Date of Award

2019

Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy in Mechanical Engineering-Engineering Mechanics (PhD)

Administrative Home Department

Department of Mechanical Engineering-Engineering Mechanics

Advisor 1

Gordon G. Parker

Advisor 2

Steven Y. Goldsmith

Committee Member 1

Wayne W. Weaver

Committee Member 2

Denise M. Rizzo

DOI

10.37099/mtu.dc.etdr/876

Abstract

Military vehicles possess attributes consistent with a microgrid, containing electrical energy generation, storage, government furnished equipment (GFE), and the ability to share these capabilities via interconnection. Many military vehicles have significant energy storage capacity to satisfy silent watch requirements, making them particularly well-suited to share their energy storage capabilities with stationary microgrids for more efficient energy management. Further, the energy generation capacity and the fuel consumption rate of the vehicles are comparable to standard diesel generators, for certain scenarios, the use of the vehicles could result in more efficient operation. Energy management of a microgrid is an open area of research especially in generation constrained scenarios where shedding of low-priority loads may be required. Typical metrics used to assess the effectiveness of an energy management strategy or policy include fuel consumption, electrical storage energy requirements, or the net exergy destruction. When considering a military outpost consisting of a stationary microgrid and a set of vehicles, the metrics used for managing the network become more complex. For example, the metrics used to manage a vehicle’s onboard equipment while on patrol may include fuel consumption, the acoustic signature, and the heat signature. Now consider that the vehicles are parked at an outpost and participating in vehicle-to-grid power-sharing and control. The metrics used to manage the grid assets may now include fuel consumption, the electrical storage’s state of charge, frequency regulation, load prioritization, and load dispatching. The focus of this work is to develop energy management and control strategies that allow a set of diverse assets to be controlled, yielding optimal operation. The provided policies result in both short-term and long-term optimal control of the electrical generation assets. The contributions of this work were: (1) development of a methodology to generate a time-varying electrical load based on (1) a U.S. Army-relevant event schedule and (2) a set of meteorological conditions, resulting in a scenario rich environment suitable for modeling and control of hybrid AC/DC tactical military microgrids, (2) the development of a multi-tiered hierarchical control architecture, suitable for development of both short and long term optimal energy management strategies for hybrid electric microgrids, and (3) the development of blending strategies capable of blending a diverse set of heterogeneous assets with multiple competing objective functions. This work could be extended to include a more diverse set of energy generation assets, found within future energy networks.

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