The effect of key parameters on the design of an optimized CAES power plant

Due to the significant variations in electricity generation and its demand, the power plant owners are
encountered with challenges of economic operation. Among all, Compressed air energy storage (CAES)
technology has proposed itself as a reliable and efficient solution to match the two sides. This paper deals with
a modeled compressed air energy storage power plant which has been optimized thermodynamically through
an efficient genetic algorithm code. The results of this optimized model, considered as the base case, show that
the power plant is technically and financially justifiable. In order to obtain a more tangible realization, it is
necessary to verify the results against the variation of key parameters. In this study, the sensitivity analysis is
performed based on main parameters including plant loading and ambient condition and the resultant trends of
each case are presented. This approach will help the designers to analyze the quality of their designs in
different situations.