false data injection attack

Modern voltage control strategies in the present distribution networks require efficient equipment as well as appropriate communication channels between these equipment, sensors and control centers, which has led to smart distribution networks with a complex cyber-physical nature. One of the efficient equipment for voltage control in modern distribution networks is the DSTATCOM, which uses using multilevel converters in its structure, provides many advantages, such as direct connection to the grid. A DSTATCOM with the multilevel converter requires a cyber-physical network between the controller and its components due to the presence of many controllable components, which makes it vulnerable to cyber-attacks, when connected to the present smart distribution networks. In this paper, a feedback linearization-based controller is developed for the cascaded multilevel DSTATCOM, and a discrete Kalman filter-based method is proposed to detect and compensate false data injection cyber-attacks on voltage sensors of the multilevel converter. The abilities of the proposed nonlinear controller to control the multilevel DSTATCOM as well as the reliable operation against false data injection attacks are verified through the simulation of a test power network in the MATLAB/Simulink environment.

Achieving optimal and safe energy management and planning, taking into account the reduction of electricity production, transmission and distribution costs, as well as the reduction of environmental pollutants, has become increasingly important in many power companies in developing countries. With the optimal use of renewable energy sources and the use of a secure platform, including blockchain technology, the aforementioned goals can be achieved. To solve optimization problem, after modeling the hybrid AC-DC microgrid and considering the high complexity of the proposed formulation, the grey wolf optimization algorithm is proposed to solve the problem. In order to check the efficiency of the system under cyber-attacks, the system is subjected to false data injection attacks in different parts of the system, and then the operation is done under normal conditions and cyber-attacks. In this paper, MATLAB software package is used to solve the optimization problem and modeling the cyber-attacks. The operation results have been examined in different scenarios and the negative effects of such attacks are shown by comparing with the normal state. Then, to enhance the security of the system and prevent attacks, blockchain technology is presented to increase the security of the data exchanged in the system.

False data injection attack (FDIA) is a destructive cyber threat to the economic performance of electricity markets in smart grids. A cyber attacker can make a huge financial profit by implementing an FDIA through penetrating the virtual transactions of the electricity markets and manipulating electricity prices. In this paper, a new approach to planning an absolutely stealthily FDIA is presented with the aim of achieving maximum financial profit from the perspective of a cyber attacker participating in virtual transactions from two markets of day-ahead (DA) and real-time (RT). A common hypothesis in studies of FDIAs against electricity markets is that the attacker has complete information about the smart grid. But the fact is that the attacker has limited resources and can hardly access all the network information. This paper proposes a robust approach in designing an attack strategy under incomplete network information conditions. In particular, it is assumed that the attacker has uncertainties about the network modeling matrices. The validity of the proposed method is evaluated based on the IEEE 14-bus standard system using the Matpower tool. Numerical results confirm the relative success of the proposed attack in cases of varying degrees of incomplete information.

Recent advances in power system monitoring and control require communication infrastructure to send and receive measurement data and control commands. These cyber-physical interactions, despite increasing efficiency and reliability, have exposed power systems to cyber attacks. The Automatic Generation Control (AGC) is one of the most important control systems in the power system, which requires communication infrastructure and has been highly regarded by cyber attackers. Since a successful attack on the AGC, not only has a direct impact on the system frequency, but can also affect the stability and economic performance of the power system. Therefore, understanding the impact of cyber attacks on AGC and developing strategies to defend against them have necessity and research importance. In most of the research in the field of attack-defense of AGC, the limitations of AGC in modeling such as governor dead band and communication network transmission delay have been ignored. On the other hand, considering two cyber attacks on the AGC and proposing a way to defend against them simultaneously, have not been considered. In this paper, while using the improved AGC model including governor dead band and communication network transmission delay, the effect of two attacks - data injection attack (FDI) and delay attack which are the most important cyber attacks on AGC - has been investigated. Also, the simultaneous effect of these two attacks is discussed as a combined cyber attack. The Kalman filter-based three-step defense method has been proposed to detect, estimate and mitigate the impact of the attacks and its effectiveness has been tested on the two-area AGC system.