Date of Award


Publication Type

Master Thesis

Degree Name



Civil and Environmental Engineering

First Advisor

Carriveau, Rupp,

Second Advisor

Ting, David S-K.


Applied sciences, Energy efficiency, Exergoeconomics, Exergy analysis, Genetic algorithm, Multi-objective optimization, Underwater compressed air energy storage




The electricity industry is currently experiencing a significant paradigm shift in managing electrical resources. With the onset of aging infrastructure and growing power demands, and the influx of intermittent renewable energy generation, grid system operators are looking towards energy storage as a solution for mitigating industry challenges. An emerging storage solution is underwater compressed air energy storage (UWCAES), where air compressors and turbo-expanders are used to convert electricity to and from compressed air stored in submerged accumulators. This work presents three papers that collectively focus on the design and optimization of an UWCAES system. In the first paper, the field performance of a distensible air accumulator is studied for application in UWCAES systems. It is followed by a paper that analyzed the energetic and exergetic performance of a theoretical UWCAES system. The final paper presents a multi-objective UWCAES optimization model utilizing a genetic algorithm to determine optimum system configurations.