Control Strategy of DC Microgrid Energy Storage Converter Based on Node Differential Current
Zhang Weiliang1, Zhang Hui1,2, Zhi Na1, Wang Hanwei1, Zeng Cheng1
1. School of Electrical Engineering Xi’an University of Technology College Xi’an 710048 China; 2. State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Tsinghua University Beijing 100084 China
Abstract：In DC microgrid (DC MG), the variation of distributed generation power and load power, as well as the short circuit of transmission line, will cause the fluctuation of DC bus voltage. Therefore, the response speed of energy storage unit is very important to improve the stability of DC MG. In this paper, a control strategy based on node differential current (NDCC) for DC MG energy storage converter is proposed. By calculating the power difference between the source and load of the DC microgrid, the energy storage interaction power is determined, and the energy storage regulation current is calculated, so as to adjust the duty cycle of the energy storage converter. Compared with the finite set model predictive control, it eliminates the process of traversing the working state and optimization of the energy storage converter, reduces the amount of on-line calculation, and the proposed strategy is not affected by the inductance. Therefore, the response the speed and the accuracy are improved. The fluctuations of the bus voltage and the load current are also reduced. Finally, simulation and experiments verify the effectiveness of the proposed strategy.
张伟亮, 张辉, 支娜, 王韩伟, 曾成. 基于节点源荷电流差分的直流微电网储能变换器控制策略[J]. 电工技术学报, 2022, 37(9): 2199-2210.
Zhang Weiliang, Zhang Hui, Zhi Na, Wang Hanwei, Zeng Cheng. Control Strategy of DC Microgrid Energy Storage Converter Based on Node Differential Current. Transactions of China Electrotechnical Society, 2022, 37(9): 2199-2210.
[1] 李霞林, 郭力, 王成山, 等. 直流微电网关键技术研究综述[J]. 中国电机工程学报, 2016, 36(1): 2-17. Li Xialin, Guo Li, Wang Chengshan, et al.Key technologies of DC microgrids: an overview[J]. Proceedings of the CSEE, 2016, 36(1): 2-17. [2] 刘迎澍, 陈曦, 李斌, 等. 多微网系统关键技术综述[J]. 电网技术, 2020, 44(10): 3804-3820. Liu Yingshu, Chen Xi, Li Bin, et al.State of art of the key technologies of multiple microgrids system[J]. Power System Technology, 2020, 44(10): 3804-3820. [3] Meng L, Shafiee Q, Trecate G F, et al.Review on control of DC microgrids and multiple microgrid clusters[J]. IEEE Journal of Emerging & Selected Topics in Power Electronics, 2017, 5(3): 928-948. [4] 刘彦呈, 庄绪州, 张勤进, 等. 基于虚拟频率的直流微电网下垂控制策略流[J]. 电工技术学报, 2021, 36(8): 1693-1702. Liu Yancheng, Zhuang Xuzhou, Zhang Qinjing, et al.A virtual current-frequency droop control in DC microgrid[J]. Transactions of China Electrotechnical Society, 2021, 36(8): 1693-1702. [5] 曾正, 赵荣祥, 汤胜清, 等. 可再生能源分散接入用先进并网逆变器研究综述[J]. 中国电机工程学报, 2013, 33(24): 1-12. Zeng Zheng, Zhao Rongxiang, Tang Shengqing, et al.An overview on advanced grid-connected inverters used for decentralized renewable energy resources[J]. Proceedings of the CSEE, 2013, 33(24): 1-12. [6] 许志荣, 杨苹, 赵卓立, 等. 中国多微网系统发展分析[J]. 电力系统自动化, 2016, 40(17): 224-231. Xu Zhirong, Yang Ping, Zhao Zhuoli, et al.Analysis on the development of multi-microgrid in China[J]. Automation of Electric Power Systems, 2016, 40(17): 224-231. [7] 支娜, 丁可, 黄庆辉, 等. 基于P-U下垂特性的虚拟直流电机控制策略[J]. 电工技术学报, 2021, 36(6): 1238-1248. Zhi Na, Ding Ke, Huang Qinghui, et al.Control strategy of virtual DC motor based on P-U droop characteristic[J]. Transactions of China Electrotechnical Society, 2021, 36(6): 1238-1248. [8] 张辉, 梁誉馨, 孙凯, 等. 直流微电网中多端口隔离型DC-DC变换器的改进虚拟电容控制策略[J]. 电工技术学报, 2021, 36(2): 292-304. Zhang Hui, Liang Yuxin, Sun Kai, et al.Improved virtual capacitor control strategy of multi-port isolated DC-DC converter in DC microgrid[J]. Transactions of China Electrotechnical Society, 2021, 36(2): 292-304. [9] 周小平, 陈燕东, 周乐明, 等. 一种微网群架构及其自主协调控制策略[J]. 