随着电力系统的快速发展,对系统状态的实时准确估计提出了更高要求.近年来,动态状态估计技术已成为监测电力系统实时运行状态的重要手段.提出了一种基于相量测量单元(phasor measurement unit,PMU)的电力系统动态状态估计(dynamic state estimation,DSE)方法,采用隐式离散化技术处理电力系统的非线性微分代数方程(nonlinear differential algebraic equations,NDAE)模型.建立了包含发电机动态、电网代数方程和潮流方程在内的电力系统NDAE模型,并结合PMU测量信息,对NDAE模型进行了线性化处理;基于隐式离散的方法提出了用于电力系统DSE的求解模型,实现对系统未知的动态和代数状态的有效地估计.基于WECC-9 节点电力测试系统进行仿真实验,仿真结果表明,提出的基于PMU的动态状态估计方法,通过隐式离散化技术和NDAE模型的线性化处理,实现了对电力系统状态的准确估计,在实时监测电力系统状态方面具有显著的有效性和可靠性.
k-Order Implicit Discrete Dynamic State Estimation of Power Systems Based on PMU Measurement
As power systems rapidly evolve,the demand for the accurate and real-time estimation of system states is heightened.Dynamic State Estimation(DSE)has emerged as a critical technique for monitoring the operational status of power systems in real time.This paper introduces a DSE approach for power systems leveraging Phasor Measurement Units(PMU),utilizing implicit discretization methods to address the Nonlinear Differential Algebraic Equations(NDAE)inherent in power system modeling.The paper begins with constructing an NDAE model of the power system that encompasses generator dynamics,network algebraic equations,and power flow equations,and then proceeds to linearize this model with PMU measurements.Furthermore,based on implicit discretization,a solution model for power system DSE is proposed to effectively estimate the unknown dynamic and algebraic states of the system.The simulation experiments based on the WECC 9-bus power test system demonstrate that the proposed PMU-based DSE method,through implicit discretization and linearization of the NDAE model,achieves the accurate estimation of power system states and has significant effectiveness and reliability in the real-time monitoring of power system states.
power systemdynamic state estimationimplicit discretizationPMUnonlinear differential algebraic equations
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