The maintenance of equipment has been an important issue for companies for many years. For systems with hidden or unrevealed failures (i.e., failures are not self-announcing), a common practice is to regularly inspect the system looking for such failures. Examples of these systems include protective devices, emergency devices, standby units, underwater devices etc. If no periodical inspection is scheduled, and a hidden failure has already occurred, severe consequences may result. Research on periodical inspection seeks to establish the optimal inspection interval (Failure Finding Interval) of systems to maximize availability and/or minimize expected cost. Research also focuses on important system parameters such as unavailability. Most research in this area considers non-negligible downtime due to repair/replacement but ignores the downtime caused by inspections. In many situations, however, inspection time is non-negligible. We address this gap by proposing an optimal failure finding interval (FFI) considering both non-negligible inspection time and repair/replacement time. A novel feature of this work is the development of models for both age-based and calendar-based inspection policies with random/constant inspection time and random/constant repair/replacement time. More specifically, we first study instantaneous availability for constant inspection and repair/replacement times. We start with the assumption of renewal of the system at each inspection. We then consider models with the assumption of renewal only after failure. We also develop limiting average availability models for random inspection and repair/replacement times, considering both age-based and calendar-based inspection policies. We optimize these availability models to obtain an optimal FFI in order to maximize the system’s availability. Finally, we develop several cost models for both age-based and calendar-based inspection policies with random inspection time and repair/replacement time. We formulate the model for constant inspection time and repair/replacement time as a special case. We investigate the optimization of cost models for each case to obtain optimal FFI in order to minimize the expected cost. The numerical examples and case study presented in the dissertation demonstrate the importance of considering non-negligible downtime due to inspection.

The maintenance of equipment has been an important issue for companies for many years. For systems with hidden or unrevealed failures (i.e., failures are not self-announcing), a common practice is to regularly inspect the system looking for such failures. Examples of these systems include protective devices, emergency devices, standby units, underwater devices etc. If no periodical inspection is scheduled, and a hidden failure has already occurred, severe consequences may result. Research on periodical inspection seeks to establish the optimal inspection interval (Failure Finding Interval) of systems to maximize availability and/or minimize expected cost. Research also focuses on important system parameters such as unavailability. Most research in this area considers non-negligible downtime due to repair/replacement but ignores the downtime caused by inspections. In many situations, however, inspection time is non-negligible. We address this gap by proposing an optimal failure finding interval (FFI) considering both non-negligible inspection time and repair/replacement time. A novel feature of this work is the development of models for both age-based and calendar-based inspection policies with random/constant inspection time and random/constant repair/replacement time. More specifically, we first study instantaneous availability for constant inspection and repair/replacement times. We start with the assumption of renewal of the system at each inspection. We then consider models with the assumption of renewal only after failure. We also develop limiting average availability models for random inspection and repair/replacement times, considering both age-based and calendar-based inspection policies. We optimize these availability models to obtain an optimal FFI in order to maximize the system’s availability. Finally, we develop several cost models for both age-based and calendar-based inspection policies with random inspection time and repair/replacement time. We formulate the model for constant inspection time and repair/replacement time as a special case. We investigate the optimization of cost models for each case to obtain optimal FFI in order to minimize the expected cost. The numerical examples and case study presented in the dissertation demonstrate the importance of considering non-negligible downtime due to inspection.

One of the objectives of this study is to develop a methodology, together with a set of software programs that evaluate, in a power system, the risks of catastrophic failures caused by hidden failures in the hardware or software components of the protection system. The disturbance propagation mechanism is revealed by the analysis of the 1977 New York Blackout. The step-by-step process of estimating the relay hidden failure probability is presented. A Dynamic Event Tree for the risk-based analysis of system catastrophic failures is proposed. A reduced 179-bus WSCC sample system is studied and the simulation results obtained from California sub-system are analyzed. System weak links are identified in the case study. The issues relating to the load and generation uncertainties for the risk assessment of system vulnerabilities are addressed. A prototype system - the Hidden Failure Monitoring and Control System (HFMCS) - is proposed to mitigate the risk of power system catastrophic failures. Three main functional modules - Hidden Failure Monitoring, Hidden Failure Control and Misoperation Tracking Database - and their designs are presented. Hidden Failure Monitoring provides the basis that allows further control actions to be initiated. Hidden Failure Control is realized by using Adaptive Dependability/Security Protection, which can effectively stop possible relay involvement from triggering or propagating disturbance under stressed system conditions. As an integrated part of the HFMCS, a Misoperation Tracking Database is proposed to track the performance of automatic station equipment, hence providing automatic management of misoperation records for hidden failure analysis. / Ph. D.