Energy-saving control method for NH₃-CO₂ cascade refrigeration system by directly regulating slide valve position in twin-screw compressor

Intermediate temperature (T_mid) is the pivotal parameter for energy-saving operation of existing cascade refrigeration systems (CRS), while few studies conducted on the on-site control method required to attain the optimal T_mid. This study proposes an energy-saving optimization method by the direct regulation of slide valve position in CRS high-temperature-stage (HTS) screw compressor rather than indirect regulation of T_mid. The backpropagation neural network relied on Levenberg-Marquardt algorithm is used to establish two prediction models for COP and slide valve position in high-temperature-stage twin-screw compressor (V_i). By selecting the maximum COP as the optimization objective, the optimal T_mid under each working condition is investigated. Meanwhile the corresponding optimal V_i is calculated through the data-driven model, so as to realize the direct control of the HTS volumetric flow. Compared to the traditional fixed T_mid operation, setting the T_mid as a real-time variable and control V_i through a data-driven model which correlated V_i with T_mid, can effectively avoid the significant fluctuation magnitude of V_i and T_mid. Meanwhile, the CRS can achieve an impressive energy-saving rate of up to 17.55%, and the average COP increases from 2.11 to 2.30. This study presents a novel solution that ensures the reliability operation of CRS, which is the crucial for sustainable reduction of energy consumption.