Online parameter identification of synchronous machines using Kalman filter and recursive least squares

Abstract

This paper investigates and implements a procedure for parameter identification of salient pole synchronous machines that is based on previous knowledge about the equipment and can be used for condition monitoring, online assessment of the electrical power grid, and adaptive control. It uses a Kalman filter to handle noise and correct deviations in measurements caused by uncertainty of instruments or effects not included in the model. Then it applies a recursive least squares algorithm to identify parameters from the synchronous machine model. Despite being affected by saturation effects, the proposed procedure estimates 8 out of 13 parameters from the machine model with minor deviations from data sheet values and is largely insensitive to noise and load conditions.

Evaluating the Precision of the DC Decay Test Method for Characterizing Wound-Field Synchronous Machines in Power Plants

“…T O BE able to analyze the transient behavior and dynamics of hydropower plants to ensure power system stability, a precise knowledge of the characteristic quantities of the wound-field synchronous machine (WFSM) is required [2], [3], [4], [5], [6], [7]. Moreover, the estimation of the saturated sub-transient reactances x ′′ d and x ′′ q are essential for calculating the electrical and mechanical integrity of the machine and its shaft line during severe transients such as under three-phase or two-phase short-circuits.…”

Estimación algebraica robusta en tiempo real de la frecuencia natural y el retardo de un robot flexible teleoperado

“…Por lo tanto, se requieren técnicas de identificación en tiempo real que garanticen estimaciones rápidas de los parámetros característicos de la dinámica del T FLR, en particular de los modos de vibración del sistema mecánico y el retardo, para implementar controles adaptativos que reduzcan la sensibilidad del robot controlado a las variaciones anteriormente mencionadas. Existen muchos métodos para llevar a cabo la identificación paramétrica de los modos de vibración, como el filtrado de ranura adaptativo (Wang et al, 2019), el filtrado de Kalman (Cui et al, 2019), y los métodos de mínimos cuadrados (Alves et al, 2019). Asimismo, para llevar a cabo la identificación de los retardos presentes en los sistemas teleoperados, se han desarrollado estimadores como el algoritmo adaptativo supertwisting (Deng et al, 2020), la formulación espectral (Mhamdi et al, 2018) o el uso de ecuaciones de convolución cruzada (Belkoura, 2010).…”