Title

Multi-objective optimization of an underwater compressed air energy storage system using genetic algorithm

Document Type

Article

Publication Date

1-1-2014

Publication Title

Energy

Volume

74

Issue

C

First Page

396

Keywords

Energy efficiency, Evolutionary algorithm, Exergoeconomics, Exergy analysis, Numerical simulation, Sustainability, UWCAES

Last Page

404

Abstract

This paper presents the findings from a multi-objective genetic algorithm optimization study on the design parameters of an underwater compressed air energy storage system (UWCAES). A 4 MWh UWCAES system was numerically simulated and its energy, exergy, and exergoeconomics were analysed. Optimal system configurations were determined that maximized the UWCAES system round-trip efficiency and operating profit, and minimized the cost rate of exergy destruction and capital expenditures. The optimal solutions obtained from the multi-objective optimization model formed a Pareto-optimal front, and a single preferred solution was selected using the pseudo-weight vector multi-criteria decision making approach. A sensitivity analysis was performed on interest rates to gauge its impact on preferred system designs. Results showed similar preferred system designs for all interest rates in the studied range. The round-trip efficiency and operating profit of the preferred system designs were approximately 68.5% and $53.5/cycle, respectively. The cost rate of the system increased with interest rates.

DOI

10.1016/j.energy.2014.07.005

ISSN

03605442

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