多机电力系统中储能装置的选址方法对比分析

任宏宇; 康积涛; 钱琳

doi:10.16513/j.cnki.10-1427/tk.2019.02.004

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分布式能源 ›› 2019, Vol. 4 ›› Issue (2) : 23-29. DOI: 10.16513/j.cnki.10-1427/tk.2019.02.004

学术研究

多机电力系统中储能装置的选址方法对比分析

作者信息 +

Comparison and Analysis of Location Methods for Energy Storage Devices in Multi-Machine Power Systems

Author information +

文章历史 +

摘要

储能装置用于抑制低频振荡(low-frequency oscillator，LFO)具有响应速度快、可灵活调节有功和无功功率的显著特点，尤其是用于抑制区域间振荡模式时，但是多机系统中如何选择储能装置的安装位置从而更有效抑制低频振荡，是一个值得深入研究的问题。首先在电力系统分析综合程序PSASP中根据电池储能(battery energy storage system，BESS)的控制系统和模块接口部分建立电池储能的仿真模型；其次通过小干扰稳定分析计算系统状态矩阵及特征值，分析对比两种储能选址方法，即特征向量法和特征值灵敏度法，通过分析得出用特征值灵敏度法选址时准确性更好的原因；最后利用典型的两区域四机系统，分别求取特征向量及特征值灵敏度，验证了灵敏度法对于储能选址具有良好的适应性。

Abstract

Energy storage devices are used to suppress low-frequency oscillator (LFO) in power systems due to their fast response and flexible adjustment of active and reactive power, especially for inter-area oscillation mode. However, the determination of location of energy storage devices in multi-machine systems to suppress LFO more effectively is a question worthy of further study. Firstly, this paper establishes the simulation model of battery energy storage system (BESS) in the PSASP according to the control system and the interface part of the module. Secondly, the system state matrix and eigenvalues are calculated through the small signal stability analysis, and two methods of energy storage location, namely the eigenvector method and the eigenvalue sensitivity method, are compared, followed by the reason that the latter is more accurate. Finally, by a typical two-region four-machine system instance, the eigenvector and the eigenvalue sensitivity are respectively calculated to verify the sensitivity method owning a better adaptability for energy storage location.

导出引用

任宏宇, 康积涛, 钱琳. 多机电力系统中储能装置的选址方法对比分析[J]. 分布式能源. 2019, 4(2): 23-29 https://doi.org/10.16513/j.cnki.10-1427/tk.2019.02.004

Hongyu REN, Jitao KANG, Lin QIAN. Comparison and Analysis of Location Methods for Energy Storage Devices in Multi-Machine Power Systems[J]. Distributed Energy Resources. 2019, 4(2): 23-29 https://doi.org/10.16513/j.cnki.10-1427/tk.2019.02.004

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