# LCOE: Simple Calculations & a self-test Quiz

To accompany this lesson, there is provided another simple online calculator (it’ll open in a new window).:

Calculator: LCOE

Please read the notes tab of the calculator before you use it, in order to be clear about the various inputs and outputs.

To illustrate how sensitive LCOE figures can be to some of the key assumptions made, you can make use of the questions posed in the quiz below.

Q1.

Start by setting up a “base case” in the calculator as follows:

A 50MW PV plant costs \$75m to build and \$400,000 (\$0.4m) to operate each year.
80% of the cost is borrowed as debt (\$60m), repaid over the 20 year assumed lifetime of the project, at an interest rate of 6%.
The plant is in a sunny location, achieving a capacity factor of 25%, with the energy output assumed to be maintained at its initial levels throughout the project life. This electricity output can be sold for \$50/MWh.

Tax is paid at 35% and a discount rate of 10% is applied to future values (of energy and costs).

Calculated on a leveraged basis, what is the base case LCOE?

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\$46 per MWh

(If you didn’t get this, check your inputs; and check you are looking at the leveraged result)

Q2.

Without changing any other assumptions, by how much does a) a reduction and b) an increase in the chosen discount rate – by 5% in each case – change the calculated LCOE?

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a) reduced discount rate lowers LCOE by \$5/MWh
b) increased discount rate raises LCOE by \$5/MWh

Discounting by a larger amount doesn’t change the actual spending on or electricity output of a project, but does mean a bigger adjustment of these quantities over time when analysing in terms of the present value of future figures. The net result is that, when the discounted project costs are summed together and divided by the sum of the discounted energy generated, the ratio of the two has decreased too: so the average – “levelised” – ratio of cost to energy over the project life is lower.

Note that in the case b), the simple revenues-costs bar (i.e. the net present value) of the project has become negative at the assumed sale price. Bear in mind that the project has cost exactly the same to build and run and is producing exactly the same amount of energy. In other words, simply by raising the discount rate we have changed our view of the desirability of the project!

The choice of discount rate is entirely down to the opinion and preference of whoever is performing the financial analysis. So two projects identical in terms of costs and energy output can be described by different LCOE figures, if they have been analysed by two different people. Higher discount rates will be used to reflect the need for higher returns (which in turn means the energy needs to command a higher “breakeven” sale price, in order to produce higher revenues). The level of return needed is a function of factors such as the types of investor, whether or not project or market risks are regarded as high and by comparison with the returns available by investing the same money elsewhere.

Q3.

Go back to the base case (you can press “reset” to do this) and now increase the installed cost by 20%, to \$90m. What is the impact on leveraged LCOE?

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\$59/MWh  (An increase of 28%)

This simply illustrates how sensitive LCOE is to installed cost (which, because it is spent now rather than in future, doesn’t benefit from any discounting)

Q4.

Go back to the base case (press reset) and now increase the O&M costs by 20%, to \$0.48m per year. What is the impact on leveraged LCOE?

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No change

There will have been one, but it’s too small to show!

In the previous question a 20% increase in installed cost had a big impact on LCOE, whereas the same increase in operating cost here has had negligible effect. Clearly for PV, the route to lower electricity costs lies more with reduced up-front costs than with improved operational processes.

Q5.

From the base case, what percentage increase in O&M costs would it take to increase leveraged LCOE by the same amount as was seen from a 20% increase in installed cost? (i.e. from \$46/MWh in the base case, to \$59/MWh)

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O&M needs to be increased to at least \$2.59m, which is an increase of 548%!

This again highlights how sensitive the cost of energy from PV plants is to changes in their up-front build cost, and how relatively insensitive to changes in operating costs. That’s because the latter are a relatively small part of the total that gets spent and of course are mostly future costs (so reduced by the discounting used to calculate LCOE).

Q6.

Go back to the base case (press reset)

Now assume that the annual energy generated reduces: degrading at 1% a year (let’s say this is due to lack of panel cleaning). What is the impact on leveraged LCOE?

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\$49/MWh
An increase of 7%

Bear in mind that we know from our previous sensitivity analysis that we could spend an extra \$80,000 per year on O&M and have no measurable impact on our LCOE. So, while it might seem a lot in isolation, spending that much on cleaning could prove worthwhile in the long run, if it keeps our panels operating at full output!

(In reality, you would always include some energy degradation assumption in a financial model, regardless of maintenance such as cleaning. Everything from solar panels to wind turbines to thermal plant components can lose performance over time, for a variety of reasons. But the principle still holds: saving money on O&M may not prove a wise decision if it simply results in an acceleration of this rate of degradation).

Q7.

Go back to the base case.

Now let’s assume less favourable terms from the debt lender: they want their money back in 10 years and charge an interest rate of 8%. How does this impact leveraged LCOE?

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\$58/MWh

An increase of 26%

This shows the importance of financing costs for power projects, particularly those for which the cost structure is dominated by (paying back) up-front costs followed by relatively small ongoing and future costs (i.e. low O&M or, in particular, no fuel to buy).

Thus it’s important to note that the steep reductions in electricity prices that have been seen for some renewables (notably solar and wind) have not simply been a result of technology costs reducing. A big part has also been played by reductions in the cost of raising money to build such projects.

This reduction in financing costs has been driven by the fact that investors have become more comfortable with these projects. Project risks are better understood and less uncertain once more have been built (and risks have reduced in absolute terms too, as lessons have been learned and earlier problems mitigated). As risks lower, so do the return expectations of investors, opening up a wider range of financing sources (along with more competition between them).

Q8.

Keeping those increased financing costs, and assuming that the debt amount cannot rise higher than 80% of the installed costs, how low would these installed cost need to be, to get back to our base case leveraged LCOE (\$46/MWh)?

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\$59m

To get to this result, you can’t just change the installed cost input: because doing that without lowering the debt amount will raise this debt amount as a percentage of the installed cost – exceeding the 80% limit. So as you lower the installed cost, you’ll need to lower the debt amount too, until you arrive back at the base case LCOE.

That gets you to an answer of \$59m, with the loan size reduced to \$47m. This is an installed cost reduction of 21%.

Again, this is illustrating how financing terms (in this case limits on the allowed degree of leverage) impact the achievable energy costs.

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