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To enhance the flexibility of residential air source heat pump (ASHP) systems and support their integration into China’s new power system, this study proposes an optimal flexible heating dispatch (OFHS) method and assesses the flexible heating potential of the new power system. The approach optimizes ASHP supply water temperature setpoints in response to time-of-use (TOU) electricity tariffs, leveraging the passive thermal storage capacity of residential buildings and accounting for variations in ASHP coefficient of performance (COP). A dynamic thermal model based on a resistance-capacitance (RC) network is developed to predict indoor air and return water temperatures, enabling proactive scheduling of heating demand. The OFHS method was tested on an ASHP–radiant floor system in a rural household. Results show that the OFHS control method accurately adjusts the set value of the ASHP water supply temperature while ensuring indoor thermal comfort. Compared with the existing control methods, the COP is increased by 6.34% and the heating power consumption is reduced by 7.16%. Meanwhile, the OFHS method can significantly enhance the demand response effect of the ASHP system in residential buildings in the new power system, increasing the power load transfer capacity by 37.01% and reducing the heating operation cost by 22.37%.

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Optimal Flexible Heating Scheduling of Air Source Heat Pumps for Residential Buildings: Application Performance in China’s New Power System

  • 会议论文

  • 发表日期：

    2025年

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  • Xintian Li,
  • Wei Wang,
  • Yuying Sun,
  • Jianhang Song,
  • Shulun han,
  • Jianfei Zhang,
  • Wenzhe Wei

摘要

To enhance the flexibility of residential air source heat pump (ASHP) systems and support their integration into China’s new power system, this study proposes an optimal flexible heating dispatch (OFHS) method and assesses the flexible heating potential of the new power system. The approach optimizes ASHP supply water temperature setpoints in response to time-of-use (TOU) electricity tariffs, leveraging the passive thermal storage capacity of residential buildings and accounting for variations in ASHP coefficient of performance (COP). A dynamic thermal model based on a resistance-capacitance (RC) network is developed to predict indoor air and return water temperatures, enabling proactive scheduling of heating demand. The OFHS method was tested on an ASHP–radiant floor system in a rural household. Results show that the OFHS control method accurately adjusts the set value of the ASHP water supply temperature while ensuring indoor thermal comfort. Compared with the existing control methods, the COP is increased by 6.34% and the heating power consumption is reduced by 7.16%. Meanwhile, the OFHS method can significantly enhance the demand response effect of the ASHP system in residential buildings in the new power system, increasing the power load transfer capacity by 37.01% and reducing the heating operation cost by 22.37%.