Research On Static And Transient Stability Evaluation Method Of Power System Based On PMU

With the gradual increase in the scale of power systems and the continuous increase in the size of new energy grids,it has brought huge challenges to the safe and stable operation of the system.How to ensure that the system operates safely and stably under more economic conditions has become more and more It is important that power system stability analysis,whether it is static stability analysis or transient stability analysis,has become an important research hotspot.With the increasing application of PMU measured data in power systems,it can well reflect the stable state information of power system nodes and branches.This article analyzes the system from the static security stability analysis and transient stability analysis respectively.In the aspect of static security stability analysis,this paper mainly analyzes the static vulnerability of the power system,and based on the transient stability assessment,based on The short-term transient power angle,power,and voltage of PMU measured data are combined with machine learning algorithms to conduct in-depth research and exploration on transient stability assessment.This paper mainly includes the following aspects:(1)This paper firstly introduces the research status of power system security stability analysis.In the field of static stability analysis,the static stability of the power system is mainly used as the starting point to analyze the static stability of the power system.The transient stability analysis mainly introduces the research status of traditional transient stability assessment methods.(2)In the study of the static vulnerability of power systems,this paper analyzes the traditional power grid structure or state vulnerability assessment methods that take into account the singleness of system factors,ignoring the overall connection effect,and brings error and distortion to the analysis of static safety and stability of the system.Therefore,a method for assessing the probability of power grid transmission based on the combination of semi-invariant and Gram-Charlier series(CGC)and considering various random factors is proposed.Simulation is carried out in the IEEE-30 bus system with wind power model.The analysis proves the feasibility and effectiveness of the proposed method for assessing the probability vulnerability of power grids,and provides a new research direction for the static stability analysis of power systems.(3)In the study of power system transient stability,this paper combines the short-term transient power angles,power and voltage dynamic information of PMU measured data,and establishes the transient feature set of transient characteristics of IEEE-39 node system.The power system transient stability assessment model is constructed based on the random forest algorithm.The model is mainly composed of several important steps such as transient stability assessment of raw feature input,test data preprocessing,random forest generation,and final prediction classification category output.The random forest algorithm is used to rank the features according to the importance degree from high to low,and the features with the most importance are selected to constitute the optimal feature combination.The transient stability performance is predicted by the random forest and fuzzy C-means clustering algorithm based on different decision tree algorithms.In contrast,to evaluate the transient stability characteristics of the analysis system.(4)In order to improve the transient stability assessment performance of power system,the transient stability feature sample set of IEEE-39 nodal system under various disturbances was used.The features were successively increased according to the feature importance degree and the genetic algorithm,particle swarm optimization algorithm and grid were calculated.Transient Stability Prediction Classification of Support Vector Machines Based on Search Algorithm Parameters Optimization.The simulation results show that the search time of the grid search algorithm is the longest,but the accuracy of misjudgment is the lowest,which is better in the transient stability prediction evaluation of the power system.