Under the “Dual-Carbon” strategy, integrating highly volatile renewable energy into the grid remains challenging. This study proposes a Toroidal Rail Gravity Energy Storage (TRGES) system, whose key engineering contribution lies in its closed-loop track architecture that enables symmetric operation of freight and empty locomotives. We developed a dynamic model of the TRGES system and conducted multi-objective optimization using the NSGA-II algorithm to maximize system efficiency and minimize response time, under constraints including ≤5% daily power fluctuation and ≥ 95% renewable energy utilization. Key quantitative results demonstrate that charging/discharging power is highly sensitive to load mass and speed, increasing from 0 MW to 51.39 MW and 30.93 MW for a 2375 t load as speed scales from 0 to 50 km/h. Conversely, system efficiency remains stable with load mass but decreases with speed, with the overall system efficiency declining by only 0.04% over the same speed range. When coupled with a hybrid wind-PV plant, the TRGES system achieved a renewable energy utilization rate of 96.3% and reduced the daily fluctuation coefficient to 0.42 on a typical winter day. This study provides a theoretical and practical foundation for deploying gravity energy storage as a viable, geographically flexible solution for large-scale renewable integration and grid peak shaving, indicating its applicability for large-scale renewable integration and grid peak shaving. • The circular orbital gravity energy storage system is proposed innovatively. • A complete dynamic model is established. • The influence of key operation parameters on system performance is revealed. • A multi-objective group model for wind-solar-storage coupling system is constructed. • The fluctuation of wind power output is effectively suppressed.
Building similarity graph...
Analyzing shared references across papers
Loading...
Yizhi Tian
Wenjie Zhang
Yale Liu
Journal of Energy Storage
Xinjiang University
Building similarity graph...
Analyzing shared references across papers
Loading...
Tian et al. (Tue,) studied this question.
www.synapsesocial.com/papers/69a75fffc6e9836116a2c665 — DOI: https://doi.org/10.1016/j.est.2026.120674