Static Voltage Stability Boundary Feature Extraction Of Power System Based On Data Mining And Its Application

With the development of the economy and the increasing power load,the operating state of the power grid is approaching the limit of its transmission capacity.New energy is connected to the power grid on a large scale,and its uncertainty induces many large-scale power outages.The assessment methods of the online security defense system based on the modeling and simulation is constrained by the model,the model parameters are difficult to measure directly,and the online analysis timeliness cannot meet the requirements of security prevention and control on power system.The theoretical framework of data-driven and information-driven power system analysis is widely proposed.It is a hot trend for realizing panoramic security defense and stable situation quantitative assessment of large power grids through big data analysis technology in power system research today.Therefore,the data mining algorithm is used to grasp the static voltage stability boundary feature,and the online static security and stability assessment research is carried out.The combination of model driving and data driving is of great significance for building a new strong smart grid.The power system static stability boundary feature extraction is the core of online assessment and control for power system static stability situation.Most of the traditional static stability situation assessment methods are based on physical models and high-intensity simulation calculations.The online engineering applicability cannot be guaranteed.The voltage boundary problems mostly focus on the study of voltage variables,and the static stability of the grid cannot be effectively measured.In this paper,a method for extracting static voltage stability boundary features of power systems based on scale-invariant feature transform is proposed.The degree of correlation of holographic information under static voltage stability critical state is directly explored,and the degree of correlation of boundary features under different operating conditions is mapped.It can fully reflect the operating state at the static stability limit,which is of great significance for improving the static stability situation assessment index of the existing power grid and improving the current static stability assessment method.The test result of IEEE39 nodes system shows that the method is effective.Static stability assessment of power system is the key to achieving optimal control of power system.Aiming at the insufficiency of applicability and timeliness of existing static stability discriminant methods,this paper improved the generalized elastic criterion of power system by the static stability boundary feature of power system.The grid-load system is equivalent to an elastic system,and the elastic potential energy of equivalent network and the improved generalized elasticity index of each Operating status are calculated.The result of the IEEE 39-node system shows that the improved grid elasticity index can effectively judge the static stability of the power system.The index changes more obviously when the system tends to stabilize the limit and the slope of the index curve is larger,easier to detect,simpler to calculate,and better for engineering application.In summary,based on a large number of static voltage stability limit simulation samples of power system,this paper has done a comprehensive study on the static voltage stability limit of power system,the extraction of static voltage stability boundary features,and the improvement of static stability situation assessment index of power system and achieved good results.