退役电池梯次利用对新能源消纳影响的研究Effect of Second-use of Retired Batteries on New Energy Consumption
樊国旗,吕盼,樊国伟,黄健,陈浩,王衡,陈梓翰
FAN Guoqi,LYU Pan,FAN Guowei,HUANG Jian,CEHN Hao,WANG Heng,CHEN Zihan
摘要(Abstract):
为提高退役电池梯次利用收益,建立了退役电池平抑新能源功率预测误差模型和改善等效负荷峰谷差模型。首先分析新能源功率预测误差的影响以及新能源波动对等效负荷峰谷差和等效负荷波动率的影响,然后设计退役电池能量管理系统,通过小波包分解方法将低频能量分量分配给退役电池,并根据等效负荷大小确定退役电池充放电时间和功率。最后利用实际算例仿真,结果表明提出的退役电池梯次利用模型可以提高新能源功率预测准确率、改善峰谷特性、降低等效负荷波动率,并大幅提高收益。
To improve the utilization benefits of second-use of retired batteries, this paper establishes a retired battery to stabilize the new energy prediction error model and improve the equivalent load peak-valley difference model. Firstly, the paper analyzes the impact of new energy prediction errors and the impact of fluctuation on the peak-valley difference and the fluctuation rate of the equivalent load; secondly, the paper designs a retired battery energy management system to distribute low-frequency energy components to the retired battery through the wavelet packet decomposition method, and the charge and discharge time and power of the retired battery are determined according to the equivalent load; finally, examples are used for simulation and the results show that the second-use model of retired batteries can improve the accuracy of new energy prediction, improve the peak and valley characteristics, reduce the equivalent load fluctuation rate, and greatly increase the profits.
关键词(KeyWords):
退役电池梯次利用;等效负荷波动率;新能源预测准确率
second-use of retired batteries;equivalent load fluctuation rate;new energy prediction accuracy
基金项目(Foundation): 国家重点研发计划项目(2017YFB0902200)
作者(Author):
樊国旗,吕盼,樊国伟,黄健,陈浩,王衡,陈梓翰
FAN Guoqi,LYU Pan,FAN Guowei,HUANG Jian,CEHN Hao,WANG Heng,CHEN Zihan
DOI: 10.19585/j.zjdl.202103018
参考文献(References):
- [1]谢宝江,娄伟明,罗扬帆,等.基于H∞无迹卡尔曼滤波的退役锂离子电池SOC估计[J].浙江电力,2020,39(8):53-60.
- [2]吴星宇,阮丁山,唐盛贺,等.退役动力锂离子电池梯次利用概述[J/OL].电池,[2020-12-08].http://kns.cnki.net/kcms/detail/43.1129.tm.20201202.1325.004.html.
- [3]徐懋,刘东,王德钊.退役磷酸铁锂动力电池梯次利用分析[J].电源技术,2020,44(8):1227-1230.
- [4]高崧,朱华炳,刘征宇,等.基于K-means聚类的退役动力电池梯次利用成组方法[J].电源技术,2020,44(10):1479-1482.
- [5]王凯丰,谢丽蓉,乔颖,等.基于退役电池阈值设定和分级控制的弃风消纳模式[J].电力自动化设备,2020,40(10):92-98.
- [6]崔传世,谢丽蓉,包洪印,等.平抑风电功率波动退役电池储能系统容量配置[J].电源技术,2020,44(8):1185-1190.
- [7]吴威,唐雨晨,叶荣,等.不同场景下基于AHP-TOPSIS退役电池梯次利用综合评价[J].电网与清洁能源,2020,36(4):115-122.
- [8]郭世枭.含退役电池梯次利用的公交车充电站优化配置及运营[D].北京:华北电力大学,2019.
- [9]方绍凤,周任军,张武军,等.源-荷协整关系与电价时间序列协整模型[J].电力自动化设备,2020,40(2)):169-176.
- [10]周任军,李斌,黄婧杰,等.含源荷相似度和曲线波动度约束的源荷储协调优化模型[J].中国电机工程学报,2020,40(13):4092-4102.
- [11]李宏仲,张仪,孙伟卿.小波包分解下考虑广义储能的风电功率波动平抑策略[J/OL].电网技术,[2020-06-23].https://doi.org/10.13335/j.1000-3673.pst.2020.0514.
- 退役电池梯次利用
- 等效负荷波动率
- 新能源预测准确率
second-use of retired batteries - equivalent load fluctuation rate
- new energy prediction accuracy