Latent thermal energy storage (LTES) using PCM is one of the most effective measures to achieve energy saving and emergency cooling in data centers. Adding metal fins is proposed as an efficient solution for the low conductivity challenge of PCM, which severely hinders the application of LTES in practice. Nevertheless, simulating the thermal performance of fin-incorporated PCM is not straightforward due to the considerable effort of modeling individual fins. In this paper, the fin-enhanced PCM is simplified as a non-uniform composite material with anisotropic equivalent conductivity to simulate tube-in-tank latent thermal energy storage. The mean absolute percentage error between simulation result and experimental data are 3.64 % and 2.08 % for charging and discharging process, respectively. The results shown that for Z-direction thermal conductivity of 0.22, 4.95, and 9.9 W/(m·K), the outlet temperature of HTF is basically unchanged. The influence of inlet conditions on the thermal performance of LTES is analyzed, and the transient temperatures and temperature profiles in the fin-enhanced PCM at critical locations are presented. With the flow rate ranging from 10 L/min to 20 L/min, and the inlet temperature ranging from 277.15 K to 281.15 K during the charging process (and 287.15 K–293.15 K for the discharging process), the solidification time varies in the scope of 20 min–43 min (15 min–40 min for the discharging process). In addition, the simulation results show that the PCM temperature difference in Z direction is very small, and PCM temperature is mainly influenced by the closest tube. This work suggests a simple while effective method for simulating metal-fin-enhanced PCM, and could assist the optimization of latent thermal energy storage used in data center. • Anisotropic equivalent conductivity of fin-enhanced PCM is developed. • For Z-direction thermal conductivity of 0.22, 4.95, and 9.9 W/(m·K), the outlet temperature of HTF is basically unchanged. • The errors between simulation result and experimental data are 3.64 % and 2.08 % for charging and discharging process. • Effects of inlet conditions and temperature profiles are analyzed through effective heat capacity method.