Идентификация кибер- атак на системы SCADA и СМПР в ЭЭС при обработке измерений методами оценивания состояния

Abstract

The hardware and software tools of the data acquisition and processing systems, as well as the state estimation procedure intended to support the actions of dispatching personnel in performing operational and emergency control of electric power systems (EPS), are critically important components of the EPS information and communication subsystem, but at the same time, they are most vulnerable to cyberattacks. To reduce the extent to which cyberattacks can affect the control quality, it is proposed to use statistical methods for processing measurement information. First of all, these are static and dynamic state estimation methods, including a procedure for verifying measurements or detecting bad data. An analysis of data quality can determine the type of cyberattack undertaken and identify overlooked vulnerabilities. The article presents the findings from a study of two most commonly used bad data detection methods: the a priori method for analyzing the residuals of test equations and the a posteriori method for analyzing the weighted estimation residuals to identify data distorted as a consequence of specially generated cyberattacks. An algorithm to detect erroneous measurements that appear during cyberattacks and are not identified by conventional measurement verification methods in performing EPS state estimation is proposed