Cooling energy storage/release performance for the proposed refrigeration and cooling energy storage coupling system

• Propose and construct refrigeration and cooling energy storage coupling system. • Simulate solidification/melting rate and uniformity in phase change material plates. • Find that regulate phase change by temperature is more effective than by flow rate. • Find that flow rate of heat transfer fluid affects phase change asymmetrically. • Obtain engineering selection program of refrigeration and cooling energy storage. Addressing the issues of high building air conditioning energy consumption and the mismatch in the timing of supply and demand for renewable energy, this paper designs a modular combined cooling and storage unit. Through the integration of cooling, storage, and supply in a unified design, it achieves flexible energy utilization with “off-peak cooling storage and peak cooling release”. The research is based on a coupled heat transfer model of thermal storage plates and thermal storage tanks, combining numerical simulation and experimental testing to systematically reveal the influence mechanism of operating parameters on the system’s energy storage and release characteristics. The results show that temperature is the dominant factor affecting the phase change process, with an effectiveness about three times that of flow rate; the influence of flow rate exhibits significant asymmetry during freezing and melting stages. Experimental validation confirms that the system achieves optimal comprehensive performance at 4 °C conditions and proposes an engineering operation optimization plan: during the energy storage phase, it recommends using 4 °C and 3.0 m³/h to maximize cooling input, while during the energy release phase, it suggests matching 4 °C, 1.0 m³/h, and 1020.0 m³/h supply air volume to enhance heat exchange balance and overall energy efficiency. This study provides theoretical and engineering references for the design and operation of combined cooling and storage units and lays a model and data foundation for subsequent integration with artificial intelligence optimization control.