计及损耗的钒电池储能系统功率优化分配策略

doi:10.19595/j.cnki.1000-6753.tces.200122

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Abstract For the large-capacity energy storage system composed of multiple sets of vanadium redox flow batteries connected in parallel, an optimized power allocation strategy considering the loss is given.This strategy first establishes a power allocation model that takes into account losses, and then takes the system loss and SOC balance as the objective optimization function.And the virtual particle-adaptive differential evolution algorithm (VP-ADE) is used to find the optimal solution under the constraints of meeting the power demand, state of charge (SOC) upper and lower limit, etc. Therefore, the optimal power distribution of the energy storage system is realized.Finally, the strategy of this paper is simulated and verified based on Matlab, and compared with the traditional strategy , the simulation results show that this the SOC of each energy storage unit gradually converge during charging and discharging.

Key words： Power distribution vanadium redox flow battery system loss state of charge (SOC) differential evolution algorithm

Received: 10 February 2020

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TM316

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	Chen Wei
	Hou Yangcheng
	Zhang Li
	Wang Juan
	Qiu Ya

Cite this article:

Chen Wei,Hou Yangcheng,Zhang Li等. Power Optimization Allocation Strategy for Vanadium Battery Energy Storage System Considering Loss[J]. Transactions of China Electrotechnical Society, 2020, 35(19): 4038-4047.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.200122 OR https://dgjsxb.ces-transaction.com/EN/Y2020/V35/I19/4038

