Multi-objective optimization and techno-economic assessment of solar-assisted medium-deep borehole seasonal thermal energy storage systems

Solar-assisted seasonal thermal energy storage (SSTES) in medium-deep boreholes can decarbonize district heating, yet its long-term techno-economics remain unclear. This study couples a 3-D finite-volume model with regression meta-modelling and NSGA-II multi-objective optimization. The workflow is validated against field data. Scenarios span 500–2500 m depth, 1–20 kg/ s flow, and realistic geological properties. The results demonstrate a long-term thermal accumulation effect, with storage and extraction performance stabilizing after approximately 5 years of operation. Compared to a system without solar assistance, the optimized design achieves a 26.3% reduction in Levelized Cost of Heat (LCOH) and shortens the payback period from 9.9 to 7.4 years. Sensitivity analysis identifies soil drilling depth as the most influential parameters affecting both economic and thermal performance. The multi-optimization results shows that optimal drilling depth lies within 1375–1560 m, while the optimal mass flow rate is 6.7–9.5 kg/s. A regression model with R² = 0.98 enables rapid prediction of seasonal heat storage based on key geological and operational variables. Internal heat exchange between coaxial pipes is found to account for up to 25% of radial heat loss in shallow sections, emphasizing the need for careful borehole configuration. These findings offer a practical framework for SSTES system design and highlight future directions, including multi-well configuration optimization and adaptive operational strategies for improved seasonal control.