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Seasonal thermal energy storage using natural structures: GIS-based potential assessment for northern China
Building Simulation ( IF 5.5 ) Pub Date : 2024-02-12 , DOI: 10.1007/s12273-024-1106-9
Yichi Zhang , Jianjun Xia

Abstract

Seasonal thermal energy storage (STES) allows storing heat for long-term and thus promotes the shifting of waste heat resources from summer to winter to decarbonize the district heating (DH) systems. Despite being a promising solution for sustainable energy system, large-scale STES for urban regions is lacking due to the relatively high initial investment and extensive land use. To close the gap, this study assesses the potentials of using two naturally available structures for STES, namely valley and ground pit sites. Based on geographical information system (GIS) methods, the available locations are searched from digital elevation model and selected considering several criteria from land uses and construction difficulties. The costs of dams to impound the reservoir and the yielded storage capacities are then quantified to guide the choice of suitable sites. The assessment is conducted for the northern China where DH systems and significant seasonal differences of energy demand exist. In total, 2,273 valley sites and 75 ground pit sites are finally identified with the energy storage capacity of 15.2 billion GJ, which is much larger than the existing DH demand in northern China. The results also prove that 682 valley sites can be achieved with a dam cost lower than 20 CNY/m3. By conducting sensitivity analysis on the design dam wall height and elevations, the choices of available natural structures are expanded but practical issues about water pressures and constructions are also found. Furthermore, the identified sites are geographically mapped with nearest urban regions to reveal their roles in the DH systems. In general, 560 urban regions are found with potential STES units and most of them have STES storage capacities larger than their own DH demand. The novel planning methodology of this study and publicly available datasets create possibilities for the implementations of large-scale STES in urban DH systems.

更新日期:2024-02-13
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