Dynamic simulation and operational feasibility of a solar-assisted thermal–mechanical vapor compression cycle with auxiliary subcooling for building cooling in hot desert climates

초록

This study proposes a TRNSYS-Python hybrid transient simulation framework to evaluate the energy, exergy, economic, and environmental performance and operational feasibility of a solar-assisted thermal–mechanical vapor compression cycle (TMVCC) with a domestic hot water (DHW)-coupled auxiliary subcooler for building cooling in hot desert climates. TRNSYS resolves weather-driven cooling loads and the dynamics of the solar thermal subsystem, thermal energy storage (TES), and auxiliary subcooler, while Python performs refrigerant-level thermodynamic cycle calculations at each time step. Using annual boundary-condition profiles, a representative peak-load week is selected to capture interactions among solar availability, TES conditions, and cooling loads. The framework explicitly represents TES-temperature-dependent mode switching between solar-assisted thermal–mechanical operation and conventional vapor compression operation. It also adjusts the compressor speed to match the evaporator capacity to the instantaneous cooling load, including compressor shutdown under mild-load conditions. The thermal–mechanical pressure ratio (α) governs a trade-off between efficiency gain and solar-assisted operating fraction, with α = 0.7 identified as the most balanced design value and a TMVCC operating fraction of 0.31. At this condition, the proposed system improves the average, total, and peak COP by 14.16%, 18.03%, and 60.14%, respectively, relative to the baseline vapor compression cycle. Among five low-GWP refrigerants, R-152a provides the most balanced performance, increasing the average and peak COP by 6.23% and 7.23%, respectively, while reducing compressor exergy destruction by 9.7%. Economic and environmental assessments show that R-152a reduces the 20-year life cycle cost by 13.2% and achieves a seasonal CO2 emission reduction ratio of 27.0%. © 2026 Elsevier Ltd.

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