大规模储能技术对于可再生能源的发展及电网稳定运行具有重要意义.铁轨重力储能(rail gravity energy storage,RGES)技术可灵活调度载重机车进行储/释能,有效解决风电场大幅度功率波动问题,在长时大规模储能应用技术中前景广阔.本文开展了RGES系统关键影响因素及其与风电场耦合调度的研究,基于MATLAB软件搭建了RGES系统模型及其与风电场的耦合系统模型,研究了储/释能过程中关键参数对RGES系统的影响规律,并且以减少风电场的弃风率为目的,选取了四个季节的典型日,详细研究了耦合系统的运行特性及RGES系统的配置方案.结果 表明,储/释能功率随载重质量增加而增大,随匀速阶段的上/下坡速度增加而增大;储/释能效率及系统效率随载重质量的变化极小,随上/下坡速度增大而减小;RGES系统与风电场耦合运行时,可根据功率需求灵活配置各时段的载重车辆数及上/下坡速度进行储/释能,并可在四个季节典型日的用电高峰期分别实现22 MW、16 MW、27 MW、29 MW的恒定功率并网,且风电利用率平均增长17.1%.
Study on key influencing factors of the rail gravity energy storage system and its coupling with wind farms
Large-scale energy storage technology plays a crucial role in the development of renewable energy and the stability of power grids.Rail gravity energy storage(RGES)technology enables flexible load locomotive dispatch for energy storage and release.It effectively addresses the issue of significant power fluctuations in wind farms and presents significant potential for long-term,large-scale energy storage applications.This paper explores the key influencing factors of the RGES system and its integrated scheduling with a wind farm.We constructed models of the RGES system and its coupled system with the wind farm using MATLAB software.The study examines how key parameters affect the RGES system during the energy storage and release process.To minimize the wind power curtailment rate,we analyzed the operational characteristics and system configurations of the coupled system during typical days across all seasons in detail.The results indicate that the power for energy storage and release increases with higher load mass and faster upward/downhill speeds during the constant speed phase.The efficiency of energy storage and release,as well as overall system efficiency,show minimal variation with load mass but decrease with increasing speeds.When coupled with a wind farm,the RGES system can adapt the number of trucks and their speeds for optimal energy storage and release,achieving stable power outputs of 22 MW,16 MW,27 MW,and 29 MW during peak consumption on typical days in each season,enhancing the wind power utilization rate by an average of 17.1%.
physical energy storagegravity energy storagerail gravity energy storagewind farmcoupling study
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