22.
    发明专利
    未知

    公开(公告)号:AT382975T

    公开(公告)日:2008-01-15

    申请号:AT03405450

    申请日:2003-06-21

    Abstract: The detection of electromechanical oscillations in power systems and the estimation of their parameters (frequency f and damping xi ) is based on a linear time-varying model. The parameters of the linear model are on-line adapted by means of Kalman filtering techniques to approximate the measured signal y (representing the behaviour of the power system) optimally in the sense of a quadratic criterion. The estimated model parameters are then the basis for the calculation of parameters of the oscillations. Adaptive algorithms are based on a recursive calculation of the estimated parameter vector for each time-step based on the new value of the measured signal and the old values of the estimated parameters. As opposed to the collection of data over a time window and then performing the parameter identification at once, any change in the system can thus be detected much faster.

    IMPROVED CONTROL OF A POWER TRANSMISSION SYSTEM

    公开(公告)号:CA2763497C

    公开(公告)日:2016-11-08

    申请号:CA2763497

    申请日:2009-06-11

    Abstract: The invention provides improved control of a power transmission system having a first group of measurement units (10, 12, 14) in a first geographical area (A_1) providing a first set of phasors and a second group of measurement units (16, 18) in a second geographical area (A_2) providing a second set of phasors, where the phasors in the sets are generated at the same instant in time. In this system the power control device (32) includes a phasor aligning unit (30) that time aligns the first and second sets of phasors and a control unit (33) that compares each set of phasors with a corresponding phasor number threshold, determines that a first control condition is fulfilled if each phasor number threshold has been exceeded and enables the provision of a common signal if the first control condition is fulfilled. The common signal is based on the obtained phasors in the first and second sets.

    ESTIMACION DE PARAMETROS PARA UN MODELO TERMICO DE UNA LINEA DE ALTA TENSION.

    公开(公告)号:ES2367399T3

    公开(公告)日:2011-11-03

    申请号:ES07787793

    申请日:2007-07-23

    Abstract: Un procedimiento de estimación de unos parámetros de modelo (A, B,...; C1,...) de un modelo térmico de una línea de alta tensión (10), que comprende - medir unos valores de una magnitud eléctrica (I, P) de la línea de alta tensión y de unas magnitudes meteorológicas (Ta, S, W) que representan unas condiciones ambientales de la línea de alta tensión, y - calcular unos valores de los parámetros de modelo a partir de dichos valores medidos, caracterizado porque el procedimiento comprende - medir, repetidamente durante el funcionamiento de la línea de alta tensión, unos valores temporales (I i , Ta i , S i , W i ) de las magnitudes eléctricas y meteorológicas, - medir de forma concurrente un valor temporal (T1 i ) de una temperatura (T1) de la línea de alta tensión, y - calcular, repetidamente durante el funcionamiento de la línea de alta tensión, los valores (A i , B i ;...; C1 i ,...) de los parámetros de modelo a partir de dichos valores medidos.

    26.
    发明专利
    未知

    公开(公告)号:DE602006011492D1

    公开(公告)日:2010-02-11

    申请号:DE602006011492

    申请日:2006-10-31

    Abstract: The present invention is concerned with the monitoring of electromechanical oscillations in electric power systems, and their identification by an adaptive algorithm based on a repeatedly measured and evaluated signal as detailed in EP-A 1 489 714. In order for an estimation of parameters of a model of the power system to reasonably converge, proper initialisation of the recursive calculation is required, including the definition of tuning parameters constraining the model and the calculation. Initialisation for a second signal to be exploited can then be simplified by copying the set of tuning parameters tuned previously for a different signal. A conditioning gain multiplying the second signal establishes compatibility between the different signals, and a signal pre-filter in turn discards contributions beyond a frequency band comprising typical electromagnetic oscillations.

    27.
    发明专利
    未知

    公开(公告)号:DE602007002809D1

    公开(公告)日:2009-11-26

    申请号:DE602007002809

    申请日:2007-05-16

    Abstract: The present invention is concerned with a faster response and an increased accuracy in power system protection. According to the invention, a fault, instability or other contingency potentially requiring some protective action, such as line tripping or load adaptation, is detected in a fast and precise way by tracking a non-frequency-selective evolution of a physical parameter (R, L) in time domain, preferably with adaptive filters. By reverting to a physical parameter having an imminent physical significance, no additional analysis is required to divulge a fault or contingency, hence the speed of fault detection increases. Due to the skin affect in electrical conductors, a time domain analysis covering a broad range of frequencies includes more information than an analysis confined to the fundamental or line frequency, hence the accuracy of the fault detection increases.

    28.
    发明专利
    未知

    公开(公告)号:AT445926T

    公开(公告)日:2009-10-15

    申请号:AT07729237

    申请日:2007-05-16

    Abstract: The present invention is concerned with a faster response and an increased accuracy in power system protection. According to the invention, a fault, instability or other contingency potentially requiring some protective action, such as line tripping or load adaptation, is detected in a fast and precise way by tracking a non-frequency-selective evolution of a physical parameter (R, L) in time domain, preferably with adaptive filters. By reverting to a physical parameter having an imminent physical significance, no additional analysis is required to divulge a fault or contingency, hence the speed of fault detection increases. Due to the skin affect in electrical conductors, a time domain analysis covering a broad range of frequencies includes more information than an analysis confined to the fundamental or line frequency, hence the accuracy of the fault detection increases.

    29.
    发明专利
    未知

    公开(公告)号:DE60318408T2

    公开(公告)日:2009-01-29

    申请号:DE60318408

    申请日:2003-06-21

    Abstract: The detection of electromechanical oscillations in power systems and the estimation of their parameters (frequency f and damping xi ) is based on a linear time-varying model. The parameters of the linear model are on-line adapted by means of Kalman filtering techniques to approximate the measured signal y (representing the behaviour of the power system) optimally in the sense of a quadratic criterion. The estimated model parameters are then the basis for the calculation of parameters of the oscillations. Adaptive algorithms are based on a recursive calculation of the estimated parameter vector for each time-step based on the new value of the measured signal and the old values of the estimated parameters. As opposed to the collection of data over a time window and then performing the parameter identification at once, any change in the system can thus be detected much faster.

    30.
    发明专利
    未知

    公开(公告)号:DE60318408D1

    公开(公告)日:2008-02-14

    申请号:DE60318408

    申请日:2003-06-21

    Abstract: The detection of electromechanical oscillations in power systems and the estimation of their parameters (frequency f and damping xi ) is based on a linear time-varying model. The parameters of the linear model are on-line adapted by means of Kalman filtering techniques to approximate the measured signal y (representing the behaviour of the power system) optimally in the sense of a quadratic criterion. The estimated model parameters are then the basis for the calculation of parameters of the oscillations. Adaptive algorithms are based on a recursive calculation of the estimated parameter vector for each time-step based on the new value of the measured signal and the old values of the estimated parameters. As opposed to the collection of data over a time window and then performing the parameter identification at once, any change in the system can thus be detected much faster.

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