Optimization of closed-loop heat pump drying systems using response surface methodology-based location quotient

Industrial drying processes are highly energy-intensive. Although closed-loop heat pump drying systems offer substantial potential for energy savings, their performance is strongly constrained by the coupling of multiple process parameters and by climatic conditions, thereby limiting further efficiency improvements and regional applicability. To address these challenges, this study systematically evaluates the energy and economic performance of a closed-loop heat pump drying system by integrating process parameter optimization with climate adaptability analysis. Quantitative relationships between drying chamber temperature, relative humidity, fan frequency, dehumidification capacity, system energy consumption, and the specific moisture extraction rate (SMER) were established using TRNSYS-based numerical simulations combined with the Box–Behnken response surface methodology (R2 > 0.999). Multi-objective optimization indicates that under optimal conditions—65 °C drying temperature, 12.5% relative humidity, 40 Hz fan frequency, and a dehumidification rate of 9.3 kg h−1—the system achieves an SMER of 1.22 kg kWh−1, with a deviation of only 1.23% between predicted and simulated values, confirming the robustness of the model. Furthermore, a location quotient (LQ) approach was introduced to standardize performance comparisons across different climatic regions. The results demonstrate that hot and humid climates are particularly favorable for latent heat recovery, yielding superior energy efficiency and economic performance, whereas system efficiency deteriorates markedly during winter operation in severe cold regions. The proposed “climate–energy–economics” evaluation framework provides a solid engineering basis for parameter design and regional deployment of closed-loop heat pump drying systems.