At the end of a long project meeting, the promoters of a proposed Sustainable Aviation Fuel plant had answered almost every technical question. They had identified a possible site, shortlisted technology providers, discussed feedstock availability and even started conversations with potential fuel buyers.
Then the finance team asked a simple question: “At what SAF selling price does this plant actually make money?”
The room became quiet.
The project had an estimated investment, but no clear connection between plant capacity, feedstock consumption, operating cost, debt repayment and actual cash flow. The promoters had been looking at the size of the SAF market, while the lender was looking at something very different: whether the project could generate enough cash every year to repay its debt and still provide a reasonable return to investors.
This is an illustrative case study, but it captures the central issue facing almost every new SAF project. Sustainable Aviation Fuel may become an important part of aviation decarbonisation, but a growing market alone does not make a plant financially viable.
India has announced indicative SAF blending targets for international aviation of around 1% from 2027, 2% from 2028 and 5% by 2030. These targets can create significant long-term demand, but investors still need to answer much more basic questions. How much will the plant cost? What will one tonne of SAF cost to produce? How sensitive is profitability to feedstock prices? What happens if commissioning is delayed by six months? And what IRR can the project generate after considering realistic utilisation rather than assuming 100% production from the first year?
That is exactly what a properly structured SAF plant financial model is designed to answer.
A SAF plant financial model converts the technical design of the project into a long-term financial picture. It connects plant capacity, technology, raw material consumption, utilities, manpower, financing, production yield and product selling prices with projected profit and cash flow.
A strong model normally covers at least 10 to 15 years of operations. For projects using significant debt, the financial projection may need to extend through the complete loan repayment period.
The objective is not simply to calculate profit.
The financial model should show whether the project remains financially workable when assumptions change. A model that produces an attractive IRR only when the plant operates at 100% capacity, feedstock prices remain unchanged and SAF sells at a premium price is not a particularly useful model.
A bankable SAF model should ultimately answer four questions.
Can the project generate sufficient operating margin? Can it service its debt? Can promoters recover their investment within an acceptable period? And does the return remain reasonable when adverse conditions are introduced?
There is no single “SAF plant cost”.
The economics change significantly according to the selected production pathway. This is one of the biggest mistakes that can occur during early-stage SAF project planning.
A HEFA plant processing used cooking oil or eligible fats and oils will have a completely different cost structure from an Alcohol-to-Jet plant using ethanol. A Fischer-Tropsch project using agricultural residue or municipal waste introduces gasification and syngas processing. A Power-to-Liquid project introduces another set of costs related to renewable electricity, electrolytic hydrogen and carbon dioxide.
For example, in certain HEFA economic assessments, feedstock can represent close to 80% of the production cost. This means a relatively small movement in the price of used cooking oil or another lipid feedstock can materially change the profitability of the entire project.
For an Alcohol-to-Jet project, ethanol price and conversion yield become major variables. If the ethanol itself is being manufactured from lignocellulosic biomass, feedstock collection and logistics become another major issue. One India-focused technical assessment illustrated how an SAF facility producing around 80,000 cubic metres annually could ultimately require roughly 554,000 tonnes of dry rice straw when the full upstream ethanol supply chain is considered.
That number demonstrates why an SAF financial model cannot be separated from the feedstock study.
The financial model must therefore start with the technology and material balance, not with an arbitrary investment figure.
CAPEX is the capital expenditure required to bring the SAF project from development to commercial operation.
Many early financial estimates focus almost entirely on the main process equipment. In reality, the process package is only one component of the total project cost.
A SAF project may require feedstock receiving and preprocessing systems, hydrogen facilities, storage tanks, utility systems, fire protection, electrical infrastructure, wastewater treatment, laboratories, piping, instrumentation and substantial civil construction.
Engineering, commissioning, contingency, pre-operative expenses and interest during construction can also become material.
Consider an illustrative 100,000 tonnes per annum HEFA-based SAF project. The numbers below are planning assumptions created only to demonstrate how a financial model can be structured. They are not vendor quotations or guaranteed project costs.
| CAPEX Component | Illustrative Cost |
|---|---|
| Land and site development | ₹70 crore |
| Civil works and buildings | ₹160 crore |
| Main process plant | ₹720 crore |
| Feedstock pretreatment system | ₹150 crore |
| Hydrogen and utility integration | ₹180 crore |
| Tank farm and product handling | ₹100 crore |
| Pollution control and fire systems | ₹60 crore |
| Electrical, automation and instrumentation | ₹115 crore |
| Engineering, project management and contingency | ₹150 crore |
| Pre-operative expenses, commissioning and IDC | ₹95 crore |
| Illustrative Total Project CAPEX | ₹1,800 crore |
Even at the feasibility stage, CAPEX should not be represented by one rounded figure such as “the project will cost ₹1,800 crore”.
Each cost should be connected with a technical assumption. If plant capacity changes by 20%, every component does not automatically increase by 20%. Some equipment costs scale differently, while land, laboratory, administration and certain utility infrastructure may remain relatively fixed.
