Abstract

System optimization methodology is an effective way to increase the efficiency of thermal system. However, at present, the multi processes of advanced compressed air energy storage (CAES) system are strongly coupled with many parameters, and the previous optimization methods lack considering the physical connection between energy storage and energy release processes, which leads to the unclear optimization direction sometimes and the failure of traditional mathematical optimization algorithm when parameters are strongly coupled and in a large scale. In this paper, an optimization strategy based on the corresponding-point methodology (CPM) for CAES systems is established, and the overall evaluation index, Mg is modified. In order to make the optimization results closer to reality, the concepts of finite time/size are introduced, and the optimization case of under-water CAES system is analyzed. Results show that under the constraint of the corresponding quotient, with the increase of the limit value of the corresponding quotient, the maximum value of the system efficiency gradually increases, which proves the effectiveness of the proposed optimization strategy. The influence mechanism of the key parameters on the optimization results is revealed. When the pressure-effectiveness correlative coefficient, C* changes, there is a compromise between the pressure loss and effectiveness of the heat exchanger. The mixing of hot water at all compression parts breaks the corresponding limit of each compressor and expander, resulting in parameters among all compressor/expanders parts that need to balance due to the mixing.

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