Static Risk Assessment Method for Smart Microgrid Considering False Data Injection Attacks

Abstract

Smart microgrids (SM) can be seen as unified agents after traditional microgrids empower autonomy. Different from the static risk assessment of traditional microgrids, the autonomy of SM makes it difficult to evaluate with classic static risk assessment indicators such as load loss risk, voltage or power flow overrun risk. What's more, it is prone to false data injection attacks and makes its normal operation invalid since SM has lots of IoT facilities. Therefore, it is necessary to conduct static risk assessment on SM considering false data injection attacks. In this paper, voltage overrun risk, power flow overrun risk and comprehensive risk are taken as indicators of static risk assessment, and a set of static risk assessment process is designed against the background of clearing SM internally by false transaction data injection attacks. Further, a 7-node SM with multiple renewable energy is taken as an example to verify the effectiveness of the proposed static risk assessment method.