A serious DPR therefore builds CAPEX from the equipment and infrastructure upward.
A promoter sees CAPEX immediately because it determines how much money must be raised. But over a 15-year operating period, OPEX can have an even greater impact on project profitability.
SAF plant OPEX usually includes feedstock, hydrogen, electricity, steam, catalysts, chemicals, manpower, maintenance, logistics, certification, laboratory testing, insurance, environmental compliance and waste management.
For the same illustrative 100 KTPA HEFA project, assume the plant eventually reaches 90% utilisation.
Its indicative steady-state operating cost could look like this:
| OPEX Component | Illustrative Annual Cost |
|---|---|
| Feedstock | ₹760 crore |
| Hydrogen | ₹85 crore |
| Electricity and steam | ₹55 crore |
| Catalysts and process chemicals | ₹35 crore |
| Maintenance and spares | ₹45 crore |
| Logistics and storage | ₹30 crore |
| Manpower and administration | ₹25 crore |
| Certification, laboratory, insurance, waste management and other costs | ₹45 crore |
| Total Illustrative OPEX | ₹1,080 crore/year |
Feedstock alone represents around 70% of the operating expenditure in this illustrative case study.
That concentration creates risk.
If feedstock prices rise by 15%, the feedstock bill increases from ₹760 crore to approximately ₹874 crore. Nothing has changed in the plant’s physical capacity, but annual operating cost has increased by roughly ₹114 crore.
If the business cannot pass that increase to its SAF customer, the amount comes directly out of operating margin.
This is why feedstock contracting can be as important to SAF finance as machinery selection.
Revenue modelling also requires caution.
The project may produce SAF together with renewable diesel, naphtha or other co-products depending on the technology configuration. Revenue should therefore be built from the complete mass balance.
Assume the illustrative plant reaches 90% utilisation and generates approximately ₹1,550 crore in annual net revenue from SAF and associated saleable products.
With annual OPEX of approximately ₹1,080 crore, EBITDA would be:
₹1,550 crore revenue – ₹1,080 crore OPEX = ₹470 crore EBITDA
This represents an EBITDA margin of approximately 30%.
That number might look attractive, but it is only useful if the underlying assumptions are credible.
The model should ask whether the SAF selling price is supported by an actual offtake discussion. Co-product selling prices should be independently assessed. Product yield should come from the technology provider or engineering design. Logistics costs should reflect the actual proposed location.
Revenue should also not automatically include subsidies, grants or carbon-related income simply because such mechanisms exist somewhere in the market.
If the project qualifies for a government incentive, it can be modelled separately. The base financial case should remain understandable even without uncertain support.
Commissioning does not mean full commercial production begins the following morning.
New industrial plants generally go through stabilisation, trial production, optimisation and gradual capacity ramp-up. SAF projects can have additional complexity because product quality and sustainability certification matter alongside physical production.
An illustrative ramp-up could therefore look like:
| Operating Year | Capacity Utilisation |
|---|---|
| Year 1 | 65% |
| Year 2 | 75% |
| Year 3 | 85% |
| Year 4 onwards | 90% |
Using this structure produces lower cash flow in the initial years but provides a more realistic picture of debt servicing.
For a lender, the important question is not whether the plant earns ₹470 crore EBITDA in a mature year. The important question is whether it can make scheduled loan repayments during Years 1, 2 and 3 while production is still ramping up.
Internal Rate of Return, or IRR, measures the return generated by the project over time after considering the timing of cash flows.
This distinction matters.
Receiving ₹100 crore next year is financially different from receiving ₹100 crore ten years later. IRR captures that time value.
For the illustrative ₹1,800 crore SAF project described above, a simplified 15-year project cash-flow model using the stated ramp-up, approximately ₹470 crore mature EBITDA and reasonable tax and sustaining-capital assumptions can produce a project IRR in the region of 15% to 16%.
This does not mean a 100 KTPA SAF plant in India will generate a 15% IRR. It means that these particular assumptions produce that result.
Change the assumptions and the IRR changes immediately.
Project IRR should also be distinguished from equity IRR. Project IRR measures the return generated by the underlying project without focusing on how it has been financed. Equity IRR measures the return to the promoter after considering debt, interest, repayments and promoter contribution.
A highly leveraged project can sometimes show an attractive equity IRR while simultaneously creating uncomfortable debt-service pressure. That is why lenders do not examine IRR alone.
The payback period tells the promoter approximately how long the project takes to recover its original investment from generated cash flows.
In the illustrative financial model above, cumulative simplified project cash flow could recover the ₹1,800 crore investment in roughly 5.8 to 6 years.
That sounds straightforward, but payback has limitations.
It does not properly reflect the time value of money unless discounted payback is calculated. It also does not tell the investor what happens after the investment has been recovered.
A project with a five-year payback and weak cash generation thereafter may be less attractive than one with a six-year payback and strong long-term cash generation.
Payback should therefore be reviewed together with NPV, IRR, DSCR and long-term free cash flow.
