收稿日期: 2022-04-08
网络出版日期: 2022-11-03
Adaptive Virtual Inertial Control Strategy of Optical Storage and Distribution Network Based on TOPSIS Algorithm
Received date: 2022-04-08
Online published: 2022-11-03
针对多光储单元共同运行时因指标不同存在的惯性功率分配问题,以自适应虚拟惯性控制作为提升电能质量水平的手段,提出一种多光储单元协同控制策略.根据蓄电池的充放电特性,对系统提供惯性大小进行调整.当系统内出现高频扰动时,首先选择超级电容来提供惯性支撑,容量不足时,蓄电池将配合起到惯性支撑作用.当系统内部出现低频扰动时,由蓄电池提供惯性功率支撑,引入优劣解距离算法,在进行协同控制时,选取换流器允许功率波动范围、储能装置允许功率波动范围等指标作为评价参考,实现多指标综合评价下多虚拟同步发电机(VSG)单元之间的协同配合.最后通过实验平台搭建含多VSG单元的交流系统,验证所提控制策略的有效性.
余威, 杨欢红, 焦伟, 周泽 . 基于优劣解距离算法的光储配电网自适应虚拟惯性控制策略[J]. 上海交通大学学报, 2022 , 56(10) : 1317 -1324 . DOI: 10.16183/j.cnki.jsjtu.2022.106
Aimed at the problem of the inertia power allocation due to different indexes when multiple optical storage units are running together, a cooperative control strategy of multiple optical storage units is proposed by using adaptive virtual inertia control as a means to improve power quality. According to the charging and discharging characteristics of the battery, the inertia provided by the system is adjusted. As high-frequency disturbance occurs in the system, the super capacitor is the first choice to provide inertia support. As low-frequency disturbance occurs in the system, the battery provides inertia power support, and the distance algorithm of the superior and inferior solutions is introduced. As cooperative control is performed, indicators such as the allowable power fluctuation range of the converter and the allowable power fluctuation range of the energy storage device are selected as the evaluation reference, the coordination among multi virtual synchronous generator (VSG) units in multi-index comprehensive evaluation is realized. Finally, an AC system with multi VSG units is built on the experiment platform, and the effectiveness of the proposed control strategy is verified.
| [1] | 赵俊瑞, 王占山, 王继东, 等. 微网故障特性分析及保护方法[J]. 上海交通大学学报, 2015, 49(6): 913-922. |
| [1] | ZHAO Junrui, WANG Zhanshan, WANG Jidong, et al. Fault characteristics of microgrid and protection strategies[J]. Journal of Shanghai Jiao Tong University, 2015, 49(6): 913-922. |
| [2] | BOROYEVICH D, CVETKOVIC I, DONG D, et al. Future electronic power distribution systems: a contemplative view[C]//2010 12th International Conference on Optimization of Electrical and Electronic Equipment. Basov, Russia: IEEE, 2010: 1369-1380. |
| [3] | DRAGICEVIC T. Hierarchical control of a direct current microgrid with energy storage systems in a distributed topology[D]. Zagreb, Croatia: Zagreb University, 2013. |
| [4] | SHAFIEE Q, DRAGICEVIC T, VASQUEZ J C, et al. Hierarchical control for multiple DC microgrids clusters[J]. IEEE Transactions on Energy Conversion, 2014, 29(4): 922-933. |
| [5] | SERBAN I AND MARINESCU C. Control strategy of three phase battery energy storage systems for frequency support in microgrids and with uninterrupted supply of local loads[J]. IEEE Transactions on Power Electronics, 2014, 29(9): 5010-5020. |
| [6] | HU J, ZHU J AND DORRELL D G. Model predictive control of inverters for both islanded and grid connected operations in renewable power generations[J]. In IET Renewable Power Generation, 2014, 8(3): 240-248. |
| [7] | 孟建辉, 彭嘉琳, 王毅, 等. 考虑储能荷电状态及频率恢复特性的改进型灵活虚拟惯性控制[J]. 电力自动化设备, 2020, 40(6): 100-107. |
| [7] | MENG Jianhui, PENG Jialin, WANG Yi, et al. Improved flexible virtual inertia control considering the state of charge and frequency recovery of energy storage[J]. Electric Power Automation Equipment, 2020, 40(6): 100-107. |
| [8] | 朱晓荣, 孟凡奇. 含虚拟惯性控制的直流微电网稳定性分析[J]. 电网技术, 2020, 44(1): 208-218. |
| [8] | ZHU Xiaorong, MENG Fanqi. Stability analysis of DC microgrid with virtual inertial control[J]. Power System Technology, 2020, 44(1): 208-218. |
| [9] | 于晶荣, 孙文, 于佳琪, 等. 基于惯性自适应的并网逆变器虚拟同步发电机控制[J]. 电力系统保护与控制, 2022, 50(4): 137-144. |
| [9] | YU Jingrong, SUN Wen, YU Jiaqi, et al. Virtual synchronous generator control of a grid-connected inverter based on adaptive inertia[J]. Power System Protection and Control, 2022, 50(4): 137-144. |
| [10] | WANG F, ZHANG L J, FENG X Y, et al. An adaptive control strategy for virtual synchronous generator[J]. IEEE Transactions on Industry Applications, 2018, 54(5): 5124-5133. |
| [11] | FATHI A, SHAFIEE Q, BEVRANI H. Robust frequency control of microgrids using an extended virtual synchronous generator[J]. IEEE Transactions on Power Systems, 2018, 33(6): 6289-6297. |
| [12] | 金皓纯, 葛敏辉, 徐波. 基于极限学习机的双馈感应风力发电机综合自适应调频参数优化方法[J]. 上海交通大学学报, 2021, 55 (Sup.2): 42-50. |
| [12] | JIN Haochun, GE Minhui, XU Bo. Optimization of DFIG comprehensive adaptive frequency regulation parameters based on extreme learning machine[J]. Journal of Shanghai Jiao Tong University, 2021, 55 (Sup.2): 42-50. |
| [13] | 伍文华, 陈燕东, 罗安, 等. 一种直流微网双向并网变换器虚拟惯性控制策略[J]. 中国电机工程学报, 2017, 37(2): 360-372. |
| [13] | WU Wenhua, CHEN Yandong, LUO An, et al. A virtual inertial control strategy for dc microgrid bidirectional grid-connected converter[J]. Proceedings of the CSEE, 2017, 37(2): 360-372. |
/
| 〈 |
|
〉 |
