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1.东南大学电气工程学院,江苏省南京市 210096
2.江苏省智能电网技术和装备重点实验室(东南大学),江苏省南京市 210096
楼冠男(1986—),女,通信作者,博士,副教授,博士生导师,主要研究方向:微电网建模及运行控制、分布式新能源接入配电网运行。E-mail:glou@seu.edu.cn
蒋啸宇(1998—),男,硕士研究生,主要研究方向:分布式电源仿真技术。E-mail:220203006@seu.edu.cn
顾伟(1981—),男,博士,教授,博士生导师,主要研究方向:电力系统仿真、分布式发电与微网、综合能源系统。E-mail:wgu@seu.edu.cn
收稿:2022-11-20,
修回:2023-02-22,
网络出版:2023-05-04,
纸质出版:2023-06-25
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楼冠男,蒋啸宇,顾伟等.基于事件触发的有源配电网改进变分算法及其稳定性分析[J].电力系统自动化,2023,47(12):66-75.
LOU Guannan,JIANG Xiaoyu,GU Wei,et al.Event Triggering Based Improved Variational Algorithm for Active Distribution Network and Its Stability Analysis[J].Automation of Electric Power Systems,2023,47(12):66-75.
楼冠男,蒋啸宇,顾伟等.基于事件触发的有源配电网改进变分算法及其稳定性分析[J].电力系统自动化,2023,47(12):66-75. DOI: 10.7500/AEPS20221120003.
LOU Guannan,JIANG Xiaoyu,GU Wei,et al.Event Triggering Based Improved Variational Algorithm for Active Distribution Network and Its Stability Analysis[J].Automation of Electric Power Systems,2023,47(12):66-75. DOI: 10.7500/AEPS20221120003.
在含高密度分布式电源的现代配电网仿真中,传统数值积分算法难以同时满足快速且稳定的仿真需求,对此提出一种基于事件触发的改进变分算法。首先,引入变分迭代法,求出配电网中双级式光伏电站典型状态变量对应的近似解。随后,对算法进行数值稳定性验证,并推导其极限步长。针对部分状态量计算消耗较多仿真资源的问题,引入事件触发机制,应用误差的范数推导锁值的触发条件,减少计算频次,提升系统的仿真效率。最后,分别对算法的数值稳定性及事件触发效果进行仿真验证。结果表明,基于事件触发的变分算法在保持高精度的前提下提升了仿真速度,且随着节点规模扩大效率优势更明显。
In the simulation of modern distribution network with high-density distributed generators
the traditional numerical integration algorithm is difficult to meet the fast and stable simulation requirements
so an event triggering based improved variational algorithm is proposed. First
the variational iteration method (VIM) is introduced to obtain the approximate solution corresponding to the typical state variables of the bipolar photovoltaic power station in the distribution network. Then
the numerical stability of the algorithm is verified
and its limit step size is deduced. Aiming at the problem that the calculation of partial state variables consumes more simulation resources
the event triggering mechanism is introduced
and the triggering condition of the locked value is deduced by using the norm of error to reduce the calculation frequency and improve the simulation efficiency of the system. Finally
the numerical stability and event triggering effect of the algorithm are simulated and verified. The results show that the event triggering based variational algorithm improves the simulation speed while maintaining high accuracy
and the efficiency advantage is more obvious with the expansion of node scale.
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