Forecasting Fusion’s Role in the Marketplace of Tomorrow

Fusion energy is moving from laboratory demonstration to commercial reality, but investment decisions remain hampered by a lack of financial models that capture its unique physics and cost structures. We present the first open-source, physics-informed financial modelling framework for fusion projects, written in Python with modular, flexible design. The model couples fusion-specific costing codes and a detailed financial model, allowing plant size and fusion technology choice to be directly translated into capital intensity. Regional adjustments for financing, taxation, and construction conditions are built in, alongside whole-life economics from construction through decommissioning. Outputs include investor-focused KPIs: levelized cost of energy (LCOE), net present value (NPV), internal rate of return (IRR), debt service coverage ratio (DSCR), and payback all delivered via an interactive dashboard that supports scenario testing, Monte Carlo and variance-based sensitivity analysis, and policy evaluation. Validation against ITER and Vogtle references, as well as Lazard’s LCOE methodology, confirms the robustness of the approach. By linking reactor physics to project finance in a transparent framework, this tool provides the first whole life cashflow assessment platform for fusion energy. It enables sovereign wealth funds, philanthropic bodies, and private investors to evaluate projects rapidly, identify leverage points such as construction duration or debt terms, and assess the role of policy in reducing cost of capital. In doing so, it lowers the barrier to investment readiness and accelerates the path toward commercial fusion deployment.