An Assessment of the Costs of the French Nuclear PWR Program 1970-2000

The paper reviews the history and the economics of the French PWR program, which is arguably the most successful nuclear-scale up experience in an industrialized country. Key to this success was a unique institutional framework that allowed for centralized decision making, a high degree of standardization, and regulatory stability, all epitomized by comparatively short reactor construction times. Drawing on largely unknown public records, the paper reveals for the first time both absolute as well as specific reactor costs and their evolution over time. Its most significant finding is that even this most successful nuclear scale-up was characterized by a substantial escalation of real-term reactor construction costs. Specific costs per kW installed capacity increased by more than a factor of three between the first and last reactor generations built. Conversely, operating costs have remained remarkably flat, despite lowered load factors resulting from the need for load modulation in a system where base-load nuclear power plants supply three quarters of electricity. The paper draws a number of cautionary lessons for technology, policy, and modeling studies in a climate-constrained world. First, the inherent technology characteristics of nuclear power: large-scale, complex, and with lumpy investments introduce a significant economic risk of cost overruns in the build-up process. Anticipated economic gains from standardization and ever larger unit scales not only have not materialized, but the corresponding increasing complexity in design and in construction operations have reversed the anticipated learning effects to their contrary: cost escalation. Second, cost projections and policy rationales based on relative economic merits of competing technology options are fraught by persistent uncertainties and biases, suggesting that the real cost of a scale up of a technology as large and complex as nuclear might be in fact unknowable ex ante, severely limiting conventional deterministic economic calculus and decision making (e.g. cost minimization) models. Lastly, the French nuclear case illustrates the perils of the assumption of robust learning effects resulting in lowered costs over time in the scale-up of large-scale, complex new energy supply technologies. The uncertainties in anticipated learning effects of new technologies might be much larger that often assumed, including also cases of "negative learning" in which specific costs increase rather than decrease with accumulated experience

Managing the Global Environment

Global environmental problems pose entirely new challenges for science, technology, and policy making. Persistent scientific uncertainties, extremely long time horizons, the potential need for radical and systemic technological changes, and huge distances in both time and space between those that are supposed to act and those that will benefit, are in stark contrast to historical experiences of dealing with environmental issues

A Comparative Analysis of Annual Market Investments in Energy Supply and End-use Technologies

Whereas the need to mobilize investment in energy supply technologies is broadly understood, with the current level of investment estimated in the order of $0.7-0.9 trillion a year, there is a notable absence of analogous investment data for end-use technologies. This paper presents a global, bottom-up estimate of total investments in end-use energy technologies based on volume data and cost estimates for 2005. Total investment in end-use technologies was conservatively found to be in the order of$0.3-4 trillion depending on the definition of end-use technology used

Long Waves, Technology Diffusion, and Substitution

There is an urgent need to drastically reduce adverse environmental impacts resulting from prevailing economic activities. Even more important is the question of the future direction of economic development and technological changes. In this paper the authors argue, from a historical perspective, that this process will remain discontinuous and spatially heterogeneous, as a result of diverse policies and strategies. The authors illustrate empirically the argument that the process of economic growth and technological change is not smooth and continuous. They demonstrate that various phases of economic expansion are driven by the host of interrelated clusters of technologies and that the timing of the transition from one dominant cluster to another is consistent with the pattern of Kondratieff long waves. The paper also illustrates that we are currently moving away from the old, materials- and energy-intensive development trajectory to a new future. There is a need to progressively close the industrial-ecology cycle and there are indications that this may indeed be possible, given the promotion of a range of carefully selected technological and policy measures for achieving sustainable development

Future capacity growth of energy technologies: are scenarios consistent with historical evidence?

Future scenarios of the energy system under greenhouse gas emission constraints depict dramatic growth in a range of energy technologies. Technological growth dynamics observed historically provide a useful comparator for these future trajectories. We find that historical time series data reveal a consistent relationship between how much a technology’s cumulative installed capacity grows, and how long this growth takes. This relationship between extent (how much) and duration (for how long) is consistent across both energy supply and end-use technologies, and both established and emerging technologies. We then develop and test an approach for using this historical relationship to assess technological trajectories in future scenarios. Our approach for “learning from the past” contributes to the assessment and verification of integrated assessment and energy-economic models used to generate quantitative scenarios. Using data on power generation technologies from two such models, we also find a consistent extent - duration relationship across both technologies and scenarios. This relationship describes future low carbon technological growth in the power sector which appears to be conservative relative to what has been evidenced historically. Specifically, future extents of capacity growth are comparatively low given the lengthy time duration of that growth. We treat this finding with caution due to the low number of data points. Yet it remains counter-intuitive given the extremely rapid growth rates of certain low carbon technologies under stringent emission constraints. We explore possible reasons for the apparent scenario conservatism, and find parametric or structural conservatism in the underlying models to be one possible explanation