Multi-objective optimization of volume in a compressed carbon dioxide energy storage system coupled with auxiliary energy storage device based on NSGA-II

Nowadays, there is a growing focus on renewable energy due to escalating environmental issues. The energy storage system plays a crucial role in maintaining a balance between renewable energy sources and the power grid. This paper proposes an integrated system that includes a wind farm, a thermal power unit, and an energy storage system. The energy storage system includes a compressed CO₂ energy storage (CCES) system and two alternative auxiliary energy storage devices (electric heater and power-to-gas device). The Non-dominated Sorting Genetic Algorithm-II is adopted to optimize the volume of the energy storage system. A comparison between three systems (System A: CCES; System B: CCES with electric heater; System C: CCES with power-to-gas device) is conducted. The result reveals that the wind curtailment cost and the power insufficient cost account for a large proportion of the total cost. System B has the lowest cost per unit generation of 0.974 $/kWh, 22.51 %, and 28.91 % lower than that of System C and System A, respectively. Compared to the addition of a Proton Exchange Membrane Electrolyzer, the addition of an electric heater has better performance. Moreover, the value and distribution of unbalanced power impact wind curtailment energy and result in insufficient energy generation. The duration time of unbalanced power determines the charge time, while the operating time affects the cost per unit generation.