| dc.description.abstract | **Please note that the full text is embargoed until 8/1/2024** ABSTRACT: Traditionally, large-scale power systems have relied on power generation always exceeding the total load demand. Though this is most often the case, there are rare occurrences where failures in the generation, distribution, or even planning, that have led to situations where load demand quickly surpasses the generation capacity. In such cases, uncontrolled shedding of loads occurs, leading to brownouts or blackouts that can have catastrophic impact to both people and property. Advanced architectures, such as microgrids, offer a variety of improvements that are aimed at mitigating or even preventing these failures. Improvements include distributed power generation, active source and load monitoring, manageable load control, enhanced resilience against distribution failures, and in some instances the integration of energy storage to buffer transient loads. Despite all these benefits, system complexity is massively increased and heightened system monitoring is required, which is costly and difficult to implement.
Shipboard power system architectures resemble microgrids and the US Navy has proposed zonal shipboard power systems that employ low voltage (LV) AC, medium voltage (MV) AC, and even MVDC nodes within the same architecture. To both evaluate and validate such architectures, the Intelligent Distributed Energy Analysis Laboratory (IDEAL) testbed was established at the University of Texas at Arlington (UTA). IDEAL is intended to emulate one zone of a shipboard power system architecture that introduces various generation sources, power electronic converters, loads, and LFP energy storage, all of which are designed and assembled at naval relevant voltages. The platform is set up to enable Hardware in the Loop (HIL) model emulation allowing for the development, testing, and validation of control algorithms in a flexible emulated environment. Such an environment also allows for collaborative opportunities, thus facilitating a partnership with institutions like Florida State University (FSU), University of South Carolina (USC), and Clarkson University (CU), further enhancing research and innovation in the field.
Realizing the full potential of zonal architectures and the associated algorithms needed to reliably operate them, may require effective utilization of energy storage. However, safety concerns surrounding lithium-ion energy storage has many weighing the risks against the benefits it introduces. Lithium-ion batteries are most often managed using battery management systems (BMS) that monitor and manage the state of charge (SoC) of the multitude of cells that make up the battery. As battery configurations expand and as new BMSs are designed and introduced into the market, the need to study and validate their operation before they introduced into real batteries is critical. Furthermore, the ability to interface the BMS with the overarching system level controller is essential, and its operation must be validated across all potential use cases where intervention may be required. Power HIL (PHIL) platforms offer unique capabilities for emulating batteries comprised of multiple lithium-ion cells. Such capabilities include increased flexibility for rapidly studying the BMS’s reaction to normal and abnormal operating conditions, as well as a safe controlled environment for these types of scenarios. Thus, leading to increased user confidence and hopefully lead to the wider scale deployment of energy storage in shipboard power systems.
The work performed in this dissertation comprises of a few different, but interrelated thrusts. In the first, it discusses the design, rational, assembly and results obtained from a PHIL testbed used to validate BMS performance and software integration operating on batteries with up to 264 cells in series, ~1 kVDC. In the second thrust, a collaborative effort performed by UTA, FSU and USC is discussed in which the UTA IDEAL testbed was interfaced with remote HIL platforms being operated at FSU and USC, respectively. The remote HIL co-simulation effort demonstrated the employed physical energy storage at UTA and it was used to provide ramp rate buffering of a 12 kVDC bus emulated in the co-simulated HIL. In the third and final thrust, the IDEAL testbed is used to demonstrate the effectiveness of predictive high ramp rate (PHRR) and advanced load shed (ALS) algorithms developed by Clarkson University (CU) for maintaining operability and power quality within shipboard power systems deploying continuous and transient loads. Each of these thrusts will be discussed in detail. | |
