Research On Automatic Generation Technology Of Power Grid Planning AC Operation Mode Data

With the construction of UHV and connection of large area power grid,the scale of AC-DC mixing power grid is expanding,the operation mode of power grid is increasingly complex.The access of new energy adds to the uncertainty of operation mode,and adds to the need of the refinement of power grid planning.Traditional preparation of power grid operation mode data is based on manual method,which is hard to characterize the operation mode accurately,and hard to handle massive amounts of data.Therefore it is urgent need to research on the automatic generation technology of power grid operation mode AC power flow data.To solve this problem,this article is based on power grid planning operation mode data,using K-means clustering method to launch relative work.First,based on the relative literature,this article analyses the problems of the preparation of power grid operation mode and management,then uses the feature quantity to build the model of AC power flow data generation,which includes common basic mode base and historical data mode base.It completes the preparation of common basic mode base,proposes AC power flow data generation method based on data mining to solve the problem of mode extraction and matching.In this part,it overviews existing cluster methods,then explained K-means cluster method and its advantages and disadvantages,and proposes operatoin mode automatic generation and matching model based on K-means cluster.It uses best cluster number method to solve the disadvantages of K-means cluster,adds to the reliability and applicability.Finally,it uses actual power grid operation data to calculate and analyse.The result vertifies the validity and reliability of the model.