PMU‐based decentralised mixed algebraic and dynamic state observation in multi‐machine power systems
PMU‐based decentralised mixed algebraic and dynamic state observation in multi‐machine power systems
复制标题
多机电力系统中基于PMU的分散混合代数和动态观测
DOI：
10.1049/iet-gtd.2020.1275
复制
发表时间：
2020
影响因子：
2.5
通讯作者：
Johannes Schiffer
中科院分区：
文献类型：
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作者：
Nicolai Lorenz;A. Bobtsov;R. Ortega;N. Nikolaev;Johannes Schiffer
针对含有相量测量单元(PMU)的具有未知输入的多机电力系统，提出了一种新的分布式混合代数动态观测方法。更具体地说，它们证明了对于同步发电机的三阶磁通衰减模型，局部PMU测量提供了足够的信息来从大脑上重建负载角和交轴内部电压。由于这种代数结构，使得该方法具有很高的数值效率，适用于大规模电力系统。此外，它们还证明了将经典的浸入不变观测器与最近引入的动态回归扩展和混合参数估计器相结合，可以全局估计相对轴速。该自适应观测器在弱激励假设下保证了全局收敛，并在实际应用中得到了验证。该方法既不需要测量励磁电压和机械扭矩等外部输入信号，也不需要了解机械子系统的参数。
The authors propose a novel decentralised mixed algebraic and dynamic state observation method for multi‐machine power systems with unknown inputs and equipped with phasor measurement units (PMUs). More specifically, they prove that for the third‐order flux‐decay model of a synchronous generator, the local PMU measurements provide enough information to reconstructalgebraicallythe load angle and quadrature‐axis internal voltage. Due to the algebraic structure, a high numerical efficiency is achieved, which makes the method applicable to large‐scale power systems. Also, they prove that the relative shaft speed can be globally estimated combining a classical immersion and invariance observer with – the recently introduced – dynamic regressor extension and mixing parameter estimator. This adaptive observer ensures global convergence under weak excitation assumptions that are verified in applications. The proposed method neither requires the measurement of exogenous input signals such as the field voltage and the mechanical torque nor the knowledge of mechanical subsystem parameters.
影响因子：
4.4
作者：
Wang, Shaobu;Zhao, Junbo;Diao, Ruisheng
通讯作者：
Diao, Ruisheng