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Synchrophasor based tracking of synchronous generator dynamic states using a fast EKF with unknown mechanical torque and field voltage

机译:基于同步发电机动态状态的同步速率使用快速EKF具有未知机械扭矩和场电压的同步发电机动态状态

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Dynamic states of a synchronous machine, i.e. rotor angle and rotor speed, are important variables for power system control, studies and analysis. Availability or estimating of these variables would help us to monitor effectively the stability condition of the power systems in order to develop local or wide-area control loop to improve power system stability and reliability. To estimate the rotor angle or rotor speed of a synchronous machine, availability, measuring or estimating the input signals, i.e. field voltage (E) and input mechanical torque (T) is always an issue. To solve this problem, in this paper the Extended Kaiman Filter with Unknown Inputs, known as EKF-UI method, is applied for dynamic state estimation of a synchronous generator using available Phasor Measurement Unit (PMU) signals while we are assuming there are two unknown inputs: E and T. Using the employed EKF-UI technique, the unknown input signals of the synchronous machine (E and T) are estimated simultaneously along with the states and outputs of the machine.
机译:同步机的动态状态,即转子角度和转子速度,是电力系统控制,研究和分析的重要变量。这些变量的可用性或估算将有助于我们有效地监控电力系统的稳定性状态,以开发局部或广域控制回路,以提高电力系统稳定性和可靠性。为了估计同步机的转子角度或转子速度,可用性,测量或估计输入信号,即场电压(e)和输入机械扭矩(t)始终是一个问题。为了解决这个问题,在本文中,具有未知输入的扩展Kaiman滤波器,称为EKF-UI方法,用于使用可用相控量测量单元(PMU)信号的同步发电机的动态状态估计,同时我们假设有两个未知输入:E和T.使用采用的EKF-UI技术,同步机(E和T)的未知输入信号以及机器的状态和输出同时估计。

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