CEEPR Working Paper
2025-20

Sophia A. E. Spitzer, Katja Pelzer, Anton Bauer, and Maximilian J. Blaschke

Fusion power has long been hailed as a transformative technology capable of delivering virtually limitless, carbon-free electricity (Armstrong et al. 2024; Takeda et al. 2023; Schwartz et al. 2023; Nicholas et al. 2021). Its expected attributes — clean baseload generation, high energy density, and siting flexibility — make it attractive to the ambitious global decarbonization agenda. Yet repeated delays and the so-called “fusion constant,” the perception that fusion is always thirty years away (Takeda and Pearson 2019; Ball 2021), have made its commercialization success and timing highly uncertain.

This study evaluates fusion’s prospective role in a future energy system through a two-stage approach. First, we implement fusion plants in PyPSA-Eur, an open-source, sector-coupled model of the European energy system with three-hour temporal resolution and a 39-node spatial network (Brown et al. 2024; Victoria et al. 2022; Victoria et al. 2020; Neumann et al. 2023). The model simulates a cost-optimal capacity mix from 2030 to 2100 under varying assumptions about fusion’s commercialization date (2035 vs. 2050), overnight capital costs, and diffusion constraints. Second, a probabilistic evaluation framework translates modeled system cost savings into an Anticipated Commercialization Probability (ACP), a measure of the likelihood investors implicitly assign to fusion’s success based on observed investment flows.

The modeling reveals three characteristic phases of fusion deployment (see Figure 1).

Diffusion phase (2035–2050): Fusion grows in parallel with increasing electricity demand during the energy transition.

Replacement phase (2050–2070): A second wave of fusion growth coincides with the end-of-life replacement of renewables installed during the pre-2040 high-growth phase. This shift is primarily driven by the phase-out of wind capacity, which has become less competitive due to its comparatively lower learning rates compared to solar PV.

Saturation phase (after 2070): Fusion’s relative advantage diminishes as cost reductions slow. The technology reaches a saturation point, where fusion’s learning rate unlocks new energy generation potential only under favorable cost trajectories.

Under low-cost assumptions (< 4,000 USD2020/kWel), fusion could supply up to 30 % of European electricity by 2100 and reduce cumulative system costs by nearly EUR 2 trillion (discounted to 2020). Crucially, these savings arise less from cheap generation per se than from avoided storage and renewable capacity: As a baseload source, each gigawatt of fusion can displace several gigawatts of variable renewables, cutting storage needs, grid expansion, and balancing services. Even with only a 10 % capacity share, fusion’s high utilization enables it to deliver roughly one-third of total generation while reducing long-distance transmission needs by up to 20 % and hydrogen transport by 45 %.

Capital costs emerge as the single strongest driver of fusion’s market share and system value. Low overnight capital costs enable fusion to scale to double-digit capacity shares even if commercialization is delayed, while high costs render the technology marginal regardless of timing or build-out limits. Timing remains critical, particularly for the economic value. A delay from 2035 to 2050 reduces the discounted system savings by more than half, even when long-run generation shares stay sizable.

By comparing modeled system benefits to cumulative European public and private investments (EUR 42 billion by 2035; EUR 76 billion by 2050), we further infer anticipated success probabilities below 20 % for a 2035 market entry. This gap between large theoretical value and modest investment reflects a high-risk/high-reward paradox typical of breakthrough technologies: uncertainty suppresses funding, which in turn limits the likelihood of success.

Policy implications are twofold. First, accelerating cost reductions — e.g., through modular reactor designs, standardized licensing, or milestone-based incentives — is critical for timely deployment. Second, current investment levels appear inconsistent with the societal value that fusion could provide. Without stronger public support or new financing mechanisms, Europe risks underinvesting in a technology that could lower long-term energy costs and enhance energy sovereignty.

 

Figure 1. Evolution of Europe’s energy generation mix with (Fusion35-base-nocap) and without (Reference) fusion.

Note: The reference scenario follows PyPSA-Eur assumptions extrapolated to 2100. The fusion scenario assumes fusion availability from 2035 under baseline cost assumptions and without capacity deployment constraints.

 

Link to the full working paper:

MIT CEEPR Working Paper 2025-20

About The Authors

Sophia A. E. Spitzer conducted her doctoral research at the TU Munich. Her work explores the commercialization and diffusion of complex energy technologies, with a focus on fusion power. Empirically, she combined high-resolution energy system modeling with conceptual analyses of technology diffusion and deep-tech entrepreneurship. Her studies assess fusion’s potential role in decarbonized energy systems, investor expectations, and strategies for accelerating the scale-up of capital-intensive innovations.

Katja Pelzer completed her studies at the TU Munich. In her research, she focused on the integration of fusion power into European energy system models, contributing extensively to the adaptation of the open-source tool PyPSA-Eur.

Anton Bauer conducted his thesis at the TU Munich, specializing in energy system optimization. He contributed to the software implementation and computational analysis of fusion deployment scenarios in PyPSA-Eur. His research interests lie at the intersection of energy modeling, low-carbon technologies, and applied data science.

Maximilian J. Blaschke is a professor and researcher at the Center for Energy Markets at TU Munich and an affiliate at MIT CEEPR. With his economic and accounting background, he explores ways of more efficient policy measures for the transition to sustainable alternatives in electricity and mobility. His recent research investigates incentivization mechanisms for residential demand response, subsidy efficacy considering carbon emissions of electric vehicles, and the related costs to ensure grid stability in future mobility scenarios.