An Intelligent Key Feature Selection Method of Power Grid Based on Artificial Intelligence Technology

With the expansion of the nationwide power grid network, the complexity of space and time of power grid is increasing. It is difficult to fully grasp the operating characteristics of the power grid based on human experience only. Therefore, finding the key features that can reflect the security information of the power grid quickly and efficiently based on artificial intelligence (AI) technology is of great significance to the monitoring and safe operation of the power grid. Aimed at the requirements above, this paper presented an intelligent feature selection method for power grid. This method uses information theory and data mining technology to intelligently select key features with integration of improved mutual information feature selection (MIFS) and wrapper method. On the first stage, improved MIFS method was used to preliminarily select features; on the second stage, wrapper method and backward search strategy were adapted to further selection. The segmentation intelligent selection method implements integrated application of multiple methods for power system security and stability assessment scenario. The method can effectively reduce the feature dimension, achieve intelligent feature selection, meets the prior knowledge of dispatchers, and facilitate the real-time monitoring of dispatching operators considering operation experience. Furthermore, it reduces the redundancy of selected feature which is conductive to the development of real-time dynamic security assessment and improves computational efficiency. The simulation result in IEEE-39 buses system verifies the effectiveness of the proposed method. © 2019 Chin. Soc. for Elec. Eng.