District heating (DH) systems in Sweden are facing growing challenges due to rising biomass prices and uncertainty surrounding future supply availability. Integrating solar thermal collectors with pit thermal energy storage (PTES) offers a promising pathway for reducing dependence on biomass and improving system sustainability. However, the optimal integration and techno-economic performance of such systems under real-world limitations (such as spatial and hydraulic constraints) remain largely underexplored. This study develops a two-stage modeling framework to evaluate solar + PTES integration while accounting for practical constraints such as sitting feasibility and discharge power limitations. A Python-based simplified model first generates a sensitivity matrix mapping heat delivery performance across a wide range of collector areas and storage volumes, which guides the selection of PTES sizes for subsequent detailed modelling in TRNSYS. Three system configurations are analyzed: a real-world case with waste heat and pipe limitations, a generalized case without waste heat but with pipe constraints, and an ideal case without any integration barriers. Monte Carlo simulations and sensitivity analyses are performed to quantify economic uncertainties and identify key influencing factors. Results show that discharge power limitations and pipe constraints significantly penalise the system performance, leading to higher levelized costs of heat (LCOH) compared with the ideal benchmark. The findings highlight the necessity of simultaneous consideration of spatial and techno-economic constraints to achieve cost-effective solar fractions and optimal storage design in real-world DH systems. • Quantify the impact of spatial and hydraulic constraints on solar + PTES in DH. • Employ a two-stage framework: Python pre-sizing and detailed TRNSYS simulations. • Conduct Monte Carlo and sensitivity analysis to assess economic uncertainties. • Show that pipe discharge limitations reduce solar fraction and increase LCOH • Reveal that optimal pipe sizing depends on target solar fraction and waste heat availability.
Saini et al. (Wed,) studied this question.