Temperature Control of Photovoltaic Thermal Heat Pump System with Quantum-Inspired Optimization under Variable Ambient Conditions

Photovoltaic thermal heat pump systems can simultaneously provide electricity and heat, but their thermal performance may decrease under low ambient temperature conditions. However, many existing planning and operational studies describe device performance using fixed conversion coefficients or fitted curves, which provide limited insight into how the outlet temperature affects system performance under varying ambient and irradiance conditions. To address this issue, this study develops a physics-based model of a photovoltaic thermal heat pump system and applies it to outlet temperature setpoint analysis and optimization. A proportional integral derivative controller is used to track the prescribed outlet temperature setpoint, and a quantum-inspired particle swarm optimization algorithm is applied to identify the optimal setpoint without requiring gradient information. The results show that the outlet temperature has a distinct optimum rather than a monotonic effect on system performance. This optimum arises from the trade off among increased heat loss at high outlet temperatures, reduced heat pump cycle efficiency at low source temperatures, and pumping power consumption. Compared with a fixed high outlet temperature baseline, the optimized setpoint increases the mean pointwise electrical efficiency by 0.68% to 2.14% and the mean pointwise thermal efficiency by up to 43.7%, with larger thermal gains under cold conditions. The proposed framework provides a physically interpretable method for determining outlet temperature setpoints and improving the operation of photovoltaic thermal heat pump systems.