电工技术学报, 2017, 32(10): 123-134. Zhou Xiaoping, Chen Yandong, Zhou Leming, et al.A microgrid cluster structure and its autonomous coordination control strategy[J]. Transactions of China Electrotechnical Society, 2017, 32(10): 123-134. [10] 程志江, 李永东, 谢永流, 等. 带超级电容的光伏发电微网系统混合储能控制策略[J]. 电网技术, 2015, 39(10): 2739-2745. Cheng Zhijiang, Li Yongdong, Xie Yongliu et al. Control strategy for hybrid energy storage of photovoltaic generation microgrid system with super capacitor[J]. Power System Technology, 2015, 39(10): 2739-2745. [11] 吴鸣, 李振伟, 孙丽敬. 一种混合储能变换器的模型预测整体控制方法[J]. 电力系统保护与控制, 2020, 48(21): 84-91. Wu Ming, Li Zhenwei, Sun Lijing.A model predictive overall control method for a hybrid energy storage converter[J]. Power System Protection and Control, 2020, 48(21): 84-91. [12] 李得民, 吴在军, 赵波, 等. 基于模型预测控制的孤岛微电网二次调节策略[J]. 电力系统自动化, 2019, 43(10): 60-67. Li Demin, Wu Zaijun, Zhao Bo, et al.Secondary regulation strategy of islanded microgrid based on model predictive control[J]. Automation of Electric Power Systems, 2019, 43(10): 60-67. [13] 朱晓荣, 候顺达, 李铮. 基于模型预测控制的直流微电网电压动态响应优化[J]. 电网技术, 2020, 44(6): 2187-2195. Zhu Xiaorong, Hou Shunda, Li Zheng.Voltage dynamic response optimization of DC microgrid based on model predictive control[J]. Power System Technology, 2020, 44(6): 2187-2195. [14] 郑子萱, 倪扶瑶, 汪颖, 等. 基于模型预测控制混合储能系统的直流微电网韧性提升策略[J]. 电力自动化设备, 2021, 41(5): 152-159. Zheng Zixuan, Ni Fuyao, Wang Ying, et al.Operation resilience enhancing strategy of DC microgrid based on model predictive controlled hybrid energy storage system[J]. Electric Power Automation Equipment, 2021, 41(5): 152-159. [15] 李军徽, 尤宏飞, 李翠萍, 等. 基于模型预测控制的风光储黑启动功率协调策略[J]. 电网技术, 2020, 44(10): 3700-3708. Li Junhui, You Hongfei, Li Cuiping, et al.Power coordination strategy based on model predictive control for black start with PV-wind-battery system[J]. Power System Technology, 2020, 44(10): 3700-3708. [16] Chen Siyuan, Yang Qiufan, Zhou Jianyu, et al.A model predictive control method for hybrid energy storage systems[J]. CSEE Journal of Power and Energy Systems, 2021, 7(2): 329-338. [17] Shan Yinghao, Hu Jiefeng, Guerrero Josep M.A model predictive power control method for PV and energy storage systems with voltage support capability[J]. IEEE Transactions on Smart Grid, 2020, 11(2): 1018-1029. [18] 年珩, 叶余桦. 三端口隔离双向DC-DC变换器模型预测控制技术[J]. 电工技术学报, 2020, 35(16): 3478-3488. Nian Heng, Ye Yuhua.Model predictive control of three-port isolated bidirectional DC-DC converter[J]. Transactions of China Electrotechnical Society, 2020, 35(16): 3478-3488. [19] 柳志飞, 杜贵平, 杜发达. 有限集模型预测控制在电力电子系统中的研究现状和发展趋势[J]. 电工技术学报, 2017, 32(22): 58-69. Liu Zhifei, Du Guiping, Du Fada, Research status and development trend of finite control set model predictive control in power electronics[J]. Transactions of China Electrotechnical Society, 2017, 32(22): 58-69. [20] 张宁, 杨经纬, 王毅, 等. 面向泛在电力物联网的5G通信:技术原理与典型应用[J]. 中国电机工程学报, 2019, 39(14): 4015-4025. Zhang Ning, Yang Jingwei, Wang Yi, et al.5G communication for the ubiquitous internet of things in electricity: technical principles and typical applications[J]. Proceedings of the CSEE, 2019, 39(14): 4015-4025. [21] 雍培, 张宁, 慈松, 等. 5G通信基站参与需求响应:关键技术与前景展望[J]. 中国电机工程学报, 2021, 41(16): 5540-5552. Yong Pei, Zhang Ning, Ci Song, et al.5G communication base stations participating in demand response: key technologies and prospects[J]. Proceedings of the CSEE, 2021, 41(16): 5540-5552. [22] 慈松, 刘前卫, 康重庆, 等. 从“信息-能量”基本关系看信息能源深度融合[J]. 中国电机工程学报, 2021, 41(7): 2289-2297. Ci Song, Liu Qianwei, Kang Chongqing, et al.Fundamental exploration into ICT-energy fusion[J]. Proceedings of the CSEE, 2021, 41(7): 2289-2297. [23] 张伟亮, 张辉, 支娜, 等. 考虑网络损耗的基于模型预测直流微电网群能量优化策略[J]. 电力系统自动化, 2021, 45(13): 49-56. Zhang Weiliang, Zhang Hui, Zhi Na, et al.Optimal strategy for energy coordination of DC microgrids based on model prediction and considering power loss[J]. Automation of Electric Power Systems, 2021, 45(13): 49-56.
2022, Vol. 37 
