Future Naval vessels are looking to incorporate a new variety of electrical loads. These loads include rail guns, high power radars, electric propulsion drives, and lasers. These loads, especially the rail gun, can be classified as high-power ramp rate loads. Before now, these types of loads were not prevalent on naval vessels; therefore, generators were used throughout the ship to power a multitude of devices that did not require high-power ramp rates. Many of the generators had a specific purpose; there were no interconnections between generators. With these new types of loads, a power system that can accommodate these devices is needed. Integrated Power Systems (IPS) look to solve the high-power ramp rate issue as well as provide a multitude of benefits such as efficiency, resiliency, and reconfigurability. The generators, loads, energy storages, protections, etc. will all be located and connected within the IPS. The IPS can provide the foundation to achieve a multitude of benefits; however, the control system must be intelligent in order to realize the IPS’ full potential. Part of the control problem is how to manage sources and loads to ensure load demand is met. In terrestrial systems, the near infinite bus takes care of changes in load demand. In a microgrid, such as those found on ships, a large change in load demand, such as those seen by high-power ramp rate loads, can have adverse effects on the power system and devices connected to the power system. The control must coordinate the sources and/or loads to ensure load demand is met with minimal impact to the system. In this dissertation, the beginnings of a distributed Energy Management control layer are shown. The control layer looks to assist in realizing the IPS’ full potential. This is done by providing a distributed type of control to fortify the resiliency and reliability, ensuring load demand is met, and certifying the energy storages state of charge is maintained to ensure an ever-ready presence. This control layer aims to meet load demand, ensure device constraints (power ratings, ramp rate limitations, etc.) are not exceeded, and maintain the energy storages desired state of charge. The control objective is met through a combined approach of a distributed spinning reserve algorithm and distributed MPC. The distributed MPC utilizes the distributed optimization technique called the Alternating Direction Method of Multipliers (ADMM). / 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 20, 2018. / Distributed Control, Energy Management, Energy Storage, Model Predictive Control, Naval / Includes bibliographical references. / Jonathan Clark, University Representative; Omar Faruque, Committee Member; Sastry Pamidi, Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_647229 |
| Contributors | Gonsoulin, David E. (author), Clark, Jonathan E. (university representative), Faruque, Md Omar (committee member), Pamidi, Sastry V. (committee member), Florida State University (degree granting institution), College of Engineering (degree granting college), Department of Electrical and Computer Engineering (degree granting departmentdgg) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text, doctoral thesis |
| Format | 1 online resource (76 pages), computer, application/pdf |
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