Study On Modal Identification For Power System Low Frequency Oscillation Based On Ambient Signals

In recent years,the scale of Chinese power grid has been continuously expanded,and the degree of interconnection between systems has been continuously improved.A large number of high-magnification fast excitation devices have been put into the power grid,resulting in increasingly low frequency oscillations(LFO).The occurrence of LFO greatly harms the stability of the power system,and at the same time,the transmission capacity of the system cannot be maximized.Therefore,monitoring and analyzing the modal parameters of LFO are of great significance to the safe and stable operation of the grid.At present,most of the modal parameter analysis methods for LFO are based on transient oscillation signals.However,transient oscillation signals have a low probability of occurrence and are difficult to obtain in real time.In contrast,ambient signals caused by load fluctuations during normal operation are easy to obtain and contain the current modal information of the system.Therefore,this paper focuses on the identification of LFO modal parameters based on ambient signals.This paper first introduces the basic theory of LFO in power system and analyses the feasibility of modal parameter identification of LFO via ambient signals.Subsequently,the basic principles of the stochastic subspace identification(SSI)algorithm and blind source separation are introduced,and the applicability of the two methods for the identification of LFO modal parameters is analyzed,laying the foundation for the following.Aiming at the difficulty of order determination and the existence of false modes in the traditional SSI,a double covariance SSI algorithm is proposed.The false modes are removed by constructing Hankel matrices of two different dimensions,and then the physical modal parameters are extracted by hierarchical clustering algorithm.The improved double covariance SSI algorithm can realize automatic picking and automatic ordering of physical modes,and can effectively and accurately identify LFO modal parameters from ambient signals.Results show that the proposed method can achieve effective and accurate identification of LFO modal parameters from ambient signals,and has good anti-noise performance.Considering that the modal identification is affected by factors such as randomness of excitation,measurement error,data window length,etc.,the estimated modal parameters inevitably have errors.This paper proposes a new method for identifying LFO modal parameters considering uncertainty.The blind source separation technique is used to decompose the multi-mode ambient signal into multiple single-mode signals.Random decrement technology is used to extract the free decay signals from the single-mode signals for modal parameter calculation,and bootstrap is introduced to calculate the confidence interval,so as to measure the uncertainty of modal parameters.The results show that the proposed method can effectively identify modal parameters of LFO,and can provide confidence intervals of modal parameters.