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Build an SMR market model around a specific site, customer, energy product and delivery date—not around a global deployment forecast. Start with evidence for demand and offtake, compare the project with local alternatives, then connect commercial value to costs, financing and delivery readiness. Until those inputs are supported by project documents and counterparties, treat the results as scenarios rather than a forecast.
What an SMR market model needs to answer
A market model tests whether a particular small modular reactor (SMR) project can serve a defined need on terms that could support a real commercial decision. It is not the same as estimating how large the global SMR industry might become. The project’s addressable market depends on its jurisdiction, location, design, capacity, customer, energy product, timing and commercial arrangements.
The OECD Nuclear Energy Agency (NEA) defines SMRs in its 2021 report Small Modular Reactors: Challenges and Opportunities as reactors with power output between 10 MWe and 300 MWe. That range describes the report’s definition; it does not establish that every design in development suits every grid, industrial load or site. A market model must test the fit between the proposed project and the specific service a customer needs.
The model should connect four questions:
- Need: What energy service is required, where, when and in what quantity?
- Fit: Can the proposed reactor and its associated infrastructure provide that service?
- Commercial route: Who would buy or use the output, under what arrangement, and who carries the main risks?
- Deliverability: Can the project reach operation in time, with a plausible route through licensing, siting, financing, supply-chain and fuel requirements?
A model that answers only the first two questions describes a potential application, not yet a market. A model that also addresses who pays, how much, when and subject to which conditions is more useful for deciding whether to advance the project.
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Set the project boundary before estimating demand
Write down the project boundary first. Without it, a demand estimate can quietly shift between a regional market, a national forecast and a single customer’s load, even though those are different markets with different evidence and risks.
Record the defining project inputs
- Jurisdiction and candidate site: Identify the market rules, regulatory context, grid or industrial infrastructure and location the model covers.
- Reactor design and capacity: Specify the design under consideration and the capacity being modeled. Do not assume that the broad 10–300 MWe SMR definition establishes project suitability.
- In-service date: State the date or schedule scenario at which the project could begin delivering energy. The date affects which demand, competing supply and contract opportunities are relevant.
- Customer or offtaker: Name the intended buyer or on-site user, if identified. If there is no confirmed counterparty, distinguish potential customers from contracted demand.
- Energy product: Clarify whether the project would sell electricity, provide useful heat, supply an industrial host, support hydrogen or synthetic-fuel production, or serve another defined use.
- Delivery arrangement: State whether output would be sold to a grid, delivered under contract to a host, or used on site. Identify the delivery point and any required connection or interface.
Then define the market by geography, product and time period. A grid-electricity market in a defined region is not interchangeable with a host facility’s process-heat demand or a potential future hydrogen market. Where a project has more than one possible product, model each route separately before considering whether they can coexist. Do not count the same reactor output as simultaneously sold to multiple customers.
Keep evidence categories visible
For each material input, record its value or range, unit, time period, source, date and status. Label whether it comes from a signed contract, a customer document, a third-party forecast, a vendor statement, a sponsor assumption or a published scenario. These categories do not carry the same weight. A prospective customer’s expression of interest, for example, is not equivalent to a binding offtake agreement.
Keep a distinction between established inputs and assumptions in the model itself. A reader should be able to trace a conclusion about revenue or schedule back to the evidence behind the input, rather than mistake an illustrative assumption for a known project fact.
Build demand from the customer and energy system
Estimate demand from evidence tied to the proposed use. The strongest starting point depends on the project: a customer’s load data may matter most for direct supply, while a grid or system forecast may be central to a project selling into an electricity market. If no project-specific customer, site or demand information has been established, the model cannot credibly produce a project-specific demand forecast.
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Use the right demand evidence
- Grid power: Use credible jurisdictional or system demand forecasts, with the relevant region and forecast period made explicit. Identify the portion of demand the project could realistically serve rather than treating total system demand as addressable demand.
- Industrial electricity or heat: Use customer load profiles and documented process-heat requirements where available. Record the timing, quantity and form of the required energy, along with any integration conditions relevant to the proposed design.
- Off-grid or remote loads: Establish the actual site load and the energy service currently provided or needed. Assess the infrastructure and alternatives relevant to that location rather than extrapolating from a national electricity market.
- Hydrogen, synthetic fuels or other products: Establish the prospective customer, process and commercial route. A broad application category does not establish demand for a particular project.
Match demand shape, not just annual totals
Annual energy consumption can conceal a mismatch between when the customer needs energy and when the project can provide it or earn value for providing it. Use hourly or seasonal profiles when the value of firm supply, flexibility or heat integration depends on timing. Note the time resolution and evidence behind the profile; do not imply that a monthly or annual total proves hourly fit.
