Medium-deep ground source heat pump systems: potential and optimization control for grid interaction

The growing adoption of heat pumps presents new opportunities for flexible power system regulation. Medium-deep ground source heat pump systems (MDGSHPS) exhibit substantial short-term power adjustment capabilities, establishing them as ideal flexible resources on the user side. However, research on MDGSHPS and their interactions with smart grids remains limited, with scarce focus on dynamic oversupply management and targeted optimization control. This study addresses these gaps by quantifying the short-term oversupply flexibility of MDGSHPS through dynamic simulation and regression analysis, which provides a quantitative basis for assessing the system’s regulation potential. It further develops a tailored model predictive control (MPC) framework that synergistically optimizes renewable energy utilization and demand response, integrating load prediction models and genetic algorithm-based optimization to adapt to the system’s nonlinear and time-varying characteristics. This dual approach fills the void in MDGSHPS’s dynamic performance evaluation and enhances its adaptability in complex grid interaction scenarios. Results indicate that adjusting source-side water temperature and leveraging geothermal oversupply can enhance grid stability: during a 1 h pre-spike price period (15°C inlet), cumulative heat intake increases by 64.4%; with thermal energy storage, heat extraction increased by 67.8% while electricity costs were reduced by 62.3%. Compared to the no-energy-storage mode, the fixed time interval control strategy cuts operating costs by 10.5%, while the MPC mode achieves an 11.5% reduction, effectively managing oversupply and supporting demand response under variable loads. This research highlights the potential of MDGSHPS to enhance grid stability and optimize renewable energy integration, thereby contributing to improved power system efficiency.