论文标题
基于PMU的分散化混合代数和动态状态观察中的多机电源系统
PMU-Based Decentralized Mixed Algebraic and Dynamic State Observation in Multi-Machine Power Systems
论文作者
论文摘要
我们为多机电力系统提供了一种新型的分散的混合代数和动态状态观察方法,该方法具有未知输入,并配备了相类测量单元(PMU)。更具体地说,我们证明,对于同步发电机的三阶通量 - 末期模型,本地PMU测量值提供了足够的信息,可以通过载荷角度和正交轴内部电压重建代数。由于代数结构,实现了高数值效率,这使得适用于大型电源系统的方法。另外,我们证明,相对轴速度可以全球估算,结合经典的沉浸式和不变性(I&i)观察者与 - 最近引入的 - 动态回归器和混合(DREM)参数估计器。这种自适应观察者可确保在应用程序中验证的弱激发假设下进行全局收敛。所提出的方法不需要测量外源输入信号,例如场电压和机械扭矩,也不需要机械子系统参数的知识。
We propose a novel decentralized mixed algebraic and dynamic state observation method for multi-machine power systems with unknown inputs and equipped with Phasor Measurement Units (PMUs). More specifically, we prove that for the third-order flux-decay model of a synchronous generator, the local PMU measurements give enough information to reconstruct algebraically the load angle and the 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, we prove that the relative shaft speed can be globally estimated combining a classical Immersion and Invariance (I&I) observer with - the recently introduced - dynamic regressor and mixing (DREM) parameter estimator. This adaptive observer ensures global convergence under weak excitation assumptions that are verified in applications. The proposed method does not require the measurement of exogenous inputs signals such as the field voltage and the mechanical torque nor the knowledge of mechanical subsystem parameters.