Highlights
• US nuclear plant cost estimation does not align with observed experience
• “Indirect” expenses, largely soft costs, contributed a majority of the cost rise
• Safety-related factors were important but not the only driver of cost increases
• Mechanistic models inform innovation by relating engineering design to cost change
Summary
Nuclear plant costs in the US have repeatedly exceeded projections. Here, we use data covering 5 decades and bottom-up cost modeling to identify the mechanisms behind this divergence. We observe that nth-of-a-kind plants have been more, not less, expensive than first-of-a-kind plants. “Soft” factors external to standardized reactor hardware, such as labor supervision, contributed over half of the cost rise from 1976 to 1987. Relatedly, containment building costs more than doubled from 1976 to 2017, due only in part to safety regulations. Labor productivity in recent plants is up to 13 times lower than industry expectations. Our results point to a gap between expected and realized costs stemming from low resilience to time- and site-dependent construction conditions. Prospective models suggest reducing commodity usage and automating construction to increase resilience. More generally, rethinking engineering design to relate design variables to cost change mechanisms could help deliver real-world cost reductions for technologies with demanding construction requirements.
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The history of nuclear energy in the US is one of mixed results. Rapid capacity growth in the 1960s was accompanied by significant unit upscaling, followed by operational improvements and rising capacity factors. But in the 1970s, rising project durations and costs, alongside studies on thermal pollution and low-level radiation, became a source of public controversy. Following the 1979 Three Mile Island accident, a long hiatus of nuclear construction began. Rising construction costs and project delays have continued to affect efforts to expand nuclear capacity in the US since the 1970s. A survey of plants begun after 1970 shows an average overnight cost overrun of 241%. Since the 1990s, two nuclear projects have begun construction, both two-reactor expansions of existing generating stations. The VC Summer project in South Carolina was abandoned in 2017 with sunk costs of $9B, and the Vogtle project in Georgia is severely delayed. Current estimates place the total price of the Vogtle expansion at $25B ($11,000/kW), almost twice as high as the initial estimate of $14B, and costs are anticipated to rise further.
Challenges in nuclear construction are not unique to the US. Recent projects in Finland (Olkiluoto 3) and France (Flamanville 3) have also experienced cost escalation, cost overrun, and schedule delays. Cost estimates for a plant under construction in the United Kingdom (Hinkley Point C) have been revised upward. In contrast to the experience in Western Europe and the US, however, China, Japan, and South Korea have achieved construction durations shorter than the global median since 1990. Cost and construction duration tend to correlate (e.g., Lovering et al.), but it should be noted that cost data from these countries are largely missing or are not independently verified. (Cost data should be provided and audited by entities not actively involved in plant procurement and construction, including data from international organizations or government agencies as opposed to data from utilities and reactor equipment providers.)
Percentage contribution of variables to increases in containment building costs These panels summarize types of variables that caused costs to increase between 1976 and 2017. In the first time period (left panel), the major contributor was a drop in the rate at which materials were deployed during construction. In the second period (middle panel), the containment building was redesigned for improved safety during possible emergencies, and the required increase in wall thickness pushed up costs. Overall, from 1976 to 2017 (right panel), the cost of a containment building more than doubled.
As the left and center panels above show, the importance of those mechanisms changed over time. Between 1976 and 1987, the cost increase was caused primarily by declining deployment rates; in other words, productivity dropped. Between 1987 and 2017, the containment building was redesigned for passive cooling, reducing the need for operator intervention during emergencies. The new design required that the steel shell be approximately five times thicker in 2017 than it had been in 1987—a change that caused 80% of the cost increase over the 1976–2017 period.
Decreases in containment building costs due to four high-level mechanisms under three innovation strategies Scenario 1 assumes a 20% improvement in all variables; Scenario 2 increases on-site material deployment rates by using advanced manufacturing and construction management techniques; and Scenario 3 involves use of advanced, high-strength construction materials. All three strategies would require significant R&D investment, but the importance of the other high-level mechanisms varies. For example, “learning-by-doing” is important in Scenario 2 because assumed improvements such as increased automation will require some on-site optimization of robot operation. In Scenario 3, the use of advanced materials is assumed to require changes in building design and workflows, but those changes can be planned off-site, so are assigned to R&D and “knowledge spillovers.”
