风电波动平抑下考虑SOC均衡及收益的电池储能功率分配策略

被引:29
作者
余洋 [1 ,2 ]
陈东阳 [1 ,2 ]
吴玉威 [1 ,2 ]
李佳丽 [1 ,2 ]
王卜潇 [1 ,2 ]
米增强 [1 ,2 ]
机构
[1] 华北电力大学新能源电力系统国家重点实验室
[2] 华北电力大学河北省分布式储能与微网重点实验室
基金
国家重点研发计划;
关键词
电池储能系统; 平抑风电波动; SOC均衡; 功率分配; 改进算术优化算法;
D O I
暂无
中图分类号
TM614 [风能发电]; TM91 [独立电源技术(直接发电)];
学科分类号
080802 [电力系统及其自动化]; 080811 [新能源发电与电能存储];
摘要
针对电池储能(battery energy storage system,BESS)平抑风电波动过程中电池单元荷电状态(state of charge,SOC)均衡性较差且未考虑风储净收益的问题,提出了风电波动平抑下考虑SOC均衡及收益的BESS功率分配策略。首先,建立综合考虑售电收益、弃风惩罚、缺电惩罚及BESS运行成本等多个因素的风电并网指令优化模型,以并网指令波动率、电池组SOC标准差等多个因素为约束条件,提出改进算术优化算法(improvedarithmeticoptimizationalgorithm,IAOA)求解该优化模型。然后,将BESS划分为两个电池组,设计了BESS双层功率分配方法(double-layer power allocation method,DPAM),上层将BESS充放电指令分配给两个电池组,下层根据最大充放电功率原则或新型SOC均衡原则将电池组充放电指令分配给各自的电池单元。最后,通过仿真对所提策略进行了验证。仿真结果表明:IAOA加快了寻优速度,提高了寻优精度;DPAM提升了电池组内电池单元SOC的均衡速度,改善了均衡程度;提出的功率分配策略进一步降低了风电并网波动率,同时提高了风储系统净收益。
引用
收藏
页码:1714 / 1723
页数:10
相关论文
共 25 条
[1]
基于智能优化算法的风电功率预测及并网稳定性研究 [D]. 
周宇健 .
湖南工业大学,
2021
[2]
Parameter extraction of single; double; and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphson methods.[J].Ridha Hussein Mohammed;Hizam Hashim;Mirjalili Seyedali;Othman Mohammad Lutfi;Ya'acob Mohammad Effendy;Ahmadipour Masoud.Renewable and Sustainable Energy Reviews.2022,
[3]
A comprehensive wind speed prediction system based on Monte Carlo and artificial intelligence algorithms.[J].Zhang Yagang;Zhao Yunpeng;Shen Xiaoyu;Zhang Jinghui.Applied Energy.2022,
[4]
Analysis of power allocation strategies in the smoothing of wind farm power fluctuations considering lifetime extension of BESS units.[J].Mohsen Jannati;Eisa Foroutan.Journal of Cleaner Production.2020, prepublish
[5]
Multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems.[J].V. V. S. N. Murty;Ashwani Kumar.Protection and Control of Modern Power Systems.2020, 4
[6]
A Novel Event Detection Method Using PMU Data With High Precision [J].
Cui, Mingjian ;
Wang, Jianhui ;
Tan, Jin ;
Florita, Anthony R. ;
Zhang, Yingchen .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2019, 34 (01) :454-466
[7]
The Whale Optimization Algorithm.[J].Seyedali Mirjalili;Andrew Lewis.Advances in Engineering Software.2016,
[8]
Coordinated Operational Planning for Wind Farm With Battery Energy Storage System [J].
Luo, Fengji ;
Meng, Ke ;
Dong, Zhao Yang ;
Zheng, Yu ;
Chen, Yingying ;
Wong, Kit Po .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2015, 6 (01) :253-262
[9]
Cost-Optimized Battery Capacity and Short-Term Power Dispatch Control for Wind Farm [J].
Cong-Long Nguyen ;
Lee, Hong-Hee ;
Chun, Tae-Won .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2015, 51 (01) :595-606
[10]
自适应t分布与动态边界策略改进的算术优化算法 [J].
郑婷婷 ;
刘升 ;
叶旭 .
计算机应用研究, 2022, 39 (05) :1410-1414