This study constructs an economic evaluation model with the dual objectives of minimizing lifecycle costs and maximizing energy efficiency. This model employs a three-tiered "parameter-indicator-optimization" architecture. Its core approach is to dynamically couple the charge-discharge efficiency decay curves of thermal energy storage devices with regional load fluctuation coefficients to establish an hourly cost-benefit mapping. This coupling addresses static parameter flaws in existing models and improves alignment with real operating conditions. The model incorporates six economic indicators and uses MATLAB/SIMULINK as its core simulation platform. Four benchmark cases (covering different climate zones and user types) and 27 comparison scenarios are designed. Simulation results show that Case 2 (Shanghai Commercial Complex) is optimal with a 1000 kWh thermal storage capacity and a medium subsidy, achieving an net present value (NPV) of 1.286 million Yuan and an ECR of 1.42. For every 0.1 Yuan/kWh increase in sub­sidy, the NPV increases by an average of 18.3%. The CER was linearly correlated with the thermal storage capacity (R2 = 0.98). Case 3 (Haikou Industrial Park) achieved a unit thermal storage carbon reduction benefit of 3500 Yuan per kWh, 1.5 times that of Case 1.