A Citation-Based Assessment Of The Performance Of U.S. Boiling Water Reactors Following Extended Power Up-Rates

Open Access
Heidrich, Brenden
Graduate Program:
Energy and Mineral Engineering
Doctor of Philosophy
Document Type:
Date of Defense:
June 20, 2012
Committee Members:
  • Samuel Oyewole, Dissertation Advisor
  • Samuel Oyewole, Committee Chair
  • Jamal Rostami, Committee Member
  • R Larry Grayson, Committee Member
  • Andris Freivalds, Committee Member
  • Nuclear Power
  • Nuclear Safety
  • Reliability
  • Failure Analysis
  • Energy Economics
  • regulation
Nuclear power plants produce 20 percent of the electricity generated in the U.S. Nuclear generated electricity is increasingly valuable to a utility because it can be produced at a low marginal cost and it does not release any carbon dioxide. It can also be a hedge against uncertain fossil fuel prices. The construction of new nuclear power plants in the U.S. is cautiously moving forward, restrained by high capital costs. Since 1998, nuclear utilities have been increasing the power output of their reactors by implementing extended power up-rates. Power increases of up to 20 percent are allowed under this process. The equivalent of nine large power plants has been added via extended power up-rates. These up-rates require the replacement of large capital equipment and are often performed in concert with other plant life extension activities such as license renewals. This dissertation examines the effect of these extended power up-rates on the safety performance of U.S. boiling water reactors. Licensing event reports are submitted by the utilities to the Nuclear Regulatory Commission, the federal nuclear regulator, for a wide range of abnormal events. Two methods are used to examine the effect of extended power up-rates on the frequency of abnormal events at the reactors. The Crow/AMSAA model, a univariate technique is used to determine if the implementation of an extended power up-rate affects the rate of abnormal events. The method has a long history in the aerospace industry and in the military. At a 95-percent confidence level, the rate of events requiring the submission of a licensing event report decreases following the implementation of an extended power up-rate. It is hypothesized that the improvement in performance is tied to the equipment replacement and refurbishment that is performed as part of the up-rate process. The reactor performance is also analyzed using the proportional hazards model. This technique allows for the estimation of the effects of multiple independent variables on the event rate. Both the Cox and Weibull formulations were tested. The Cox formulation is more commonly used in survival analysis because of its flexibility. The best Cox model included fixed effects at the multi-reactor site level. The Weibull parametric formulation has the same base hazard rate as the Crow/AMSAA model. This theoretical connection was confirmed through a series of tests that demonstrated both models predicted the same base hazard rates. The Weibull formulation produced a model with most of the same statistically significant variables as the Cox model. The beneficial effect of extended power up-rates was predicted in the proportional hazards models as well as the Crow/AMSAA model. The Weibull model also indicated an effect that can be traced back to a plant’s construction. Performance was also found to improve in plants that had been divested from their original owners. This research developed a consistent evaluation toolkit for nuclear power plant performance using either a univariate method that allows for simple graphical evaluation at its heart or a more complex multivariate method that includes the effects of several independent variables with data that are available from public sources. Utilities or regulators with access to proprietary data may be able to expand upon this research with additional data that is not readily available to an academic researcher. Even without access to special data, the methods developed are valuable tools in evaluating and predicting nuclear power plant reliability performance.