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4E analysis and optimization of a novel combined cooling, heating and power system integrating compressed air and chemical energy storage with internal combustion engine

Journal of Energy Storage(2023)

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摘要
The combined cooling, heating and power (CCHP) system assisted by the renewable energy sources (RESs) is a promising solution in the distributed energy network owing to its high efficiency and flexible operation. In this study, the compressed air energy storage (CAES) is introduced into the CCHP system to alleviate the negative impact of the intermittent characteristic of RESs and improve the supply capacity and stability of the distributed electricity grid. In addition, the compression heat is converted to the syngas fuel through the methanol decomposition reaction during charging stage, and then the syngas fuel is fed into the internal combustion engine for power output boost during discharging stage. By establishing the 4E (Energy, Exergy, Economic, and Environmental) models of the proposed system, the parametric analysis is first conducted to investigate the effects of seven crucial design parameters on the 4E performances of this system. Moreover, a multi-objective optimization method is carried out to achieve optimal system performances with the maximization of thermodynamic efficiency and economic profits while the minimization of environmental pollution. The results demonstrate that the proposed system could have the ability to provide power, heating, and cooling at loads of 7.96 MWh, 5.34 MWh, and 1.26 MWh with the total exergy efficiency being 45.14 % under the design condition, and the total system energy efficiency, levelized cost of energy, CO2 emissions are 82.72 %, 140.35 $/MWh and 216.28 kg/MWh, respectively. The multi-objective optimization results indicate that by reducing 3.06 kg/MWh of the CO2 emissions, the optimal total system exergy efficiency can reach 47.84 %, which is 2.70 % higher than that under the design condition.
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关键词
Combined cooling, heating, and power,Compressed air and chemical energy storage,4E analysis,Multi-objective optimization
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