| Nowadays, with the increasing of electrical loads and the distance between them, the application of large-scale high voltage (HV) transmission and Flexible AC Transmission System (FACTS) complicates the current dynamic characteristics of the grid. Therefore, it is more important to analyse the dynamic stability of power systems.In this essay, measured signal features and filtering method are analysed based on WAMS Light. A new method of online monitoring of low frequency oscillation with integration of monitoring and identification is proposed. The main contributions are state below.Measured signals obtained from WAMS Light have noises, which will affect characteristics of usable signals. Hence, in this essay I analyse common noise signals and noises in the actual measured signals and find the Gaussian noise and impulse noise existed in the actual measured signals of the power system. Moreover, several conventional algorithms of filtering are selected and compared and SNR is chosen as the main performance index. Finally, after comparing and analysing, I select a suitable filtering method which could remove noises effectively.A mass of data is able to be collected by PMU Light everyday. Low frequency oscillation can be identified based on these data. Moreover, low frequency oscillation is able to be identified from the feature of the measured data based on negative damping mechanism. Therefore, it is particularly important to analyse the statistical characteristics of these data. In this essay, steady and dynamic characteristics of measured data are statistically analysed based on data obtained from WAMS Light. The steady characteristics mainly include the average value and variance, extreme value and the qualified rate, abnormal events and frequency distribution of the measured signal. The macro features of frequency of power systems in China are firstly revealed, which is helpful to control the operation situation of power system, to improve the controlling strategy and even to improve the security and stability of power systems.Generally, there are obvious trajectory indications before the destruction of dynamic stability of power systems. Dynamic stability information, which includes oscillation frequency, damping coefficient, oscillation amplitude and phase, is contained by the response trajectory after the disturbance of the power system. According to the steady and dynamic characteristics of the measured data in power systems, and negative damping mechanism of low-frequency oscillation, I propose an online monitoring method of low frequency oscillation based on integration of WAMS Light monitoring and identification. By using this method, the time and oscillation modes of low-frequency oscillation occurred in any area of the power system can be obtained. It is known at the same time that a slight oscillation will occur before a large oscillation occurs on the same day. Oscillation warning can be realised through comparing the several damping ratios of low frequency oscillations within that day, which is significance for the safe and stable operation of power systems. |
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