Optimization Of PSS Parameters Based On Low Frequency Oscillation Mode Identification In Power System

With the increasing scale of power system and the increase of system interconnection in large areas,the stability of power grid has attracted more and more attention.Among them,the problem of low frequency oscillation in power system has become one of the important problems affecting the stability of power system,which has been concerned and studied by many experts and scholars.Based on the analysis of the mechanism of low frequency oscillations,this paper focuses on the analysis method of low frequency oscillations in power system,and designs the corresponding suppression strategy on the basis of analyzing the modes of low frequency oscillations.In order to solve the problem that the identification accuracy of the traditional Prony method is not high due to its sensitivity to noise,the denoising characteristics of the variational modal decomposition algorithm are used as the pre-filtering link.In this paper,a method of low frequency oscillation mode identification based on improved VMD-Prony algorithm is proposed,and the vibration mode of sampled signal with noise interference is accurately identified.In order to solve the problem that the mirror continuation of the original VMD algorithm can not improve the end effect,an end point continuation method based on adaptive waveform matching is proposed to improve the VMD.The signal after noise removal is identified by Prony algorithm,and the mode parameters of low frequency oscillation can be obtained accurately.Then,we study a new optimization algorithm: gravity search algorithm(GSA),which has been widely used since its new search mechanism has been put forward.On the basis of analyzing the optimization mechanism of gravity search algorithm,aiming at the common problem of slow convergence rate of meta-heuristic optimization algorithm,in order to improve the overall performance of gravity search algorithm,An improved gravity search algorithm(ABHGSA)which based on random black hole and adaptive strategy is proposed.By introducing the adaptive strategy,the gravitational constant formula of the algorithm is improved to optimize the exploration ability of the algorithm in the early stage and the development ability in the later stage,and the stochastic black hole strategy is merged to improve the performance of the algorithm.Local convergence ability improves the convergence precision and speed of the algorithm as a whole,and improves the optimization performance of GSA algorithm.In order to test the performance of the proposed improvedABHGSA algorithm and compare with the original GSA algorithm,the typical standard test function is used to test the algorithm to verify the effectiveness of the proposed algorithm.The improved GSA algorithm is applied to the optimization design of PSS parameters in multi-machine power system.The low frequency oscillation mode parameters are identified by the improved VMD-Prony algorithm,and the maximum correlation unit is found according to the participation factor method,so as to determine the installation position of PSS.The eigenvalues and electromechanical oscillation mode characteristics of the system under various operation modes are taken as the optimized objective functions to ensure the adaptability and robustness of the coordinated optimization strategy.Moreover,the ABHGSA algorithm is used to optimize multiple PSS parameters at the same time,and the better dynamic performance of the system is obtained,the weak damping or even underdamping of the power system is improved,and the running stability of the system is improved.The effectiveness of the proposed method is verified by the classical examples of four machines and two regions and 10 machines and 39 nodes.