Advanced algorithm to detect stealthy cyber attacks on automatic generation control in smart grid

Abstract

One of the basic requirements of today's sophisticated world is the availability of electrical energy, and neglect of this matter may have irreparable damages such as an extensive blackout. The problems which were introduced about the traditional power grid, and also, the growing advances in smart technologies make the traditional power grid go towards smart power grid. Although widespread utilisation of telecommunication networks in smart power grid enhances the efficiency of the system, it will create a critical platform for cyber attacks and penetration into the system. Automatic generation control (AGC) is a fundamental control system in the power grid, and it is responsible for controlling the frequency of the grid. An attack on the data transmitted through the telecommunications link from the sensors to the AGC will cause frequency deviation, resulting in disconnection of the load, generators and ultimately global blackout. In this study, by using a Kalman filter and a proposed detector, a solution has been presented to detect the attack before it can affect the system. Contrary to existing methods, this method is able to detect attacks that are stealthy from the area control error signal and χ^2-detector. Simulations confirm the effectiveness of this method.

Keywords

• security of data
• power system interconnection
• power generation control
• power system security
• smart power grids
• kalman filters
• control engineering computing
• frequency control
• power engineering computing
• telecommunication links
• power system reliability
• stealthy cyber attacks
• automatic generation control
• traditional power grid
• smart technologies
• smart power grid
• fundamental control system
• area control error signal
• telecommunications link
• frequency deviation
• kalman filter