Author
Listed:
- Du, Anran
- Shan, Kui
- Yuan, Liyuan
- Gao, Dian-ce
Abstract
The rising demand from electric vehicle (EV) charging introduces significant new loads to existing buildings, placing growing pressure on building-level power infrastructure. In many aging buildings, transformers are unable to support large-scale EV charging, leading to overloading risks and the need for costly infrastructure upgrades. To address these challenges, this study proposes a risk-aware life-cycle optimal design framework to retrofit existing building heating, ventilation and air-conditioning (HVAC) systems by integrating a chilled water storage (CWS). Unlike existing design methods, the proposed design framework incorporates both risk-aware and life-cycle design perspectives, accounting for the transformer overloading risks and the long-term growing demand from EV charging. It determines the CWS capacity and optimizes its charging/discharging schedules, aiming not only to improve building economic performance but also to mitigate the impact of rising EV charging on the building-level power infrastructure. Applied to an existing building community, the proposed design (Design #B) can fully eliminate the cumulative overload power on the typical day compared to the baseline. Over the 20-year period, Design #B can reduce total cumulative overload hours by 36.8% and defer transformer upgrades by six years (85.7% longer) compared to the baseline (without CWS), providing a 22.7% additional reduction and a four-year longer deferral (57.1%) compared to Design #A. Design #B can also achieve a 3.9% reduction in life-cycle costs compared to the baseline and provide an additional 2.0% reduction compared to Design #A. The proposed framework offers a cost-effective retrofit solution for existing buildings, supporting widespread EV penetration while deferring costly local grid upgrades.
Suggested Citation
Du, Anran & Shan, Kui & Yuan, Liyuan & Gao, Dian-ce, 2026.
"Thermal storage integration in buildings towards long-term rising EV charging demand: risk-aware and life-cycle optimal design framework,"
Energy, Elsevier, vol. 355(C).
Handle:
RePEc:eee:energy:v:355:y:2026:i:c:s0360544226012703
DOI: 10.1016/j.energy.2026.141164
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