worth more
in the past than it is today.
And then a term called the weighted average
cost of capital, or WAC, is often used as
the discount rate.
WAC is calculated using a company's ratio
of debt to equity financing, as well as the
respective cost of debt and cost of equity,
where the cost of debt is essentially the
interest rate on the debt, and the cost of
equity is the return rate for investors that
hold equity in the company.
Okay, so now we'll show the video on how to
estimate the product price using our TEA methods.
[Video played, 0:08:50 to 0:13:10]
[Music playing]
Let's say you're working on the next big thing
in solar energy.
Maybe you're a researcher, wanting to know
how your technology fits into the current
market.
Or maybe you're a manufacturer, trying to
identify trying to lower costs.
For scenarios like these, minimum sustainable
price, or MSP, is a useful metric to consider.
Minimum sustainable price is exactly what
it sounds like.
It's a price that provides the minimum rate
of return necessary in a given industry to
support a sustainable business over a long
term.
Specifically, MSP is influenced by manufacturing
costs, overhead costs, and other financial
considerations such as financing, discount
rates, and tax incentives.
Let's take a closer look at manufacturing
costs, also known as the cost of goods sold.
Understanding manufacturing costs can help
identify the major cost drivers for a particular
technology.
Manufacturing costs include materials, labor,
electricity, maintenance, equipment costs,
and facilities.
The next set of costs that influence MSP are
overhead costs.
These include research and development costs,
as well as sales, general, and administrative
costs.
Overhead costs can vary significantly between
companies, as well as over time within a given
company.
After summing up manufacturing and overhead
costs, we then obtain the minimum sustainable
price by assuming an operating margin, typically
desired when pricing products within a given
industry.
An operating margin accounts for interest
payments, profit, and the corporate tax rate.
A sustainable operating margin can be estimated
by interviewing industry members or by calculating
the price needed for a business to break even
over an assumed business lifespan, while adjusting
for inflation and the cost of capital.
Given all these factors, the MSP is the price
you would have to charge to break even at
any given point in time.
Let's look at a few different ways that MSP
can be used.
First, minimum sustainable price allows us
to directly compare costs of different technologies.
Market prices aren't ideal for such a comparison
because manufacturers might be selling well
above or below their actual costs.
MSP focuses on the actual costs of the two
technologies, removing market factors like
supply and demand fluctuations from the comparison.
While you could compare technologies based
solely on manufacturing costs, the MSP also
takes into account financial factors, such
as different financing fees, that can create
cost differences between technologies.
Furthermore, considering MSP can provide a
way to estimate what prices and margins might
be for manufacturers when no public information
is available.
Another important aspect of MSP is that it
will adjust over time, as costs change.
MSP is not the absolute minimum sustainable
price that could be achieved by a given technology,
just the minimum at that time and location.
Here you can see how for one technology, NREL's
estimated costs, MSP, and market prices have
changed over time.
Our costs and MSPs are benchmarks, suggesting
a typical case within the industry.
Sometimes the market price is below the MSP,
which can reflect low margins in the industry.
A company may also price below our benchmark
MSP if they have achieved lower overall costs
than the industry as a whole.
Additionally, MSP is a good metric for setting
policy and cost targets for a technology.
Ideally, these targets should reflect actual
technology costs, not prices that have been
inflated or depressed by market factors.
In a nutshell, minimum sustainable price can
be a useful metric when comparing existing
energy technologies or introducing new ones.
To learn more about MSP, see NREL's solar
cost analysis plications.
Here is an example of cost model results,
shown here for a vertically integrated manufacturer
that produces monocrystalline wafers, PERC
cells, and modules.
The materials, labor, electricity, and maintenance
costs represent the variable cost component
of COGS, and the depreciation category represents
the fixed cost component of COGS, where that's
buildings and equipment depreciation.
Then there is the gross margin, which includes
R&D expenses, S, G, & A expenses, and the
operating margin.
We typically estimate R&D and S, G, & A expenses
from quarterly financial statements of relevant
publicly-traded companies, and apply them
as a percentage of COGS.
The operating margin includes interest payments
on debt, equity payments for investors, and
any additional profit, as well as federal,
state, and local corporate taxes on that profit.
So just as an illustration, even though we
assume sustainable margins for our cost models,
this isn't always the case in the actual market.
As you can see here, operating margins are
often negative in PV industry.
Negative margins can often reflect external
market factors such as supply and demand.
Now I'll just go over some advice and suggestions
for how to collect the cost of ownership data
that we listed previously.
Here I'll review some typical sources for
different types of cost of ownership data.
If you're looking for equipment costs, your
best bet is vendors of the equipment.
Many vendors have a cost of ownership fact
sheet prepared for prospective buyers.
For material costs, there are a few different
options.
You can request quotes from material suppliers.
Make sure to specify what purchase scale you're
interested in.
You can sometimes find commodity pricing online
or through certain subscriptions.
Market reports can also provide material costs,
but the reports can be expensive, and they
don't always have great a degree of data transparency.
Finally, for many of the process flow parameters,
these are best sourced from manufacturers
of the product you are modeling or manufacturers
of similar products.
Finally, once your model is built and data
gathered, there is an iterative process to
refine and discuss your TEA results.
This includes, once you've generated your
preliminary analysis, you then share those
results with relevant companies and industry
members to gather feedback and critiques.
Iterating your TEA results using feedback
from industry can be useful to focus on and
discuss areas of more interest, or even catch
inaccurate assumptions which will make the
final analysis more relevant and robust.
