What Is LCOE?

 

LCOE, or Levelized Cost of Energy, is a way to estimate the average cost of producing electricity from a power-generating asset over its operating life.

It is commonly used when comparing technologies such as solar, wind, gas, coal, nuclear and other electricity-generation systems. Instead of looking only at the initial construction cost or the price of fuel, LCOE attempts to combine the major lifetime costs of a project and relate them to the amount of electricity the project is expected to generate.

The result is normally expressed as a cost per unit of electricity, such as dollars per megawatt-hour ($/MWh) or cents per kilowatt-hour (¢/kWh).

LCOE can be extremely useful, but it is not a universal measure of which electricity source is “best.” Its value depends heavily on the assumptions behind the calculation.

The Basic Idea Behind LCOE

At its simplest, LCOE asks:

How much does each unit of electricity effectively cost when the project's lifetime costs and lifetime electricity generation are considered together?

Conceptually, the calculation looks like this:

LCOE = discounted lifetime costs ÷ discounted lifetime electricity generation

The word discounted matters because money spent or earned today is not normally treated as having exactly the same value as money several decades in the future.

A full LCOE model may therefore calculate costs and electricity generation year by year, adjust future values using a discount rate and then divide the total present value of the costs by the total present value of the electricity produced.

The precise methodology can vary between organisations and studies, so two published LCOE figures should not automatically be assumed to have been calculated using identical assumptions.

What Costs Are Included in LCOE?

The numerator of the LCOE calculation represents the costs associated with building and operating the electricity-generating asset.

Depending on the model, these may include:

• initial capital expenditure;
• construction and installation;
• equipment replacement;
• operation and maintenance;
• fuel;
• financing-related assumptions;
• decommissioning costs;
• other project-specific expenses.

Different technologies have very different cost structures.

For a solar project, much of the cost is typically concentrated near the beginning of the project because the panels, inverters, mounting systems and installation must be paid for before electricity production begins.

Once operating, solar has no fuel cost, although maintenance, inverter replacement and other expenses can still occur.

A gas-fired power plant has a different profile. Its construction costs may be accompanied by substantial fuel expenses throughout its operating life.

LCOE allows those different cost patterns to be converted into a common cost-per-unit-of-electricity measure.

Electricity Generation Is the Other Half of the Calculation

Looking only at project cost is not enough.

A power plant costing $1 billion and another costing $2 billion cannot be meaningfully compared without asking how much electricity each is expected to generate.

That is why the denominator of the LCOE calculation is just as important as the numerator.

Expected lifetime generation depends on factors such as:

• installed capacity;
• capacity factor;
• resource quality;
• degradation;
• outages;
• project lifetime;
• curtailment;
• operational performance.

Consider two solar farms with the same construction cost and rated capacity.

If one is located in an area with stronger solar resources and produces substantially more electricity over its lifetime, its calculated LCOE may be lower.

The asset has effectively spread its lifetime costs across a larger amount of generated electricity.

Why Capacity Factor Matters

Capacity factor describes how much electricity a generating asset actually produces compared with the maximum it could theoretically produce if it operated at full rated output continuously.

It can have a major influence on LCOE.

Suppose a project has significant fixed costs. If those costs are spread over a relatively small amount of electricity generation, the calculated cost per MWh will be higher.

If the same level of fixed cost can be spread over much more generation, LCOE can decrease.

This is one reason assumptions about renewable-resource quality, downtime and project utilisation should be examined carefully when comparing LCOE estimates.

A small change in an input can sometimes produce a meaningful change in the final result.

Project Lifetime Also Changes the Result

The assumed lifetime of a generating asset matters for a similar reason.

Imagine an energy project with high upfront construction costs but relatively low annual operating costs.

If those initial costs are effectively spread across 20 years of electricity production, the result will differ from a model in which the same project operates productively for 30 or 40 years.

But simply assuming a longer life does not guarantee a realistic lower LCOE.

Longer operating periods may require additional maintenance, replacement equipment or refurbishment. Output may also decline as equipment ages.

The lifetime assumption therefore needs to be consistent with the technical and financial assumptions used elsewhere in the model.

The Discount Rate Can Have a Large Effect

LCOE models usually account for the time value of money through a discount rate.

This can have a particularly strong effect on technologies with large upfront costs.

A solar farm, wind project or nuclear plant may require substantial investment before much electricity is produced. A technology with lower construction costs but continuing fuel expenditure distributes its costs differently over time.

Changing the discount rate can therefore change the apparent relative economics of different technologies.

This is one reason readers should be cautious when comparing LCOE figures taken from unrelated reports.

