The anomalous data identification study of reactive power optimization system based on big data

Abstract

With the continuous development of smart grid and energy Internet, modern power system is gradually evolved into the one with funnel large amounts of data and calculation of large information systems, which shows the applicability and feasibility of the analysis technology of data mining. This paper puts forward a big data modeling method for the reactive power optimization based on the theory of the large dimensional random matrix. On the basis of it, large dimensional random matrix is disposed, applied with higher dimensional random matrix theory related to the characteristics of abnormal data detection, for judging the existence of abnormal data. If existed, this matrix is used in accordance with Pauta criterion identification to find the abnormal data. At the end of the article, it is verified by analysis examples of its effectiveness and applicability.