[1] 李建林, 袁晓冬, 郁正纲, 等. 利用储能系统提升电网电能质量研究综述[J]. 电力系统自动化, 2019, 43(8): 15-24.
Li Jianlin, Yuan Xiaodong, Yu Zhenggang, et al.Comments on power quality enhancement research for power grid by energy storage system[J]. Automation of Electric Power Systems, 2019, 43(8): 15-24.
[2] 赖昌伟, 黎静华, 陈博, 等. 光伏发电出力预测技术研究综述[J]. 电工技术学报, 2019, 34(6): 1201-1217.
Lai Changwei, Li Jinghua, Chen Bo, et al.Review of research on photovoltaic power output prediction technology[J]. Transactions of China Electrotechnical Society, 2019, 34(6): 1201-1217.
[3] Vine E.Building a sustainable organizational energy evaluation system in the Asia Pacific[J]. Global Energy Interconnection, 2019, 2(5): 378-385.
[4] 李建林, 马会萌, 惠东. 储能技术融合分布式可再生能源的现状及发展趋势[J]. 电工技术学报, 2016, 31(14): 1-10, 20.
Li Jianlin, Ma Huimeng, Hui Dong.Present development condition and trends of energy storage technology in the integration of distributed renewable energy[J]. Transactions of China Electrotechnical Society, 2016, 31(14): 1-10, 20.
[5] 刘舒, 李正力, 王翼, 等. 含分布式发电的微电网中储能装置容量优化配置[J]. 电力系统保护与控制, 2016, 44(3): 78-84.
Liu Shu, Li Zhengli, Wang Yi, et al.Optimal capacity allocation of energy storage in micro-grid with distributed generation[J]. Power System Protection and Control, 2016, 44(3): 78-84.
[6] 施云辉, 王橹裕, 陈玮, 等. 基于风电预测误差聚类的分布鲁棒含储能机组组合[J]. 电力系统自动化, 2019, 43(22): 3-12.
Shi Yunhui, Wang Luyu, Chen Wei, et al.Distributed robust unit commitment with energy storage based on forecasting error clustering of wind power[J]. Automation of Electric Power Systems, 2019, 43(22): 3-12.
[7] 贾科, 宣振文, 林瑶琦, 等. 基于Adaboost算法的并网光伏发电系统的孤岛检测法[J]. 电工技术学报, 2018, 33(5): 1106-1113.
Jia Ke, Xuan Zhenwen, Lin Yaoyi, et al.An islanding detection method for grid-connected photovoltaic power system based on Adaboost algorithm[J]. Transactions of China Electrotechnical Society, 2018, 33(5): 1106-1113.
[8] Benzahia A, Boualaga R, Moussi A, et al.A PV powered shunt active power filter for power quality improvement[J]. Global Energy Interconnection, 2019, 2(2): 143-149.
[9] 刘坚. 储能技术应用潜力与经济性研究[M]. 北京: 中国经济出版社, 2016.
[10] 胡国珍, 段善旭, 蔡涛, 等. 基于液流电池储能的光伏发电系统容量配置及成本分析[J]. 电工技术学报, 2012, 27(5): 260-267.
Hu Guozhen, Duan Shanxu, Cai Tao, et al.Sizing andcost analysis of photovoltaic generation system based onvanadium redox battery[J]. Transactions of China Electrotechnical Society, 2012, 27(5): 260-267.
[11] 凌志斌, 黄中, 田凯. 大容量电池储能系统技术现状与发展[J]. 供用电, 2018, 35(9): 3-8, 21.
Ling Zhibin, Huang Zhong, Tian Kai.Current status and development of large capacity battery energy storage system technology[J]. Power Supply, 2018, 35(9): 3-8, 21.
[12] Lu Minghui, Duan Shanxu, Chen Changsong, et al.Coordinate control of parallel connected power conditioning system for battery energy storage system in microgrid[C]// IEEE Applied Power Electronics Conference and Exposition, Fort Worth, TX, USA, 2014: 707-711.
[13] Li Xiangjun, Hui Dong, Lai Xiaokang.Battery energy storage station (BESS)-based smoothing control of photovoltaic (PV) and wind power generation fluctuations[J]. IEEE Transactions on Sustainable Energy, 2013, 4(2): 464-473.
[14] Li Xiangjun, Yao Liangzhong, Hui Dong.Optimal control and management of a large-scale battery energy storage system to mitigate fluctuation and intermittence of renewable generations[J]. Journal of Modern Power Systems and Clean Energy, 2016, 4(4): 593-603.
[15] 唐芬, 姜久春, 吴丹, 等. 考虑电池储能系统荷电状态的有功功率协调控制[J]. 电力系统自动化, 2015, 39(22): 30-36.
Tang Fen, Jiang Jiuchun, Wu Dan, et al.Active power coordinated control considering SOC of battery energy storage system[J]. Automation of Electric Power Systems, 2015, 39(22): 30-36.
[16] 刘忠, 杨陈, 蒋玮, 等. 基于一致性算法的直流微电网储能系统功率分配技术[J]. 电力系统自动化, 2020, 44(7): 61-75.
Liu Zhong, Yang Chen, Jiang Wei, et al.Power distribution technology of DC microgrid energy storage system based on consensus algorithm[J]. Automation of Electric Power Systems, 2020, 44(7): 61-75.
[17] Wu Dan, Tang Fen, Dragicevic T, et al.Coordinated control based on bus-signaling and virtual inertia for islanded DC microgrids[J]. IEEE Transactions on Smart Grid, 2015, 6(6): 2627-2638.
