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Distributed Adaptive Droop Control for Power Management in DC Distribution Systems

The current trend for naval destroyer-class ships is the move toward DC distribution systems as the next generation of ships is developed. The main motivation for using DC is to increase the power density of the ships to accommodate advanced weaponry such as the electromagnetic railgun. The distribution systems are also expected to be modular and plug-n-play in nature, leading toward a distributed control scheme to integrate the distributed sources and loads that could be online at any given time. One of the main performance requirements for the future power distribution systems is the ability to accurately share power among the distributed resources on the ship, while also maintaining the voltage stability of the distribution system, often referred to as power management. The primary candidate to accomplish the power management of the ship systems is droop control. Droop control has been extensively studied for terrestrial applications for sharing power between paralleled sources. Specifically, its application to DC microgrids is of interest since islanded microgrids have similar properties to ship systems. In these studies, it has been shown that conventional droop control is limited in its power sharing capabilities due to a tradeoff between the accuracy of the power sharing between devices and the regulation of the bus voltage. Secondary controllers have been proposed to modify the droop control scheme to alleviate these issues based on linear controllers or heuristic methods. However, accurate models for DC microgrids are difficult to derive for linear control design, and heuristic methods do not present an autonomous way to adjust the parameters of the controller. Therefore, adaptive control is proposed to adjust the droop controller’s parameters in an online fashion to find the optimal values based on the system conditions. Model reference adaptive control is chosen in this research for its ability to deal with system uncertainties and ensure stability. Specifically, combined model reference adaptive control is chosen for its improvements in transient response and robustness over the direct and indirect versions. The method is developed and simulated using MATLAB/Simulink to determine the performance of the algorithm. Additionally, a notional MVDC ship power system is developed in the same environment to provide a test system with various distributed sources and loads. A load profile is developed for the main system components such as propulsion, service loads, and the advanced weaponry to reflect a notional battle scenario. The algorithm is first tested in simulation, and then deployed to external distributed controllers to validate the performance of the power management scheme under hardware constraints and communication latency. The algorithm is also demonstrated in conjunction with a management layer for distributed energy storage modules throughout the ship system to further illustrate the real-world viability of the method. / A Dissertation submitted to the Department of Electrical and Computer Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Summer Semester 2018. / July 19, 2018. / Includes bibliographical references. / Chris S. Edrington, Professor Directing Dissertation; Juan Ordonez, University Representative; Simon Foo, Committee Member; Pedro Moss, Committee Member.

Identiferoai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_647279
ContributorsPerkins, Dallas (author), Edrington, Christopher S. (professor directing dissertation), Ordóñez, Juan Carlos, 1973- (university representative), Foo, Simon Y. (committee member), Moss, Pedro L. (committee member), Florida State University (degree granting institution), College of Engineering (degree granting college), Department of Electrical and Computer Engineering (degree granting departmentdgg)
PublisherFlorida State University
Source SetsFlorida State University
LanguageEnglish, English
Detected LanguageEnglish
TypeText, text, doctoral thesis
Format1 online resource (85 pages), computer, application/pdf

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