Compare demand with existing and planned generation, grid connections, storage, demand response and other relevant supply options. Account for the electricity system expected when the project would operate, not only the system as it exists today. The NEA’s 2021 report Advanced Nuclear Reactor Systems and Future Energy Market Needs discusses electricity systems changing with renewables, storage and demand-side management. Those changes can affect when additional generation is needed and the value of its output; their effect must be assessed in the project’s actual market.
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Choose a credible route from output to revenue
List only revenue routes that the proposed design, site, customer and market arrangement can support. The OECD/NEA material describes possible applications and economic dependencies, but it does not prescribe a universally valid SMR revenue stack. A project model therefore needs to show how each proposed source of value would be earned, rather than treating possible uses as guaranteed income.
Separate revenue by commercial status
- Contracted revenue: Identify the counterparty, contract term, price basis, volume, delivery point and allocation of relevant risks. Keep any conditions, limits or uncontracted volumes visible.
- Merchant revenue: Model sales exposed to market prices separately from contracted sales. State the market and price assumptions used, and show how the outcome changes if those assumptions change.
- Capacity or reliability value: Include it only where the relevant market or contract compensates the project for that service. Describe the basis for compensation rather than assuming that reliability has a cash value in every jurisdiction.
- Policy support: Identify the applicable support mechanism and its conditions. Separate confirmed support from prospective or assumed support.
- Industrial products or services: Model heat, direct industrial supply, hydrogen, synthetic fuels or other outputs only where the customer, technical fit and commercial arrangement are substantiated.
For each route, show the energy or service sold, expected volume, price basis, timing and party responsible for each delivery obligation. If one customer or contract would provide several forms of value, make clear how the amounts relate so that one benefit is not counted twice. Treat potential revenue without a named customer or supported market mechanism as uncontracted upside, not as base-case income.
Model project costs and financing as separate inputs
A market opportunity is not a business case unless the model also represents the cost and financing needed to deliver it. Keep cost categories distinct and document their scope, timing and evidence. The available OECD/NEA reports emphasize that SMR economics depend on market development and enabling conditions; they do not supply the capital cost, financing terms or operating costs for an unspecified project.
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Build a transparent cost structure
- Construction and owner’s costs: Record these separately so the model makes clear what is included in the project estimate and what the owner must provide.
- Financing during construction: Represent financing needs and timing explicitly. A project that takes longer to build may require more financing and may begin earning revenue later.
- Fuel and operations: Keep fuel, operations and maintenance inputs visible rather than burying them in a single cost assumption.
- End-of-life and waste: Include documented assumptions for decommissioning and waste management as separate model categories.
- Connection and integration: Include grid connection and any required heat or industrial interface. These may be central to whether the proposed product can reach its customer.
Do not present one total project-cost figure without defining what it covers, when it is incurred and whether financing is included. If an input is not established, label it as an assumption and show its effect through scenarios rather than supplying an unsupported point estimate.
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OECD/NEA’s 2016 report Small Modular Reactors: Nuclear Energy Market Potential for Near-term Deployment discusses potential cost advantages associated with serial production, optimized supply chains and smaller financing costs. Those are conditional possibilities, not guaranteed attributes of every project. Test whether the project’s procurement plan, build sequence and financing structure actually support the assumed benefit.
Keep first-of-a-kind project assumptions distinct from repeat-build assumptions. Do not apply a prospective series-production benefit to the first project as if repetition, supply-chain optimization or financing improvements had already occurred. Show which conditions would need to be met for a repeat-build case to become relevant.
Treat deployment readiness as schedule and commercial risk
Technical feasibility is only one part of whether a project can be delivered. The NEA Small Modular Reactor Dashboard framework tracks licensing, siting, financing, supply chain, engagement and fuel. Use these dimensions to structure a project milestone and risk register, while keeping project-specific status grounded in current evidence. Do not assign readiness scores or probabilities without evidence for this project.
| Readiness area | What to document | How it can affect the model |
|---|---|---|
| Licensing | Relevant approval path, required milestones and the evidence for expected timing. | Changes the plausible operating date and the period before revenue can begin. |
| Siting | Site status, required land or infrastructure decisions and unresolved siting steps. | Can affect schedule, connection assumptions and whether the proposed use is practicable. |
| Financing | Proposed financing structure, timing and status of financing commitments. | Affects construction funding needs and the project’s exposure to delay. |
| Supply chain | Procurement approach and evidence that required suppliers and inputs can support the project. | Can affect delivery timing and whether repeat-build cost assumptions are credible. |
| Engagement | Relevant stakeholder engagement and unresolved issues that could affect the project path. | May influence whether schedule assumptions remain plausible. |
| Fuel | Fuel requirements, availability arrangements and their status for the proposed design. | Can affect readiness to operate and the assumptions behind fuel costs. |
For each material milestone, record the expected timing, evidence, responsible party, dependencies and consequence if it slips. Connect schedule scenarios to the financial model: a delay can defer revenue, change financing during construction and affect contract obligations. The size of those effects is project-specific, so calculate them from the model’s actual cost, financing and contract inputs rather than applying a generic delay penalty.