Debt Service Coverage Ratio, or DSCR, becomes particularly important when a substantial portion of project CAPEX is funded through loans.
In simplified terms:
DSCR = Cash available for debt service / Principal and interest payable
If a project generates ₹150 crore of cash available for debt service in a particular year and must pay ₹100 crore in principal and interest, the DSCR is 1.50.
A ratio below 1.00 means the project is not generating enough cash to meet scheduled debt obligations from operations.
Banks usually examine annual DSCR as well as the average DSCR over the loan period.
This is one reason an aggressive repayment schedule can damage an otherwise viable SAF project. Even if the plant produces strong cash flow after Year 4, heavy repayments during the commissioning and ramp-up years can place unnecessary pressure on the company.
Returning to our illustrative project, assume a 100 KTPA nameplate facility requires approximately ₹1,800 crore in project investment.
Production ramps from 65% utilisation in Year 1 to 90% from Year 4 onward. At mature operations, annual revenue reaches approximately ₹1,550 crore and annual OPEX reaches approximately ₹1,080 crore, producing around ₹470 crore EBITDA.
Under a simplified 15-year project model, the result could look approximately like this:
Project IRR: 15% to 16%
Simple payback: approximately 6 years
Mature annual EBITDA: approximately ₹470 crore
Mature EBITDA margin: approximately 30%
Now change only one assumption.
Increase feedstock cost by 15%.
Annual feedstock expenditure rises by approximately ₹114 crore and mature EBITDA falls from ₹470 crore to approximately ₹356 crore. Under the same simplified financial structure, project IRR can fall towards 10% to 11%, while payback can move towards approximately 7.5 years.
Now reduce revenue by 10% because the anticipated SAF premium is not realised.
Mature EBITDA could fall towards approximately ₹315 crore. Under the same simplified model, project IRR can fall towards approximately 8% to 9%, with payback extending beyond 8 years.
This is why a financial model is valuable. The original plant has not changed. The equipment is the same, the capacity is the same and the site is the same. But a relatively small movement in commercial assumptions has substantially changed the investment outcome.
A base financial model tells management what could happen if assumptions are achieved. Sensitivity analysis tells management what happens if they are not.
For an SAF project, the most important sensitivity checks generally include:
One useful test is to remove every incentive and uncertain revenue source from the model.
If the project immediately becomes financially unworkable, management should understand how dependent the investment is on external support.
A second useful test is to calculate the break-even SAF selling price. Instead of asking, “What IRR will we earn at ₹X per tonne?”, ask, “What is the minimum SAF selling price required to achieve a 12%, 15% or 18% project IRR?”
That question is often more useful during offtake negotiations.
SAF projects ultimately convert feedstock into fuel. The financial model cannot therefore treat feedstock procurement as a simple line item.
For a HEFA project, the team needs to evaluate the availability and price behaviour of used cooking oil, fats, oils or other eligible feedstocks.
For an AtJ project, the model must examine the cost and availability of ethanol. If ethanol is being produced within an integrated facility, the model must go further upstream into grain, molasses or lignocellulosic biomass economics.
For FT-based SAF, biomass collection, preprocessing, moisture, transportation and storage influence economics.
For e-SAF or Power-to-Liquid, electricity and hydrogen can become dominant cost drivers.
A plant with excellent technology but unreliable feedstock may struggle to reach the capacity utilisation assumed in its financial model.
The feedstock study and financial model should therefore be prepared together.
Before an SAF project’s financial model is presented to lenders or investors as an investment case, key assumptions need evidence behind them.
Technology yield should be supported by the licensor or engineering provider. CAPEX should progressively move from conceptual estimates towards vendor quotations. Feedstock assumptions should be checked against actual procurement geography. The offtake model should reflect conversations with credible buyers rather than only international SAF price reports.
Working capital also deserves attention. Large fuel projects can require considerable money for feedstock inventory, receivables, product storage and operating reserves. A project may appear profitable on its profit and loss statement and still experience cash pressure because money is locked in working capital.
The final model should therefore connect the technical DPR, market study, feedstock study, vendor quotations, project schedule and financing structure.
There is understandable excitement around Sustainable Aviation Fuel in India. Aviation decarbonisation, international sustainability requirements and India’s announced blending direction are creating a serious long-term opportunity.
But an SAF plant cannot be evaluated simply by saying that demand will increase.
A financially sound project must connect the production pathway with feedstock availability, technology yield, realistic capital expenditure, annual operating costs, product pricing, debt servicing and long-term offtake.
The difference between a 16% IRR project and an 8% IRR project may not require a major technological failure. As the illustrative case study showed, a 15% feedstock increase or a 10% reduction in revenue can materially change the project’s economics.
That is why feasibility assessment should happen before promoters commit major capital.
Green Permits supports project developers with SAF plant feasibility assessment, Detailed Project Reports, financial modelling, site and approval planning, feedstock assessment and project-development advisory. The objective is to understand the commercial and regulatory structure of the project before investment decisions become difficult to reverse.
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