Impact Analysis of Cyber Attack on Automatic Generation Control Signal of Hydropower Plant

Abstract

Energy is a crucial component of economic progress, social advancement, and human wellbeing for any country. Hydropower is the most affordable, clean, and ecologically friendly renewable source of energy. For hydropower plants to operate efficiently and provide enough electricity to meet demand, the hydro energy is either stored in reservoirs for dam-based schemes or settling basins for run-of-river systems. Cyber systems are essential for increasing the effectiveness and dependability of the operation of the power system and assuring that the system operates within safe operating limits. The increasing dependence on digital technology has made hydropower plants more vulnerable to cyber-attacks. This study aims to analyze the cyber-attacks impact of on the automatic generation control (AGC) system of hydropower plants. AGC is a crucial component in the operation of those hydropower plant which satisfy the criteria to participate in AGC as it ensures that the power output is in sync with the demand. By bypassing the control and monitoring technology made possible by the layer of cyber, an adversary might cause significant harm to the underlying physical system. For power systems to be stable and function properly, the system frequency must be kept within predefined operational limits. The AGC system must effectively neutralize any slight deviation from the permitted frequency range; otherwise, it may cause service disruptions and/or harm to the equipment that makes up the power grid. The AGC control system sends the data it needs to the control center using communication channels that are open to cyberattacks. As a result, AGC system must be well protected against false data injection (FDI) attacks. Traditional cyber-security solutions that use host-based and network-based security technologies have been used to protect important assets from electronic threats. It is known, though, that trained and experienced attackers can get beyond these security measures and affect the proper working of control systems. Detecting highly skilled attacks requires the use of cyber-attack-resistant control approaches that go beyond conventional cyber defensive measures. Therefore, to overcome this Kalman filter is used in AGC system to estimate and detect any intrusion or any fault in system. A two-area AGC system was modeled and implementation of cyber-attack was carried out to show the impact on the system frequency. As a combination of intelligent attack detection, suggestion of a broad framework for the application of attack resilient control to power systems. The study will focus on the various types of cyber-attacks that can target AGC systems, their impact on the performance of the system, and the measures that can be taken to mitigate such attacks. The iii analysis based on both theoretical and practical which includes simulations and case results. The result of the study provides insights into the criticality of cyber security in the context of AGC systems and will contribute to the development of robust and secure AGC systems for hydropower plants. Findings of this work demonstrate that the algorithm is effective at identifying cyber attacks. The system is modeled and simulated in MATLAB/SIMULINK 2022a software. The Hardware- In-Loop (HIL) simulation setup built for this research is developed using Typhoon HIL 604. Results from the HIL simulator and laboratory test results were compared. Furthermore, results of the simulator test were found to have a good correlation with laboratory data verifying the functionality of HIL simulators and validating generated simulation models. Results showed that the use of an HIL simulation is a feasible alternative to full power laboratory testing operating conditions that are difficult or impossible to replicate in the field.