If the underlying financing and discount-rate assumptions differ, the numbers may not represent a true apples-to-apples comparison.

A Simple LCOE Example

Imagine a simplified project that costs $10 million over its lifetime and produces 200,000 MWh of electricity.

Ignoring discounting for this basic illustration:

$10,000,000 ÷ 200,000 MWh = $50/MWh

Its simplified LCOE would therefore be $50 per MWh.

Now imagine the project generates only 160,000 MWh while lifetime costs remain the same:

$10,000,000 ÷ 160,000 MWh = $62.50/MWh

Nothing changed in the total cost. The difference came entirely from lower electricity generation.

Real LCOE models are more detailed, but this example shows the basic relationship:

higher lifetime costs tend to increase LCOE, while greater lifetime electricity generation tends to reduce it.

What LCOE Is Good For

LCOE is particularly useful for comparing the approximate lifetime generation costs of different technologies or projects using a standardised framework.

It can help researchers, developers, policymakers and analysts examine questions such as:

• How have solar generation costs changed over time?
• How do onshore and offshore wind compare under particular assumptions?
• How much does fuel price affect the cost of gas generation?
• How sensitive is a project to its capacity factor?
• How does financing affect capital-intensive technologies?

This is also why LCOE appears frequently in renewable-energy datasets and industry reports.

Well-maintained collections of energy statistics can make metrics such as LCOE much easier to compare across technologies and time periods. The principles behind building useful renewable-energy statistics resources are discussed here:

https://seolabsdp.blogspot.com/2026/09/renewable-energy-statistics-pages.html

What LCOE Does Not Tell You

LCOE is useful, but it does not capture every characteristic that determines the value or cost of an electricity system.

For example, two technologies may have similar LCOE figures but produce electricity at very different times.

A solar plant concentrates generation during daylight hours. Wind generation depends on wind conditions. Dispatchable generators may be able to increase or decrease output when required.

A basic LCOE figure does not necessarily capture the value of that timing.

It may also fail to fully represent:

• transmission requirements;
• grid congestion;
• energy-storage requirements;
• balancing costs;
• curtailment;
• system reliability;
• location-specific grid constraints;
• environmental externalities;
• subsidies or policy mechanisms, depending on methodology.

This means LCOE should not automatically be interpreted as the complete cost of delivering electricity to consumers.

Nor does the technology with the lowest published LCOE automatically provide the optimal solution for every electricity system.

Always Check the Assumptions Behind an LCOE Number

A figure such as $45/MWh looks precise.

But its usefulness depends on the assumptions that produced it.

When evaluating an LCOE estimate, check details such as:

Technology and location. Renewable-resource quality varies geographically.

Capital cost. Equipment and construction costs may differ substantially between projects and markets.

Capacity factor. Expected generation strongly influences the denominator.

Project lifetime. Longer or shorter assumed operating periods can change the result.

Discount rate. Financing assumptions may significantly affect capital-intensive technologies.

Fuel prices. These can materially change the economics of thermal generation.

Degradation and maintenance. Equipment does not necessarily perform identically throughout its entire operating life.

Study year. Technology costs can change, so older LCOE estimates may not describe current projects well.

Without this context, comparing two LCOE numbers can create a false impression of precision.

LCOE Works Best When the Data Is Visible

A good LCOE chart should show more than a collection of bars.

Readers should be able to identify the units, technologies, year, source and major assumptions behind the comparison.

Ranges can also be more informative than a single number because actual projects differ in financing, geography, resource quality and construction cost.

This makes LCOE a good example of why energy data needs careful presentation. A strong visual does not merely make data attractive; it helps readers understand what is actually being compared.

For a broader framework on turning energy data into clear, citation-friendly graphics, see:

https://seolabsdp.blogspot.com/2026/09/data-visualisation-as-linkable-asset.html

LCOE Is a Comparison Tool, Not a Complete Answer

The most useful way to think about LCOE is as a normalised lifetime generation-cost metric.

It brings construction costs, operating costs, fuel and expected electricity production into a common framework, making very different generating technologies easier to compare.

But every LCOE value is built from assumptions.

Capacity factor, financing, project lifetime, fuel prices, degradation and other variables can all change the result. And even a well-calculated LCOE does not capture every system-level cost or every type of value provided by an electricity source.

So the important question is not only:

“What is the LCOE?”

It is also:

“What assumptions produced this LCOE, and what does the number leave out?”

Metrics explained with that level of context can become useful reference material rather than isolated statistics. That principle also matters when energy companies use technical resources as part of a wider content and link-building strategy:

https://seolabsdp.blogspot.com/2025/09/link-building-for-green-energy.html