Future all-electric warships with an integrated power system (IPS) are capable of unlocking large amounts of power dedicated to propulsion and redirecting this power for service loads, weapon loads, and other loads. The IPS for all-electric ships combines the power generation system, electric propulsion system, power distribution system, and power control and management system all together. The move to IPS design will significantly improve efficiency, effectiveness, and survivability. To meet the needs of the US Navy, enhancing survivability by reducing susceptibility to damage, a IPS prefers decentralized reconfiguration system is preferred for IPS instead of traditional reconfiguration techniques used for terrestrial power grids. A multi-agent system (MAS) is a loosely coupled network composed of several agents. These agents interact with their environments and communicate with each other to solve problems that are beyond the individual capabilities or knowledge of each single agent. Because of its decentralized feature and lack of a global control feature, MAS appears to be the best candidate for IPS reconfiguration. This research work proposes a new model of an IPS, based on the Naval Combat Survivability, DC Distribution Test-bed (NCS DCDT). The new model combines the electric power generation system, electric propulsion system, and AC-DC zonal distribution system. To decrease the probability of distribution zones losing power, the new model modifies original design of the zonal distribution system in NCS DCDT. Another main endeavor of this research work is to design a MAS for reconfiguration of an IPS with AC-DC zonal distribution system. The MAS consists of three sub-MAS, named power generation MAS, propulsion MAS, and distribution MAS, and includes forty-one different agents which are instances of nineteen different abstract agent classes. The MAS is implemented with JAVA/JADE software and simulated on a platform of JADE 3.4.1 and JAVA jdk 1.5.0_08. Simulation results show that the MAS can execute reconfiguration functions such as fault area isolation, automatic switching, and load shedding.

This dissertation aims to address two optimization problems involving power system reliabilty analysis, namely multi-area power system adequacy planning and transformer maintenance optimization. A new simulation method for power system reliability evaluation is proposed. The proposed method provides reliability indexes and distributions which can be used for risk assessment. Several solution methods for the planning problem are also proposed. The first method employs sensitivity analysis with Monte Carlo simulation. The procedure is simple yet effective and can be used as a guideline to quantify effectiveness of additional capacity. The second method applies scenario analysis with a state-space decomposition approach called global decomposition. The algorithm requires less memory usage and converges with fewer stages of decomposition. A system reliability equation is derived that leads to the development of the third method using dynamic programming. The main contribution of the third method is the approximation of reliability equation. The fourth method is the stochastic programming framework. This method offers modeling flexibility. The implementation of the solution techniques is presented and discussed. Finally, a probabilistic maintenance model of the transformer is proposed where mathematical equations relating maintenance practice and equipment lifetime and cost are derived. The closed-form expressions insightfully explain how the transformer parameters relate to reliability. This mathematical model facilitates an optimum, cost-effective maintenance scheme for the transformer.

This dissertation aims to address two optimization problems involving power system reliabilty analysis, namely multi-area power system adequacy planning and transformer maintenance optimization. A new simulation method for power system reliability evaluation is proposed. The proposed method provides reliability indexes and distributions which can be used for risk assessment. Several solution methods for the planning problem are also proposed. The first method employs sensitivity analysis with Monte Carlo simulation. The procedure is simple yet effective and can be used as a guideline to quantify effectiveness of additional capacity. The second method applies scenario analysis with a state-space decomposition approach called global decomposition. The algorithm requires less memory usage and converges with fewer stages of decomposition. A system reliability equation is derived that leads to the development of the third method using dynamic programming. The main contribution of the third method is the approximation of reliability equation. The fourth method is the stochastic programming framework. This method offers modeling flexibility. The implementation of the solution techniques is presented and discussed. Finally, a probabilistic maintenance model of the transformer is proposed where mathematical equations relating maintenance practice and equipment lifetime and cost are derived. The closed-form expressions insightfully explain how the transformer parameters relate to reliability. This mathematical model facilitates an optimum, cost-effective maintenance scheme for the transformer.

The primary goal of this work is to develop a PSCAD/EMTDC simulation model which can emulate the reclosing capabilities of an actual reclosing relay. The first part of this work will demonstrate the capabilities of a commercially available, microprocessor-based reclosing relay, the SEL-551c. Next, a computer simulation model of this relay's reclosing capability will be developed in PSCAD/EMTDC and validated. The performance of the model will be compared to the performance of the SEL-551c. Because it is impractical to test the relay operation under fault conditions in a real distribution system, fault characteristics will be determined in PSCAD. Utilizing a test system for the SEL relay, we can show the accuracy of the PSCAD recloser model compared to the SEL-551c relay for similar fault scenarios. The validation is done by analyzing the data from the simulation and experiment. The results show that both the PSCAD recloser model and SEL-551c operate close to the expected theoretical values. The primary contribution of this work is the development of a PSCAD recloser model and validation with a real world reclosing relay. In previous works where recloser analysis was done in PSCAD, such as [14], recloser operation was manually accomplished. However, the recloser model developed in this work allows the user to enter any standard TCC equation that may be programmed into an actual relay and achieve similar results. The model is useful when analyzing larger distribution systems with multiple reclosers. Additionally, validating the PSCAD recloser model with a real world device provides confidence that the simulations provide reasonable and meaningful results. / text

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

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