MULTI-OBJRCTIVE OPTIMAL CONFIGURATION OF HYBRID ENERGY STORAGE CAPACITY CONSIDERING TWO-WAY DEMAND

Meng Xian; Guo Qimeng; Li Yinghuan; Liu Jicheng

doi:10.19912/j.0254-0096.tynxb.2022-0602

PDF(1792 KB)

Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (8) : 45-53. DOI: 10.19912/j.0254-0096.tynxb.2022-0602

MULTI-OBJRCTIVE OPTIMAL CONFIGURATION OF HYBRID ENERGY STORAGE CAPACITY CONSIDERING TWO-WAY DEMAND

Meng Xian^1,2, Guo Qimeng¹, Li Yinghuan¹, Liu Jicheng¹

Author information +

History +

Abstract

Energy storage, as a flexible resource, can effectively suppress wind power fluctuations and improve the utilization rate of wind power through reasonable capacity allocation. Demand response, as an interactive resource for power generation side and users , can reduce electricity purchase cost and promote wind power consumption at the same time. Based on this, a hybrid energy storage capacity configuration method is proposed, which takes into account the consumption demand of wind power suppliers and the power demand of users. Firstly, based on the flexible load response characteristics on the user side, the models of shifting load and reducing load are constructed. Secondly, a hybrid energy storage system composed of batteries and ultracapacitors is established, and the charging and discharging strategy is put forward. Thirdly, the hybrid energy storage capacity optimization model is constructed with the objective function of the lowest cost, minimum wind abandoning rate and highest electricity comfort of the hybrid energy storage system, and solved by multi-objective particle swarm optimization algorithm. Finally, the validity of the proposed model is verified by example analysis. The results show that the proposed hybrid energy storage capacity configuration model can not only meet the requirements of multiple parties, but also improve the system economy.

Key words

wind power / energy storage / demand side management / capacity allocation / multi-objective optimization

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Meng Xian, Guo Qimeng, Li Yinghuan, Liu Jicheng. MULTI-OBJRCTIVE OPTIMAL CONFIGURATION OF HYBRID ENERGY STORAGE CAPACITY CONSIDERING TWO-WAY DEMAND[J]. Acta Energiae Solaris Sinica. 2023, 44(8): 45-53 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0602

