Levelized Cost of Electricity and Internal Rate of Return for Photovoltaic Projects (Text Version)
This is the text version for a video—Levelized Cost of Electricity (LCOE) and Internal Rate of Return for Photovoltaic (PV) Projects—about how NREL conducts such pro forma analysis.
It’s Part 4 of NREL’s Solar Techno-Economic Analysis (TEA) Tutorials video series.
Methods and Demonstration of LCOE and IRR Calculations
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.
NREL’s Solar Plus Storage Techno-Economic Analysis Portfolio
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 pro forma analysis and that’s what we’ll be diving into in this section.
Pro Forma Cash Flow Graphic for PV and Storage Projects
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 pro forma analysis involving cash flows.
And on the bottom you can see a graphical representation of the cash flows 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 U.S. 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. 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.
Capital Cost Inputs for PV Modules and Systems
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 U.S. 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 U.S. 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.
Partial List of O&M Cost Items for PV Systems
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.
Pro Forma Cash Flow Graphic for PV and Storage Projects
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 (SAM), 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.
The Two Primary Pro Forma Cash Flow Analysis Modes within SAM
And when you do LCOE modeling within SAM, there are two modes that you can select, and it really changes how the cash flow model works within SAM. The first mode is calculating 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 pro forma 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 pro forma.
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. 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 clearer to understand the PPA revenue side.
Solar Resource Affects Energy Yield and Pro Forma Calculations
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 simplified LCOE dollars per kilowatt-hour. More kilowatt-hours increase the denominator so that lowers the LCOE. In terms of cash flows 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.
Degradation Profiles Used for the Example Project Cash Flow Model
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 data sheets, perhaps marketing materials as much as anything, but looking at some module data sheets, 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 mono PERC warranty degradation profile.
So this is, again, taken from a module data sheet 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 data sheets. And we want to translate that to impacts of PV project economics.
Inputting the Degradation Profiles into SAM
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 into 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.
Project PPA Revenues for the Different Warranty Values
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.
Examining PPA Revenues for the Different Warranty Profiles
Just to show you where this appears within SAM is what I’m … [Audio skips to next slide]
Project EBITDA for the Different Warranty Profiles
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 minus 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.
Examining PPA Revenues for the Different 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 minus 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.
Impacts and Break-Even Analysis for Warranty Profiles
But just to summarize, if you did want to go into SAM and input some representative tax assumptions – and I’ll discuss the U.S. 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 LBNL 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 break-even 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 U.S. 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.
Introduction to LCOE Analysis of PV Projects
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 involve spreadsheets and pro forma cash flow 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 U.S. and doing LCOE calculations, I would encourage you to also research what tax incentives can be monetized and would be relevant for your pro forma 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.
Tools for Calculating 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 a 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.
Walk-Through of NREL’s Online PV LCOE Tool
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 nrel.gov/pv/lcoe-calculator. 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 input section 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 balance-of-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 similarly for this system’s 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 updated 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.
Walk-Through of SAM
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 Sandia 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 techno-economic 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 data sheet.
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 have 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 example, 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.
Tips for Using SAM for PV R&D Evaluation
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.
To continue with Part 5 of the Solar TEA Tutorials video series, see Levelized Cost of Solar Plus Storage (Text Version).