Optimization of cold thermal energy storage systems with commissioning and storage time approach by using intelligent algorithms

The use of cold thermal energy storage systems (CTES) is to decrease power consumption in air conditioning systems. CTES systems have 2 types full operating mode (FOM) and partial operating mode (POM). Objective functions are considered as exergy efficiency and total annual cost because of releasing co2 of CTES systems. Multi-objective techniques are used in MOPSO and SEAP2 algorithm to optimize target functions. The fidings achieved from multi-objective analysis indicate a difference in the optimal amounts of design points compared to single- objective optimization, objective function 1 (exergy efficiency) and objective function2 (total annual costs). Also the report of studying this model represent that because of the use of CTES, there is reduction of electricity consumption. Also because of transferring cooling load from peak hours to low consumption and reduced power consumption, we have a reduction in operating costs comparing to a traditional air conditioning system. Finally, the results show that the payback period for an CTES system in partial storage mode is 3.43 years and for a full storage system is close to 3.88 years, however, due to further reduction of operating costs in full storage mode, the total stored cost of this system after the useful life of the set (15 years) is more than partial storage type. it should be noted that the use of the CTES system decreases the production of CO2, which reduces environmental pollution. Finally, the PCMs used in the construction industry are introduced and compared with each other in terms of exergy efficiency.