Doctoral Dissertations
Date of Award
12-2017
Degree Type
Dissertation
Degree Name
Doctor of Philosophy
Major
Energy Science and Engineering
Major Professor
Brennan T. Smith
Committee Members
Sudersanam Suresh Babu, Kivanc Ekici, Thanos Papanicolaou
Abstract
This research develops a framework for reconciling expert opinions of component lifetimes and empirical failure data to predict powertrain failure probabilities for Asset Management decision making purposes. Using probability models of component failures, fleetwide dispatch and component replacement history along with a large hydroelectric utility’s powertrain expert elicitation we propose a four use cases. The first use case enables a more detailed calculation of average component life. The second use case provides risk managers the ability to understand how dispatch affects the risk of a single component failure. The third and fourth use cases enables the recommendation of the distribution of generation dispatch at a 2-unit and a 4-unit facility to maximize the reliability of all of the facilities modelled powertrain components for a given timeframe. The third use case uses this information in a historical sense to develop a Reliability Index while the fourth use case recommends future dispatch. Three historic operating years will establish constraints to the future operating scenarios used to assess powertrain risk.
Recommended Citation
Signore, Stephen Robert, "A Framework for Reconciling Expert Opinions and Empirical Data for Hydropower Asset Management Decision-Making. " PhD diss., University of Tennessee, 2017.
https://trace.tennessee.edu/utk_graddiss/4830