4E analysis and optimization of cold thermal-energy storage under partial operating mode and demand-limiting mode for air-conditioning systems

Abstract

Abstract Cold thermal energy storage is an active method for reducing the peak electrical demand and electricity consumption of air conditioners. This paper investigates two different cases: partial operating mode–load levelling (POM–LL) and demand-limiting mode (DLM). 4E (energy, exergy, economic, environment) analyses along with a multi-objective optimization process based on a genetic algorithm is applied to determine optimal design values. Exergy efficiency, total annual cost and payback-period time are considered as objective functions in this study. The results have shown that POM and DLM decreased the electricity consumption by 10.36% and 11.29%, respectively, resulting in raising the annual costs by 11.08% and 11.42%. Also, their annual payback periods were 4.36 and 4.18 years each. In addition, using off-peak hours instead of on-peak hours for electricity consumption and reducing electricity consumption are the two main ways of decreasing CO2 emissions during electricity generation. Therefore, the CO2 emissions through POM and DLM are 13.31% and 13.72% less than those of conventional systems, respectively.