摘要
轨道交通不间断供电系统中的蓄电池直接影响所带负荷的安全可靠运行,但其容量配置往往过大,存在投资浪费问题。造成该问题的主要原因是容量设计时负荷预估偏大以及采用了恒功率放电模型,也缺乏对负荷类型和后备供电时间关系的研究,因此文中提出一种新的蓄电池容量削减办法。为了更精确地得到不间断供电系统的最大运行负荷,文中首先对负荷进行聚类,再对不同类型的负荷采用不同的预测方法。其中,波动负荷采取双参数Weibull模拟负荷曲线预测最大负荷;时序关联性不强的平稳负荷则直接采用负荷系数法。然后,考虑到不同类负荷对后备时间要求的差异,基于得到的不间断供电系统最大运行预测负荷,采用阶梯负荷法进一步削减蓄电池容量。最后,基于苏州轨道交通3号线通信不间断供电系统实际数据,削减了不间断供电系统的蓄电池容量,论证了所提方法的合理性和有效性。
The storage battery in rail transit uninterruptible power supply system directly affects the safety and reliability of the load,but its capacity is often configured far beyond normal use,leading to waste of resources.The main reasons for this problem are the overestimation of load and using constant power discharge model in the setting stage.Besides,there is a lack of research on the relationship between load type and backup power supply time.Therefore,a new method for battery capacity reduction is proposed in this paper.In order to get the maximum operating load more accurately,the loads are clustered first.Secondly,different prediction methods are used for different types of loads.The two parameter Weibull simulated load curve is adopted to predict the maximum load for fluctuating loads.The load coefficient method is directly used for the steady load with weak time series correlation.Then,the step load method is used for further reduction of battery capacity,considering the different backup time requirements of different loads.Finally,the battery capacity is reduced based on the actual data of the uninterruptible power supply system of Suzhou rail transit line 3,verifying the accuracy and effectiveness of this method.
作者
郭阳
李舜康
梁君
施祎辰
黄学良
GUO Yang;LI Shunkang;LIANG Jun;SHI Yichen;HUANG Xueliang(Suzhou Rail Transit Group Co.,Ltd.,Suzhou 215000,China;School of Electrical Engineering,Southeast University,Nanjing 210096,China)
出处
《电力工程技术》
北大核心
2021年第6期157-164,共8页
Electric Power Engineering Technology
基金
国家重点研发计划“智能电网技术与装备”重点专项(2016YFB0900600)
国家电网有限公司科技项目(52094017000W)。
关键词
不间断供电系统
蓄电池容量削减
负荷持续曲线
阶梯负荷法
轨道交通通信系统
负荷聚类
uninterruptible power supply system
battery capacity reduction
continuous load curve
step load method
rail transit communication system
load clustering