Our model is complete and copied all the way to the right.

We're now going to go to the bottom of the assumptions tab where we've got the outputs.

First thing I'm going to do is just make this column a bit narrower, which would be a problem for understanding if we were to scroll up.

But just from the point of view of teaching this section, it's good to have a little bit more space left to right.

We've got these concepts of P 90 and P 50, and so we're looking at this from two points of view.

The P 90 is a very conservative view.

It's something that's gonna happen 90% of the time, and we could in fact turn that into P 99 if we want to be ultra conservative.

The P 90 view in this model is that our turbine efficiency is quite low.

A lower turbine efficiency makes sense because it will cover more circumstances where there are breakdowns, problems, unreliability.

And so it's gonna cover more of the spectrum of P than the P 50.

The P 50 is a 50 50 chance, so it's an average.

So if we were to run this project over and over again, we'd find that on average we have a turbine efficiency of 40%.

Whereas if we were to be absolutely sure that the eventuality would be covered, we would have to assume a lower turbine efficiency, which is what P 90 represents.

Now, the two stakeholders that are gonna be doing this are the bank or lenders and the shareholders.

The lenders are more concerned with downside.

They're going to worry about the project going wrong.

They're gonna be assessing the project on the basis of a very conservative view.

So they're gonna say, okay, let's take the P 90 view.

We want you to assess the project as if the turbine efficiency is 25%.

Now, they're not actually interested in the IRR as such, but we need to have two hats on at the same time.

The P 50 people will be interested in the IRR, but the P 90 people will be interested in the breaches, and that's the bank.

So our objective with these two tables is to create effectively an analysis which says, how far can we push the debt? Remember, debt is cheap, but how far can we push the debt without creating breaches? Because the more we push the debt, the more mandatory payments there will be, the more interest there will be, and the more scope for breaches there will be.

If there are forecast breaches, we are very unlikely to be able to get that financing package.

And so we want a good IRR 12, but without there being any breaches, the first step towards this is actually creating the IRR.

We need the IRR to be able to create sensitivity around the IRR and to create the IRR, the first cash flows will be negative, and we'll get them from source and uses.

We want the equity financing, and from the point of view of the stakeholders, the shareholders, that will be a cash outflow.

Then we're going to assume that the major output of this is the dividends, and we've decided on a hundred percent.

After the DSRA, we'll go and find the dividends.

Here they are on the debt tab.

You can see to the right that they're negative and from the point of view of the shareholders, they will be positive.

So there we go. Now the total cash flows, we'll add those two up.

We then copy to the right.

So note some on year 71, and we have our string of cash flows there.

What we can do then is create the IRR.

It's a little uncomfortable knowing where to put the IRR.

I'm going to put it here. I know it says input column, but I don't really know where else to put it.

I want it to be visible apart from the freeze.

So I'm going to put it here on the left.

We then gonna point it to all of the cash flows, but excluding my formula there, you can see we've got an IRR, which is 11.3%.

Now, you can immediately see that that is not going to excite our shareholders because they will expect a 12% IRR.

The thing is, what we've done is we've created a scenario with our assumptions, and the way this model works is those assumptions are inputs as opposed to being outputs.

So like I said earlier, what we are going to eventually do once we've got the breaches is we are going to set up a series of data tables to explore this situation.