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Title: Modeling time to recovery and initiating event frequency for loss of off-site power incidents at nuclear power plants

Technical Report ·
OSTI ID:5226113

Industry data representing the time to recovery of loss of off-site power at nuclear power plants for 63 incidents caused by plant-centered losses, grid losses, or severe weather losses are fit with exponential, lognormal, gamma and Weibull probability models. A Bayesian analysis is used to compare the adequacy of each of these models and to provide uncertainty bounds on each of the fitted models. A composite model that combines the probability models fitted to each of the three sources of data is presented as a method for predicting the time to recovery of loss of off-site power. The composite model is very general and can be made site specific by making adjustments on the models used, such as might occur due to the type of switchyard configuration or type of grid, and by adjusting the weights on the individual models, such as might occur with weather conditions existing at a particular plant. Adjustments in the composite model are shown for different models used for switchyard configuration and for different weights due to weather. Bayesian approaches are also presented for modeling the frequency of initiating events leading to loss of off-site power. One Bayesian model assumes that all plants share a common incidence rate for loss of off-site power, while the other Bayesian approach models the incidence rate for each plant relative to the incidence rates of all other plants. Combining the Bayesian models for the frequency of the initiating events with the composite Bayesian model for recovery provides the necessary vehicle for a complete model that incorporates uncertainty into a probabilistic risk assessment.

Research Organization:
Sandia National Labs., Albuquerque, NM (USA)
DOE Contract Number:
AC04-76DP00789
OSTI ID:
5226113
Report Number(s):
NUREG/CR-5032; SAND-87-2428; ON: TI88007663
Country of Publication:
United States
Language:
English