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The Dashboard’s counts also need edition context. Its 2023 Volume II publication page describes the volume as tracking an additional 21 SMRs; the first volume assessed 21 designs. Those are counts within the stated report scope and editions, not a current total of all designs or a measure of how many are ready for a particular project.
Compare the project with local alternatives
Compare the SMR option with alternatives that could provide the same service to the same customer or system. Depending on the use case, these may include grid supply, renewables plus storage, other firm generation, efficiency or industrial process changes. The relevant set depends on the site and market; the source material does not establish one universally superior technology.
Use consistent service, delivery and financing assumptions wherever possible. A comparison is misleading if one option is evaluated on delivered energy while another is evaluated on generation alone, or if the alternatives are assumed to arrive on different schedules without accounting for that difference.
| Comparison axis | Question for the model |
|---|---|
| Delivered cost and financing exposure | What does it cost to provide the required service, and how does each option depend on financing and construction timing? |
| Load and reliability fit | How well does each option match the customer’s load shape and reliability requirements? |
| Construction and connection timing | When could each option plausibly begin serving the need, and what connection work is required? |
| Licensing and siting readiness | What relevant approvals, site steps and schedule evidence exist for each option? |
| Supply-chain and fuel readiness | What procurement, fuel or other delivery dependencies could affect each option? |
| System interaction | How does the option interact with renewables, storage and demand-side management in the relevant system? |
| Contractability | Can the output be sold or used through a supportable contract or market mechanism? |
| Emissions, land and infrastructure | What differences matter for the defined service and location, and what evidence supports them? |
Select comparison axes that match the actual decision. For a direct industrial host, connection and heat-integration needs may matter more than a broad comparison of national generation mixes. For a grid-connected project, system-level demand, competing supply and market rules may be more central. Explain exclusions so readers can see what the comparison does and does not establish.
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SMR economics depend on uncertain market, financing, supply-chain and delivery conditions. Present a reference case alongside conservative and upside cases, with each case tied to explicit assumptions. A scenario is a way to test the consequences of an assumption; it is not evidence that the assumption will occur.
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Test the variables that can change the decision
- Demand, utilization and the shape of customer or system load.
- Realized capital cost and the scope included in that cost.
- Financing rate, financing structure and the timing of funding needs.
- Construction schedule and the effect of delay on revenue and contract obligations.
- Fuel, operations and maintenance costs.
- Market prices, contract terms and the share of output that is actually contracted.
- Availability and conditions of policy support.
- Whether serial production, supply-chain optimization or financing benefits are achieved under the project’s actual plan.
Show which variables drive value and where the project reaches its break-even conditions under the model’s assumptions. Avoid presenting a single project IRR or levelized cost as a complete answer without its ranges, date, geography and assumptions. If the project lacks supported cost, tariff, demand or schedule inputs, report what evidence is missing rather than constructing a numerical example from invented values.
Label the origin of assumptions consistently. Sponsor assumptions, vendor statements, third-party forecasts and published historical scenarios should remain distinguishable throughout the analysis. In particular, a published global deployment scenario should not silently become a project-demand assumption.
Use global market figures only as context
The OECD/NEA 2016 report’s high case estimated that up to 21 GWe of SMRs could be added globally by 2035, representing approximately 3% of installed nuclear capacity in that scenario. This is a historical scenario from the 2016 report, not a current actual, updated forecast or estimate of demand at a particular site. It may provide context for the report’s view of possible market development, but it cannot substitute for customer evidence, local system demand or an offtake route.
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The same distinction applies to general statements about potential SMR applications. The 2023 NEA Dashboard Volume II summary describes applications that can include grid power, industrial heat and power, off-grid mining power, hydrogen and synthetic fuels. A category’s inclusion signals a possible application area; it does not demonstrate that a particular reactor, site and customer have a viable technical or commercial arrangement.
Turn the model into a decision and evidence plan
The model’s final output should make clear what is known, what remains conditional and what evidence would change the decision. A concise decision view can report the following without implying false precision:
- Addressable demand: The defined customer or system need, the period it covers and the evidence behind it.
- Offtake route: The proposed buyer or user, energy product, contract status and uncontracted exposure.
- Competing supply: The alternatives considered and the common terms used for comparison.
- Delivery readiness: The licensing, siting, financing, supply-chain, engagement and fuel milestones that matter to the schedule.
- Scenario economics: The outcomes under stated assumptions and the factors that most affect them.
- Next evidence: The project documents, market data, counterparty commitments or current regulatory and vendor records needed to replace material assumptions.
If no location, design, customer, load profile, alternatives, tariff, capital cost, financing structure, licensing schedule or fuel arrangement has been established, the model should stop short of claiming a project-specific forecast. Its useful result is then a structured account of the market questions, the assumptions that need testing and the evidence required before a commercial conclusion is supportable.
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