A Costing Framework for Fusion Power Plants

The Need for a Standardised Costing Framework for Fusion

As fusion concepts move from small-scale lab demonstrations toward integrated pilot plants, a familiar question keeps coming back from developers, funders, and policymakers: are the economics credible? In practice, the answer comes down to whether cost estimates are transparent, comparable across different fusion architectures, and traceable back to the technical assumptions that produced them. This need for economic credibility is the motivation behind the Costing Framework for Fusion Power Plants, described fully in this recent publication from Woodruff Scientific LTD.

At the heart of the framework is a repeatable workflow inspired by the ARIES family of fusion power plant studies: begin with a power balance, translate that into a feasible radial build subject to engineering constraints, size the dominant driver systems (for example magnets, lasers, and power supplies), and then map thermal performance and plant layout into balance-of-plant (BOP) equipment and buildings. Crucially, the assumptions and cost bases are stated explicitly so the path from the inputs is auditable.

The project goals are two-fold: (1) create a clear structure for fusion power plant costs, and (2) create a comparable framework for understanding major cost drivers and what happens when key machine/power parameters change. The longer-term ambition is to support credible techno-economic analysis and ultimately an accurate Levelised Cost of Electricity (LCOE).

How the Framework Evolved

Developed as ARPA-E support work between 2017-2024, the work evolved in distinct stages, each adding realism and improving comparability.

Figure 1: this capability exists for a range of fusion concepts, including tokamaks, stellarators and tandem mirrors, across MFE, IFE and MIF. Image credit: Max Planck Institute for Plasma Physics, Germany (tokamak and stellarator), GPT-generated (tandem mirror).

In 2017, the methodology was piloted with Bechtel and Decysive Systems to calibrate ARIES-derived outputs against EPC (engineering, procurement, construction) experience and sanity-check plant-level reasonableness, especially for BOP-related costs. This phase also highlighted how sensitive total capital cost can be to layout, buildings, and major equipment sizing.

In 2019, work with Lucid Catalyst and Decysive Systems expanded the focus beyond the fusion power core. The emphasis shifted toward indirect costs and actionable “cost-out” pathways for non-power-core parts of the plant - standardised layouts, modularisation and learning effects.

During 2022–2023, as ARPA-E’s fusion portfolio grew, the capability matured into portfolio-scale support for BETHE and GAMOW awardees (and selected ALPHA revisits). This phase improved the realism of tritium handling and fuel-cycle assumptions, supported by Princeton/PPPL operational and safety expertise, an important step toward analyses that reflect what future plants will actually need to build and operate.

By 2023, cross-concept comparability became a central driver. The framework was refactored toward international standards - aligning with the IAEA (2001), GEN-IV EMWG (2007), and EPRI (2024) code-of-accounts lineage - and legacy ARIES scalings were increasingly replaced with bottom-up subsystem models for major fusion cost drivers. This is where structure and traceability became the foundation for credible comparison.

Figure 2: unoptimised renders from ARPA-E costing study, 2020, showing different fusion concepts across MFE, IFE and MIF.

How it Works

The framework follows a general flow from physics to economics: physics inputs and global assumptions feed a power balance; that drives geometry, equipment sizing, and layout; and those intermediate quantities then roll up into standardised cost accounts and an estimated (preliminary) LCOE. The final report supplements the outputs with the models and references needed to trace assumptions back to sources.

A major design choice is the use of standardised cost account categories. Each generated report follows the same major sections and taxonomy, enabling cross-concept comparability across magnetic fusion energy (MFE), inertial fusion energy (IFE), and magneto-inertial fusion (MIF): one top-level structure, consistently applied.

Figure 3: standardised cost categories used in the Costing Framework for Fusion. Image credit: Simon Woodruff

This accounting structure draws on three major sources: IAEA methodology, the GEN-IV Economics Modelling Working Group (G4EMWG), and Geoffrey Rothwell’s Economics of Nuclear Power. Importantly, the paper emphasises that the point is not to hide fusion inside fission accounting, but to use a vetted, standards-aligned structure while making fusion-specific departures explicit at the subsystem level, preserving comparability without losing the reality of fusion cost drivers.

This costing capability has been implemented into NuPlant at nTtau Digital and used to support multiple private fusion companies by tailoring the analysis to their specific concept.

Application Access and Outputs

Check out this link to generate your very own comprehensive costing report.

The report includes a cost-accounting table with high-level totals and detailed breakdowns (including total capital cost, direct costs, and reactor plant equipment costs), and it visualises key cost categories so users can quickly see which components dominate. The final output is a preliminary LCOE, intended to progress in parallel with technology and improved realism.

Two key tables are provided in the report:

• A Cost Accounting Structure (CAS) table: includes a hierarchical breakdown of capital costs. Sub-accounts (for example, first wall & blanket) allow detailed tracking, and the table reports both absolute cost and percent of total capital cost.

• A Power Accounting table: a full power-flow breakdown from fusion output through conversion and recirculating loads to net electric power, including metrics like scientific/engineering Q and recirculating power fraction.

  
  

Structure and traceability are as important as the numbers: the framework is built so assumptions can be inspected, updated, and compared cleanly as designs mature.

Safety Inclusion

One of the most important additions, especially as fusion moves toward commercialisation, is the explicit inclusion of safety and re

gulatory drivers within the costing structure. Hazards are identified and mapped onto cost categories using a hazard category index that reflects regulatory importance and consequence severity, translating the highest-index hazards into cost impacts carried through the model.

The report also includes region-dependent safety and licensing components. Regulatory/insurance costs are treated via adaptations of fission premiums into the fusion landscape by weighting the level of safety insurance using prior ARIES studies.

What Does This Mean for Fusion?

If fusion is going to be taken seriously as an energy technology, it needs a common language for costs, one that lets people compare concepts fairly and understand why a number changes when the design changes. This framework is built around that idea; it’s providing a disciplined way to reveal dominant cost drivers and run sensitivity studies, so when someone asks “what will this cost, and why?” the answer isn’t a black box, but a traceable story from design choices all the way to economic outputs.

You can also check out this webinar from the Clean Air Task Force for more information.