[18] 毕恺韬, 孙力, 安群涛, 等. 基于模块化多电平直流变换器的储能系统分布式能量均衡控制策略[J]. 电工技术学报, 2018, 33(16): 3811-3821.
Bi Kaitao, Sun Li, An Quntao, et al.Distributed energy balance control strategy of energy storage system based on modular multilevel DC converter[J]. Transactions of China Electrotechnical Society, 2018, 33(16): 3811-3821.
[19] 吴青峰, 孙孝峰, 王雅楠, 等. 基于分布式下垂控制的微电网分布式储能系统SOC平衡策略[J]. 电工技术学报, 2018, 33(6): 1247-1256.
Wu Qingfeng, Sun Xiaofeng, Wang Yanan, et al.SOC balancing strategy of microgrid distributed energy storage system based on distributed droop control[J]. Transactions of China Electrotechnical Society, 2018, 33(6): 1247-1256.
[20] 王炜信, 段建东, 张润松, 等. 孤岛电网中多储能设备SOC一致性优化策略[J]. 电工技术学报, 2015, 30(23): 126-135.
Wang Weixin, Duan Jiandong, Zhang Runsong, et al.Optimal state-of-charge balancing control for paralleled battery energy storage devices in islanded microgrid[J]. Transactions of China Electrotechnical Society, 2015, 30(23): 126-135.
[21] 张继元, 舒杰, 宁佳, 等. 考虑SOC自均衡的光储独立微电网协调控制[J]. 电工技术学报, 2018, 33(增刊2): 527-537.
Zhang Jiyuan, Shu Jie, Ning Jia, et al.Coordinated control of optical storage independent microgrid considering SOC self-balance[J]. Transactions of China Electrotechnical Society, 2018, 33(S2): 527-537.
[22] 朱永强, 王甜婧, 许阔, 等. 基于动态规划-遗传算法的混合储能系统实时协调调度和经济运行[J]. 太阳能学报, 2019, 40(4): 1059-1066.
Zhu Yongqiang, Wang Tianjing, Xu Kuo, et al.Real-time coordinated scheduling and economic operation of hybrid energy storage system based on dynamic programming-genetic algorithm[J]. Journal of Solar Energy, 2019, 40(4): 1059-1066.
[23] 李亚楠, 王倩, 宋文峰, 等. 混合储能系统平滑风电出力的变分模态分解-模糊控制策略[J]. 电力系统保护与控制, 2019, 47(7): 58-65.
Li Yanan, Wang Qian, Song Wenfeng, et al.Variational mode decomposition and fuzzy control strategy of hybrid energy storage for smoothing wind power outputs[J]. Power System Protection and Control, 2019, 47(7): 58-65.
[24] 李蓓, 郭剑波, 陈继忠, 等. 液流储能电池系统支路电流的建模与仿真分析[J]. 中国电机工程学报, 2011, 31(27): 1-7.
Li Bei, Guo Jianbo, Chen Jizhong, et al.Modeling and simulation analysis of branch current of liquid flow energy storage battery system[J]. Proceedings of the CSEE, 2011, 31(27): 1-7.
[25] 赵航飞, 刘承志, 刘湘东, 等. 液流电池的效率分析[J]. 电源技术, 2018, 42(12): 1872-1875.
Zhao Hangfei, Liu Chengzhi, Liu Xiangdong, et al.Efficiency analysis of flow battery[J]. Power Technology, 2018, 42(12): 1872-1875.
[26] 迟晓妮, 朱敏刚, 吴秋轩. 基于等效模型的全钒液流电池运行优化控制研究[J]. 储能科学与技术, 2018, 7(3): 530-538.
Chi Xiaoni, Zhu Mingang, Wu Qiuxuan.Research on optimal operation control based on the equivalent model of VRFB system[J]. Energy Storage Science and Technology, 2018, 7(3): 530-538.
[27] Wu Zhenwei, Jiang Xiaoping, Ma Huimeng, et al.Wavelet packet-fuzzy control of hybrid energy storage systems for PV power smoothing[J]. Proceedings of the CSEE, 2014, 34(3): 317-324.
[28] 邱亚, 李鑫, 魏达, 等. 全钒液流电池的柔性充放电控制[J]. 储能科学与技术, 2017, 6(1): 78-84.
Qiu Ya, Li Xin, Wei Da, et al.Flexible charge-discharge control of vanadium redox battery[J]. Energy Storage Science and Technology, 2017, 6(1): 78-84.
[29] 尤东江, 张华民. 氧化还原电池组等效电路模型[J]. 电化学, 2014, 20(2): 156-163.
You Dongjiang, Zhang Huamin.Equivalent circuit model of redox battery pack[J]. Electrochemistry, 2014, 20(2): 156-163.
[30] Chahwan J, Abbey C, Joos G, et al.VRB modelling for the study of output terminal voltages, internal losses and performance[C]//2007 IEEE Canada Electrical Power Conference, Montreal Que, Canada, 2007: 387-392.
[31] 王亚光, 王秋源, 陆继明, 等. 大容量液流电池系统数学模型与仿真[J]. 电力自动化设备, 2015, 35(8): 72-78.
Wang Yaguang, Wang Qiuyuan, Lu Jiming, et al.Mathematical model and simulation of large-capacity flow battery system[J]. Electric Power Automation Equipment, 2015, 35(8): 72-78.
[32] 彭思敏, 施刚, 蔡旭, 等. 基于等效电路法的大容量蓄电池系统建模与仿真[J]. 中国电机工程学报, 2013, 33(7): 11-18.
Peng Simin, Shi Gang, Cai Xu, et al.Modeling and simulation of large-capacity battery system based on equivalent circuit method[J]. Proceedings of the CSEE, 2013, 33(7): 11-18.