References

[1] 王苏蓬, 张新慧, 吴文浩,等. 用于风电平抑的混合储能选型和容量优化配置方法[J]. 智慧电力, 2021, 49(9): 16-23.
WANG S P, ZHANG X H, WU W H, et al.Hybrid energy storage selection and capacity optimization configuration method for wind power smoothing[J]. Smart power, 2021, 49(9): 16-23.
[2] 齐晓光, 姚福星, 朱天曈, 等. 考虑大规模风电接入的电力系统混合储能容量优化配置[J]. 电力自动化设备, 2021, 41(10): 11-19.
QI X G, YAO F X, ZHU T T, et al.Capacity optimization configuration of hybrid energy storage in power system considering large-scale wind power integration[J]. Electric power automation equipment, 2021, 41(10): 11-19.
[3] 徐衍会, 徐宜佳. 平抑风电波动的混合储能容量配置及控制策略[J]. 中国电力, 2022, 55(6): 186-193.
XU Y H, XU Y J.Capacity configuration and control strategy of hybrid energy storage to smooth wind power fluctuations[J]. Electric power, 2022, 55(6): 186-193.
[4] 杨立滨, 曹阳, 魏韡, 等. 计及风电不确定性和弃风率约束的风电场储能容量配置方法[J]. 电力系统自动化, 2020, 44(16): 45-52.
YANG L B, CAO Y, WEI W, et al.Configuration method of energy storage for wind farms considering wind power uncertainty and wind curtailment constraint[J]. Automation of electric power systems, 2020, 44(16): 45-52.
[5] 马瑞, 李浩, 吴震宇.考虑置信水平的混合储能平抑风电波动[J]. 电力科学与技术学报, 2022, 37(1): 35-40.
MA R, LI H, WU Z Y.Wind power fluctuations suppression with hybrid energy storage considering the confidence level[J]. Journal of electric power science and technology, 2022, 37(1): 35-40.
[6] 韩晨阳, 张鹏, 徐金华. 基于电池特性的风电场综合储能优化配置[J]. 现代电力, 2023, 40(1): 92-99.
HAN C Y, ZHANG P, XU J H.Optimal configuration of integrated energy storage for wind farms based on battery characteristics[J]. Modern electric power, 2023, 40(1): 92-99.
[7] 吴倩, 王洋, 王琳媛, 等. 计及波动平抑与经济性的风光储系统中混合储能容量优化配置[J]. 电测与仪表, 2022, 59(4): 112-119.
WU Q, WANG Y, WANG L Y, et al.Optimal capacity allocation of hybrid energy storage system in wind-solar-battery system considering fluctuation smoothing and economy[J]. Electrical measurement & instrumentation, 2022, 59(4): 112-119.
[8] ZHANG S, BAI X Z, GE L J, et al.Optimal configuration of energy storage system considering uncertainty of load and wind generation[C]//2020 IEEE Power & Energy Society General Meeting (PESGM), Toronto, Canada, 2020.
[9] 陈长青, 阳同光. 计及柔性负荷的电网储能和光伏协调规划研究[J]. 电力系统保护与控制, 2021, 49(4): 169-177.
CHEN C Q, YANG T G.Research on grid energy storage and photovoltaic coordination planning with flexible load[J]. Power system protection and control, 2021, 49(4): 169-177.
[10] 史林军, 杨帆, 刘英, 等. 计及社会发展的多场景用户侧储能容量优化配置[J]. 电力系统保护与控制, 2021, 49(22): 59-66.
SHI L J, YAN F, LIU Y,et al.Multi-scenario user-side energy storage capacity optimization configuration considering social development[J]. Power system protection and control, 2021, 49(22): 59-66.
[11] 郭久亿, 刘洋, 郭焱林, 等. 不同典型用户侧储能配置评估与运行优化模型[J]. 电网技术, 2020, 44(11): 4245-4253.
GUO J Y, LIU Y, GUO Y L, et al.Configuration evaluation and operation optimization model of energy storage in different typical user-side[J]. Power system technology, 2020, 44(11): 4245-4253.
[12] 蒋伟, 陈照光, 颜浩. 基于改进人工蜂群算法的家庭储能容量优化配置[J]. 电测与仪表, 2022, 59(10): 1-7.
JIANG W, CHEN Z G, YAN H.Optimal allocation of household energy storage capacity based on improved artificial bee colony algorithm[J]. Electrical measurement & instrumentation, 2022, 59(10): 1-7.
[13] 王帅, 尹忠东, 田硕文, 等. 基于退役动力电池的家庭储能容量优化配置[J]. 电测与仪表, 2020, 57(9): 58-64, 88.
WANG S, YIN Z D, TIAN S W, et al.Capacity allocation of household energy storage system based on second-use of retired power battery[J]. Electrical measurement & instrumentation, 2020, 57(9): 58-64, 88.
[14] 刘仲民, 齐国愿, 高敬更, 等. 基于自适应VMD的混合储能容量优化配置研究[J]. 太阳能学报, 2022, 43(4): 75-81.
LIU Z M, QI G Y, GAO J G, et al.Research on optimal configuration of hybrid energy storage capacity based on adaptive VMD[J]. Acta energiae solaris sinica, 2022, 43(4): 75-81.
[15] 蒋向兵, 汤波, 余光正, 等. 面向新能源就地消纳的园区储能与电价协调优化方法[J]. 电力系统自动化, 2022, 46(5): 51-64.
JIANG X B, TANG B, YU G Z, et al.Coordination and optimization method of park-level energy storage and electricity price for local accommodation of renewable energy[J]. Automation of electric power systems, 2022, 46(5): 51-64.
[16] 冯浩洋, 陈明丽, 潘峰, 等. 基于改进强度Pareto进化算法的居民用户侧源储荷协调优化[J]. 南方电网技术, 2022, 16(4): 86-94.
FENG H Y, CHEN M L, PAN F, et al.Coordinated optimization of source-storage-load for residents based on improved strength Pareto evolutionary algorithm[J]. Southern power system technology, 2022, 16(4): 86-94.
[17] 徐方秋. 非并网风电价值链优化与评价模型及协同云平台研究[D]. 北京: 华北电力大学, 2019.
XU F Q.Research on the optimization and evaluation model for non-grid-connected wind power and the cooperation cloud platform[D]. Beijing: North China Electric Power University, 2019.
[18] MAMUN A, LIU Z, RIZZO D, et al.An integrated design and control optimization framework for hybrid military vehicle using lithium-ion battery and supercapacitor as energy storage devices[J]. IEEE transactions on transportation electrification, 2019, 5(1): 239-251.
[19] 邵振, 邹晓松, 袁旭峰, 等. 基于改进多目标粒子群优化算法的配电网削峰填谷优化[J]. 科学技术与工程, 2020, 20(10): 3984-3989.
SHAO Z, ZOU X S, YUAN X F, et al.Optimization of peak load shifting in distribution network based on improved MOPSO algorithm[J]. Science technology and engineering, 2020, 20(10): 3984-3989.