Future naval ships will be all-electric, with an integrated power system that combines the propulsion power system with the rest of the ship?s electrical distribution system. Reconfiguration of the power system will increase fight-through and survivability of ships, but will also require the systems that support the power system, such as the protection system, to be automatically updated to match current power system needs. This thesis presents an adaptive relaying scheme for shipboard power systems, to automatically modify relay settings after power system topology changes. Multiple Groups of relay settings are predetermined and stored in the digital relays that are protecting the power system. The active Group of settings is automatically determined based on the open/close status of breakers and switches. The developed protection scheme is tested on two test cases by digital simulation using CAPE software and on one case by closed-loop simulation with RTDS and SEL-351S relays.

The work presented in this thesis was concerned with the implementation of a damage control method for U.S. Navy shipboard power systems (SPS). In recent years, the Navy has been seeking an automated damage control and power system management approach for future reconfigurable shipboard power systems. The methodology should be capable of representing the dynamic performance (differential algebraic description), the steady state performance (algebraic description), and the system reconfiguration routines (discrete events) in one comprehensive tool. The damage control approach should also be able to improve survivability, reliability, and security, as well as reduce manning through the automation of the reconfiguration of the SPS network. To this end, this work implemented a damage control method for a notional Next Generation Integrated Power System. This thesis presents a static implementation of a dynamic formulation of a new damage control method at the DC zonal Integrated Flight Through Power system level. The proposed method used a constrained binary genetic algorithm to find an optimal network configuration. An optimal network configuration is a configuration which restores all of the de-energized loads that are possible to be restored based on the priority of the load without violating the system operating constraints. System operating limits act as constraints in the static damage control implementation. Off-line studies were conducted using an example power system modeled in PSCAD, an electromagnetic time domain transient simulation environment and study tool, to evaluate the effectiveness of the damage control method in restoring the power system. The simulation results for case studies showed that, in approximately 93% of the cases, the proposed damage algorithm was able to find the optimal network configuration that restores the power system network without violating the power system operating constraints.