Optimization of design parameters and operation conditions of solar-air source heat pump coupled system for rural buildings in cold and severe cold regions

Integrating solar energy utilization into air source heat pump heating systems can effectively cut down on energy consumption. However, the complexity of coupled systems poses a challenge to system performance optimization. In this paper, a solar-air source heat pump coupled system designed for heating in cold (Beijing) and severe cold (Changchun) regions is developed and analyzed by TRNSYS software. Response surface methodology (RSM) is employed to establish regression models for different performance indicators, and then the non-dominated sorting genetic algorithm-II (NSGA-II) is adopted to solve the multi-objective optimization of interactive performance parameters through Pareto optimal solution set. The regression models of the performance indicators, i.e., the energy consumption (P), the solar energy assurance rate (Ar) and the ratio of heating supply from solar energy storage tank to building load (Hs), are found to be closely related to the area of solar collectors (A) and the volumes of storage tanks (V_l for solar collector loop and V_s for ASHP loop). The obtained Pareto set successfully balances the optimal values of interactive performance indicators. In cold regions, P, Ar, Hs of the coupled system can be improved respectively by 31.79%, 33.00% and 40.07% compared to the single air source heat pump system. While in severe cold regions, these improvements are 16.25%, 15.35% and 28.38%, respectively. The design method and optimization procedure of this study provide a basis for the optimization of the solar and auxiliary heat source coupled heating systems.