Abstract
Air source heat pump (ASHP) is a key technology for the electrification of building heating, and its participation in demand response (DR) has important implications for reducing the grid peak load. However, current DR strategies mainly focus on changing the setpoint of indoor temperature, using the building’s thermal mass as a passive thermal storage, while the impacts of water temperature on the performance of ASHP units are often overlooked. Therefore, this study proposes an optimal water temperature scheduling (OWTS) method to respond time–of–use tariffs. It is developed based on a room thermal dynamic prediction model and an ASHP power consumption prediction model, optimizing supply water temperature schedule with objectives of maintaining indoor thermal comfort and reducing heating operating costs. The effectiveness of the OWTS method was tested on a field ASHP system in Beijing, and compared with two benchmark methods. Results demonstrate that the application of the OWTS method can enhance the DR capability of the ASHP heating system, with the average value of Flexibility Factor increasing from 0.134 to 0.728, and can reduce the heating operating costs by 20.8%–43.0%. This study thereby offers a promising method for ASHP heating systems to effectively participate in DR.
Published Version
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