Multi-factor optimization of a solar heating system with seasonal thermal energy storage: A case study in northern China

Solar heating systems with seasonal thermal energy storage (SHS-STES) offer a promising pathway to resolve the temporal mismatch between solar energy supply and building heating demand. Yet, multi-factor design optimization that simultaneously enforces thermal comfort, clean-heating compliance, and collector configuration remains insufficiently explored in cold regions. This study proposes a novel optimization framework in which the solar fraction is treated as a continuous optimization variable subject to a minimum policy-mandated lower bound, rather than a pre-specified rigid target, and a unified economic objective function is constructed by introducing dual penalty functions for indoor heating temperature and solar fraction. For the first time, the area allocation of single- and double-cover flat-plate collectors is simultaneously incorporated as independent optimization variables, revealing their distinct contributions to system thermal efficiency and solar fraction. Applied to a real SHS-STES project on a northern Chinese university campus, annual thermal performance analysis of the baseline system first establishes the seasonal dynamics that motivate the optimization: the collector field achieves 452 MWh of annual heat collection at 39% mean efficiency governed by the evolving STES thermal state, and the STES maintains 85% annual storage efficiency across the full charge–discharge cycle. Building on this characterization, multi-factor optimization reduces STES volume by 32.1%, initial investment by 22.0%, and annualized cost by 18.37%, with single- and double-cover collector areas decreasing by 11.4% and 11.2%, respectively, while water-to-water heat pump coefficient of performance and part-load ratio increase by up to 11.96% and 48.41%. The optimized system avoids 120,754.2 kg of CO₂ emissions annually, confirming that the optimization framework simultaneously advances economic accessibility and environmental sustainability. This work provides a replicable optimization methodology for SHS-STES systems that balances economic performance, thermal comfort, and clean-heating compliance in cold-climate applications.