Despite historical precedence for rising costs, nuclear industry, government, and research agencies continue to forecast cost reductions in nuclear construction. These entities make significant investments in the development and commercialization of next-generation reactor designs based on the expectation that successive plants of standard design will cost less than first-of-a-kind plants. This notion is applied to all commercial reactors, though the anticipated cost reductions are greatest for small modular reactors (SMRs) due to expected learning effects in factory settings. The first SMR has yet to be built.
The projected role of nuclear power in many decarbonization scenarios (e.g., Iyer et al. and the Intergovernmental Panel on Climate Change) also stands in contrast to recent trends. In the US, nuclear power plants provided roughly 20% of the electricity supply in 2019, down from a reported peak of 23% in 1995, and roughly 50% of low-carbon electricity, though the exact reported values show a small amount of variation. Low-cost domestic natural gas supply and declining costs of renewable power have put several plants at risk of premature retirement, and equipment replacements to extend plant lifetimes have proven challenging. Four US plants have shut down despite possible license extensions, and closure of 15–20 more plants is expected by 2030. Other countries with aging nuclear infrastructure (e.g., Spain and the UK) are facing similar challenges.
Previous literature has presented various hypotheses on the causes of nuclear construction cost increases. These studies fall into two groups: (1) studies of nuclear technology cost trends over time; (2) engineering cost models of nuclear power plants for a given design, at a given point in time. By studying time series of overnight capital costs, studies in the first group have shown that nuclear costs in the US have increased before and after Three Mile Island, cost trends differ across countries, and construction costs have increased even in countries with comparatively short construction times. Previous work has reported cost reductions when the same firm built multiple plants of the same model in France, and stable costs in Japan between 1980 and 2011, owing among other factors to supportive national policies. Overall, the majority of studies document construction cost increases and conclude that the nuclear experience has been one of limited or even negative cost-related learning.
Cost increases have been associated with reactor upscaling, a lack of technology standardization, fragmented industry structure and plant ownership, and increasing plant complexity including increases in the number of plant components, new control systems, redundancy in equipment, and added safety features. Studies of cost escalation in mega-projects more broadly have found that nuclear power plant projects exhibit greater and more frequent cost overruns and delays compared to other electricity generation infrastructure, which has been linked to reduced modularity and more complex project governance compared to other technologies.
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In this paper we begin to address these gaps by examining US construction cost data from five decades and modeling the cost evolution of entire plants and of one major plant component, the reactor containment building. We present a collection of insights on cost trends and the sources of these trends. Contrary to standard engineering estimates for expected cost declines, we find that costs have instead risen in the US, even for plants of the same design class. This specific finding is missing in previous literature. Next, we examine what types of costs contributed most to cost increases, using cost accounting data on individual plant components and mechanistic models of cost change determinants. We find that declining labor productivity and increasing commodity use were major contributors to cost increases. Overall, a common theme emerging from this analysis is the lack of anticipation in engineering models of the cost-increasing contributions of soft technology external to standard reactor hardware, in response to changing regulations and other factors such as variable project-specific conditions. Prospective modeling shows the potentially transformative effect of rethinking engineering design to adapt to these factors, for example through reduced commodity usage and the automation of some construction processes.
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by Philip Eash-Gates 1 and 4, Magdalena M.Klemun 1and 4; Goksin Kavlak 1, James McNerney 1, Jacopo Buongiorno 2, and Jessika E.Trancik 1, 3 and 5
1. Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
2. Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
3. Santa Fe Institute, Santa Fe, NM 87501, USA
Joule via Elsevier Science Direct www.ScienceDirect.com
Volume 4, Issue 11; November, 2020; Pages 2348-2373; Available online 18 November 2020; Published: November 11, 2020
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Separately on December 17, 2020 in "Want cheaper nuclear energy? Turn the design process into a game - Researchers show that deep reinforcement learning can be used to design more efficient nuclear reactors." at https://tinyurl.com/yd3vuotm Kim Martineau notes "Researchers at MIT and Exelon show that by turning the design process into a game, an AI system can be trained to generate dozens of optimal configurations that can make each rod last about 5 percent longer, saving a typical power plant an estimated $3 million a year, the researchers report. The AI system can also find optimal solutions faster than a human, and quickly modify designs in a safe, simulated environment. Their results appear this month in the journal Nuclear Engineering and Design."
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