Analysis And Prediction Method Of Frequency Dynamic Characteristics In Interconnected Power Grid

With the interconnection of the power networks,the coupling degree between networks is increasing,the probability of all kinds of disturbances is also increasing.The stability of the power grid is facing greater challenges.The dynamic frequency behavior of power system directly affects the quality of electrical power and stability of the system.If the frequency dynamics of the power system can be predicted after the disturbance,the corresponding measures can be taken in advance to prevent the occurrence of the accident.The main contents of this thesis are as follows:(1)This thesis briefly introduces some basic concepts of the frequency in power system,It also introduces the application fields of Hilbert-Huang transform theory,the support vector machine theory and the current frequency dynamic analysis methods,.The frequency dynamic characteristics of the power system are simulated and analyzed through the mathematical model of the single machine system and the interconnected power system respectively.(2)Because Hilbert-Huang Transform method can make the nonstationary and nonlinear signal smooth and stable.We can use Hilbert-Huang transform to analyze the frequency characteritics of large-scale power system after disturbances.the method is validated by New England 10-machine and 39-node system.(3)In this thesis,a dynamic predction method based on empirical mode decomposition and online support vector regression is used to predict the frequency time series after disturbance.This method firstly decomposes the time series of frequency fluctuation into a set of intrinsic mode functions and a residual through empirical mode decomposition,so as to reduce the interaction between different feature information.Then,the prediction model of each component is established by using the online SVR method.Finaly,the prediction method of this paper is applied to frequency dynamic change prediction analysis of New England 10-machine 39-node system.The analysis results show that the EMD-OSVR combination method adopted in this thesis can effectively predict the dynamic frequency changes of the power grid after disturbance and improve the prediction accuracy as well as meet the requirements of practical application.