Economies of Scale in Nuclear Power Generation

Krautmann, Anthony C.; Solow, John L.

doi:10.2307/1058857

Cited by 40 publications

(20 citation statements)

References 16 publications

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“…The negative labor and maintenance elasticity of capital demand indicates that capital and labor are complements, but the results are insignificant due to the large standard error. These results are consistent with those of Krautmann and Solow (1988). The estimate for the own-price elasticity of capital is -2.102, which is also very close to their estimate of -2.334.…”

Section: Resultssupporting

confidence: 90%

“…These studies used data on the generation source, which represents the dominant part of the U.S. electricity supply industry. However, the number of previously published studies on the cost structures and scale economies of nuclear power generation is relatively small and not recent [e.g., Krautmann and Solow (1988), Marshall and Navarro (1991), Canterbery, Johnson, and Reading (1996)]. …”

Section: Introductionmentioning

confidence: 99%

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Estimating Cost Structures in the U.S. Nuclear Power Industry

Rungsuriyawiboon

2008

Energy Exploration & Exploitation

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With growing concerns about global warming and surging oil prices, nuclear power is now back on the U.S. energy policy agenda. This paper provides firm level analysis of the production technology and cost structures in the U.S. nuclear power generation industry. The paper applies an econometric approach into a dual restricted variable cost function within a "temporal equilibrium" framework. A panel data set of 32 nuclear power generations for major U.S. investor owned utilities over the period 1986-2002 is used. The major finding indicates that most electric utilities in the nuclear electricity generation industry over utilized capital in production. The estimated results show evidence of scale economies in the production of the electricity industry. The paper presents supporting evidence that nuclear technology is cheaper than other alternative technologies and fuels, and it can offer possible cost savings to other alternative technologies.

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Section: Resultssupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Estimating Cost Structures in the U.S. Nuclear Power Industry

Rungsuriyawiboon

2008

Energy Exploration & Exploitation

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“…These include factors such as regional labour costs or whether sites at different latitudes require different amounts of construction to be done indoors [17,[37][38][39][40][41].…”

Section: Shipments (Thousands)mentioning

confidence: 99%

Learning curves and technology assessment

McDonald¹,

Schrattenholzer²

2002

IJTM

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This paper uses the formal concept of learning curves to analyse regular behaviour of performance improvements in various energy technologies. The concept allows the estimation of a single indicator of technological progress, the learning rate, which expresses the constant percentage improvement (usually in terms of cost reductions) in a technology for each doubling of the technology's cumulative installed capacity. We present 42 energy-related learning rates, either calculated directly from available data or assembled from the literature. We elaborate briefly on eight of these to illustrate issues addressed by technology assessments to convert these raw historical learning rates into prospective learning rate distributions for use in long-term energy models. The paper includes a sensitivity analysis of policyrelevant variables with respect to learning rates, a discussion of possible extensions and limitations of the approach and an outlook on future work in the field. Keywords Leaming curves and technology assessmentincluding the analysis of the role of research and development in enhancing technological progress.

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“…Zimmerman (1982), Krautmann and Solow (1988), Cantor and Hewlett (1988) and McCabe (1996) found that the construction of larger reactors 8 increased the cost per MW installed. According to Cantor and Hewlett (1988), bigger units increase project complexity, subjecting them to managerial problems and stricter regulatory scrutiny.…”

Section: Construction Cost Escalation: Data and Modelmentioning

confidence: 99%

Revisiting the Cost Escalation Curse of Nuclear Power: New Lessons from the French Experience

Rangel¹,

Lévèque²

2015

EEEP

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Since the first wave of nuclear reactors in 1970 to the construction of Generation III+ reactors in Finland and France in 2005 and 2007 respectively, nuclear power seems to be doomed to a cost escalation curse. In this paper we reexamine this issue for the French nuclear power fleet. Using the construction costs from the Cour des Comptes report, that was publicly available in 2012, we found that previous studies overestimated the cost escalation. Although, it is undeniable that the scale-up ended up in more costly reactors, we found evidence of a learning curve within the same size and type of reactors. This result confirms that standardization is a good direction to look, in order to overcome the cost escalation curse.

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Economies of Scale in Nuclear Power Generation

Cited by 40 publications

References 16 publications

Estimating Cost Structures in the U.S. Nuclear Power Industry

Estimating Cost Structures in the U.S. Nuclear Power Industry

Learning curves and technology assessment

Revisiting the Cost Escalation Curse of Nuclear Power: New Lessons from the French Experience

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